Publications

Field Guide to Northern Tree-related Microhabitats: Descriptions and size limits for their inventory in boreal and hemiboreal forests of Europe and North America

R. Bütler Sauvain; L. Larrieu; L. F. Lunde; M. Maxence; B. Nordén et al. 

A tree-related microhabitat (abbreviated as TreM) is a morphological feature present on a tree, which is used by sometimes highly specialised species during at least one part of their life cycle. These features may serve as shelters, breeding spots, or crucial hibernation or feeding places for thousands of species. Each TreM provides very specific conditions to the inhabiting species, depending on its characteristics, such as size, shape, position in the tree, degree of decomposition of the surrounding wood, condition of the bearing tree (living or dead), exposure to sunlight, microclimate, and moisture content. The diversity of TreMs in a forest stand directly influences the diversity of species because different TreMs provide optimal conditions for various species to thrive. To reinforce biodiversity in a stand and thus improve its resilience, we need to know which TreMs are present, and to preserve and favour them through adapted management practices. This field guide describes 52 TreMs in boreal and hemiboreal forests. These microhabitats can be categorised into 17 groups, with these groups falling within 7 overarching forms. The guide also indicates recommended minimum inventory sizes for each TreM and gives information about the TreM’s life traits, development rhythm, and associated species. This booklet is specifically tailored to boreal and hemiboreal forests.

Data Champions Lunch Talks – Green Bytes: Data-Driven Approaches to EPFL Sustainability

M. S. P. Cubero-Castan; M. Peon Quiros; C. Gabella; F. Varrato; Loïc Lannelongue 

For this edition of the DC Lunch Talks series, the discussion centered around Data-Driven Approaches to sustainability at EPFL, a topic of significant relevance in the contemporary academic landscape. The event featured a series of short talks by experts who shared their insights and perspectives on the integration of green technologies and hints for research data management and analysis. The speakers and their respective topics are: * “Data and sustainability at a server level”, by Dr. Miguel Peon Quiros, Computer Scientist and administrator of the EPFL EcoCloud; * “Computational work as part of a solution: extracting electricity from heat”, by Enrico Di Lucente, EPFL PhD Student in Materials Science and Engineering, ; * “GREENER principles for environmentally sustainable computational science”, by Dr. Loïc Lannelongue, Specialist in Biomedical data science and research sustainability at Univ. of Cambridge; * “Situation at EPFL and experiences in minimizing our data footprint”, by Dr. Manuel Cubero-Castan, Manager for Sustainable IT Systems Project at EPFL Sustainability. Following the presentations, attendees had the opportunity to engage with the panel in a lively Q&A session, fostering thoughtful conversations on the pivotal role of research data production and storage for tackling the goals of sustainability. The event was held on April 18th, 2024, thanks to the organization of the RDM Team of EPFL Library. You can find here the files of the presentations. You can learn more here about the EPFL Data Champions here, https://go.epfl.ch/datachampions.

Timelapse: Geneva Lake, in front of Chexbres – 2019

V. Kindschi 

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019.

German Democratic Radio

A. Thiermann 

Aesthetics of Conservation; Aesthetics of Extinction. The Chilean Pavilion at the 59th Art Biennale

A. Thiermann 

Alfredo Thiermann in Conversation with Sarah Alberani at the Accademia Tedesca Roma Villa Massimo.

Type and History

A. Thiermann 

The Broadcasting House: Architecture, Type, and the Culture Industry

A. Thiermann 

Infrastructures of Solidarity, Infrastructures of Totalitarism

A. Thiermann 

Between 11 September 1973 and 11 March 1990, the silenced voices of many were dissolved into electromagnetic waves so they could be transmitted and heard in Chile. For sixteen years, the broadcasting house of the German Democratic Republic (GDR) – the Funkhaus in Nalepastrasse in Berlin– broadcast, every day, a radio programme with information, music, and news from Berlin to Chile. Hundreds of Chilean exiles and cultural and political figures passed through the Funkhaus to talk back to their distant country. Broadcast at night, ‘Chile al Día’ was listened to attentively and secretly from the beginning to the end of the dictatorship. Far from being an ephemeral phenomenon, the desire for global hegemony over the production and transmission of information through radio demanded large infrastructures and sophisticated buildings that were conceived as technical wonders as much as political agents. In this presentation, those buildings are analyzed and the programme is contextualised within the broader set of conflicts and political disputes that characterized the Cold War and still haunt us in the present.

Notes on Los Angeles

A. Thiermann 

Jean-Louis Cohen was a historian and curator of architecture who inspired and impacted the work of many. His unexpected passing this summer was a loss to the entire expanded field of architecture. A pioneer of transnational and transmedial histories of architecture, he was a cultural translator whose work and influence crossed boundaries between continents and epochs – from Paris to Moscow, Casablanca to Kharkiv, New York to Brasilia. He had the true gift to mediate and connect people and ideas within academia as well as beyond it. Based in between France and the US for most of his life, his work, impact, and network was profoundly transnational. This gathering – convened and chaired by Markus Lähteenmäki (UCL Institute of Advanced Studies) and Michał Murawski (UCL School of Slavonic and East European Studies) – brings together his former mentees, collaborators, interlocutors, friends and followers in and around the UK. The symposium presents a dozen short speeches that vary from anecdotes and recollections to reflections on his method and its impact and critical reconsiderations of historiography.

Comparison of Three Viral Nucleic Acid Preamplification Pipelines for Sewage Viral Metagenomics

X. Fernandez Cassi; T. Kohn 

Viral metagenomics is a useful tool for detecting multiple human viruses in urban sewage. However, more refined protocols are required for its effective use in disease surveillance. In this study, we investigated the performance of three different preamplification pipelines (specific to RNA viruses, DNA viruses or both) for viral genome sequencing using spiked-in Phosphate Buffered Saline and sewage samples containing known concentrations of viruses. We found that compared to the pipeline targeting all genome types, the RNA pipeline performed better in detecting RNA viruses in both spiked and unspiked sewage samples, allowing the detection of various mammalian viruses including members from the Reoviridae, Picornaviridae, Astroviridae and Caliciviridae. However, the DNA-specific pipeline did not improve the detection of mammalian DNA viruses. We also measured viral recovery by quantitative reverse transcription polymerase chain reaction and assessed the impact of genetic background (non-viral genetic material) on viral coverage. Our results indicate that viral recoveries were generally lower in sewage (average of 11.0%) and higher in Phosphate Buffered Saline (average of 23.4%) for most viruses. Additionally, spiked-in viruses showed lower genome coverage in sewage, demonstrating the negative effect of genetic background on sequencing. Finally, correlation analysis revealed a relationship between virus concentration and genome normalized reads per million, indicating that viral metagenomic sequencing can be semiquantitative.

How to Support Students to Develop Skills that Promote Sustainability

How to Support Students Giving Each Other Constructive Feedback, Especially When It Is Difficult to Hear

How teachers can use the 3T PLAY trident framework to design an activity that develops transversal skills

The conceptual foundations of innate immunity: Taking stock 30 years later

Pradeu Thomas; Thomma Bart T.P.H.; Girarding Stephen; B. Lemaitre 

While largely neglected over decades during which adaptive immunity captured most of the attention, innate immune mechanisms have now become central to our understanding of immunology. Innate immunity provides the first barrier to infection in vertebrates, and it is the sole mechanism of host defense in invertebrates and plants. Innate immunity also plays a critical role in maintaining homeostasis, shaping the microbiota, and in disease contexts such as cancer, neurodegeneration, metabolic syndromes, and aging. The emergence of the field of innate immunity has led to an expanded view of the immune system, which is no longer restricted to vertebrates and instead concerns all metazoans, plants, and even prokaryotes. The study of innate immunity has given rise to new concepts and language. Here, we review the history and definition of the core concepts of innate immunity, discussing their value and fruitfulness in the long run.

Radio-Activities: Architecture and Broadcasting in Cold War Berlin

A. Thiermann 

A historical and theoretical account of the city of Berlin from the intertwined perspectives of architecture, environmental, and media studies. In 1945, having occupied German territory, Soviet troops made two strategic moves: they dismantled the Deutschlandsender III radio transmission tower, the single tallest structure at the time in Europe, and they seized the Haus des Rundfunks in West Berlin, a monumental building designed by Hans Poelzig. These moves were crucial both symbolically and technically, as together they sparked what would become a veritable radio war between the Eastern and Western blocs during the Cold War. In Radio-Activities, Alfredo Thiermann Riesco investigates this spatial conflict as he interrogates the political, technological, and environmental dimensions of architecture at a time when buildings began to interact with the remote transmission of information. By its very nature, the medium of radio promised to evaporate the intrinsic material aspect of architecture; in fact, it did no such thing. By way of transscalar analyses, Thiermann Riesco pays particular attention to Berlin’s buildings, walls, transmission towers, factories, research institutions, and territorial organizations during the Cold War period, which enabled the production, reproduction, and transmission of sonic-based content across the divide of the Iron Curtain. In doing so he reveals underresearched continuities between politics, technology, media, and architecture, in the process reframing notions of national and transnational boundaries. A timely and fascinating study, Radio-Activities brilliantly interrogates the status and agency of buildings during a period-not unlike today’s-of increasingly hyperconnected, ubiquitous, and invisible modes of coexistence.

No Last One

A. Thiermann 

All That is Solid

Turba Tol – Hol Hol Tol

A. Thiermann 

Echo’s Chambers by Joseph Clarke (Book Review)

A. Thiermann 

Coming to Terms with Drawing

Drawing the Line

A. Thiermann 

Learning to Learn: Review of ‘The University Is Now on Air: Broadcasting Modern Architecture

A. Thiermann 

The House at the End of the World: On the Possibility of Architecture in Capitalist Ruins

A. Thiermann 

Radio as Architecture: Notes toward the Redefinition of the Berlin Walls

Radio-Activities

A. Thiermann 

The Ground as Forensic Evidence: Alfredo Thiermann in Conversation with Eyal Weizman

A. Thiermann 

White on White

What Does an Invisible Architecture Look Like

A. Thiermann 

Dynamics of the Void

A. Thiermann 

Dynamics of the Void

A. Thiermann 

Artefact Nr. I

A. Thiermann 

Artefact Nr. I

A. Thiermann 

Artefacto Nr. I

A. Thiermann 

Artefact Nr. I.

A. Thiermann 

Characterization of the gut-bone marrow axis through bile acid signaling

Studies of crystal collimation for heavy ion operation at the LHC

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Querying the Digital Archive of Science: Distant Reading, Semantic Modelling and Representation of Knowledge

Hybrid organic/metal-oxide shells on semiconductor nanocrystals via colloidal atomic layer deposition

Electrical and Optical Manifestations of Flat Band Physics in Van der Waals Materials

Plasmonically enhanced molecular junctions for investigation of atomic-scale fluctuations in self-assembled monolayers

Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

S-acylation and lipid exchange at the ER-Golgi membrane contact sites regulate pathogen entry in human cells

Serial Dependence in Human Visual Perception and Decision-Making

Data-Driven Methods for Controller Design in Atomic Force Microscopy

Aesthetics of Extinction, Aesthetics of Conservation: the Chilean Pavilion at the 59th Venice Art Biennale

A. Thiermann 

Quantum-mechanical effects in photoluminescence from thin crystalline gold films

A. R. Bowman; A. Rodríguez Echarri; F. Kiani Shahvandi; F. Iyikanat; T. Tsoulos et al. 

Luminescence constitutes a unique source of insight into hot carrier processes in metals, including those in plasmonic nanostructures used for sensing and energy applications. However, being weak in nature, metal luminescence remains poorly understood, its microscopic origin strongly debated, and its potential for unraveling nanoscale carrier dynamics largely unexploited. Here, we reveal quantum-mechanical effects in the luminescence emanating from thin monocrystalline gold flakes. Specifically, we present experimental evidence, supported by first-principles simulations, to demonstrate its photoluminescence origin (i.e., radiative emission from electron/hole recombination) when exciting in the interband regime. Our model allows us to identify changes to the measured gold luminescence due to quantum-mechanical effects as the gold film thickness is reduced. Excitingly, such effects are observable in the luminescence signal from flakes up to 40 nm in thickness, associated with the out-of-plane discreteness of the electronic band structure near the Fermi level. We qualitatively reproduce the observations with first-principles modeling, thus establishing a unified description of luminescence in gold monocrystalline flakes and enabling its widespread application as a probe of carrier dynamics and light-matter interactions in this material. Our study paves the way for future explorations of hot carriers and charge-transfer dynamics in a multitude of material systems.

Quantifying the effects of rainfall temporal variability on landscape evolution processes

T. Lian; N. Peleg; S. Bonetti 

Rainfall characteristics such as intensity, duration, and frequency are key determinants of the hydro-geomorphological response of a catchment. The presence of non-linear and threshold effects makes the relationship between rainfall variability and geomorphological dynamics difficult to quantify. This is particularly relevant under predicted exacerbated erosion induced by an intensification of hydroclimatic extremes. In this study, we quantify the effects of changes in rainfall temporal variability on catchment morphology and sediment erosion, transport, and deposition across a broad spectrum of grain size distributions and climatic conditions. To this purpose, multiple rainfall realizations are simulated using a numerical rainfall generator, while geomorphic response and soil erosion dynamics are assessed through a landscape evolution model (CAESAR-Lisflood). Virtual catchments are used for the numerical experiments and simulations are conducted over centennial time scales. Simulation results show that higher rainfall temporal variability increases net sediment discharge, domain erosion and deposition volumes, and secondary channel development. Particularly, dry regions respond more actively to rainfall variations and finer grain size configurations amplify the hydro-geomorphological response. We find that changes in erosion rates due to rainfall variations can be expressed as a power-law function of the ratio of rainfall temporal variabilities (quantified here through the Gini index). Results are further supported by long-term observational data and simulations over real catchments. Such quantification of the effects of predicted changes in rainfall patterns on catchment hydro-geomorphic response, as mediated by local soil properties, is crucial to forecasting modifications in sediment dynamics due to climate change.

Towards a metabolic theory of catchments: scaling of water and carbon fluxes with size

F. Bassani; S. Fatichi; S. Bonetti 

Allometric scaling relations are widely used to link biological processes in nature. They are typically expressed as power laws, postulating that the metabolic rate of an organism scales as its mass to the power of an allometric exponent, which ranges between 2/3 and 3/4. Several studies have shown that such scaling laws hold also for natural ecosystems, including individual trees and forests, riverine metabolism, and river network organization. Here, we focus on allometric relations at watershed scale to investigate “catchment metabolism”, defined as the set of ecohydrological and biogeochemical processes through which the catchment maintains its structure and reacts to the environment. By revising existing plant size-density relationships and integrating them across large-scale domains, we show that the ecohydrological fluxes (representative of metabolic rates of a large and diverse vegetation assemblage) occurring at the catchment scale are invariant with respect to its average above-ground biomass, while they scale linearly with the basin size. We verify our theory with hyper-resolution ecohydrological simulations across the European Alps, which represent an ideal case study due to the large elevation gradient affecting the availability of energy and water resources. Deviations from the isometric scaling are observed and ascribable to energy limitations at high elevations. Remote sensing data from semiarid and tropical basins are also used to show that the observed scaling of water and carbon fluxes with size holds across a broad spectrum of climatic conditions.

Biohybrid Superorganisms—On the Design of a Robotic System for Thermal Interactions With Honeybee Colonies

R. Barmak; D. N. Hofstadler; M. Stefanec; L. Piotet; R. Cherfan et al. 

Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where collaboration and division of labor enhance survival of the whole colony, and are thus considered “superorganisms”. Historically, studying behaviors involving large groups under natural conditions posed significant challenges, often leading to experiments with a limited number of organisms under artificial laboratory conditions that incompletely reflected the animals’ natural habitat. A promising approach to exploring animal behaviors, beyond observation, is using robotics that produce stimuli to interact with the animals. However, their application has predominantly been constrained to small groups in laboratory conditions. Here we present the design choices and development of a biocompatible robotic system intended to integrate with complete honeybee colonies in the field, enabling exploration of their collective thermoregulatory behaviors via arrays of thermal sensors and actuators. We tested the system’s ability to capture the spatiotemporal signatures of two key collective behaviors. A 121-day observation revealed thermoregulation activity of the broodnest area during the foraging season, followed by clustering behavior during winter. Then we demonstrated the system’s ability to influence the colony by guiding a cluster of bees along an unnatural trajectory, via localized thermal stimuli emitted by two robotic frames. These results showcase a system with the capability to experimentally modulate honeybee colonies from within, as well as to unobtrusively observe their dynamics over extended periods. Such biohybrid systems uniting complete societies of thousands of animals and interactive robots can be used to confirm or challenge the existing understanding of complex animal collectives.

Dataset to accompany publication “Quantum-mechanical effects in photoluminescence from thin crystalline gold films”

A. R. Bowman; Á. Rodríguez Echarri; F. Kiani Shahvandi; F. Iyikanat; T. Tsoulos et al. 

This dataset accompanies the publication “Quantum-mechanical effects in photoluminescence from thin crystalline gold films” published in Light: Science & Applications (https://doi.org/10.1038/s41377-024-01408-2). The data can be used to reproduce plots 1-4 in the main text and all plots with data in the supporting information. This data was generated through a combination of raman spectroscopy, microscale absorption meaurements and density functional theory modelling. All files are in excel spreadsheets and easily readable, except compressed files which have a readme file in the appropriate section. The abstract for the associated paper is as follows: Luminescence constitutes a unique source of insight into hot carrier processes in metals, including those in plasmonic nanostructures used for sensing and energy applications. However, being weak in nature, metal luminescence remains poorly understood, its microscopic origin strongly debated, and its potential for unravelling nanoscale carrier dynamics largely unexploited. Here, we reveal quantum-mechanical effects emanating in the luminescence from thin monocrystalline gold flakes. Specifically, we present experimental evidence, supported by first-principles simulations, to demonstrate its photoluminescence origin (i.e., radiative emission from electron/hole recombination) when exciting in the interband regime. Our model allows us to identify changes to the measured gold luminescence due to quantum-mechanical effects as the gold film thickness is reduced. Excitingly, such effects are observable in the luminescence signal from flakes up to 40 nm in thickness, associated with the out-of-plane discreteness of the electronic band structure near the Fermi level. We qualitatively reproduce the observations with first-principles modelling, thus establishing a unified description of luminescence in gold monocrystalline flakes and enabling its widespread application as a probe of carrier dynamics and light-matter interactions in this material. Our study paves the way for future explorations of hot carriers and charge-transfer dynamics in a multitude of material systems. 

Impact of CO2-rich seawater injection on the flow properties of basalts

E. Stavropoulou; C. Griner; L. Laloui 

Permanent CO storage in basalts through mineralisation offers a promising solution for reducing carbon emissions and mitigating climate change. This study focuses on the impact of potential mineralisation on the flow properties of the basaltic material. Fluid flow evolution before and after exposure to CO dissolved in seawater is measured in terms of hydraulic conductivity and permeability under field-like conditions over 1 to 3.5 months. Permeability reduction of up to one order of magnitude suggests that porosity decreases due to mineral precipitation after CO exposure. X-ray tomography measurements of the tested cores reveal a maximum porosity decrease of 1.5% at the given resolution (50 μm/px). To better understand eventual modifications of the connected pore network after mineralisation, fluid flow simulations are performed on the 3D pore network of the material that is reconstructed directly from the acquired x-ray images. A double porosity is proposed: macro-porosity as visible from the tomographies (pores >50 μm) and micro-porosity (pores <50 μm). To reproduce the post-CO exposure flow, reduction of macro-porosity is not enough. Instead, a decrease of the micro-pores is necessary by up to 43%. The experimental and numerical results suggest that potential mineralisation can substantially modify the pore space of the intact basaltic material and consequently impact storage efficiency if flow is not preserved.

Material Reform: Building for a Post-Carbon Future

D. Amica; C. Malterre-Barthes; J. Gough; S. S. Islam; P. Gormley et al. 

This acclaimed and bestselling book by design and research practice Material Cultures brings together a series of short, incisive essays on the cultures, systems, and infrastructures that shape the architectural industry and the destructive ecologies it fosters. Texts centred around key topics including resources, maintenance, agriculture, land use, and value are interwoven with a visual essay capturing the impact of industrialisation on landscapes at different scales. The building practices dominating contemporary architecture are rooted in the exploitation of people and the degradation of our landscapes. Here, Paloma Gormley, Summer Islam, and George Massoud explore how this has come about and how alternative systems, with holistic approaches to the built environment, might be formulated. Through text and visuals, concepts and practice, Material Reform explores how developing a direct relationship with materials can help us find new languages with the potential to supersede those we have inherited from a narrow lineage of authors. These discursive threads come together to form a vital sourcebook for rethinking our relationships to materials, land, and development, in all their crucial intersections. This new edition has been updated for 2024.

Architecture of a decentralised decision support system for futuristic beehives

V. Komasilovs; R. Mills; A. Kviesis; F. Mondada; A. Zacepins 

Honeybees are essential to human society, providing pollination services globally as well as producing honey and other valuable products. Effective management of apiaries should not only rely on beekeeper knowledge and skill, but also incorporate new information technologies. The options to identify, predict and prevent beekeeping problems are becoming more affordable and applicable. The interdisciplinary Horizon 2020 project HIVEOPOLIS focuses on developing a new approach in beekeeping, by creating novel mechatronic beehives and implementing new bio-hybrid ideas. These intelligent beehives aim to help honeybees to cope with adverse environmental factors and increase the survival rate of the bee colonies. This paper focuses on the software architecture design for these intelligent beehives, providing infrastructure for data management and decision support system operation. The presented infrastructure is suitable for highly dynamic and diverse environments where a multitude of components interact and exchange information across technology domains (embedded, cloud, UIs) in a reliable and secure way. Besides user support, the decision support system built upon this infrastructure enables closed-loop automated decision making and control.

Comment une situation d’investigation policière fait évoluer les conceptions d’élèves de troisième sur l’ADN

R. Saavedra; P. Marzin-janvier; I. Girault 

The work presented focuses on the analysis of a police investigation implemented in the computing environment SCY-Lab. The prime objective is to check if the implementation of the situation helps pupils change their conceptions concerning the DNA molecule on the one hand and pupils’ representations of the biological analysis of a crime scene that refers to the professional practices of the technician in scientific analysis. The second objective is to examine the problem-solving processes pupils are faced with. The results of a test with four volunteer pupils at the end of grade 9 show that they are more familiar with the structural aspects of DNA (sequence of nucleotides and double helix) and with its biological level (in the cell and in the core). As far as the understanding of the techniques of biological analysis used as part of a police investigation is concerned, the findings reveal that pupils still do not have a clear vision of what the term “DNA profile” means, even if they have understood how genetic profiles can be obtained. The pre-experimentation was useful to improve the resources, instructions and activities performed on the platform. They will then be given to a greater number of pupils.

TSLAM: a tag-based object-centered monocular navigation system for augmented manual woodworking.

S. Andrea; H-B. Yang; G. Julien; W. Yves 

TimberSLAM (TSLAM) is an object-centered, tag-based visual self-localization and mapping (SLAM) system for monocular RGB cameras. It was specifically developed to support a robust and augmented reality pipeline for close-range, noisy, and cluttered fabrication sequences that involve woodworking operations, such as cutting, drilling, sawing, and screwing with multiple tools and end-effectors. By leveraging and combining multiple open-source projects, we obtain a functional pipeline that can map, three-dimensionally reconstruct, and finally provide a robust camera pose stream during fabrication time to overlay an execution model with its digital-twin model, even under close-range views, dynamic environments, and heavy scene obstructions. To benchmark the proposed navigation system under real fabrication scenarios, we produce a data set of 1344 closeups of different woodworking operations with multiple tools, tool heads, and varying parameters (e.g., tag layout and density). The evaluation campaign indicates that TSLAM is satisfyingly capable of detecting the camera’s millimeter position and subangular rotation during the majority of fabrication sequences. The reconstruction algorithm’s accuracy is also gauged and yields results that demonstrate its capacity to acquire shapes of timber beams with up to two preexisting joints. We have made the entire source code, evaluation pipeline, and data set open to the public for reproducibility and the benefit of the community.

Water weakening and the compressive brittle strength of carbonates: Influence of fracture toughness and static friction

C. Noël; B. Fryer; P. Baud; M. Violay 

Water is ubiquitous within the pore space of rocks and has been shown to affect their physical and mechanical behaviour. Indeed, water can act on the rock strength via mechanical (i.e., reducing the effective stresses) or chemical effects (e.g., mineral dissolution, mineral alteration, subcritical crack growth, etc.). As rock macroscopic strength is controlled by both fracture toughness and friction at the grain-scale, these parameters should also be affected in presence of water. While some recent studies have measured the effect of water on both fracture toughness and frictional parameters to constrain the water weakening of porous rock compressive strength, the physical parameters, or rock characteristics, that influence this weakening are as of yet unclear. Here, we report a series of laboratory experiments in order to determine the influence of a water-saturated, as opposed to dry, environment on five limestones’ strengths. The uniaxial compressive strength, the mode-I fracture toughness and the static friction parameters are of interest. The experiments show that, for the tested limestones, water-saturated conditions provoke a reduction of the uniaxial compressive strength by up to 53 %. This reduction is accompanied by a reduction of the mode-I fracture toughness by up to 34 % and of the static friction by up to 16 %. Even though the water weakening of the uniaxial compressive strength is not influenced by the sample porosity, the mode-I fracture toughness reduction in the presence of water is accentuated for high-porosity limestones. Additionally, low porosity limestones appear to promote higher static friction reductions in water-saturated environments.

Integration of the Pilatus3 detector for soft X-ray diagnostics on TCV

S. Masillo 

Siloxide tripodal ligands as a scaffold for stabilizing lanthanides in the +4 oxidation state

M. C. G. Tricoire; F-C. Hsueh; M. R. Keener; T. Rajeshkumar; R. Scopelliti et al. 

Synthetic strategies to isolate molecular complexes of lanthanides, other than cerium, in the +4 oxidation state remain elusive, with only four complexes of Tb(iv) isolated so far. Herein, we present a new approach for the stabilization of Tb(iv) using a siloxide tripodal trianionic ligand, which allows the control of unwanted ligand rearrangements, while tuning the Ln(iii)/Ln(iv) redox-couple. The Ln(iii) complexes, [LnIII((OSiPh2Ar)3-arene)(THF)3] (1-LnPh) and [K(toluene){LnIII((OSiPh2Ar)3-arene)(OSiPh3)}] (2-LnPh) (Ln = Ce, Tb, Pr), of the (HOSiPh2Ar)3-arene ligand were prepared. The redox properties of these complexes were compared to those of the Ln(iii) analogue complexes, [LnIII((OSi(OtBu)2Ar)3-arene)(THF)] (1-LnOtBu) and [K(THF)6][LnIII((OSi(OtBu)2Ar)3-arene)(OSiPh3)] (2-LnOtBu) (Ln = Ce, Tb), of the less electron-donating siloxide trianionic ligand, (HOSi(OtBu)2Ar)3-arene. The cyclic voltammetry studies showed a cathodic shift in the oxidation potential for the cerium and terbium complexes of the more electron-donating phenyl substituted scaffold (1-LnPh) compared to those of the tert-butoxy (1-LnOtBu) ligand. Furthermore, the addition of the -OSiPh3 ligand further shifts the potential cathodically, making the Ln(iv) ion even more accessible. Notably, the Ce(iv) complexes, [CeIV((OSi(OtBu)2Ar)3-arene)(OSiPh3)] (3-CeOtBu) and [CeIV((OSiPh2Ar)3-arene)(OSiPh3)(THF)2] (3-CePh), were prepared by chemical oxidation of the Ce(iii) analogues. Chemical oxidation of the Tb(iii) and Pr(iii) complexes (2-LnPh) was also possible, in which the Tb(iv) complex, [TbIV((OSiPh2Ar)3-arene)(OSiPh3)(MeCN)2] (3-TbPh), was isolated and crystallographically characterized, yielding the first example of a Tb(iv) supported by a polydentate ligand. The versatility and robustness of these siloxide arene-anchored platforms will allow further development in the isolation of more oxidizing Ln(iv) ions, widening the breadth of high-valent Ln chemistry.|Robust arene-anchored polydentate siloxide ligands allow to control unwanted ligand rearrangements for the isolation of Tb(iv) complexes thus enabling the use of the Tb(iii)/Tb(iv) couple for the separation of Tb from the neighboring Dy ion.

High-Permittivity Polysiloxanes for Bright, Stretchable Electroluminescent Devices

J. von Szczepanski; J. Wolf; W-H. Hu; R. Schneider; P. M. Danner et al. 

Stretchable alternating current electroluminescent (ACEL) devices have a bright future in wearable electronics and soft robotics. Still, their market application is hindered by high operating voltages. The voltage can be reduced by increasing the relative permittivity of the dielectric elastomer in the emissive layer. Here, a fluorine-free high-permittivity silicone elastomer functionalized with cyanopropyl side groups, specially designed for application in stretchable ACEL devices, is introduced. The polar silicone elastomer exhibits excellent mechanical properties and a dielectric permittivity four times higher than commercial PDMS. Light-emitting devices based on the polar elastomer reach 7.5 times higher maximum luminance at the same electric field than PDMS-based devices and turn on at a 50% lower electric field. Besides, the polar elastomer-based devices perform better than all materials tested in literature in achieving high luminance at low electric fields. Stretchable ACEL devices are built from the polar elastomer which shows bright and uniform light emission and can be operated up to 50% strain. The high-permittivity silicones are promising materials for stretchable ACEL devices and can help their breakthrough to market application by overcoming the drawback of high operating voltages.|A high-permittivity, nitrile-functional silicone elastomer for application in stretchable electroluminescent devices is introduced. The polar elastomer emissive layer reaches significantly higher luminance and needs lower operating voltages than an emissive layer based on commercially available PDMS. Besides, the polar elastomer can be used to build bright and stretchable devices in a simple bottom-up procedure. image

An extension of the stochastic sewing lemma and applications to fractional stochastic calculus

T. Matsuda; N. Perkowski 

We give an extension of Le’s stochastic sewing lemma. The stochastic sewing lemma proves convergence in $L_m$ of Riemann type sums $\sum _{[s,t] \in \pi } A_{s,t}$ for an adapted two-parameter stochastic process A, under certain conditions on the moments of $A_{s,t}$ and of conditional expectations of $A_{s,t}$ given $\mathcal F_s$ . Our extension replaces the conditional expectation given $\mathcal F_s$ by that given $\mathcal F_v$ for $v

Forum Of Mathematics Sigma

2024-04-11

DOI : 10.1017/fms.2024.32

A bridge between trust and control: computational workflows meet automated battery cycling

P. Kraus; E. Bainglass; F. F. Ramirez; E. Svaluto-Ferro; L. Ercole et al. 

Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We successfully interface off-the-shelf battery cycling hardware with the computational workflow management software AiiDA, allowing us to control experiments, while ensuring trust in the data by tracking its provenance. We design user interfaces compatible with this tooling, which span the inventory, experiment design, and result analysis stages. Other features, including monitoring of workflows and import of externally generated and legacy data are also implemented. Finally, the full software stack required for this work is made available in a set of open-source packages.

Capsizing due to friction-induced twist in the failure of stopper knots

P. Johanns; P. M. Reis 

We investigate the failure mechanism of stopper knots, with a particular focus on the figure -8 knot as a representative example. Stopper knots are widely used in climbing, sailing, racket stringing, and sewing to maintain tension in ropes, strings, or threads while preventing them from passing through an orifice. Combining high -precision model experiments and Finite Element Analyses, we systematically explore the influence of frictional interactions and their role in the build-up of mechanical twist. Our findings reveal that the failure of stopper knots via capsizing, which involves configurational alterations of the filament, is primarily due to friction -induced twisting when loading the knot against a restraining plate containing a clearance hole. Our study offers a comprehensive understanding of the mechanical behavior of stopper knots under diverse loading conditions, thereby providing crucial insights for their reliable application across various domains.

A CTCF-dependent mechanism underlies the Hox timer relation to a segmented body plan

H. Rekaik; D. Duboule 

During gastrulation, Hox genes are activated in a timesequence that follows the order of the genes along their clusters. This property, which is observed in all animals that develop following a progressive rostral-to-caudal morphogenesis, is associated with changes in the chromatin structure and epigenetic profiles of Hox clusters, suggesting a process at least partly based on sequential gene accessibility. Here, we discuss recent work on this issue, as well as a possible mechanism based on the surprising conservation in both the distribution and orientation of CTCF sites inside vertebrate Hox clusters.

Gradient High-Q Dielectric Metasurfaces for Broadband Sensing and Control of Vibrational Light-Matter Coupling

F. U. Richter; I. Sinev; S. Zhou; A. Leitis; S-H. Oh et al. 

Surface-enhanced infrared absorption spectroscopy (SEIRA) has emerged as a powerful technique for ultrasensitive chemical-specific analysis. SEIRA can be realized by employing metasurfaces that can enhance light-matter interactions in the spectral bands of molecular vibrations. Increasing sample complexity emphasizes the need for metasurfaces that can operate simultaneously at different spectral bands, both accessing rich spectral information over a broad band, and resolving subtle differences in the absorption fingerprints through narrow-band resonances. Here, a novel concept of resonance-gradient metasurfaces is introduced, where the required spectral selectivity is achieved via local high-quality-factor (high-Q) resonances, while the continuous coverage of a broad band is enabled by the gradual adjustment of the unit-cell dimensions along the planar structure. The highly tailorable design of the gradient metasurfaces provides flexibility for shaping the spectral sampling density to match the relevant bands of target analytes while keeping a compact device footprint. The versatility of the gradient metasurfaces is demonstrated through several sensing scenarios, including polymer mixture deconvolution, detecting a multistep bioassay, and identification of the onset of vibrational strong coupling regime. The proposed gradient-resonance platform significantly contributes to the rapidly evolving landscape of nonlocal metasurfaces, enabling applications in molecular detection and analysis of fundamental light-matter interaction phenomena.

SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

J. A. Borrel; J. Waser 

We report the detailed background for the discovery and development of the synthesis of homopropargylic azides by the azidoalkynylation of alkenes. Initially, a strategy involving SOMOphilic alkynes was adopted, but only resulted in a 29% yield of the desired product. By switching to a radical-polar crossover approach and after optimization, a high yield (72%) of the homopropargylic azide was reached. Full insights are given about the factors that were essential for the success of the optimization process.

Dielectric elastomer actuator-based valveless pump as Fontan failure assist device: introduction and preliminary study

A. Benouhiba; A. M. Walter; S. E. Jahren; T. G. Martinez; F. Clavica et al. 

OBJECTIVES: Fontan failure refers to a condition in which the Fontan circulation, a surgical procedure used to treat certain congenital heart defects, becomes insufficient, leading to compromised cardiac function and potential complications. This in vitro study therefore investigates the feasibility of bladeless impedance-driven cavopulmonary assist device via dielectric elastomer actuator (DEA) as a means to address Fontan failure. METHODS: A cavopulmonary assist device, constructed using DEA technologies and employing the impedance pump concept, is subjected to in vitro testing within a closed-loop setup. This study aims to assess the device’s functionality and performance under controlled conditions, providing valuable insights into its potential application as a cavopulmonary assistive technology. RESULTS: The DEA-based pump, measuring 50 mm in length and 30 mm in diameter, is capable of achieving substantial flow rates within a closed-loop setup, reaching up to 1.20 l/min at an activation frequency of 4 Hz. It also provides a broad range of working internal pressures (<10 to >20 mmHg). Lastly, the properties of the flow (direction, magnitude, etc.) can be controlled by adjusting the input signal parameters (frequency, amplitude, etc.). CONCLUSIONS: In summary, the results suggest that the valveless impedance-driven pump utilizing DEA technology is promising in the context of cavopulmonary assist devices. Further research and development in this area may lead to innovative and potentially more effective solutions for assisting the right heart, ultimately benefiting patients with heart-related health issues overall, with a particular focus on those experiencing Fontan failure.

Tree diversity reduces variability in sapling survival under drought

H. Blondeel; J. Guillemot; N. Martin-StPaul; A. Druel; S. Bilodeau-Gauthier et al. 

Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantations. We conducted an analysis of seedling and sapling survival from 34 globally distributed tree diversity experiments (363,167 trees, 168 species, 3744 plots, 7 biomes) to answer two questions: (1) Do drought and tree diversity alter the mean and variability in plot-level tree survival, with higher and less variable survival as diversity increases? and (2) Do species that survive poorly in monocultures survive better in mixtures and do specific functional traits explain monoculture survival? Tree species richness reduced variability in plot-level survival, while functional diversity (Rao’s Q entropy) increased survival and also reduced its variability. Importantly, the reduction in survival variability became stronger as drought severity increased. We found that species with low survival in monocultures survived comparatively better in mixtures when under drought. Species survival in monoculture was positively associated with drought resistance (indicated by hydraulic traits such as turgor loss point), plant height and conservative resource-acquisition traits (e.g. low leaf nitrogen concentration and small leaf size). Synthesis. The findings highlight: (1) The effectiveness of tree diversity for decreasing the variability in seedling and sapling survival under drought; and (2) the importance of drought resistance and associated traits to explain altered tree species survival in response to tree diversity and drought. From an ecological perspective, we recommend mixing be considered to stabilize tree survival, particularly when functionally diverse forests with drought-resistant species also promote high survival of drought-sensitive species.|Rising climate extremes, such as drought, can cause major uncertainty in the survival of young trees. Tree diversity can reduce survival variability and stabilize tree survival. Functionally diverse communities with drought-tolerant species can promote the survival of drought-sensitive species.image

Probing structural and dynamic properties of MAPbCl3 hybrid perovskite using Mn2+ EPR

G. Usevicius; J. Turcak; Y. Zhang; A. Eggeling; Z. Einoryte et al. 

Hybrid methylammonium (MA) lead halide perovskites have emerged as materials exhibiting excellent photovoltaic performance related to their rich structural and dynamic properties. Here, we use multifrequency (X-, Q-, and W-band) electron paramagnetic resonance (EPR) spectroscopy of Mn2+ impurities in MAPbCl(3) to probe the structural and dynamic properties of both the organic and inorganic sublattices of this compound. The temperature dependent continuous-wave (CW) EPR experiments reveal a sudden change of the Mn2+ spin Hamiltonian parameters at the phase transition to the ordered orthorhombic phase indicating its first-order character and significant slowing down of the MA cation reorientation. Pulsed EPR experiments are employed to measure the temperature dependences of the spin-lattice relaxation T-1 and decoherence T-2 times of the Mn2+ ions in the orthorhombic phase of MAPbCl(3) revealing a coupling between the spin center and vibrations of the inorganic framework. Low-temperature electron spin echo envelope modulation (ESEEM) experiments of the protonated and deuterated MAPbCl(3) analogues show the presence of quantum rotational tunneling of the ammonium groups, allowing to accurately probe their rotational energy landscape.

Dalton Transactions

2024-04-03

DOI : 10.1039/d4dt00116h

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

P. E. Van Gerwen; K. R. Briling; Y. Calvino Alonso; M. Franke; C. Corminboeuf 

In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based models to methods based on the three-dimensional structure of reactants and products. In tandem, many representations have been developed to predict experimental targets, which may hold promise for barrier prediction as well. Here, we bring together all of these efforts and benchmark various methods (Morgan fingerprints, the DRFP, the CGR representation-based Chemprop, SLATMd, B2Rl2, EquiReact and language model BERT + RXNFP) for the prediction of computed activation barriers on three diverse datasets.|We benchmark various methods for the prediction of computed activation barriers on three diverse datasets.

Quantum radio astronomy: Data encodings and quantum image processing

T. Brunet; E. E. Tolley; S. Corda; R. Ilic; P. C. Broekema et al. 

We explore applications of quantum computing for radio interferometry and astronomy using recent developments in quantum image processing. We evaluate the suitability of different quantum image representations using a toy quantum computing image reconstruction pipeline, and compare its performance to the classical computing counterpart. For identifying and locating bright radio sources, quantum computing can offer an exponential speedup over classical algorithms, even when accounting for data encoding cost and repeated circuit evaluations. We also propose a novel variational quantum computing algorithm for self -calibration of interferometer visibilities, and discuss future developments and research that would be necessary to make quantum computing for radio astronomy a reality.

Comprehensive Memory Safety Validation: An Alternative Approach to Memory Safety

K. Huang; M. Payer; Z. Qian; J. Sampson; G. Tan et al. 

Comprehensive memory safety validation identifies the memory objects whose accesses provably comply with all classes of memory safety, protecting them from memory errors elsewhere at low overhead. We assess the breadth and depth of comprehensive memory safety validation.

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

G. A. Pavliotis; A. Zanoni 

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear system which is constructed by imposing appropriate conditions on the moments of the invariant distribution of the mean field limit and on the quadratic variation of the process. Our approach is easy to implement as it only requires the approximation of the moments via the ergodic theorem and the solution of a low-dimensional linear system. Moreover, we prove that our estimator is asymptotically unbiased in the limits of infinite data and infinite number of particles (mean field limit). In addition, we present several numerical experiments that validate the theoretical analysis and show the effectiveness of our methodology to accurately infer parameters in systems of interacting particles.

A setup for hard x-ray time-resolved resonant inelastic x-ray scattering at SwissFEL

H-Y. Chen; R. B. Versteeg; R. Mankowsky; M. Puppin; L. M. Diniz Leroy et al. 

We present a new setup for resonant inelastic hard x-ray scattering at the Bernina beamline of SwissFEL with energy, momentum, and temporal resolution. The compact R = 0.5 m Johann-type spectrometer can be equipped with up to three crystal analyzers and allows efficient collection of RIXS spectra. Optical pumping for time-resolved studies can be realized with a broad span of optical wavelengths. We demonstrate the performance of the setup at an overall similar to 180 meV resolution in a study of ground-state and photoexcited (at 400 nm) honeycomb 5d iridate alpha-Li2IrO3. Steady-state RIXS spectra at the iridium L-3-edge (11.214 keV) have been collected and are in very good agreement with data collected at synchrotrons. The time-resolved RIXS transients exhibit changes in the energy loss region <2 eV, whose features mostly result from the hopping nature of 5d electrons in the honeycomb lattice. These changes are ascribed to modulations of the Ir-to-Ir inter-site transition scattering efficiency, which we associate to a transient screening of the on-site Coulomb interaction. (c) 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

X. Zheng; X. Hu; J. Lu; R. Arista; J. Lentes et al. 

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Traditional design methods heavily rely on domain expert knowledge using documents to define assembly solutions which are later verified through simulations. However, these document -centric approaches cannot provide graphical notations for engineers to efficiently understand the entire assembly process. Moreover, it is difficult to analyze the performance of the designed assembly processes using simulations since the simulation models have to be developed based on the documents manually rather than be generated automatically from the design models. In this paper, a semantic -driven approach is proposed to support aircraft assembly process formalism and performance analysis. First, meta -models of aircraft assembly processes are developed based on SysML and discrete -event simulation models using a semantic modeling language named KARMA. Then an application ontology is defined for generating semantic models from KARMA architecture models to capture domain knowledge, system requirements and simulation model information of the aircraft assembly process. A model transformer is developed to transform the KARMA models to discrete -event simulation models based on the application ontology. Then the generated simulation models are executed to obtain the simulation results for verifying the designed assembly process. Finally, the obtained simulation results are used to support decision -making of selecting the optimal aircraft assembly process. A case study is conducted to verify the proposed method.

Stellar Metallicities and Gradients in the Isolated, Quenched Low-mass Galaxy Tucana

S. W. Fu; D. R. Weisz; E. Starkenburg; N. Martin; F. J. Mercado et al. 

We measure the metallicities of 374 red giant branch (RGB) stars in the isolated, quenched dwarf galaxy Tucana using Hubble Space Telescope (HST) narrow-band (F395N) Calcium H & K (CaHK) imaging. Our sample is a factor of similar to 7 similar to 7 larger than what is published. Our main findings are: (i) A global metallicity distribution function (MDF) with <[Fe/H]>=-1.55(-0.04)(+0.04) and( sigma)[Fe/H]= =0.54(-0.03)(+)(0.03) (ii) A metallicity gradient of -0.54 +/- 0.07-0.54 +/- 0.07 dex R-e(-1) (-2.1 +/- 0.3- dex kpc(-1)) over the extent of our imaging (similar to 2.5R(e)), which is steeper than literature measurements. Our finding is consistent with predicted gradients from the publicly-available FIRE-2 simulations, in which bursty star formation creates stellar population gradients and dark matter cores; (iii) Tucana’s bifurcated RGB has distinct metallicities: a blue RGB with <[Fe/H]>=-1.78(-0.06)(+0.06)<[Fe/H]>=-1.78(-0.06)(+0.06) and sigma([Fe/H])=0.44(-0.06)(+0.07 )and a red RGB with <[Fe/H]> = -1.08(-0.07)(+0.07 and alpha)[Fe/H] 0.42 +/- 0.06(iv) At fixed stellar mass, Tucana is more MR than MW satellites by similar to 0.4, but its blue RGB is chemically comparable to the satellites. Tucana’s MDF appears consistent with star-forming isolated dwarfs, though MDFs of the latter are not as well-populated; (v) similar to 2 similar to 2% of Tucana’s stars have [Fe/H]<-3[Fe/H]<-3 and 20% [Fe/H]>-1[Fe/H]>-1. We provide a catalog for community spectroscopic follow-up.

Twisted pair transmission line coil – a flexible, self-decoupled and robust element for 7 T MRI

J. Vliem; Y. Xiao; D. Wenz; L. Xin; W. Teeuwise et al. 

Objective: This study evaluates the performance of a twisted pair transmission line coil as a transceive element for 7 T MRI in terms of physical flexibility, robustness to shape deformations, and interelement decoupling. Methods: Each coil element was created by shaping a twisted pair of wires into a circle. One wire was interrupted at the top, while the other was interrupted at the bottom, and connected to the matching circuit. Electromagnetic simulations were conducted to determine the optimal number of twists per length (in terms of B,+ field efficiency, SAR efficiency, sensitivity to elongation, and interelement decoupling properties) and for investigating the fundamental operational principle of the coil through fields streamline visualisation. A comparison between the twisted pair coil and a conventional loop coil in terms of B,+ fields, maxSAR,0g, and stability of S,, when the coil was deformed was performed. Experimentally measured interelement coupling between individual elements of multichannel arrays was also investigated. Results: Increasing the number of twists per length resulted in a more physically robust coil. Poynting vector streamline visualisation showed that the twisted pair coil concentrated most of the energy in the near field. The twisted pair coil exhibited comparable B,+ fields and improved maxSAR,0g to the conventional coil but demonstrated exceptional stability with respect to coil deformation and a strong self-decoupling nature when placed in an array configuration. Discussion: The findings highlight the robustness of the twisted pair coil, showcasing its stability under shape variations. This coil holds great potential as a flexible RF coil for various imaging applications using multipleelement arrays, benefiting from its inherent decoupling.

Equilibria in Network Constrained Energy Markets

G. Como; F. Fagnani; L. Massai 

We study an energy market composed of producers who compete to supply energy to different markets and want to maximize their profits. The energy market is modeled by a graph representing a constrained power network where nodes represent the markets and links are the physical lines with a finite capacity connecting them. Producers play a networked Cournot game on such a network together with a centralized authority, called market maker, that facilitates the trade between geographically separate markets via the constrained power network and aims to maximize a certain welfare function. We first study the existence and uniqueness of Nash equilibria. Then, we prove an important result that links capacity bottlenecks in the power network and the emergence of price differences between different markets that are separated by saturated lines, a phenomenon that is often observed in real power networks.

Minimal regret state estimation of time-varying systems

J-S. Brouillon; F. Dorfler; G. F. Trecate 

Kalman and H-infinity filters, the most popular paradigms for linear state estimation, are designed for very specific specific noise and disturbance patterns, which may not appear in practice. State observers based on the minimization of regret measures are a promising alternative, as they aim to adapt to recognizable patterns in the estimation error. In this paper, we show that the regret minimization problem for finite horizon estimation can be cast into a simple convex optimization problem. For this purpose, we first rewrite linear time-varying system dynamics using a novel system level synthesis parametrization for state estimation, capable of handling both disturbance and measurement noise. We then provide a tractable formulation for the minimization of regret based on semi-definite programming. Both contributions make the minimal regret observer design easily implementable in practice. Finally, numerical experiments show that the computed observer can significantly outperform both H-2 and H-infinity filters.

Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control

A. Martin; L. Furieri; F. Dorfler; J. Lygeros; G. Ferrari-Trecate 

We consider control of dynamical systems through the lens of competitive analysis. Most prior work in this area focuses on minimizing regret, that is, the loss relative to an ideal clairvoyant policy that has noncausal access to past, present, and future disturbances. Motivated by the observation that the optimal cost only provides coarse information about the ideal closed-loop behavior, we instead propose directly minimizing the tracking error relative to the optimal trajectories in hindsight, i. e., imitating the clairvoyant policy. By embracing a system level perspective, we present an efficient optimization-based approach for computing follow-the-clairvoyant (FTC) safe controllers. We prove that these attain minimal regret if no constraints are imposed on the noncausal benchmark. In addition, we present numerical experiments to show that our policy retains the hallmark of competitive algorithms of interpolating between classical H-2 and H-infinity control laws – while consistently outperforming regret minimization methods in constrained scenarios thanks to the superior ability to chase the clairvoyant. Copyright (c) 2023 The Authors.

3D Printing of Double Network Granular Elastomers with Locally Varying Mechanical Properties

E. J. Baur; B. Tiberghien; E. Amstad 

Fast advances in the design of soft actuators and robots demand for new soft materials whose mechanical properties can be changed over short length scales. Elastomers can be formulated as highly stretchable or rather stiff materials and hence, are attractive for these applications. They are most frequently cast such that their composition cannot be changed over short length scales. A method that allows to locally change the composition of elastomers on hundreds of micrometer lengths scales is direct ink writing (DIW). Unfortunately, in the absence of rheomodifiers, most elastomer precursors cannot be printed through DIW. Here, 3D printable double network granular elastomers (DNGEs) whose ultimate tensile strain and stiffness can be varied over an unprecedented range are introduced. The 3D printability of these materials is leveraged to produce an elastomer finger containing rigid bones that are surrounded by a soft skin. Similarly, the rheological properties of the microparticle-based precursors are leveraged to cast elastomer slabs with locally varying stiffnesses that deform and twist in a predefined fashion. These DNGEs are foreseen to open up new avenues in the design of the next generation of smart wearables, strain sensors, prosthesis, soft actuators, and robots.|A novel ink composed of jammed precursor-loaded elastomeric microparticles that can be direct ink written into double network granular elastomers that can attain a wide range of stiffnesses and ultimate tensile strains is presented. Inks with different stiffnesses can be 3D printed into cm-sized structures with locally varying compositions and hence mechanical properties using commercial multinozzle 3D printers. image

Dopant-additive synergism enhances perovskite solar modules

B. Ding; Y. Ding; J. Peng; J. Romano-deGea; L. E. K. Frederiksen et al. 

Perovskite solar cells (PSCs) are among the most promising photovoltaic technologies owing to their exceptional optoelectronic properties 1,2 . However, the lower efficiency, poor stability and reproducibility issues of large-area PSCs compared with laboratory-scale PSCs are notable drawbacks that hinder their commercialization 3 . Here we report a synergistic dopant-additive combination strategy using methylammonium chloride (MACl) as the dopant and a Lewis-basic ionic-liquid additive, 1,3-bis(cyanomethyl)imidazolium chloride ([Bcmim]Cl). This strategy effectively inhibits the degradation of the perovskite precursor solution (PPS), suppresses the aggregation of MACl and results in phase-homogeneous and stable perovskite films with high crystallinity and fewer defects. This approach enabled the fabrication of perovskite solar modules (PSMs) that achieved a certified efficiency of 23.30% and ultimately stabilized at 22.97% over a 27.22-cm2 aperture area, marking the highest certified PSM performance. Furthermore, the PSMs showed long-term operational stability, maintaining 94.66% of the initial efficiency after 1,000 h under continuous one-sun illumination at room temperature. The interaction between [Bcmim]Cl and MACl was extensively studied to unravel the mechanism leading to an enhancement of device properties. Our approach holds substantial promise for bridging the benchtop-to-rooftop gap and advancing the production and commercialization of large-area perovskite photovoltaics.|A synergistic dopant-additive combination strategy using methylammonium chloride as the dopant and a Lewis-basic ionic-liquid additive is shown to enable the fabrication of perovskite solar modules achieving record certified performance and long-term operational stability.

Proliferation-driven mechanical compression induces signalling centre formation during mammalian organ development

N. P. Shroff; P. Xu; S. Kim; E. R. Shelton; B. J. Gross et al. 

Localized sources of morphogens, called signalling centres, play a fundamental role in coordinating tissue growth and cell fate specification during organogenesis. However, how these signalling centres are established in tissues during embryonic development is still unclear. Here we show that the main signalling centre orchestrating development of rodent incisors, the enamel knot (EK), is specified by a cell proliferation-driven buildup in compressive stresses (mechanical pressure) in the tissue. Direct mechanical measurements indicate that the stresses generated by cell proliferation are resisted by the surrounding tissue, creating a circular pattern of mechanical anisotropy with a region of high compressive stress at its centre that becomes the EK. Pharmacological inhibition of proliferation reduces stresses and suppresses EK formation, and application of external pressure in proliferation-inhibited conditions rescues the formation of the EK. Mechanical information is relayed intracellularly through YAP protein localization, which is cytoplasmic in the region of compressive stress that establishes the EK and nuclear in the stretched anisotropic cells that resist the pressure buildup around the EK. Together, our data identify a new role for proliferation-driven mechanical compression in the specification of a model signalling centre during mammalian organ development.|Shroff and colleagues report that cell proliferation induces localized mechanical compression in the tissue, driving the formation of the main mouse tooth signalling centre via differential YAP expression.

Spin-Reorientation-Driven Linear Magnetoelectric Effect in Topological Antiferromagnet Cu3TeO6

V. Kisicek; D. Dominko; M. Culo; Z. Rapljenovic; M. Kuvezdic et al. 

The search for new materials for energy -efficient electronic devices has gained unprecedented importance. Among the various classes of magnetic materials driving this search are antiferromagnets, magnetoelectrics, and systems with topological spin excitations. Cu3TeO6 is a material that belongs to all three of these classes. Combining static electric polarization and magnetic torque measurements with phenomenological simulations we demonstrate that magnetic -field -induced spin reorientation needs to be taken into account to understand the linear magnetoelectric effect in Cu3TeO6. Our calculations reveal that the magnetic field pushes the system from the nonpolar ground state to the polar magnetic structures. However, nonpolar structures only weakly differing from the obtained polar ones exist due to the weak effect that the field -induced breaking of some symmetries has on the calculated structures. Among those symmetries is the PT (1 over bar ‘) symmetry, preserved for Dirac points found in Cu3TeO6. Our findings establish Cu3TeO6 as a promising playground to study the interplay of spintronics-related phenomena.

Is There a Special Role for Ovarian Hormones in the Pathogenesis of Lobular Carcinoma?

R. L. Flaherty; G. Sflomos; C. Brisken 

Lobular carcinoma represent the most common special histological subtype of breast cancer, with the majority classed as hormone receptor positive. Rates of invasive lobular carcinoma in postmenopausal women have been seen to increase globally, while other hormone receptor-positive breast cancers proportionally have not followed the same trend. This has been linked to exposure to exogenous ovarian hormones such as hormone replacement therapy. Reproductive factors resulting in increased lifetime exposure to endogenous ovarian hormones have also been linked to an increased risk of lobular breast cancer, and taken together, these data make a case for the role of ovarian hormones in the genesis and progression of the disease. In this review, we summarize current understanding of the epidemiological associations between ovarian hormones and lobular breast cancer and highlight mechanistic links that may underpin the etiology and biology.

Stick-slip-to-stick transition of liquid oscillations in a U-shaped tube

A. Bongarzone; F. Gallaire 

The nonlinear decay of oscillations of a liquid column in a U-shaped tube is investigated within the theoretical framework of the projection method formalized by Bongarzone et al. [Chaos 31, 123124 (2021)]. Starting from the full hydrodynamic system supplemented by a phenomenological contact line model, this physics -inspired method uses successive linear eigenmode projections to simulate the relaxation dynamics of liquid oscillations in the presence of sliding triple lines. Each projection is shown to eventually induce a rapid loss of total energy in the liquid motion, thus contributing to its nonlinear damping. A thorough quantitative comparison with experiments by Dollet et al. [Phys. Rev. Lett. 124, 104502 (2020)] demonstrates that, in contradistinction with their simplistic one -degree -of -freedom model, the present approach not only describes well the transient stick -slip dynamics, but also correctly captures the global stick -slip to stick transition, as well as the residual exponentially decaying bulk motion following the arrest of the contact line, which has been so far overlooked by existing theoretical analyses but is clearly attested experimentally. This study offers a further contribution to rationalizing the impact of contact angle hysteresis and its associated solidlike friction on the decay of liquid oscillations in the presence of sliding triple lines.

Opportunities and challenges in design and optimization of protein function

D. Listov; C. A. Goverde; B. E. Correia; S. J. Fleishman 

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to alpha-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities.|Recent combinations of structure-based and sequence-based calculations and machine learning tools have dramatically improved protein engineering and design. Although designing complex protein structures remains challenging, these methods have enabled the design of therapeutically relevant activities, including vaccine antigens, antivirals and drug-delivery nano-vehicles.

An Annotated Corpus of Tonal Piano Music from the Long 19th Century

J. Hentschel; Y. Rammos; F. C. Moss; M. Neuwirth; M. A. Rohrmeier 

We present a dataset of 264 annotated piano pieces of nine composers, composed in the long 19th century (https://doi.org/10.5281/zenodo.7483349). Annotations adhere to the DCML harmony annotation standard and include Roman numerals, phrase boundaries, and cadence types. The scores are encoded in the XML-based MuseScore 3 format. Annotations are embedded within the MuseScore files. In addition, all harmony information, alongside key features of the encoded measure and note objects, is provided in the form of plaintext TSV-formatted tables for increased interoperability with other datasets and analysis tools. Annotations were collaboratively created and reviewed by a pool of trained music theorists. Collaboration took place asynchronously online via a semi-automated GitHub-based workflow designed for quality assurance, allowing cycles of revisions and reviews until consensus is reached. The full revision history is retained, providing data for further empirical research on inter-annotator agreement and related topics. We also present descriptive statistics about the nine corpora and the dataset as a whole, including comparisons of pitch-class contents, phrase lengths, modulations, and cadence types. We conclude with a discussion of our musicological principles for corpus building and considerations of representability.

Impact of beam-coupling impedance on the Schottky spectrum of bunched beam

C. Lannoy; K. Lasocha; T. Pieloni; D. Alves; N. Mounet 

The Schottky monitors of the Large Hadron Collider (LHC) can be used for non-invasive beam diagnostics to estimate various bunch characteristics, such as tune, chromaticity, bunch profile or synchrotron frequency distribution. However, collective effects, in particular beam -coupling impedance, can significantly affect Schottky spectra when large bunch charges are involved. In such conditions, the available interpretation methods are difficult to apply directly to the measured spectra, thus preventing the extraction of beam and machine parameters, which is possible for lower bunch charges. To study the impact of impedance on such spectra, we introduce a method for building Schottky spectra from macro -particle simulations performed with the PyHEADTAIL code, applied to LHC beam conditions. In this case, the use of a standard Fast Fourier Transform (FFT) algorithm to recover the spectral content of the beam becomes computationally intractable memory -wise, because of the relatively short bunch length compared to the large revolution period. To circumvent this difficulty, a semi -analytical method was developed to efficiently compute the Fourier transform. The simulated Schottky spectrum is then compared against theoretical formulas and measurements of Schottky signals previously obtained with lead ion beams in the LHC where impedance effects are expected to be limited. Furthermore, this study provides preliminary interpretations of the impact of beam -coupling impedance on proton Schottky spectra by incorporating longitudinal and transverse resonator -like impedance models into the simulations. A theoretical framework is also introduced for the case of the longitudinal impedance, allowing the extension of the existing theoretical formalism.

Gaussian universality of perceptrons with random labels

F. Gerace; F. Krzakala; B. Loureiro; L. Stephan; L. Zdeborova 

While classical in many theoretical settings-and in particular in statistical physics-inspired works-the assumption of Gaussian i.i.d. input data is often perceived as a strong limitation in the context of statistics and machine learning. In this study, we redeem this line of work in the case of generalized linear classification, also known as the perceptron model, with random labels. We argue that there is a large universality class of high-dimensional input data for which we obtain the same minimum training loss as for Gaussian data with corresponding data covariance. In the limit of vanishing regularization, we further demonstrate that the training loss is independent of the data covariance. On the theoretical side, we prove this universality for an arbitrary mixture of homogeneous Gaussian clouds. Empirically, we show that the universality holds also for a broad range of real data sets.

Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study

J. Mosso; G. Briand; K. Pierzchala; D. Simicic; A. Sierra et al. 

Introduction Type C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H magnetic resonance spectroscopy (MRS), most noticeably a strong increase in glutamine to detoxify brain ammonia. In addition, alterations of brain cellular architecture have been measured ex vivo by histology in a rat model of type C HE. The aim of this study was to assess the potential of diffusion-weighted MRS (dMRS) for probing these cellular shape alterations in vivo by monitoring the diffusion properties of the major brain metabolites.Methods The bile duct-ligated (BDL) rat model of type C HE was used. Five animals were scanned before surgery and 6- to 7-week post-BDL surgery, with each animal being used as its own control. 1H-MRS was performed in the hippocampus (SPECIAL, TE = 2.8 ms) and dMRS in a voxel encompassing the entire brain (DW-STEAM, TE = 15 ms, diffusion time = 120 ms, maximum b-value = 25 ms/mu m2) on a 9.4 T scanner. The in vivo MRS acquisitions were further validated with histological measures (immunohistochemistry, Golgi-Cox, electron microscopy).Results The characteristic 1H-MRS pattern of type C HE, i.e., a gradual increase of brain glutamine and a decrease of the main organic osmolytes, was observed in the hippocampus of BDL rats. Overall increased metabolite diffusivities (apparent diffusion coefficient and intra-stick diffusivity-Callaghan’s model, significant for glutamine, myo-inositol, and taurine) and decreased kurtosis coefficients were observed in BDL rats compared to control, highlighting the presence of osmotic stress and possibly of astrocytic and neuronal alterations. These results were consistent with the microstructure depicted by histology and represented by a decline in dendritic spines density in neurons, a shortening and decreased number of astrocytic processes, and extracellular edema.Discussion dMRS enables non-invasive and longitudinal monitoring of the diffusion behavior of brain metabolites, reflecting in the present study the globally altered brain microstructure in BDL rats, as confirmed ex vivo by histology. These findings give new insights into metabolic and microstructural abnormalities associated with high brain glutamine and its consequences in type C HE.

Teaching about non-deterministic physics: an almost forgotten fundamental contribution of Marie Curie

G. Margaritondo 

The first historical steps of radioactivity research offer an excellent opportunity to teach a key concept of modern physics: non-deterministic phenomena. However, this opportunity is often wasted because of historical misconceptions and of the irrational fear of radioactive effects. We propose here a lecturing strategy – primarily for undergraduate students – based on interesting historical facts. In particular, on a key conceptual contribution by Marie Curie, an attractive figure for the young women and men of today. Paradoxically, this milestone is almost unknown, whereas it should contribute to her immortal fame — perhaps as much as the discovery of radium.

The angiogenic growth of cities

I. Capel-Timms; D. Levinson; B. Lahoorpoor; S. Bonetti; G. Manoli 

Describing the space-time evolution of urban population is a fundamental challenge in the science of cities, yet a complete theoretical treatment of the underlying dynamics is still missing. Here, we first reconstruct the evolution of London (UK) over 180 years and show that urban growth consists of an initial phase of diffusion-limited growth, followed by the development of the railway transport network and a consequential shift from central to suburban living. Such dynamics-which are analogous to angiogenesis in biological systems-can be described by a minimalist reaction-diffusion model coupled with economic constraints and an adaptive transport network. We then test the generality of our approach by reproducing the evolution of Sydney, Australia, from 1851 to 2011. We show that the rail system coevolves with urban population, displaying hierarchical characteristics that remain constant over time unless large-scale interventions are put in place to alter the modes of transport. These results demonstrate that transport schemes are first-order controls of long-term urbanization patterns and efforts aimed at creating more sustainable and healthier cities require careful consideration of population-transport feedbacks.

Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms

A. Goujon; S. J. Neumayer; M. Unser 

We propose to learn non-convex regularizers with a prescribed upper bound on their weak-convexity modulus. Such regularizers give rise to variational denoisers that minimize a convex energy. They rely on few parameters (less than 15,000) and offer a signal-processing interpretation as they mimic handcrafted sparsity-promoting regularizers. Through numerical experiments, we show that such denoisers outperform convex-regularization methods as well as the popular BM3D denoiser. Additionally, the learned regularizer can be deployed to solve inverse problems with iterative schemes that provably converge. For both CT and MRI reconstruction, the regularizer generalizes well and offers an excellent tradeoff between performance, number of parameters, guarantees, and interpretability when compared to other data-driven approaches.

Euclid: Improving the efficiency of weak lensing shear bias calibration

H. Jansen; M. Tewes; T. Schrabback; N. Aghanim; A. Amara et al. 

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and consequently a substantial computational effort, seeking methods to speed the calibration up is valuable. We study the efficiency of different noise cancellation methods that aim at reducing the simulation volume required to reach a given precision in the shear measurement. The more efficient a method is, the faster we can estimate the relevant biases up to a required precision level. Explicitly, we compared fit methods with different noise cancellations and a method based on responses. We used GalSim to simulate galaxies both on a grid and at random positions in larger scenes. Placing the galaxies at random positions requires their detection, which we performed with SExtractor. On the grid, we neglected the detection step and, therefore, the potential detection bias arising from it. The shear of the simulated images was measured with the fast moment-based method KSB, for which we note deviations from purely linear shear measurement biases. For the estimation of uncertainties, we used bootstrapping as an empirical method. We extended the response-based approach to work on a wider range of shears and provide accurate estimates of selection biases. We find that each method we studied on top of shape noise cancellation can further increase the efficiency of calibration simulations. The improvement depends on the considered shear amplitude range and the type of simulations (grid-based or random positions). The response method on a grid for small shears provides the biggest improvement. Here the runtime for the estimation of multiplicative biases can be lowered by a factor of 145 compared to the benchmark simulations without any cancellation. In the more realistic case of randomly positioned galaxies, we still find an improvement factor of 70 for small shears using the response method. Alternatively, the runtime can be lowered by a factor of 7 already using pixel noise cancellation on top of shape noise cancellation. Furthermore, we demonstrate that the efficiency of shape noise cancellation can be enhanced in the presence of blending if entire scenes are rotated instead of individual galaxies.

Randomized flexible GMRES with deflated restarting

Y. Jang; L. Grigori; E. Martin; C. Content 

For a high dimensional problem, a randomized Gram-Schmidt (RGS) algorithm is beneficial in computational costs as well as numerical stability. We apply this dimension reduction technique by random sketching to Krylov subspace methods, e.g. to the generalized minimal residual method (GMRES). We propose a flexible variant of GMRES with the randomized Gram-Schmidt-based Arnoldi iteration to produce a set of basis vectors of the Krylov subspace. Even though the Krylov basis is no longer l2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$l_2$$\end{document} orthonormal, its random projection onto the low dimensional space achieves l2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$l_2$$\end{document} orthogonality. As a result, the numerical stability is observed which turns out to be independent of the dimension of the problem even in extreme scale problems. On the other hand, as the harmonic Ritz values are commonly used in GMRES with deflated restarting to improve convergence, we consider another deflation strategy, for instance disregarding the singular vectors associated with the smallest singular values. We thus introduce a new algorithm of the randomized flexible GMRES with singular value decomposition (SVD)-based deflated restarting. At the end, we carry out numerical experiments in the context of compressible turbulent flow simulations. Our proposed approach exhibits a quite competitive numerical behaviour to existing methods while reducing computational costs.

An interior penalty coupling strategy for isogeometric non-conformal Kirchhoff-Love shell patches

G. Guarino; P. Antolin; A. Milazzo; A. Buffa 

This work focuses on the coupling of trimmed shell patches using Isogeometric Analysis, based on higher continuity splines that seamlessly meet the C 1 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C<^>1$$\end{document} requirement of Kirchhoff-Love-based discretizations. Weak enforcement of coupling conditions is achieved through the symmetric interior penalty method, where the fluxes are computed using their correct variationally consistent expression that was only recently proposed and is unprecedentedly adopted herein in the context of coupling conditions. The constitutive relationship accounts for generically laminated materials, although the proposed tests are conducted under the assumption of uniform thickness and lamination sequence. Numerical experiments assess the method for an isotropic and a laminated plate, as well as an isotropic hyperbolic paraboloid shell from the new shell obstacle course. The boundary conditions and domain force are chosen to reproduce manufactured analytical solutions, which are taken as reference to compute rigorous convergence curves in the L 2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L<^>2$$\end{document} , H 1 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$H<^>1$$\end{document} , and H 2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$H<^>2$$\end{document} norms, that closely approach optimal ones predicted by theory. Additionally, we conduct a final test on a complex structure comprising five intersecting laminated cylindrical shells, whose geometry is directly imported from a STEP file. The results exhibit excellent agreement with those obtained through commercial software, showcasing the method’s potential for real-world industrial applications.

Stress tolerance of lightweight glass-free PV modules for vehicle integration

U. B. Desai; K. Nicolet; S. Prabhudesai; G. Cattaneo; J. Robin et al. 

Electric vehicles (EVs) currently dominate the sales in the automotive market. A big leap in this market can be made by developing a photovoltaic product that can be integrated to an EV, as it can boost the driving range of the EV while reducing the charging frequency. Such vehicle-integrated photovoltaic (VIPV) products are already successfully demonstrated, but they are usually made with glass as a front sheet – making them bulky and limiting their use to the car roofs due to safety reasons. The contemporary focus of the research in the field of VIPV is on developing a product that is lightweight (LW) and easily integrable into the complex shapes of an EV. Therefore, in this work, we present our initial findings on a novel architecture for LW VIPV modules employing polycarbonate (PC) as a front sheet. The mechanical behaviour of the LW module under bending is successfully simulated using finite elements (FE) modelling to predict the fracture of the solar cells, which can then be used as a predictive tool to check the maximal load on the PV body of an EV before cracking the c-Si solar cells. We demonstrate that a change in the temperature of the PC-based LW modules can modify the interspacing between the cells and thus create stress on the connectors. The dog-bone connectors are found to allow almost unconstrained movement of the cells in the module when subjected to variation of temperature. The cell movements may result in mechanical fatigue of the interconnection, which can ultimately result in disconnection of the cells. Initial performance of the dog-bone connectors is investigated by applying mechanical fatigue experiments, which demonstrate that the special geometry of the dog-bone connector could endure a greater number of thermal cycles than a simple prismatic shape would.

On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference

M. Kayaalp; Y. Inan; E. Telatar; A. H. Sayed 

We study the asymptotic learning rates of belief vectors in a distributed hypothesis testing problem under linear and log-linear combination rules. We show that under both combination strategies, agents are able to learn the truth exponentially fast, with a faster rate under log-linear fusion. We examine the gap between the rates in terms of network connectivity and information diversity. We also provide closed-form expressions for special cases involving federated architectures and exchangeable networks.

Alpha1-antitrypsin improves survival in murine abdominal sepsis model by decreasing inflammation and sequestration of free heme

J. D. Zemtsovski; S. Tumpara; S. Schmidt; V. Vijayan; A. Klos et al. 

Background Excessive inflammation, hemolysis, and accumulation of labile heme play an essential role in the pathophysiology of multi-organ dysfunction syndrome (MODS) in sepsis. Alpha1-antitrypsin (AAT), an acute phase protein with heme binding capacity, is one of the essential modulators of host responses to inflammation. In this study, we evaluate the putative protective effect of AAT against MODS and mortality in a mouse model of polymicrobial abdominal sepsis.Methods Polymicrobial abdominal sepsis was induced in C57BL/6N mice by cecal ligation and puncture (CLP). Immediately after CLP surgery, mice were treated intraperitoneally with three different forms of human AAT-plasma-derived native (nAAT), oxidized nAAT (oxAAT), or recombinant AAT (recAAT)-or were injected with vehicle. Sham-operated mice served as controls. Mouse survival, bacterial load, kidney and liver function, immune cell profiles, cytokines/chemokines, and free (labile) heme levels were assessed. In parallel, in vitro experiments were carried out with resident peritoneal macrophages (MPM phi) and mouse peritoneal mesothelial cells (MPMC).Results All AAT preparations used reduced mortality in septic mice. Treatment with AAT significantly reduced plasma lactate dehydrogenase and s-creatinine levels, vascular leakage, and systemic inflammation. Specifically, AAT reduced intraperitoneal accumulation of free heme, production of cytokines/chemokines, and neutrophil infiltration into the peritoneal cavity compared to septic mice not treated with AAT. In vitro experiments performed using MPMC and primary MPM phi confirmed that AAT not only significantly decreases lipopolysaccharide (LPS)-induced pro-inflammatory cell activation but also prevents the enhancement of cellular responses to LPS by free heme. In addition, AAT inhibits cell death caused by free heme in vitro.Conclusion Data from the septic CLP mouse model suggest that intraperitoneal AAT treatment alone is sufficient to improve sepsis-associated organ dysfunctions, preserve endothelial barrier function, and reduce mortality, likely by preventing hyper-inflammatory responses and by neutralizing free heme.

Quantitative prediction of crystallization in laser powder bed fusion of a Zr-based bulk metallic glass with high oxygen content

N. Sohrabi; T. Ivas; J. Jhabvala; J. E. K. Schawe; J. F. Loffler et al. 

One of the main challenges in the fabrication of bulk metallic glasses (BMGs) via laser-based additive manufacturing (AM) is undesirable crystal phase formation, which usually deteriorates the mechanical properties of the BMG fabricated parts. Understanding the crystallization process therefore helps to manufacture parts with desirable properties. In this study, partially crystallized Zr-based BMG (AMZ4) samples were fabricated via laser powder-bed fusion (LPBF). Samples with a different time delay between each adjacent laser tracks were produced to vary the thermal history during the manufacturing process. Two characteristic thermal effects were decoupled, a global one and a local one. The global thermal effect originates from heat accumulation in the whole sample, increasing the overall sample temperature, reducing local cooling rates from the melt and changing thermal cycles in the heat-affected zones (HAZs). The local thermal effect refers to the contribution of each individual laser-track pass, happening even in the absence of the global effect. As the time delay is increased, the sample has more time to dissipate heat, which implies a reduced influence of the global thermal effects, and therefore lower crystalline fractions. The experiments were designed such as to allow for detailed validations of the thermal fields predicted by a Finite Element (FEM) model of the LPBF process. These were indeed used as an input to predict the crystallized fraction in each AMZ4 sample, using previously measured TTT diagrams. For the first time, quantitative predictions with a numerical model could be made over a wide range of crystallized fractions, and were in good agreement with those measured by DSC. To validate the model, a 0 % crystallized fraction was also simulated, corresponding to optimized printing conditions despite the high oxygen content (>1000 ppm) of the AMZ4 chosen for the experiments. It therefore represents a reliable tool for finding optimal processing parameters of BMGs known to be challenging to print.

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

A. Caboussat; J. Hess; A. Masserey; M. Picasso 

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces between phases, and contact angles. The volume -of -fluid approach is used to track the interfaces and the free surfaces between the various phases and the ambient air. The numerical method relies on an operator splitting strategy. The space discretization relies on a two -grid approach that uses an unstructured finite element mesh for diffusion phenomena and a structured Cartesian grid for advection phenomena. An adaptive mesh refinement algorithm is incorporated to better track the interfaces and free surfaces on the finite element mesh, and approximate more accurately surface forces. The model is validated through numerical experiments, in particular for emulsion problems.

Speciation of Lanthanide Metal Ion Dopants in Microcrystalline All-Inorganic Halide Perovskite CsPbCl3

D. J. Kubicki; D. Prochowicz; A. Hofstetter; A. Ummadisingu; L. Emsley 

Lanthanides are versatile modulators of optoelectronic properties owing to their narrow optical emission spectra across the visible and near-infrared range. Their use in metal halide perovskites (MHPs) has recently gained prominence, although their fate in these materials has not yet been established at the atomic level. We use cesium-133 solid-state NMR to establish the speciation of all nonradioactive lanthanide ions (La3+, Ce3+, Pr3+, Nd3+, Sm3+, Sm2+, Eu3+, Eu2+, Gd3+, Tb3+, Dy3+, Ho3+, Er3+, Tm3+, Yb3+, Lu3+) in microcrystalline CsPbCl3. Our results show that all lanthanides incorporate into the perovskite structure of CsPbCl3 regardless of their oxidation state (+2, +3).

Can Gas Consumption Data Improve the Performance of Electricity Theft Detection?

W. Liao; R. Zhu; T. Ishizaki; Y. Li; Y. Jia et al. 

Machine learning techniques have been extensively developed in the field of electricity theft detection. However, almost all typical models primarily rely on electricity consumption data to identify fraudulent users, often neglecting other pertinent household information such as gas consumption data. This article aims to explore the untapped potential of gas consumption data, a critical yet overlooked factor in electricity theft detection. In particular, we perform theoretical, qualitative, and quantitative correlation analyses between gas and electricity consumption data. Then, we propose two model-agnostic frameworks (i.e., multichannel network and twin network frameworks) to seamlessly integrate gas consumption data into machine learning models. Simulation results show a significant improvement in model performance when gas consumption data are incorporated using our proposed frameworks. Also, our proposed gas and electricity convolutional neural network, based on the proposed framework, demonstrates superior performance compared to classical and recent machine learning models on datasets with varying fraudulent ratios.

Design and in vitro Characterization of a Wearable Multisensing System for Hydration Monitoring

S. Tonello; A. Zacchini; A. Galli; A. Golparvar; A. Meimandi et al. 

Dehydration is a frequent condition in the elderly and can lead to serious health complications if not compensated timely. Early diagnosis can be problematic, as medical examinations in the hospital would be needed. Fully wearable low-cost multisensing devices for home use could help investigate and prevent critical conditions. We introduce a sensing platform designed for operation in remote healthcare for the elderly. It combines a low-cost, highly customizable flexible inkjet-printed multisensor bracelet, including sensors for body impedance, skin hydration, and temperature monitoring, with a small, low-power front-end circuit and an embedded unit that communicates by a Low Power Wide Area Network (LoRaWAN) transmission interface. We describe individual system components and present in vitro experiments for their characterization. Reported results represent the fundamental proof of concept for the development of a fully operating device that can be used satisfactorily to monitor dehydration in a real-life application scenario.

Gamma-ray Spectroscopy in Low-Power Nuclear Research Reactors

O. V. Pakari; A. Lucas; F. B. Darby; V. P. Lamirand; T. Maurer et al. 

Gamma-ray spectroscopy is an effective technique for radioactive material characterization, routine inventory verification, nuclear safeguards, health physics, and source search scenarios. Gamma-ray spectrometers typically cannot be operated in the immediate vicinity of nuclear reactors due to their high flux fields and their resulting inability to resolve individual pulses. Low-power reactor facilities offer the possibility to study reactor gamma-ray fields, a domain of experiments hitherto poorly explored. In this work, we present gamma-ray spectroscopy experiments performed with various detectors in two reactors: The EPFL zero-power research reactor CROCUS, and the neutron beam facility at the Ohio State University Research Reactor (OSURR). We employed inorganic scintillators (CeBr3), organic scintillators (trans-stilbene and organic glass), and high-purity germanium semiconductors (HPGe) to cover a range of typical-and new-instruments used in gamma-ray spectroscopy. The aim of this study is to provide a guideline for reactor users regarding detector performance, observed responses, and therefore available information in the reactor photon fields up to 2 MeV. The results indicate several future prospects, such as the online (at criticality) monitoring of fission products (like Xe, I, and La), dual-particle sensitive experiments, and code validation opportunities.

Accretion Disk Size and Updated Time-delay Measurements in the Gravitationally Lensed Quasar SDSS J165043.44+425149.3

A. B. Rivera; C. W. Morgan; S. M. Florence; K. Kniezewski; M. Millon et al. 

We analyze variability in 15-season optical lightcurves from the doubly imaged lensed quasar SDSS J165043.44+425149.3 (SDSS1650), comprising five seasons of monitoring data from the Maidanak Observatory (277 nights in total, including the two seasons of data previously presented in Vuissoz et al.), five seasons of overlapping data from the Mercator telescope (269 nights), and 12 seasons of monitoring data from the US Naval Observatory, Flagstaff Station at lower cadence (80 nights). We update the 2007 time-delay measurement for SDSS1650 with these new data, finding a time delay of Delta t AB = – 55.1 – 3.7 + 4.0 days, with image A leading image B. We analyze the microlensing variability in these lightcurves using a Bayesian Monte Carlo technique to yield measurements of the size of the accretion disk at lambda rest = 2420 angstrom, finding a half-light radius of log(r 1/2/cm) = 16.19 – 0.58 + 0.38 assuming a 60 degrees inclination angle. This result is unchanged if we model 30% flux contamination from the broad-line region. We use the width of the Mg ii line in the existing Sloan Digital Sky Survey spectra to estimate the mass of this system’s supermassive black hole, finding M BH = 2.47 x 109 M circle dot. We confirm that the accretion disk size in this system, whose black hole mass is on the very high end of the M BH scale, is fully consistent with the existing quasar accretion disk size-black hole mass relation.

The molecular scale mechanism of deposition ice nucleation on silver iodide

G. Roudsari; M. Lbadaoui-Darvas; A. Welti; A. Nenes; A. Laaksonen 

Heterogeneous ice nucleation is a ubiquitous process in the natural and built environment. Deposition ice nucleation, i.e. heterogeneous ice nucleation that – according to the traditional view – occurs in a subsaturated water vapor environment and in the absence of supercooled water on the solid, ice-forming surface, is among the most important ice formation processes in high-altitude cirrus and mixed-phase clouds. Despite its importance, very little is known about the mechanism of deposition ice nucleation at the microscopic level. This study puts forward an adsorption-based mechanism for deposition ice nucleation through results from a combination of atomistic simulations, experiments and theoretical modelling. One of the most potent laboratory surrogates of ice nucleating particles, silver iodide, is used as a substrate for the simulations. We find that water initially adsorbs in clusters which merge and grow over time to form layers of supercooled water. Ice nucleation on silver iodide requires at minimum the adsorption of 4 molecular layers of water. Guided by the simulations we propose the following fundamental freezing steps: (1) Water molecules adsorb on the surface, forming nanodroplets. (2) The supercooled water nanodroplets merge into a continuous multilayer when they grow to about 3 molecular layers thick. (3) The layer continues to grow until the critical thickness for freezing is reached. (4) The critical ice cluster continues to grow.|Schematic of the proposed deposition ice nucleation mechanism on AgI (0001).

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

R. Golman; R. Giterman; A. Teman 

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher power due to larger memory bitcells. Gain-cell eDRAM is a high-density alternative for multi-ported operation with a small silicon footprint. However, conventional gain-cell memories have limited data availability, as they require periodic refresh operations to maintain their data. In this paper, we propose a novel multi-ported gain-cell design, which provides up-to N read ports and M independent write ports (NRMW). In addition, the proposed design features a configurable mode of operation, supporting a hidden refresh mechanism for improved memory availability, as well as a novel opportunistic refresh port approach. An 8kbit memory macro was implemented using a four-transistor bitcell with four ports (2R2W) in a 28 nm FD-SOI technology, offering up-to a 3x reduction in bitcell area compared to other dual-ported SRAM memory options, while also providing 100% memory availability, as opposed to conventional dynamic memories, which are hindered by limited availability.

On the Sums over Inverse Powers of Zeros of the Hurwitz Zeta Function and Some Related Properties of These Zeros

S. Sekatskii 

Recently, we have applied the generalized Littlewood theorem concerning contour integrals of the logarithm of the analytical function to find the sums over inverse powers of zeros for the incomplete gamma and Riemann zeta functions, polygamma functions, and elliptical functions. Here, the same theorem is applied to study such sums for the zeros of the Hurwitz zeta function zeta(s,z), including the sum over the inverse first power of its appropriately defined non-trivial zeros. We also study some related properties of the Hurwitz zeta function zeros. In particular, we show that, for any natural N and small real epsilon, when z tends to n = 0, -1, -2 horizontal ellipsis we can find at least N zeros of zeta(s,z) in the epsilon neighborhood of 0 for sufficiently small |z+n|, as well as one simple zero tending to 1, etc.

Realization of Organocerium-Based Fullerene Molecular Materials Showing Mott Insulator-Type Behavior

P. Pandey; X. Wang; H. Gupta; P. W. Smith; E. Lapsheva et al. 

Electron-rich organocerium complexes (C5Me4H)(3)Ce and [(C5Me5)(2)Ce(ortho-oxa)], with redox potentials E-1/2 = -0.82 V and E-1/2 = -0.86 V versus Fc/Fc(+), respectively, were reacted with fullerene (C-60) in different stoichiometries to obtain molecular materials. Structurally characterized cocrystals: [(C5Me4H)(3)Ce](2)C-60 (1) and [(C5Me5)(2)Ce(ortho-oxa)](3)C-60 (2) of C-60 with cerium-based, molecular rare earth precursors are reported for the first time. The extent of charge transfer in 1 and 2 was evaluated using a series of physical measurements: FT-IR, Raman, solid-state UV-vis-NIR spectroscopy, X-ray absorption near-edge structure (XANES) spectroscopy, and magnetic susceptibility measurements. The physical measurements indicate that 1 and 2 comprise the cerium(III) oxidation state, with formally neutral C-60 as a cocrystal in both cases. Pressure-dependent periodic density functional theory calculations were performed to study the electronic structure of 1. Inclusion of a Hubbard-U parameter removes Ce f states from the Fermi level, opens up a band gap, and stabilizes FM/AFM magnetic solutions that are isoenergetic because of the large distances between the Ce(III) cations. The electronic structure of this strongly correlated Mott insulator-type system is reminiscent of the well-studied Ce2O3.

Mean-field transport equations and energy theorem for plasma edge turbulent transport

R. A. J. Coosemans; W. Dekeyser; M. Baelmans 

This paper establishes a mean-field equation set and an energy theorem to provide a theoretical basis in view of the development of self-consistent, physics-based turbulent transport models for mean-field transport codes. A rigorous averaging procedure identifies the exact form of the perpendicular turbulent fluxes which are modelled by ad hoc diffusive terms in mean-field transport codes, next to other closure terms which are not commonly considered. Earlier work suggested that the turbulent $E\times B$ particle and heat fluxes, which are thus identified to be important closure terms, can be modelled to reasonable accuracy using the kinetic energy in the $E\times B$ velocity fluctuations ($k_{E}$). The related enstrophy led to further modelling improvements in an initial study, although further analysis is required. To support this modelling approach, transport equations are derived analytically for both quantities. In particular, an energy theorem is established in which the various source and sink terms of $k_{E}$ are shown to couple to mean-field and turbulent parallel kinetic energy, kinetic energy in the other perpendicular velocity components, the thermal energy and the magnetic energy. This provides expressions for the interchange, drift-wave and Reynolds stress terms amongst others. Note that most terms in these energy equations are in turn closure terms. It is suggested to evaluate these terms using reference data from detailed turbulence code simulations in future work.

Two- and Three-Dimensional Superconducting Phases in the Weyl Semimetal TaP at Ambient Pressure. (vol 10, 288, 2020)

M. R. Van Delft; S. Pezzini; M. Koenig; P. Tinnemans; N. E. Hussey et al. 

Microbial genome collection of aerobic granular sludge cultivated in sequencing batch reactors using different carbon source mixtures

J. S. Saini; A. Adler; L. Cardona; P. N. R. Ramirez; R. Pei et al. 

Aerobic granular sludge (AGS) consists of a microbial consortium that has an important role in wastewater treatment. This study investigates AGS microorganisms cultivated in a laboratory-scale sequencing batch reactor. Metagenomic sequencing was conducted using PacBio and Illumina, resulting in 759 metagenome-assembled genomes, 331 of which remained after dereplication.

The Extraordinary March 2022 East Antarctica “Heat” Wave. Part II: Impacts on the Antarctic Ice Sheet

J. D. Wille; S. P. Alexander; C. Amory; R. Baiman; L. Barthelemy et al. 

Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave with widespread 30 degrees-40 degrees C temperature anomalies across the ice sheet. In Part I, we assessed the meteorological drivers that generated an intense atmospheric river (AR) that caused these record-shattering temperature anomalies. Here, we continue our large collaborative study by analyzing the widespread and diverse impacts driven by the AR landfall. These impacts included widespread rain and surface melt that was recorded along coastal areas, but this was outweighed by widespread high snowfall accumulations resulting in a largely positive surface mass balance contribution to the East Antarctic region. An analysis of the surface energy budget indicated that widespread downward longwave radiation anomalies caused by large cloudliquid water contents along with some scattered solar radiation produced intense surface warming. Isotope measurements of the moisture were highly elevated, likely imprinting a strong signal for past climate reconstructions. The AR event attenuated cosmic ray measurements at Concordia, something previously never observed. Last, an extratropical cyclone west of the AR landfall likely triggered the final collapse of the critically unstable Conger Ice Shelf while further reducing an already record low sea ice extent.

The Key Players of CNS function: Exploring the Effects of Region, Age, and Sex on Human Glia Diversity

L. A. Seeker; N. Bestard-Cuche; S. Jaekel; N. -L. Kazakou; S. M. K. Bostrand et al. 

Resolving the morpho-functional responses of locally-constrained retinal microglia with morphOMICs

R. J. Cubero; G. Colombo; A. Venturino; R. Schulz; M. Maes et al. 

MorphOMICs: a new algorithm to unravel region- and sex-dependent microglia morphological plasticity in health and disease

G. Colombo; R. J. A. Cubero; A. Venturino; L. Kanari; R. Schulz et al. 

Profiling the chromatin landscape of adult human oligodendroglia using single-cell epigenomics

M. Kabbe; L. Seeker; E. Agirre; K. Carlstrom; F. B. Pohl et al. 

Loss of TDP-43 in microglia leads to abnormal brain development

A. C. Compagnion; A. Ivanov; F. G. Ibanez; D. Beule; M. E. Tremblay et al. 

The multimodality cell segmentation challenge: toward universal solutions

J. Ma; R. Xie; S. Ayyadhury; C. Ge; A. Gupta et al. 

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multimodality cell segmentation benchmark, comprising more than 1,500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.|Cell segmentation is crucial in many image analysis pipelines. This analysis compares many tools on a multimodal cell segmentation benchmark. A Transformer-based model performed best in terms of performance and general applicability.

Towards a muon collider

C. Accettura; D. Adams; R. Agarwal; C. Ahdida; C. Aime et al. 

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.

Euclid: The search for primordial features

M. Ballardini; Y. Akrami; F. Finelli; D. Karagiannis; B. Li et al. 

Primordial features, in particular oscillatory signals, imprinted in the primordial power spectrum of density perturbations represent a clear window of opportunity for detecting new physics at high-energy scales. Future spectroscopic and photometric measurements from the Euclid space mission will provide unique constraints on the primordial power spectrum, thanks to the redshift coverage and high-accuracy measurement of nonlinear scales, thus allowing us to investigate deviations from the standard power-law primordial power spectrum. We consider two models with primordial undamped oscillations superimposed on the matter power spectrum described by 1 + A(X) sin (omega(X)Xi(X) + 2 pi phi(X)), one linearly spaced in k space with Xi(lin) equivalent to k/k(*) where k(*) = 0.05 Mpc(-1) and the other logarithmically spaced in k space with Xi(log) equivalent to ln(k/k(*)). We note that AX is the amplitude of the primordial feature, omega(X) is the dimensionless frequency, and phi(X) is the normalised phase, where X = {lin, log}. We provide forecasts from spectroscopic and photometric primary Euclid probes on the standard cosmological parameters Omega(m,0), Omega(b,0), h, ns, and sigma(8), and the primordial feature parameters A(X), omega(X), and phi(X). We focus on the uncertainties of the primordial feature amplitude A(X) and on the capability of Euclid to detect primordial features at a given frequency. We also study a nonlinear density reconstruction method in order to retrieve the oscillatory signals in the primordial power spectrum, which are damped on small scales in the late-time Universe due to cosmic structure formation. Finally, we also include the expected measurements from Euclid’s galaxy-clustering bispectrum and from observations of the cosmic microwave background (CMB). We forecast uncertainties in estimated values of the cosmological parameters with a Fisher matrix method applied to spectroscopic galaxy clustering (GC(sp)), weak lensing (WL), photometric galaxy clustering (GC(ph)), the cross correlation (XC) between GC(ph) and WL, the spectroscopic galaxy clustering bispectrum, the CMB temperature and E-mode polarisation, the temperature-polarisation cross correlation, and CMB weak lensing. We consider two sets of specifications for the Euclid probes (pessimistic and optimistic) and three di fferent CMB experiment configurations, that is, Planck, Simons Observatory (SO), and CMB Stage-4 (CMB-S4). We find the following percentage relative errors in the feature amplitude with Euclid primary probes: for the linear (logarithmic) feature model, with a fiducial value of A(X) = 0.01, omega(X) = 10, and phi(X) = 0.21% (22%) in the pessimistic settings and 18% (18%) in the optimistic settings at a 68.3% confidence level (CL) using GC(sp) +WL +GC(ph) +XC. While the uncertainties on the feature amplitude are strongly dependent on the frequency value when single Euclid probes are considered, we find robust constraints on A X from the combination of spectroscopic and photometric measurements over the frequency range of (1, 10(2.1)). Due to the inclusion of numerical reconstruction, the GC(sp) bispectrum, SO-like CMB reduces the uncertainty on the primordial feature amplitude by 32%-48%, 50%-65%, and 15%-50%, respectively.|Combining all the sources of information explored expected from Euclid in combination with the future SO-like CMB experiment, we forecast A(lin) similar or equal to 0.010 +/- 0.001 at a 68.3% CL and A(log) similar or equal to 0.010 +/- 0.001 for GC(sp)(PS rec + BS) +WL +GC(ph) +XC +SO-like for both the optimistic and pessimistic settings over the frequency range (1, 10(2.1)).

Search for Inelastic Dark Matter in Events with Two Displaced Muons and Missing Transverse Momentum in Proton-Proton Collisions at p s=13 TeV

A. Hayrapetyan; A. Tumasyan; W. Adam; J. W. Andrejkovic; T. Bergauer et al. 

A search for dark matter in events with a displaced nonresonant muon pair and missing transverse momentum is presented. The analysis is performed using an integrated luminosity of 138 fb-1 of protonproton (pp) collision data at a center -of -mass energy of 13 TeV produced by the LHC in 2016-2018. No significant excess over the predicted backgrounds is observed. Upper limits are set on the product of the inelastic dark matter production cross section sigma(pp -> A0 -> chi 1 chi 2) and the decay branching fraction B(chi 2 -> chi 1 mu thorn mu-), where A0 is a dark photon and chi 1 and chi 2 are states in the dark sector with near mass degeneracy. This is the first dedicated collider search for inelastic dark matter.

Tumor-educated Gr1+CD11b+cells drive breast cancer metastasis via OSM/IL-6/JAK-induced cancer cell plasticity

S. Peyvandi; M. Bulliard; A. Yilmaz; A. Kauzlaric; R. Marcone et al. 

Cancer cell plasticity contributes to therapy resistance and metastasis, which represent the main causes of cancer-related death, including in breast cancer. The tumor microenvironment drives cancer cell plasticity and metastasis, and unraveling the underlying cues may provide novel strategies for managing metastatic disease. Using breast cancer experimental models as a clinically relevant paracrine/autocrine axis instigating breast cancer cell plasticity and triggering metastasis.

Search for Scalar Leptoquarks Produced via τ-Lepton-Quark Scattering in pp Collisions at ffiffi s p=13 TeV

A. Hayrapetyan; A. Tumasyan; W. Adam; J. W. Andrejkovic; T. Bergauer et al. 

The first search for scalar leptoquarks produced in z-lepton-quark collisions is presented. It is based on a set of proton-proton collision data recorded with the CMS detector at the LHC at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138 fb-1. The reconstructed final state consists of a jet, significant missing transverse momentum, and a z lepton reconstructed through its hadronic or leptonic decays. Limits are set on the product of the leptoquark production cross section and branching fraction and interpreted as exclusions in the plane of the leptoquark mass and the leptoquark-z-quark coupling strength.

Measurement of the K+ → π+γγ decay

E. C. Gil; A. Kleimenova; E. Minucci; S. Padolski; P. Petrov et al. 

A sample of 3984 candidates of the K+ -> pi(+)gamma gamma decay, with an estimated background of 291 +/- 14 events, was collected by the NA62 experiment at CERN during 2017-2018. In order to describe the observed di-photon mass spectrum, the next-to-leading order contribution in chiral perturbation theory was found to be necessary. The decay branching ratio in the full kinematic range is measured to be (9.61 +/- 0.17) x 10(-7). The first search for production and prompt decay of an axion-like particle with gluon coupling in the process K+ -> pi(+) a, a -> gamma gamma is also reported.

Dynamics of the charge transfer to solvent process in aqueous iodide

J. Lan; M. Chergui; A. Pasquarello 

Charge-transfer-to-solvent states in aqueous halides are ideal systems for studying the electron-transfer dynamics to the solvent involving a complex interplay between electronic excitation and solvent polarization. Despite extensive experimental investigations, a full picture of the charge-transfer-to-solvent dynamics has remained elusive. Here, we visualise the intricate interplay between the dynamics of the electron and the solvent polarization occurring in this process. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the charge-transfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. Our assignment of the charge-transfer-to-solvent states is supported by the good agreement between calculated and measured vertical binding energies. Our results reveal the charge transfer process in terms of the underlying atomic processes and mechanisms.|Solvated electrons can be formed through photo-induced charge-transfer-to-solvent electronic states of halide ions in water. Here, the authors use machine learning accelerated molecular dynamics simulations to follow the evolution of these states for aqueous iodide in detail.

Cortical cell assemblies and their underlying connectivity: An in silico study

A. Ecker; D. E. Santander; S. Bolanos-Puchet; J. B. Isbister; M. W. Reimann 

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies remains challenging. To address this, we developed a complementary, simulation-based approach, using a detailed, large-scale cortical network model. Using a combination of established methods we detected functional cell assemblies from the stimulus-evoked spiking activity of 186,665 neurons. We studied how the structure of synaptic connectivity underlies assembly composition, quantifying the effects of thalamic innervation, recurrent connectivity, and the spatial arrangement of synapses on dendrites. We determined that these features reduce up to 30%, 22%, and 10% of the uncertainty of a neuron belonging to an assembly. The detected assemblies were activated in a stimulus-specific sequence and were grouped based on their position in the sequence. We found that the different groups were affected to different degrees by the structural features we considered. Additionally, connectivity was more predictive of assembly membership if its direction aligned with the temporal order of assembly activation, if it originated from strongly interconnected populations, and if synapses clustered on dendritic branches. In summary, reversing Hebb’s postulate, we showed how cells that are wired together, fire together, quantifying how connectivity patterns interact to shape the emergence of assemblies. This includes a qualitative aspect of connectivity: not just the amount, but also the local structure matters; from the subcellular level in the form of dendritic clustering to the presence of specific network motifs.

Disulfide-Cross-Linked Tetra-PEG Gels

Z. Meng; L. Loeser; K. Saalwaechter; U. Gasser; H-A. Klok 

The preparation of polymer gels via cross-linking of four-arm star-shaped poly(ethylene glycol) (Tetra-PEG) precursors is an attractive strategy to prepare networks with relatively well-defined topologies. Typically, Tetra-PEG gels are obtained by cross-linking heterocomplementary reactive Tetra-PEG precursors. This study, in contrast, explores the cross-linking of self-reactive, thiol-end functional Tetra-PEG macromers to form disulfide-cross-linked gels. The structure of the disulfide-cross-linked Tetra-PEG gels was studied with multiple-quantum NMR (MQ-NMR) spectroscopy and small-angle neutron scattering (SANS) experiments. In line with earlier simulation studies, these experiments showed a strong dependence of the relative fractions of the different network connectivities on the concentration of the thiol-end functional Tetra-PEG macromer that was used for the synthesis of the networks. Disulfide-cross-linked Tetra-PEG gels prepared at macromer concentrations below the overlap concentration (c = 0.66c*) primarily feature defect connectivity motifs, such as primary loops and dangling ends. For networks prepared at macromer concentrations above the overlap concentration, the fraction of single-link connectivities was found to be similar to that in amide-cross-linked Tetra-PEG gels obtained by heterocomplementary cross-linking of N-hydroxysuccinimide ester and amine functional Tetra-PEG macromers. Since disulfide bonds are susceptible to reductive cleavage, these disulfide-cross-linked gels are of interest, e.g., as reduction-sensitive hydrogels for a variety of biomedical applications.

Evaluation of controllers for augmentative hip exoskeletons and their effects on metabolic cost of walking: explicit versus implicit synchronization

A. R. Manzoori; D. Malatesta; J. Primavesi; A. Ijspeert; M. Bouri 

Background: Efficient gait assistance by augmentative exoskeletons depends on reliable control strategies. While numerous control methods and their effects on the metabolic cost of walking have been explored in the literature, the use of different exoskeletons and dissimilar protocols limit direct comparisons. In this article, we present and compare two controllers for hip exoskeletons with different synchronization paradigms. Methods: The implicit-synchronization-based approach, termed the Simple Reflex Controller (SRC), determines the assistance as a function of the relative loading of the feet, resulting in an emerging torque profile continuously assisting extension during stance and flexion during swing. On the other hand, the Hip-Phase-based Torque profile controller (HPT) uses explicit synchronization and estimates the gait cycle percentage based on the hip angle, applying a predefined torque profile consisting of two shorter bursts of assistance during stance and swing. We tested the controllers with 23 naive healthy participants walking on a treadmill at 4 km & sdot; h-1, without any substantial familiarization. Results: Both controllers significantly reduced the metabolic rate compared to walking with the exoskeleton in passive mode, by 18.0% (SRC, p < 0.001) and 11.6% (HPT, p < 0.001). However, only the SRC led to a significant reduction compared to walking without the exoskeleton (8.8%, p = 0.004). The SRC also provided more mechanical power and led to bigger changes in the hip joint kinematics and walking cadence. Our analysis of mechanical powers based on a whole-body analysis suggested a reduce in ankle push-off under this controller. There was a strong correlation (Pearson's r = 0.778, p < 0.001) between the metabolic savings achieved by each participant with the two controllers. Conclusion: The extended assistance duration provided by the implicitly synchronized SRC enabled greater metabolic reductions compared to the more targeted assistance of the explicitly synchronized HPT. Despite the different assistance profiles and metabolic outcomes, the correlation between the metabolic reductions with the two controllers suggests a difference in individual responsiveness to assistance, prompting more investigations to explore the person-specific factors affecting assistance receptivity.

Boosting likelihood learning with event reweighting

S. Chen; A. Glioti; G. Panico; A. Wulzer 

Extracting maximal information from experimental data requires access to the likelihood function, which however is never directly available for complex experiments like those performed at high energy colliders. Theoretical predictions are obtained in this context by Monte Carlo events, which do furnish an accurate but abstract and implicit representation of the likelihood. Strategies based on statistical learning are currently being developed to infer the likelihood function explicitly by training a continuous-output classifier on Monte Carlo events. In this paper, we investigate the usage of Monte Carlo events that incorporate the dependence on the parameters of interest by reweighting. This enables more accurate likelihood learning with less training data and a more robust learning scheme that is more suited for automation and extensive deployment. We illustrate these advantages in the context of LHC precision probes of new Effective Field Theory interactions.

Deconvolution of the X-ray absorption spectrum of trans-1,3-butadiene with resonant Auger spectroscopy

D. M. P. Holland; J. Suchan; J. Janos; C. Bacellar; L. M. Diniz Leroy et al. 

High-resolution carbon K-edge X-ray photoelectron, X-ray absorption, non-resonant and resonant Auger spectra are presented of gas phase trans-1,3-butadiene alongside a detailed theoretical analysis utilising nuclear ensemble approaches and vibronic models to simulate the spectroscopic observables. The resonant Auger spectra recorded across the first pre-edge band reveal a complex evolution of different electronic states which remain relatively well-localised on the edge or central carbon sites. The results demonstrate the sensitivity of the resonant Auger observables to the weighted contributions from multiple electronic states. The gradually evolving spectral features can be accurately and feasibly simulated within nuclear ensemble methods and interpreted with the population analysis.

The Extraordinary March 2022 East Antarctica “Heat” Wave. Part I: Observations and Meteorological Drivers

J. D. Wille; S. P. Alexander; C. Amory; R. Baiman; L. Barthelemy et al. 

Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave with widespread 30 degrees-40 degrees C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of -9.4 degrees C on 18 March at Concordia Station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an intense atmospheric river advecting subtropical/midlatitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heat wave’s meteorological drivers, impacts, and historical climate context. Here we focus on describing those temperature records along with the intricate meteorological drivers that led to the most intense atmospheric river observed over East Antarctica. These efforts describe the Rossby wave activity forced from intense tropical convection over the Indian Ocean. This led to an atmospheric river and warm conveyor belt intensification near the coastline, which reinforced atmospheric blocking deep into East Antarctica. The resulting moisture flux and upper-level warm-air advection eroded the typical surface temperature inversions over the ice sheet. At the peak of the heat wave, an area of 3.3 million km(2) in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about 100 years, a closer recurrence of such an event is possible under future climate projections. In Part II we describe the various impacts this extreme event had on the East Antarctic cryosphere.|SIGNIFICANCE STATEMENT: In March 2022, a heat wave and atmospheric river caused some of the highest temperature anomalies ever observed globally and captured the attention of the Antarctic science community. Using our diverse collective expertise, we explored the causes of the event and have placed it within a historical climate context. One key takeaway is that Antarctic climate extremes are highly sensitive to perturbations in the midlatitudes and subtropics. This heat wave redefined our expectations of the Antarctic climate. Despite the rare chance of occurrence based on past climate, a future temperature extreme event of similar magnitude is possible, especially given anthropogenic climate change.

Measurement of the τ lepton polarization in Z boson decays in proton-proton collisions at √s=13 TeV

A. Hayrapetyan; A. Tumasyan; W. Adam; J. W. Andrejkovic; T. Bergauer et al. 

The polarization of tau leptons is measured using leptonic and hadronic tau lepton decays in Z -> tau(+)tau(-) events in proton-proton collisions at root s = 13 TeV recorded by CMS at the CERN LHC with an integrated luminosity of 36.3 fb(-1). The measured tau(-) lepton polarization at the Z boson mass pole is P-tau(Z) = -0.144 +/- 0.006 (stat) +/- 0.014 (syst) = -0.144 +/- 0.015, in good agreement with the measurement of the tau lepton asymmetry parameter of A(tau) = 0.1439 +/- 0.0043 = -P-tau(Z) at LEP. The tau lepton polarization depends on the ratio of the vector to axial-vector couplings of the tau leptons in the neutral current expression, and thus on the effective weak mixing angle sin(2)theta(eff)(W), independently of the Z boson production mechanism. The obtained value sin(2)theta(eff)(W) = 0.2319 +/- 0.0008(stat) +/- 0.0018(syst) = 0.2319 +/- 0.0019 is in good agreement with measurements at e(+)e(-) colliders.

Light-Controlled Multiconfigurational Conductance Switching in a Single 1D Metal-Organic Wire

A. Cahlik; M. Ondracek; C. Wackerlin; A. P. Sole; O. Siri et al. 

Precise control of multiple spin states on the atomic scale presents a promising avenue for designing and realizing magnetic switches. Despite substantial progress in recent decades, the challenge of achieving control over multiconfigurational reversible switches in low-dimensional nanostructures persists. Our work demonstrates multiple, fully reversible plasmon-driven spin-crossover switches in a single pi-d metal-organic chain suspended between two electrodes. The plasmonic nanocavity stimulated by external visible light allows for reversible spin crossover between low- and high-spin states of different cobalt centers within the chain. We show that the distinct spin configurations remain stable for minutes under cryogenic conditions and can be nonperturbatively detected by conductance measurements. This multiconfigurational plasmon-driven spin-crossover demonstration extends the available toolset for designing optoelectrical molecular devices based on SCO compounds.

Redox Properties of Flavin in BLUF and LOV Photoreceptor Proteins from Hybrid QM/MM Molecular Dynamics Simulation

M. Kilic; B. Ensing 

Flavins play an important role in many oxidation and reduction processes in biological systems. For example, flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN) are common cofactors found in enzymatic proteins that use the special redox properties of these flavin molecules for their catalytic or photoactive functions. The redox potential of the flavin is strongly affected by its (protein) environment; however, the underlying molecular interactions of this effect are still unknown. Using hybrid quantum mechanics/molecular mechanics (QM/MM) simulation techniques, we have studied the redox properties of flavin in the gas phase, aqueous solution, and two different protein environments, in particular, a BLUF and a LOV photoreceptor domain. By mapping the changes in electrostatic potential and solvent structure, we gain insight into how specific polarization of the flavin by its environment tunes the reduction potential. We find also that accurate calculation of the reduction potentials of these systems by using the hybrid QM/MM approach is hampered by a too limited sampling of the counterion configurations and by artifacts at the QM/MM boundary. We make suggestions for how these issues can be overcome.

Multiplicity-free Representations of Algebraic Groups

M. W. Liebeck; G. M. Seitz; D. M. Testerman 

Let K be an algebraically closed field of characteristic zero, and let G be a connected reductive algebraic group over K. We address the problem of classifying triples (G, H, V ), where H is a proper connected subgroup of G, and V is a finitedimensional irreducible G -module such that the restriction of V to H is multiplicityfree – that is, each of its composition factors appears with multiplicity 1. A great deal of classical work, going back to Dynkin, Howe, Kac, Stembridge, Weyl and others, and also more recent work of the authors, can be set in this context. In this paper we determine all such triples in the case where H and G are both simple algebraic groups of type A, and H is embedded irreducibly in G. While there are a number of interesting familes of such triples (G, H, V ), the possibilities for the highest weights of the representations defining the embeddings H < G and G < GL(V) are very restricted. For example, apart from two exceptional cases, both weights can only have support on at most two fundamental weights; and in many of the examples, one or other of the weights corresponds to the alternating or symmetric square of the natural module for either G or H.

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

H. Park; S. Majumdar; X. Zhang; J. Kim; B. Smit 

The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the ever-expanding and nearly infinite chemical space of MOFs makes it extremely challenging to identify the most optimal materials for a given application. In this work, we present a novel approach using deep reinforcement learning for the inverse design of MOFs, our motivation being designing promising materials for the important environmental application of direct air capture of CO2 (DAC). We demonstrate that our reinforcement learning framework can successfully design MOFs with critical characteristics important for DAC. The reinforcement learning framework uniquely integrates two separate predictive models within its structure, uncovering two distinct subspaces in the MOF chemical space: one with high CO2 heat of adsorption and the other with preferential adsorption of CO2 from humid air, with few structures having both characteristics. Our model can thus serve as an essential tool for the rational design and discovery of materials for different target properties and applications.

Thouless pumping in Josephson junction arrays

S. Athanasiou; I. E. Nielsen; M. M. Wauters; M. Burrello 

Recent advancements in fabrication techniques have enabled unprecedented clean interfaces and gate tunability in semiconductor-superconductor heterostructures. Inspired by these developments, we propose protocols to realize Thouless quantum pumping in electrically tunable Josephson junction arrays. We analyze, in particular, the implementation of the Rice -Mele and the Harper-Hofstadter pumping schemes, whose realization would validate these systems as flexible platforms for quantum simulations. We investigate numerically the long-time behavior of chains of controllable superconducting islands in the Coulomb-blockaded regime. Our findings provide new insights into the dynamics of periodically driven interacting systems and highlight the robustness of Thouless pumping with respect to boundary effects typical of superconducting circuits.

Characteristics and ultra-high total ionizing dose response of 22nm fully depleted silicon-on-insulator

G. Termo; G. Borghello; F. Faccio; K. Kloukina; M. Caselle et al. 

The radiation response of MOS transistors in a 22 nm Fully Depleted Silicon -On -Insulator (FDSOI) technology exposed to ultra -high total ionizing dose (TID) was investigated. Custom structures including n- and p -channel devices with different sizes and threshold voltage flavours were irradiated with X-rays up to a TID of 100 Mrad(SiO2) with different back -gate bias configurations, from -8 V to 2 V. The investigation revealed that the performance is significantly affected by TID, with the radiation response being dominated by the charge trapped in the buried oxide.

A Coverage Control-Based Idle Vehicle Rebalancing Approach for Autonomous Mobility-on-Demand Systems

P. Zhu; I. I. Sirmatel; G. Ferrari-Trecate; N. Geroliminis 

As an emerging mode of urban transportation, autonomous mobility-on-demand (AMoD) systems show the potential in improving mobility in cities through timely and door-to-door services. However, the spatiotemporal imbalances between mobility demand and supply may lead to inefficiencies and a low quality of service. Vehicle rebalancing (i.e., dispatching idle vehicles to high-demand areas) is a potential solution for efficient AMoD fleet management. In this article, we formulate the vehicle rebalancing problem as a coverage control problem for the deployment of a fleet of mobile agents for AMoD operation in urban areas. Performance is demonstrated via microscopic simulations representing a large urban road network in Shenzhen, China. The results reveal the potential of the proposed method in improving service rates and decreasing passenger waiting times.

Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (μCAPs)

F. Delavari; C. Sandini; N. Kojovic; L. F. Saccaro; S. Eliez et al. 

The temporal variability of the thalamus in functional networks may provide valuable insights into the pathophysiology of schizophrenia. To address the complexity of the role of the thalamic nuclei in psychosis, we introduced micro-co-activation patterns (mu CAPs) and employed this method on the human genetic model of schizophrenia 22q11.2 deletion syndrome (22q11.2DS). Participants underwent resting-state functional MRI and a data-driven iterative process resulting in the identification of six whole-brain mu CAPs with specific activity patterns within the thalamus. Unlike conventional methods, mu CAPs extract dynamic spatial patterns that reveal partially overlapping and non-mutually exclusive functional subparts. Thus, the mu CAPs method detects finer foci of activity within the initial seed region, retaining valuable and clinically relevant temporal and spatial information. We found that a mu CAP showing co-activation of the mediodorsal thalamus with brain-wide cortical regions was expressed significantly less frequently in patients with 22q11.2DS, and its occurrence negatively correlated with the severity of positive psychotic symptoms. Additionally, activity within the auditory-visual cortex and their respective geniculate nuclei was expressed in two different mu CAPs. One of these auditory-visual mu CAPs co-activated with salience areas, while the other co-activated with the default mode network (DMN). A significant shift of occurrence from the salience+visuo-auditory-thalamus to the DMN + visuo-auditory-thalamus mu CAP was observed in patients with 22q11.2DS. Thus, our findings support existing research on the gatekeeping role of the thalamus for sensory information in the pathophysiology of psychosis and revisit the evidence of geniculate nuclei hyperconnectivity with the audio-visual cortex in 22q11.2DS in the context of dynamic functional connectivity, seen here as the specific hyper-occurrence of these circuits with the task-negative brain networks.|Unveiling thalamic dynamics in psychosis susceptibility using mu CAPs analysis. Our novel method reveals finer foci of thalamic activity, identifying abnormal connectivity patterns associated with positive psychotic symptoms. Geniculate hyperconnectivity with audio-visual cortex is prevalent during rest in patients, shedding light on thalamic sensory gatekeeping in the pathophysiology of psychosis. image

Overhead-constrained circuit knitting for variational quantum dynamics

G. Gentinetta; F. Metz; G. Carleo 

Simulating the dynamics of large quantum systems is a formidable yet vital pursuit for obtaining a deeper understanding of quantum mechanical phenomena. While quantum computers hold great promise for speeding up such simulations, their practical application remains hindered by limited scale and pervasive noise. In this work, we propose an approach that addresses these challenges by employing circuit knitting to partition a large quantum system into smaller subsystems that can each be simulated on a separate device. The evolution of the system is governed by the projected variational quantum dynamics (PVQD) algorithm, supplemented with constraints on the parameters of the variational quantum circuit, ensuring that the sampling overhead imposed by the circuit knitting scheme remains controllable. We test our method on quantum spin systems with multiple weakly entangled blocks each consisting of strongly correlated spins, where we are able to accurately simulate the dynamics while keeping the sampling overhead manageable. Further, we show that the same method can be used to reduce the circuit depth by cutting long-ranged gates.

High-resolution MHz time- and angle-resolved photoemission spectroscopy based on a tunable vacuum ultraviolet source

L. Hellbruck; M. Puppin; F. Guo; D. D. Hickstein; S. Benhabib et al. 

The time- and angle-resolved photoemission spectroscopy (trARPES) allows for direct mapping of the electronic band structure and its dynamic response on femtosecond timescales. Here, we present a new ARPES system, powered by a new fiber-based femtosecond light source in the vacuum ultraviolet range, accessing the complete first Brillouin zone for most materials. We present trARPES data on Au(111), polycrystalline Au, Bi2Se3, and TaTe2, demonstrating an energy resolution of 21 meV with a time resolution of <360 fs, at a high repetition rate of 1 MHz. The system is integrated with an extreme ultraviolet high harmonic generation beamline, enabling an excellent tunability of the time-bandwidth resolution.

Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity

A. Milousis; A. P. Tsimpidi; H. Tost; S. N. Pandis; A. Nenes et al. 

This study explores the differences in performance and results by various versions of the ISORROPIA thermodynamic module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Three different versions of the module were used, ISORROPIA II v1, ISORROPIA II v2.3, and ISORROPIA-lite. First, ISORROPIA II v2.3 replaced ISORROPIA II v1 in EMAC to improve pH predictions close to neutral conditions. The newly developed ISORROPIA-lite has been added to EMAC alongside ISORROPIA II v2.3. ISORROPIA-lite is more computationally efficient and assumes that atmospheric aerosols exist always as supersaturated aqueous (metastable) solutions, while ISORROPIA II includes the option to allow for the formation of solid salts at low RH conditions (stable state). The predictions of EMAC by employing all three aerosol thermodynamic models were compared to each other and evaluated against surface measurements from three regional observational networks in the polluted Northern Hemisphere (Interagency Monitoring of Protected Visual Environments (IMPROVE), European Monitoring and Evaluation Programme (EMEP), and Acid Deposition Monitoring Network of East Asia (EANET)). The differences between ISORROPIA II v2.3 and ISORROPIA-lite were minimal in all comparisons with the normalized mean absolute difference for the concentrations of all major aerosol components being less than 11 % even when different phase state assumptions were used. The most notable differences were lower aerosol concentrations predicted by ISORROPIA-lite in regions with relative humidity in the range of 20 % to 60 % compared to the predictions of ISORROPIA II v2.3 in stable mode. The comparison against observations yielded satisfactory agreement especially over the USA and Europe but higher deviations over East Asia, where the overprediction of EMAC for nitrate was as high as 4 mu g m-3 (similar to 20%). The mean annual aerosol pH predicted by ISORROPIA-lite was on average less than a unit lower than ISORROPIA II v2.3 in stable mode, mainly for coarse-mode aerosols over the Middle East. The use of ISORROPIA-lite accelerated EMAC by nearly 5 % compared to the use of ISORROPIA II v2.3 even if the aerosol thermodynamic calculations consume a relatively small fraction of the EMAC computational time. ISORROPIA-lite can therefore be a reliable and computationally efficient alternative to the previous thermodynamic module in EMAC.

Hybrid mesoporous electrodes evidence CISS effect on water oxidation

P. Vensaus; Y. Liang; N. Zigon; N. Avarvari; V. Mujica et al. 

Controlling product selectivity is essential for improving the efficiency of multi-product reactions. Electrochemical water oxidation is a reaction of main importance in different applications, e.g., renewable energy schemes and environmental protection, where H2O2 and O-2 are the two principal products. In this Communication, the product selectivity of electrochemical water oxidation was controlled by making use of the chiral induced spin selectivity (CISS) effect at mesoporous-TiO2 on the molecule-modified Au substrate. Our results show a decrease in H2O2 formation when using chiral hetero-helicene molecules adsorbed on the Au substrate. We propose a mechanism for this kinetic effect based on the onset of CISS-induced spin polarization on the Au-helicene chiral interface. We also present a new tunable substrate to investigate the CISS mechanism.

Land Cover Mapping From Multiple Complementary Experts Under Heavy Class Imbalance

V. Zermatten; X. Lu; J. Castillo-Navarro; T. Kellenberger; D. Tuia 

Deep learning has emerged as a promising avenue for automatic mapping, demonstrating high efficacy in land cover categorization through various semantic segmentation models. Nonetheless, the practical deployment of these models encounters important challenges from the imbalanced distribution of samples between the classes, a problem inherent to real-world datasets. This results in models biased towards frequent classes that perform poorly on rare classes. While existing approaches to fight class imbalance mainly focus on image classification, here we propose to address this issue for semantic segmentation with a multiple complementary experts (MCE) structure. Taking inspiration from ensemble models, each expert in our MCE specializes in certain classes and works with other experts in a complementary manner to generate robust predictions for rare classes. We compare our approach to other existing methods and also explore different logit aggregation methods, to identify the performance upper bounds and improvement directions. Our model is evaluated on a large-scale and challenging alpine land cover dataset that we make openly available. In addition, we evaluated our model on an imbalanced land cover mapping dataset, FLAIR, to highlight its adaptability. Overall, our MCE model yields notable improvement in performances on the medium and rare classes compared to baseline methods, while only slightly compromising on the overall accuracy. Despite its simplicity, the MCE approach stands as a practical solution for more operational semantic segmentation models, not trading off performances on rare but important classes.

Machine learning method for the classification of the state of living organisms’ oscillations

D. Kweku; M. I. Villalba; R. G. Willaert; O. M. Yantorno; M. E. Vela et al. 

The World Health Organization highlights the urgent need to address the global threat posed by antibiotic-resistant bacteria. Efficient and rapid detection of bacterial response to antibiotics and their virulence state is crucial for the effective treatment of bacterial infections. However, current methods for investigating bacterial antibiotic response and metabolic state are time-consuming and lack accuracy. To address these limitations, we propose a novel method for classifying bacterial virulence based on statistical analysis of nanomotion recordings. We demonstrated the method by classifying living Bordetella pertussis bacteria in the virulent or avirulence phase, and dead bacteria, based on their cellular nanomotion signal. Our method offers significant advantages over current approaches, as it is faster and more accurate. Additionally, its versatility allows for the analysis of cellular nanomotion in various applications beyond bacterial virulence classification.

Climbing into their Skin to Understand Contextual Protein-Protein Associations and Localizations: Functional Investigations in Transgenic Live Model Organisms

M. J. C. Long; Y. Aye 

Borrowing some quotes from Harper Lee’s novel “To Kill A Mockingbird” to help frame our manuscript, we discuss methods to profile local proteomes. We initially focus on chemical biology regimens that function in live organisms and use reactive biotin species for this purpose. We then consider ways to add new dimensions to these experimental regimens, principally by releasing less reactive (i. e., more selective) (preter)natural electrophiles. Although electrophile release methods may have lower resolution and label fewer proteins than biotinylation methods, their ability to probe simultaneously protein function and locale raises new and interesting possibilities for the field.|What Stirs Beneath. Understanding protein-specific interactomes, or localization, is crucial for decoding protein function. New biotinylation methods can do just that even in live organisms. However, these methods have some limitations as they are intrinsically unable to directly probe function. Here new methods that can investigate locale-specific reactivity, are discussed, opening routes to locale-specific perturbation of function. image

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer

A. Tumasyan; W. Adam; J. W. Andrejkovic; T. Bergauer; S. Chatterjee et al. 

A generic search is presented for the associated production of a Z boson or a photon with an additional unspecified massive particle X, pp -> pp + Z/gamma + X, in proton-tagged events from proton-proton collisions at root s = 13 TeV, recorded in 2017 with the CMS detector and the CMS-TOTEM precision proton spectrometer. The missing mass spectrum is analysed in the 600-1600 GeV range and a fit is performed to search for possible deviations from the background expectation. No significant excess in data with respect to the background predictions has been observed. Model-independent upper limits on the visible production cross section of pp -> pp + Z/gamma + X are set.

Luminosity determination using Z boson production at the CMS experiment

A. Hayrapetyan; A. Tumasyan; W. Adam; J. W. Andrejkovic; T. Bergauer et al. 

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton-proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13 TeV. Events with Z bosons decaying into a pair ofmuons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20 pb(-1) of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.

Measurement of the Higgs boson production via vector boson fusion and its decay into bottom quarks in proton-proton collisions at √s=13 TeV

A. Hayrapetyan; A. Tumasyan; W. Adam; J. W. Andrejkovic; T. Bergauer et al. 

A measurement of the Higgs boson (H) production via vector boson fusion (VBF) and its decay into a bottom quark-antiquark pair (b (b) over bar) is presented using proton-proton collision data recorded by the CMS experiment at root s = 13TeV and corresponding to an integrated luminosity of 90.8 fb(-1). Treating the gluon-gluon fusion process as a background and constraining its rate to the value expected in the standard model (SM) within uncertainties, the signal strength of the VBF process, defined as the ratio of the observed signal rate to that predicted by the SM, is measured to be mu(qqH)(Hb (b) over bar) = 1.01(-0.46)(+0.55). The VBF signal is observed with a significance of 2.4 standard deviations relative to the background prediction, while the expected significance is 2.7 standard deviations. Considering inclusive Higgs boson production and decay into bottom quarks, the signal strength is measured to be mu(incl.)(Hb (b) over bar) = 0.99(-0.41)(+0.48), corresponding to an observed (expected) significance of 2.6 (2.9) standard deviations.

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Y. Zhao; C. Ma; R. Cai; L. Xin; Y. Li et al. 

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre- and one-week post-operative sera and urines from 560 participants across three hospitals, with machine learning and WGCNA. Aberrations in ‘alanine, aspartate and glutamate metabolism’ proved to be prevalent throughout the ESCC evolution, consistently identified by NMR and MS, and reflected in 16 serum and 10 urine metabolic signatures in both discovery and validation sets. NMR-based simplified panels of any five serum or urine metabolites outperform clinical serological tumor markers (AUC = 0.984 and 0.930, respectively), and are effective in distinguishing early-stage ESCC in test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively, NMR-based biofluid screening can reveal characteristic metabolic events of ESCC and be feasible for early detection (ChiCTR2300073613).|Metabolic changes often occur during the early stages of cancer development. Here, the authors develop metabolomics signatures from tissues, pre- and post-operative sera and urines in esophageal squamous cell carcinoma, which may aid in early diagnosis.

Six-dimensional sphere packing and linear programming

M. De Courcy-Ireland; M. Dostert; M. Viazovska 

We prove that the Cohn-Elkies linear programming bound for sphere packing is not sharp in dimension 6. The proof uses duality and optimization over a space of modular forms, generalizing a construction of Cohn- Triantafillou [Math. Comp. 91 (2021), pp. 491-508] to the case of odd weight and non -trivial character.

Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform

A. Sturm; G. Jozwiak; M. P. Verge; L. Munch; G. Cathomen et al. 

Antimicrobial resistance (AMR) is a major public health threat, reducing treatment options for infected patients. AMR is promoted by a lack of access to rapid antibiotic susceptibility tests (ASTs). Accelerated ASTs can identify effective antibiotics for treatment in a timely and informed manner. We describe a rapid growth-independent phenotypic AST that uses a nanomotion technology platform to measure bacterial vibrations. Machine learning techniques are applied to analyze a large dataset encompassing 2762 individual nanomotion recordings from 1180 spiked positive blood culture samples covering 364 Escherichia coli and Klebsiella pneumoniae isolates exposed to cephalosporins and fluoroquinolones. The training performances of the different classification models achieve between 90.5 and 100% accuracy. Independent testing of the AST on 223 strains, including in clinical setting, correctly predict susceptibility and resistance with accuracies between 89.5% and 98.9%. The study shows the potential of this nanomotion platform for future bacterial phenotype delineation.|Sturm et. al developed a 2 to 4 h antibiotic susceptibility test based on bacterial vibrations. This diagnostic test applies to the most frequently found gram-negative bacteria in bloodstream infections and demonstrates its potential in contributing to faster treatment decisions.

Dynamical simulation via quantum machine learning with provable generalization

J. Gibbs; Z. Holmes; M. C. Caro; N. Ezzell; H-Y. Huang et al. 

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we develop a framework for using QML methods to simulate quantum dynamics on near-term quantum hardware. We use generalization bounds, which bound the error a machine learning model makes on unseen data, to rigorously analyze the training data requirements of an algorithm within this framework. Our algorithm is thus resource efficient in terms of qubit and data requirements. Furthermore, our preliminary numerics for the XY model exhibit efficient scaling with problem size, and we simulate 20 times longer than Trotterization on IBMQ-Bogota.

The role of computational methods in cardiovascular medicine: a narrative review

I. Fumagalli; S. Pagani; C. Vergara; L. Dede’; D. A. Adebo et al. 

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data with physical knowledge of the processes underlying the heart function. These models have been increasingly employed in clinical practice to understand pathological mechanisms and their progression, design medical devices, support clinicians in improving therapies. Hinging upon a long-year experience in cardiovascular modeling, we have recently constructed a computational multi-physics and multi-scale integrated model of the heart for the investigation of its physiological function, the analysis of pathological conditions, and to support clinicians in both diagnosis and treatment planning. This narrative review aims to systematically discuss the role that such model had in addressing specific clinical questions, and how further impact of computational models on clinical practice are envisaged. Methods: We developed computational models of the physical processes encompassed by the heart function myocardial perfusion) and of their inherently strong coupling. To solve the equations of such models, we devised advanced numerical methods, implemented in a flexible and highly efficient software library. We also developed computational procedures for clinical data post-processing-like the reconstruction of the heart geometry and motion from diagnostic images-and for their integration into computational models. Key Content and Findings: Our integrated computational model of the heart function provides noninvasive measures of indicators characterizing the heart function and dysfunctions, and sheds light on its underlying processes and their coupling. Moreover, thanks to the close collaboration with several clinical partners, we addressed specific clinical questions on pathological conditions, such as arrhythmias, ventricular dyssynchrony, hypertrophic cardiomyopathy, degeneration of prosthetic valves, and the way coronavirus disease 2019 (COVID-19) infection may affect the cardiac function. In multiple cases, we were also able to provide quantitative indications for treatment. Conclusions: Computational models provide a quantitative and detailed tool to support clinicians in patient care, which can enhance the assessment of cardiac diseases, the prediction of the development of pathological conditions, and the planning of treatments and follow-up tests.

A Spectral Ansatz for The Long-Time Homogenization of The Wave Equation

M. Duerinckx; A. Gloria; M. Ruf 

– Consider the wave equation with heterogeneous coefficients in the homogenization regime. At large times, the wave interacts in a nontrivial way with the heterogeneities, giving rise to effective dispersive effects. The main achievement of the present work is a new ansatz for the long-time two -scale expansion inspired by spectral analysis. Based on this spectral ansatz, we extend and refine all previous results in the field, proving homogenization up to optimal timescales with optimal error estimates, and covering all the standard assumptions on heterogeneities (both periodic and stationary random settings).

A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation

Y. Ren; H. Harb; Y. Shen; A. Balatsoukas-Stimming; A. Burg 

5G New Radio (NR) has stringent demands on both performance and complexity for the design of low-density parity-check (LDPC) decoding algorithms and corresponding VLSI implementations. Furthermore, decoders must fully support the wide range of all 5G NR blocklengths and code rates, which is a significant challenge. In this paper, we present a high-performance and low-complexity LDPC decoder, tailor-made to fulfill the 5G requirements. First, to close the gap between belief propagation (BP) decoding and its approximations in hardware, we propose an extension of adjusted min-sum decoding, called generalized adjusted min-sum (GA-MS) decoding. This decoding algorithm flexibly truncates the incoming messages at the check node level and carefully approximates the non-linear functions of BP decoding to balance the error-rate and hardware complexity. Numerical results demonstrate that the proposed fixed-point GA-MS has only a minor gap of 0.1 dB compared to floating-point BP under various scenarios of 5G standard specifications. Secondly, we present a fully reconfigurable 5G NR LDPC decoder implementation based on GA-MS decoding. Given that memory occupies a substantial portion of the decoder area, we adopt multiple data compression and approximation techniques to reduce 42.2% of the memory overhead. The corresponding 28nm FD-SOI ASIC decoder has a core area of 1.823 mm(2) and operates at 895 MHz. It is compatible with all 5G NR LDPC codes and achieves a peak throughput of 24.42 Gbps and a maximum area efficiency of 13.40 Gbps/mm(2) at 4 decoding iterations.

Surface properties of clinker phases and clay minerals characterized by inverse gas chromatography (IGC) and their link to reactivity

F. Zunino; M. Palacios; P. Bowen; K. Scrivener 

This paper presents a preliminary study of the characterization of the surface energy properties of clinker phases (C3S and C3A), kaolin and metakaolin by Inverse Gas Chromatography (IGC). For this, a reliable measurement methodology was developed. By looking at changes in the whole series of results (dispersive surface energy, specific polar interaction parameter, acid and base constants, morphology index, nanoroughness and adsorption energy distribution function), it is possible to discern changes between the same powders with different surface treatments. A promising correlation between surface properties and the reactivity of studied materials have been found. However, based on the IGC characterization, the increased reactivity of metakaolin compared to the raw kaolinite seems to be strongly linked to the change in local order rather than significant changes in the surface energetics, although a change in the acid/base nature of the surface has been observed.

Automated all-functionals infrared and Raman spectra

L. Bastonero; N. Marzari 

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials’ features as spectroscopic fingerprints. Nevertheless, these measurements frequently need theoretical and computational support in order to unambiguously decipher and assign complex spectra. Linear-response theory provides an effective way to obtain the higher-order derivatives needed, but its applicability to modern exchange-correlation functionals and pseudopotential formalism remains limited. Here, we devise an automated, open-source, user-friendly approach based on density-functional theory and the electric-enthalpy functional to allow seamless calculation from first principles of infrared absorption and reflectivity, together with zone-center phonons, static dielectric tensor, and Raman spectra. By employing a finite-displacement and finite-field approach, we allow for the use of any functional, as well as an efficient treatment of large low-symmetry structures. Additionally, we propose a simple scheme for efficiently sampling the Brillouin zone at different electric fields. To demonstrate the capabilities of the present approach, we study ferroelectric LiNbO3 crystal as a paradigmatic example, and predict infrared and Raman spectra using various (semi)local, Hubbard corrected, and hybrid functionals. Our results also show how PBE0 and extended Hubbard functionals (PBEsol+U+V) yield for this case the best match in term of peak positions and intensities, respectively.

Inhibition of urease-mediated ammonia production by 2-octynohydroxamic acid in hepatic encephalopathy

D. Evstafeva; F. Ilievski; Y. Bao; Z. Luo; B. Abramovic et al. 

Hepatic encephalopathy is a neuropsychiatric complication of liver disease which is partly associated with elevated ammonemia. Urea hydrolysis by urease-producing bacteria in the colon is often mentioned as one of the main routes of ammonia production in the body, yet research on treatments targeting bacterial ureases in hepatic encephalopathy is limited. Herein we report a hydroxamate-based urease inhibitor, 2-octynohydroxamic acid, exhibiting improved in vitro potency compared to hydroxamic acids that were previously investigated for hepatic encephalopathy. 2-octynohydroxamic acid shows low cytotoxic and mutagenic potential within a micromolar concentration range as well as reduces ammonemia in rodent models of liver disease. Furthermore, 2-octynohydroxamic acid treatment decreases cerebellar glutamine, a product of ammonia metabolism, in male bile duct ligated rats. A prototype colonic formulation enables reduced systemic exposure to 2-octynohydroxamic acid in male dogs. Overall, this work suggests that urease inhibitors delivered to the colon by means of colonic formulations represent a prospective approach for the treatment of hepatic encephalopathy.

Sub-mm3 dimensional scaling of fully-integrated additively-fabricated microsupercapacitors for embedded energy storage applications

A. Hodaei; V. Subramanian 

Microsupercapacitors (MSCs) are attractive energy devices for applications in IoT, wireless sensors, and other microelectronic systems due to their small footprints. In this work, the dimensional scaling of fully-integrated additively-fabricated MSCs is systematically investigated. The dimensions of the MSCs are scaled by varying the length and cross-section of their electrodes to study their scalability to the mm(3) range, making them attractive for even chip-scale embedding. MSCs with the thickest electrodes demonstrate the highest values of capacitance and energy density, while MSCs with the thinnest electrodes show lower capacitance and energy densities, but deliver higher power densities. We observe that as expected, capacitance scales with dimensions. We observe excellent performance levels, including maximum areal capacitance of similar to 731.7 mF cm(-2), areal energy density of similar to 36.59 mu W h cm(-2), areal power density of similar to 2669.8 mW cm(-2), and similar to 95% capacitance retention after 17 000 cycles. These MSCs also show maximum volumetric capacitance, volumetric energy density, and volumetric power density of 8.7 F cm(-3), 0.436 mW h cm(-3), and 31.78 W cm(-3), respectively. Overall, these are the highest values reported to date for such systems. These results are achieved by utilizing novel chemistries for the components of the MSCs and from tuning their geometry. The electrodes of the MSCs are formed from a nanocomposite of edge-oxidized graphite oxide (EOGO)/cerium oxide nanoparticles to benefit from both electrical double-layer capacitance (EDLC) and pseudocapacitance, the electrolyte is a UV-curable hydrogel based on (poly(ethylene glycol) diacrylate (PEGDA) + LiCl + lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) + water), and the current collector is a silver paste. These MSCs are fully packaged and sealed by 3D printing a package using polycaprolactone (PCL) and depositing a UV-curable resin-based encapsulant. Our findings demonstrate that such devices can be scaled to mm(3) volumes while continuing to deliver excellent performance, making them attractive candidates for a range of embedded energy storage applications.

Muon Collider Forum report

K. M. Black; S. Jindariani; D. Li; F. Maltoni; P. Meade et al. 

A multi-TeV muon collider offers a spectacular opportunity in the direct exploration of the energy frontier. Offering a combination of unprecedented energy collisions in a comparatively clean leptonic environment, a high energy muon collider has the unique potential to provide both precision measurements and the highest energy reach in one machine that cannot be paralleled by any currently available technology. The topic generated a lot of excitement in Snowmass meetings and continues to attract a large number of supporters, including many from the early career community. In light of this very strong interest within the US particle physics community, Snowmass Energy, Theory and Accelerator Frontiers created a cross-frontier Muon Collider Forum in November of 2020. The Forum has been meeting on a monthly basis and organized several topical workshops dedicated to physics, accelerator technology, and detector R&D. Findings of the Forum are summarized in this report.

Report A sensory-motor hand prosthesis with integrated thermal feedback

J. L. Muheim; F. Iberite; O. Akouissi; R. Monney; F. Morosato et al. 

Background: Recently, we reported the presence of phantom thermal sensations in amputees: thermal stimulation of specific spots on the residual arm elicited thermal sensations in their missing hands. Here, we exploit phantom thermal sensations via a standalone system integrated into a robotic prosthetic hand to provide real-time and natural temperature feedback. Methods: The subject (a male adult with unilateral transradial amputation) used the sensorized prosthesis to manipulate objects and distinguish their thermal properties. We tested his ability to discriminate between (1) hot, cold, and ambient temperature objects, (2) different materials (copper, glass, and plastic), and (3) artificial versus human hands. We also introduced the thermal box and block test (thermal BBT), a test to evaluate real-time temperature discrimination during standardized pick -and -place tasks. Findings: The subject performed all three discrimination tasks above chance level with similar accuracies as with his intact hand. Additionally, in all 15 sessions of the thermal BBT, he correctly placed more than half of the samples. Finally, the phantom thermal sensation was stable during the 13 recording sessions spread over 400 days. Conclusion: Our study paves the way for more natural hand prostheses that restore the full palette of sensations.

Lake surface cooling drives littoral-pelagic exchange of dissolved gases

T. Doda; C. L. Ramon; H. N. Ulloa; M. S. Brennwald; R. Kipfer et al. 

The extent of littoral influence on lake gas dynamics remains debated in the aquatic science community due to the lack of direct quantification of lateral gas transport. The prevalent assumption of diffusive horizontal transport in gas budgets fails to explain anomalies observed in pelagic gas concentrations. Here, we demonstrate through high-frequency measurements in a eutrophic lake that daily convective horizontal circulation generates littoral-pelagic advective gas fluxes one order of magnitude larger than typical horizontal fluxes used in gas budgets. These lateral fluxes are sufficient to redistribute gases at the basin-scale and generate concentration anomalies reported in other lakes. Our observations also contrast the hypothesis of pure, nocturnal littoral-to-pelagic exchange by showing that convective circulation transports gases such as oxygen and methane toward both the pelagic and littoral zones during the daytime. This study challenges the traditional pelagic-centered models of aquatic systems by showing that convective circulation represents a fundamental lateral transport mechanism to be integrated into gas budgets.

Extremely Red Galaxies at z=5-9 with MIRI and NIRSpec: Dusty Galaxies or Obscured Active Galactic Nuclei?

G. Barro; P. G. Perez-Gonzalez; D. D. Kocevski; E. J. McGrath; J. R. Trump et al. 

We study a new population of extremely red objects (EROs) recently discovered by the James Webb Space Telescope (JWST) based on their NIRCam colors F277W – F444W > 1.5 mag. We find 37 EROs in the Cosmic Evolution Early Release Science Survey (CEERS) field with F444W < 28 mag and photometric redshifts between 5 < z < 7, with median z=6.9(-1.6)(+1.0) . Surprisingly, despite their red long-wavelength colors, these EROs have blue short-wavelength colors (F150W - F200W similar to 0 mag) indicative of bimodal spectral energy distributions (SEDs) with a red, steep slope in the rest-frame optical, and a blue, flat slope in the rest-frame UV. Moreover, all these EROs are unresolved, point-like sources in all NIRCam bands. We analyze the SEDs of eight of them with MIRI and NIRSpec observations using stellar population models and active galactic nucleus (AGN) templates. We find that dusty galaxies or obscured AGNs provide similarly good SED fits but different stellar properties: massive and dusty, logM(star)/M-circle dot similar to 10 and A(V) greater than or similar to 3 mag, or low mass and obscured, logM(star)/M-circle dot similar to 7.5 and A(V) similar to 0 mag, hosting an obscured quasi-stellar object (QSO). SED modeling does not favor either scenario, but their unresolved sizes are more suggestive of AGNs. If any EROs are confirmed to have logM(star)/M-circle dot greater than or similar to 10.5, it would increase the pre-JWST number density at z > 7 by up to a factor similar to 60. Similarly, if they are QSOs with luminosities in the L-bol > 10(45-46) erg s(-1) range, their number would exceed that of bright blue QSOs by more than three orders of magnitude. Additional photometry at mid-infrared wavelengths will reveal the true nature of the red continuum emission in these EROs and will place this puzzling population in the right context of galaxy evolution.

EXPANDING AMJ’S MANUSCRIPT PORTFOLIO: RESEARCH METHODS ARTICLES DESIGNED TO ADVANCE THEORY AND SPAN BOUNDARIES

M. Gruber; P. Bliese 

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

A. G. Adame; J. Aguilar; S. Ahlen; S. Alam; G. Aldering et al. 

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg(2) using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg(2) program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

Multigraded algebras and multigraded linear series

Y. Cid-Ruiz; F. Mohammadi; L. Monin 

This paper is devoted to the study of multigraded algebras and multigraded linear series. For an Ns$\mathbb {N}<^>s$-graded algebra A$A$, we define and study its volume function FA:N+s -> R$F_A:\mathbb {N}_+<^>s\rightarrow \mathbb {R}$, which computes the asymptotics of the Hilbert function of A$A$. We relate the volume function FA$F_A$ to the volume of the fibers of the global Newton-Okounkov body Delta(A)$\Delta (A)$ of A$A$. Unlike the classical case of standard multigraded algebras, the volume function FA$F_A$ is not a polynomial in general. However, in the case when the algebra A$A$ has a decomposable grading, we show that the volume function FA$F_A$ is a polynomial with nonnegative coefficients. We then define mixed multiplicities in this case and provide a full characterization for their positivity. Furthermore, we apply our results on multigraded algebras to multigraded linear series. Our work recovers and unifies recent developments on mixed multiplicities. In particular, we recover results on the existence of mixed multiplicities for (not necessarily Noetherian) graded families of ideals and on the positivity of the multidegrees of multiprojective varieties.

Flood, farms and credit: The role of branch banking in the era of climate change

P. Abedifar; S. J. Kashizadeh; S. Ongena 

Using Iran’s unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietary information on more than 53,000 farmers, we find that farmers with a stronger relationship with their branch – particularly younger and females – are more likely to receive a recovery loan. Our findings underscore that despite recent technological advancements, relationship -based branch banking is still important for agrarian societies during catastrophic events.

Nanostructure and Optical Property Tailoring of Zinc Tin Nitride Thin Films through Phenomenological Decoupling: A Pathway to Enhanced Control

C. Hain; K. Wieczerzak; D. Casari; A. Sharma; A. Xomalis et al. 

This work addresses the need for precise control of thin film sputtering processes to enable thin film material tailoring on the example of zinc tin nitride (ZTN) thin films deposited via microwave plasma-assisted high power reactive magnetron sputtering (MAR-HiPIMS). The applied in situ diagnostic techniques (Langmuir probe and energy-resolved time-of-flight mass spectrometry) supported monitoring changes in the deposition environment with respect to microwave (MW) power. During MAR-HiPIMS, the presence of nitride ions in the gas phase (ZnN+, ZnN2+, SnN+, SnN2+) was detected. This indicates that the MW plasma facilitated their production, as opposed to pure R-HiPIMS. Additionally, MW plasma caused post-ionisation of sputtered atoms and reduced the overall energy-per-charge range of incoming charged species. By varying the MW power and substrate biasing, films with comparable chemical compositions (approximately Zn0.92Sn1.08N2) but different structures, ranging from polycrystalline to preferentially textured, were successfully produced. The application of density functional theory (DFT) further enabled the relationship between the lattice parameters and the optical properties of ZTN to be explored, where the material’s optical anisotropy nature was determined. It was found that despite considerable differences in crystallinity, the changes induced in the lattice parameters were subangstrom, causing only minor changes in the final optical properties of ZTN.

Dual-shot approach for polarization retrieval through a scattering medium

A. Roy; R. Parvin; A. Karmakar; A. Mandal; R. K. Singh et al. 

A dual-shot technique based on the field basis addition of two statistically independent speckle patterns is developed to recover an input polarization through a scattering layer. It is proposed theoretically, and demonstrated both numerically and experimentally that by tuning the linear polarization orientation of the reference speckle pattern to 0 degrees and 45 degrees w.r.t. the x-axis, polarization retrieval of an object beam through a scattering layer can be achieved by measuring the degree of polarization of the superposed speckle pattern. The proposed technique can have a wide range of applications in polarization sensing and biomedical imaging.

Flux correlators and semiclassics

E. C. Firat; A. Monin; R. Rattazzi; M. T. Walters 

We consider correlators for the flux of energy and charge in the background of operators with large global U(1) charge in conformal field theory (CFT). It has recently been shown that the corresponding Euclidean correlators generically admit a semiclassical description in terms of the effective field theory (EFT) for a conformal superfluid. We adapt the semiclassical description to Lorentzian observables and compute the leading large charge behavior of the flux correlators in general U(1) symmetric CFTs. We discuss the regime of validity of the large charge EFT for these Lorentzian observables and the subtleties in extending the EFT approach to subleading corrections. We also consider the Wilson-Fisher fixed point in d = 4 – epsilon dimensions, which offers a specific weakly coupled realization of the general setup, where the subleading corrections can be systematically computed without relying on an EFT.

Dislocation Hardening in a New Manufacturing Route of Ferritic Oxide Dispersion-Strengthened Fe-14Cr Cladding Tube

F. Salliot; A. Borbely; D. Sornin; R. E. Loge; G. Spartacus et al. 

The microstructure evolution associated with the cold forming sequence of an Fe-14Cr-1W-0.3Ti-0.3Y2O3 grade ferritic stainless steel strengthened by dispersion of nano oxides (ODS) was investigated. The material, initially hot extruded at 1100 degrees C and then shaped into cladding tube geometry via HPTR cold pilgering, shows a high microstructure stability that affects stress release heat treatment efficiency. Each step of the process was analyzed to better understand the microstructure stability of the material. Despite high levels of stored energy, heat treatments, up to 1350 degrees C, do not allow for recrystallization of the material. The Vickers hardness shows significant variations along the manufacturing steps. Thanks to a combination of EBSD and X-ray diffraction measurements, this study gives a new insight into the contribution of statistically stored dislocation (SSD) recovery on the hardness evolution during an ODS steel cold forming sequence. SSD density, close to 4.1015 m-2 after cold rolling, drops by only an order of magnitude during heat treatment, while geometrically necessary dislocation (GND) density, close to 1.1015 m-2, remains stable. Hardness decrease during heat treatments appears to be controlled only by the evolution of SSD.

Collimation simulations for the FCC-ee

A. Abramov; G. Broggi; R. Bruce; F. Carlier; M. Hofer et al. 

The collimation system of the Future Circular Collider, operating with leptons (FCC-ee), must protect not only the experiments against backgrounds, but also the machine itself from beam losses. With a 17.8 MJ stored energy of the electron and positron beams, they are highly destructive, and beam losses risk to cause damage or a quench of superconducting elements. Accurate collimation simulation tools and models are needed to design the collimation system and optimize the collimation performance, including magnetic tracking, synchrotron radiation and optics tapering, as well as particle -matter interactions. As no existing code was found that incorporated all these features, a new simulation software tool has been developed. The tool is based on an interface between a particle tracking engine, pyAT or Xtrack, and a Monte -Carlo particle -matter interaction engine for collimator scattering, BDSIM, which is based on Geant4. Results from a simulation of edge scattering from a beam halo collimator in the FCC-ee are presented to demonstrate the capabilities of the tool.

Impact of anthropogenic emission control in reducing future PM2.5 concentrations and the related oxidative potential across different regions of China

J. Liu; Z. Ye; J. H. Christensen; S. Dong; C. Geels et al. 

Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated historical and future PM2.5 concentrations and associated OP using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from WRF weather forecast model. Considering different future socio-economic pathways and emission scenario assumptions, we quantified how the contribution from various anthropogenic emission sectors will change under these scenarios. Results show that compared to the CESM_SSP2-4.5_CLE scenario (based on moderate radiative forcing and Current Legislation Emission), the CESM_SSP1-2.6_MFR scenario (based on sustainability development and Maximum Feasible Reductions) is projected to yield greater environmental and health benefits in the future. Under the CESM_SSP1-2.6_MFR scenario, annual average PM2.5 concentrations (OP) are expected to decrease to 30 jig m- 3 (0.8 nmol min -1 m- 3) in almost all regions by 2030, which will be 65 % (67 %) lower than that in 2010. From a long-term perspective, it is anticipated that OP in the Fen -Wei Plain region will experience the maximum reduction (82.6 %) from 2010 to 2049. Largely benefiting from the effective control of PM2.5 in the region, it has decreased by 82.1 %. Crucially, once emission reduction measures reach a certain level (in 2040), further reductions become less significant. This study also emphasized the significant role of secondary aerosol formation and biomass -burning sources in influencing OP during both historical and future periods. In different scenarios, the reduction range of OP from 2010 to 2049 is estimated to be between 71 % and 85 % by controlling precursor emissions involved in secondary aerosol formation and emissions from biomass burning. Results indicate that strengthening the control of anthropogenic emissions in various regions are key to achieving air quality targets and safeguarding human health in the future.

Processing factors affecting roughness, optical and mechanical properties of nanocellulose films for optoelectronics

J. J. Kaschuk; Y. Al Haj; J. V. Garcia; A. Kamppinen; O. J. Rojas et al. 

This work aims to understand how nanocellulose (NC) processing can modify the key characteristics of NC films to align with the main requirements for high-performance optoelectronics. The performance of these devices relies heavily on the light transmittance of the substrate, which serves as a mechanical support and optimizes light interactions with the photoactive component. Critical variables that determine the optical and mechanical properties of the films include the morphology of cellulose nanofibrils (CNF), as well as the concentration and turbidity of the respective aqueous suspensions. This study demonstrates that achieving high transparency was possible by reducing the grammage and adjusting the drying temperature through hot pressing. Furthermore, the use of modified CNF, specifically carboxylated CNF, resulted in more transparent films due to a higher nanosized fraction and lower turbidity. The mechanical properties of the films depended on their structure, homogeneity (spatial uniformity of local grammage), and electrokinetic factors, such as the presence of electrostatic charges on CNF. Additionally, we investigated the angle-dependent transmittance of the CNF films, since solar devices usually operate under indirect light. This work demonstrates the importance of a systematic approach to the optimization of cellulose films, providing valuable insight into the optoelectronic field.

Weak gravitational lensing measurements of Abell 2744 using JWST and shear measurement algorithm pyRRG-JWST

D. R. Harvey; R. Massey 

We update the publicly available weak lensing shear measurement algorithm pyRRG for the JWST, and apply it to UNCOVER DR1 imaging of galaxy cluster Abell 2744. At short wavelengths (<2.5 mu m), shear measurements are consistent between independent observations through different JWST bandpasses, and calibrated within 1.5 per cent of those from the Hubble Space Telescope. At longer wavelengths, shear is underestimated by similar to 5 per cent, probably due to coarser pixellization. We model the spatially varying point spread function using WebbPSF, whose moments are within 0.05 of real stars near the centre of the mosaic, where there are sufficient stars to also generate an empirical model. We measure shear from up to 162 galaxies arcmin(-2) to derive a map of dark plus baryonic mass with 12 arcsec (55 kpc) spatial resolution. All code, catalogues, and maps are available from https://github.com/davidharvey1986/pyRRG.

The CRL5-SPSB3 ubiquitin ligase targets nuclear cGAS for degradation

P. Xu; Y. Liu; C. Liu; B. Guey; L. Li et al. 

Cyclic GMP-AMP synthase (cGAS) senses aberrant DNA during infection, cancer and inflammatory disease, and initiates potent innate immune responses through the synthesis of 2 ‘ 3 ‘-cyclic GMP-AMP (cGAMP)1-7. The indiscriminate activity of cGAS towards DNA demands tight regulatory mechanisms that are necessary to maintain cell and tissue homeostasis under normal conditions. Inside the cell nucleus, anchoring to nucleosomes and competition with chromatin architectural proteins jointly prohibit cGAS activation by genomic DNA8-15. However, the fate of nuclear cGAS and its role in cell physiology remains unclear. Here we show that the ubiquitin proteasomal system (UPS) degrades nuclear cGAS in cycling cells. We identify SPSB3 as the cGAS-targeting substrate receptor that associates with the cullin-RING ubiquitin ligase 5 (CRL5) complex to ligate ubiquitin onto nuclear cGAS. A cryo-electron microscopy structure of nucleosome-bound cGAS in a complex with SPSB3 reveals a highly conserved Asn-Asn (NN) minimal degron motif at the C terminus of cGAS that directs SPSB3 recruitment, ubiquitylation and cGAS protein stability. Interference with SPSB3-regulated nuclear cGAS degradation primes cells for type I interferon signalling, conferring heightened protection against infection by DNA viruses. Our research defines protein degradation as a determinant of cGAS regulation in the nucleus and provides structural insights into an element of cGAS that is amenable to therapeutic exploitation.|The ubiquitin proteasomal system degrades nuclear cGAS in cycling cells.

Wandering principal optical axes in van der Waals triclinic materials

G. A. Ermolaev; K. V. Voronin; A. N. Toksumakov; D. V. Grudinin; I. M. Fradkin et al. 

Nature is abundant in material platforms with anisotropic permittivities arising from symmetry reduction that feature a variety of extraordinary optical effects. Principal optical axes are essential characteristics for these effects that define light-matter interaction. Their orientation – an orthogonal Cartesian basis that diagonalizes the permittivity tensor, is often assumed stationary. Here, we show that the low-symmetry triclinic crystalline structure of van der Waals rhenium disulfide and rhenium diselenide is characterized by wandering principal optical axes in the space-wavelength domain with above pi/2 degree of rotation for in-plane components. In turn, this leads to wavelength-switchable propagation directions of their waveguide modes. The physical origin of wandering principal optical axes is explained using a multi-exciton phenomenological model and ab initio calculations. We envision that the wandering principal optical axes of the investigated low-symmetry triclinic van der Waals crystals offer a platform for unexplored anisotropic phenomena and nanophotonic applications.|Principal optical axes define light-matter interactions in crystals and they are usually assumed to be stationary. Here, the authors report the observation of wavelength-dependent principal optical axes in ternary van der Waals crystals (ReS2 and ReSe2), leading to wavelength-switchable propagation directions of their waveguide modes.

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

P. Rahimi; C. Ecabert; S. Marcel 

Recently, it has been exposed that some modern facial recognition systems could discriminate specific demographic groups and may lead to unfair attention with respect to various facial attributes such as gender and origin. The main reason are the biases inside datasets, unbalanced demographics, used to train theses models. Unfortunately, collecting a large-scale balanced dataset with respect to various demographics is impracticable. In this paper, we investigate as an alternative the generation of a balanced and possibly bias-free synthetic dataset that could be used to train, to regularize or to evaluate deep learning-based facial recognition models. We propose to use a simple method for modeling and sampling a disentangled projection of a StyleGAN latent space to generate any combination of demographic groups (e.g. hispanic). Our experiments show that we can synthesis any combination of demographic groups effectively and the identities are different from the original training dataset. We also released the source code (1).

Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

A. Zappatore; N. Bykovskiy; G. De Marzi 

Numerous conductor designs for pulsed magnets based on High Temperature Superconductors (HTS), featuring stacks of tapes are currently being proposed. A major contribution to the AC losses is expected to be given by hysteresis losses. Several numerical models have been developed for the computation of hysteresis losses, however the lack of experimental data in conditions relevant for the coil operation did not allow extensive validation of those models. Here, we present the AC loss tests performed on HTS conductor with transport current in conditions of partial or full field penetration. After the validation of a numerical model on those data, we analyze the losses expected during the operation of the EU DEMO CS coil, assessing possible analytical formulations for the calculation of hysteresis losses in DEMO-relevant conditions.

Machine Learning Security Against Data Poisoning: Are We There Yet?

A. E. Cina; K. Grosse; A. Demontis; B. Biggio; F. Roli et al. 

Poisoning attacks compromise the training data utilized to train machine learning (ML) models, diminishing their overall performance, manipulating predictions on specific test samples, and implanting backdoors. This article thoughtfully explores these attacks while discussing strategies to mitigate them through fundamental security principles or by implementing defensive mechanisms tailored for ML.

An Optimal Control Formulation of Tool Affordance Applied to Impact Tasks

B. Ti; Y. Gao; J. Zhao; S. Calinon 

Humans use tools to complete impact-aware tasks, such as hammering a nail or playing tennis. The postures adopted to use these tools can significantly influence the performance of these tasks, where the force or velocity of the hand holding a tool plays a crucial role. The underlying motion planning challenge consists of grabbing the tool in preparation for the use of this tool with an optimal body posture. Directional manipulability describes the dexterity of force and velocity in a joint configuration along a specific direction. In order to take directional manipulability and tool affordances into account, we apply an optimal control method combining iterative linear quadratic regulator with the alternating direction method of multipliers. Our approach considers the notion of tool affordances to solve motion planning problems, by introducing a cost based on directional velocity manipulability. The proposed approach is applied to impact tasks in simulation and on a real 7-axis robot, specifically in a nail-hammering task with the assistance of a pilot hole. Our comparison study demonstrates the importance of maximizing directional manipulability in impact-aware tasks.

Hosing of a Long Relativistic Particle Bunch in Plasma

T. Nechaeva; L. Verra; J. Pucek; L. Ranc; M. Bergamaschi et al. 

Experimental results show that hosing of a long particle bunch in plasma can be induced by wakefields driven by a short, misaligned preceding bunch. Hosing develops in the plane of misalignment, selfmodulation in the perpendicular plane, at frequencies close to the plasma electron frequency, and are reproducible. Development of hosing depends on misalignment direction, its growth on misalignment extent and on proton bunch charge. Results have the main characteristics of a theoretical model, are relevant to other plasma -based accelerators and represent the first characterization of hosing.

SPAD Developed in 55 nm Bipolar-CMOS-DMOS Technology Achieving Near 90% Peak PDP

W-Y. Ha; E. Park; D. Eom; H-S. Park; F. Gramuglia et al. 

We present a single-photon avalanche diode (SPAD) developed in 55 nm bipolar-CMOS-DMOS (BCD) technology, which achieves high photon detection probability (PDP) while its breakdown voltage is lower than 20 V. To enhance the PDP performance, the SPAD junction is optimized with lightly-doped-drain and high-voltage-well layers which are provided in the BCD process. In addition, the dielectric layers over the SPAD are properly etched to reduce multilayer reflections so that the photon collection efficiency can be maximized. The SPAD achieves a peak PDP of 89.4% at 450 nm wavelength with the excess bias voltage of 7 V, while its breakdown voltage is 16.1 V. At the same bias condition, the device shows a dark count rate (DCR) of 38.2 cps/mu m(2). It also achieves a timing jitter of 55 ps at 940 nm with the 7 V excess bias. This new high-performance SPAD implemented in such an advanced node BCD technology operating at a low breakdown voltage is expected to have a major impact on several single-photon applications, especially biomedical sensing and imaging.

A Gradient-Gated SPAD Array for Non-Line-of-Sight Imaging

J. Zhao; F. Gramuglia; P. Keshavarzian; E-H. Toh; M. Tng et al. 

Time-resolved non-line-of-sight (NLOS) imaging based on single-photon avalanche diode (SPAD) detectors have demonstrated impressive results in recent years. To acquire adequate number of indirect photons from a hidden scene in the presence of overwhelming amount of early-arrival photons, a single-gated SPAD is widely employed to mitigate pile-up. However, additional prior knowledge of the hidden range and relay surface profile are required to preset the gating position and implement the reconstruction. With this work, we propose a gradient-gated technique to alleviate these shortcomings (pile-up and prior knowledge) in NLOS imaging with the development of a 6 x 6 SPAD array fabricated in a standard 55-nm Bipolar-CMOS-DMOS (BCD) technology. The SPAD sensor includes a delay-locked loop (DLL) block, a gating generator and a pixel array, which can be flexibly configured to free-running, single-gating and gradient-gating modes. The rise time of the gates is less than 450 ps (from 10% to 90%). In gradient-gating mode, the interval time between adjacent gates can be configured from 300 ps to 2 ns. In single-gating mode, the minimum gate window is measured below 5 ns. We demonstrated the sensor in a confocal NLOS imaging system that reconstructs hidden scenes with both retroreflective and diffuse objects. The presented scheme enables the development of calibration-free NLOS imaging modality for practical applications.

A 73% Peak PDP Single-Photon Avalanche Diode Implemented in 110 nm CIS Technology With Doping Compensation

M-J. Lee; U. Karaca; E. Kizilkan; C. Bruschini; E. Charbon 

In this article, we present 10 mu m diameter SPADs fabricated in 110 nm CIS technology based on an N (+) /HVPW junction, with enhanced sensitivity at short wavelengths. To reduce tunneling noise due to the highly-doped layers in the process, a doping compensation technique is used, which allows to adjust the doping profile of the HVPW. Thanks to this technique, DCR is reduced by a factor of 24 at 2 V excess bias voltage when compared to non-compensated devices. Furthermore, the maximum achievable PDP is enhanced by 49% thanks to the much lower DCR leading to a PDP of 73%, the highest ever reported at 440 nm, while the DCR is 12.5 cps/ mu m(2) , all at the 5 V excess bias. Since the junction is formed very close to the surface, the SPAD has excellent sensitivity in the UV spectrum, with a PDP of 43% at a wavelength of 350 nm. The proposed SPAD also achieves a PDP of 7% with a timing jitter of 68 ps at 850 nm at 5 V excess bias, which makes the device very useful for RGB-Z (RGB-D) sensors.

Data-driven statistical optimization of a groundwater monitoring network

M. Meggiorin; N. Naranjo-Fernandez; G. Passadore; A. Sottani; G. Botter et al. 

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurface hydrology and to assess water resources management and protection. Here, the basic idea to optimize the efficiency of existing gauging networks is to identify correlated timeseries to guide the removal of redundant measurement sites. Three data -driven statistical methods are compared: Oscillation correlation (OC) hierarchical (HC) and timeseries clustering (TSC). These methods are applied to a hydrogeologically complex groundwater system within the Bacchiglione basin (IT). Results suggest that: (i) the OC method returns well -gathered correlation clusters while being fast and easy to apply; (ii) HC underpins more spread clusters but it is useful when considering multiple groundwater characteristics; and (iii) TSC proves the best performing method for the study area, at the cost of being the most complex to implement. The latter identified 30 out of 59 existing timeseries as redundant, i.e., where sensors might be relocated elsewhere thus gaining in information quality (or else simply saving money if dismissed). We also suggest that the microscale of a random piezometric head field is a suitable measure to extract from data the monitoring frequency of manual measures in dismissed locations.

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

J. A. Frej; N. Shah; M. Knezevic; T. Nazaretsky; T. Kaser 

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners and courses. While these enriched representations allow more accurate and personalized recommendations, explainability remains a significant challenge which is especially problematic for certain domains with significant impact such as education and online learning. Recently, a novel class of recommender systems that uses reinforcement learning and graph reasoning over KGs has been proposed to generate explainable recommendations in the form of paths over a KG. Despite their accuracy and interpretability on e-commerce datasets, these approaches have scarcely been applied to the educational domain and their use in practice has not been studied. In this work, we propose an explainable recommendation system for MOOCs that uses graph reasoning. To validate the practical implications of our approach, we conducted a user study examining user perceptions of our new explainable recommendations. We demonstrate the generalizability of our approach by conducting experiments on two educational datasets: COCO and Xuetang.

Federated Linear Bandit Learning via Over-the-air Computation

J. Wang; Y. Jiang; X. Liu; T. Wang; Y. Shi 

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model updates to the server. The primary objective is to minimize cumulative regret across all devices within a finite time horizon. To reduce the communication overhead, devices communicate with the server via over-the-air computation (AirComp) over noisy fading channels, where the channel noise may distort the signals. In this context, we propose a customized federated linear bandits scheme, where each device transmits an analog signal, and the server receives a superposition of these signals distorted by channel noise. A rigorous mathematical analysis is conducted to determine the regret bound of the proposed scheme. Both theoretical analysis and numerical experiments demonstrate the competitive performance of our proposed scheme in terms of regret bounds in various settings.

Governing Outer Space as a Commons is Critical for Addressing Commons on Earth

M. A. Janssen; X-S. Yap 

Editorial for the special issue on “Commons in Space”.

Fungal mycelia: From innovative materials to promising products: Insights and challenges

W. Sun 

In transitioning toward a sustainable economy, mycelial materials are recognized for their adaptability, biocompatibility, and eco-friendliness. This paper updates the exploration of mycelial materials, defining their scope and emphasizing the need for precise terminology. It discusses the importance of mycelial type and characteristics, reviews existing and future research directions, and highlights the need for improved understanding, clarity, and standardization in this emerging field, aiming to foster and guide future research and development in sustainable material science.

High-Throughput and Flexible Belief Propagation List Decoder for Polar Codes

Y. Ren; Y. Shen; L. Zhang; A. T. Kristensen; A. Balatsoukas-Stimming et al. 

Due to its high parallelism, belief propagation (BP)decoding is amenable to high-throughput applications and thusrepresents a promising solution for the ultra-high peak datarate required by future communication systems. To bridge theperformance gap compared to the widely used successive cancel-lation list (SCL) decoding algorithm, BP list (BPL) decoding forpolar codes extends candidate codeword exploration via multiplepermuted factor graphs (PFGs) to improve the error-correctingperformance of BP decoding. However, it is a significant challengeto design a unified and flexible BPL hardware architecture thatsupports various PFGs and code configurations. In this paper,we present the first VLSI implementation of a BPL decoder forpolar codes that overcomes this implementation challenge with ahardware-friendly algorithm for on-the-fly flexible permutations.First, we introduce a sequential generation (SG) algorithm toobtain a near-optimal PFG set. Additionally, we demonstratethat any permutation can be decomposed into a combination ofmultiple fixed routings, and design a low-complexity permutationnetwork to generate graphs in an on-the-fly fashion. Our BPLdecoder has a low decoding latency by executing decoding andpermutation generation in parallel and supports arbitrary listsizes without area overhead. Experimental results based on 28nmFD-SOI technology show that for length-1024 polar codes witha code rate of one-half, our BPL decoder with 32 PFGs exhibitssimilar error-correcting performance to SCL with a list size of 4and achieves an average throughput of 25.63 Gbps and an areaefficiency of 29.46 Gbps/mm2, which is 1.82xand 4.33xfasterthan the state-of-the-art BP flip and SCL decoders, respectively

Deep learning approach for identification of H II regions during reionization in 21-cm observations – II. Foreground contamination

M. Bianco; S. K. Giri; D. Prelogovic; T. Chen; F. G. Mertens et al. 

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as noise and galactic foreground contamination that pose a challenge for accurate detection. In this study, we present the SegU-Net v2 framework, an enhanced version of our convolutional neural network, built to identify neutral and ionized regions in the 21-cm signal contaminated with foreground emission. We trained our neural network on 21-cm image data processed by a foreground removal method based on Principal Component Analysis achieving an average classification accuracy of 71 per cent between redshift z = 7 and 11. We tested SegU-Net v2 against various foreground removal methods, including Gaussian Process Regression, Polynomial Fitting, and Foreground-Wedge Removal. Results show comparable performance, highlighting SegU-Net v2’s independence on these pre-processing methods. Statistical analysis shows that a perfect classification score with AUC = 95 is possible for 8 < z < 10. While the network prediction lacks the ability to correctly identify ionized regions at higher redshift and differentiate well the few remaining neutral regions at lower redshift due to low contrast between 21-cm signal, noise, and foreground residual in images. Moreover, as the photon sources driving reionization are expected to be located inside ionized regions, we show that SegU-Net v2 can be used to correctly identify and measure the volume of isolated bubbles with V-ion > (10cmpc)(3 )at z > 9, for follow-up studies with infrared/optical telescopes to detect these sources.

Open-source microscope add-on for structured illumination microscopy

M. T. M. Hannebelle; E. Raeth; S. M. Leitao; T. Lukes; J. Pospisil et al. 

Super-resolution techniques expand the abilities of researchers who have the knowledge and resources to either build or purchase a system. This excludes the part of the research community without these capabilities. Here we introduce the openSIM add-on to upgrade existing optical microscopes to Structured Illumination super-resolution Microscopes (SIM). The openSIM is an open-hardware system, designed and documented to be easily duplicated by other laboratories, making super-resolution modality accessible to facilitate innovative research. The add-on approach gives a performance improvement for pre-existing lab equipment without the need to build a completely new system.|Researchers developed an open-hardware structured illumination microscopy add-on. This affordable upgrade provides super-resolution capabilities for normal optical microscopes. Detailed instructions enable easy reproduction to help democratize advanced microscopy.

An Ultralow Power Short-Range 60-GHz FMCW Radar in 22-nm FDSOI CMOS

S. C. Rengifo; F. Chicco; E. Le Roux; C. Enz 

This article presents the design of an ultralow power short-range 57-66 GHz frequency-modulated continuous-wave (FMCW) radar. The transmitter (TX) path includes a BPSK modulator in order to implement a low-IF architecture and it is optimized for short-range operation with 0 dBm output power. The receiver (RX) path is designed accordingly as a low-IF I/Q mixer-first for low power. The low-IF modulation minimizes the impact of LO-RX leakage, dc offsets, and flicker noise. It also allows orthogonal modulations for RX separation in multiple-input multiple-output (MIMO) operation. A band-tuning technique is used in the TX and RX for covering the wide band and it is tuned as the frequency is swept. The local oscillator (LO) distribution is designed in a modular approach to be able to extend the number of TX and RX paths for MIMO. The frequency synthesis is based on a quadrature digitally-controlled oscillator (QDCO) exploiting the coupling mechanism to achieve a maximum seamless and ultrawide frequency tuning range up to 11 GHz. A wide-band and low-power divider chain is designed using dynamic topologies. An all-digital phase-locked loop (ADPLL) is closed off-chip by means of an FPGA platform providing flexibility for the design and test of the digital loop filter without the need for extensive calibration. The 2-TX & 2-RX radar is integrated into GF 22-nm FDSOI CMOS technology. The average continuous power consumption is only 44.2 and 68.5 mW for 1-TX & 1-RX and 2-TX & 2-RX configuration, respectively.

Recovering Static and Time-Varying Communities Using Persistent Edges

K. Avrachenkov; M. Dreveton; L. Leskela 

This article focuses on spectral methods for recovering communities in temporal networks. In the case of fixed communities, spectral clustering on the simple time-aggregated graph (i.e., the weighted graph formed by the sum of the interactions over all temporal snapshots) does not always produce satisfying results. To utilise information carried by temporal correlations, we propose to employ different weights on freshly appearing and persistent edges. We show that spectral clustering on such weighted graphs can be explained as a relaxation of the maximum likelihood estimator of an extension of the degree-corrected stochastic block model with Markov interactions. We also study the setting of evolving communities, for which we use the prediction at time t-1 as an oracle for inferring the community labels at time t. We demonstrate the accuracy of the proposed methods on synthetic and real data sets.

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

A. Cortinovis; D. Kressner; Y. Nakatsukasa 

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov subspace. Such compression is usually computed by forming an orthonormal basis of the Krylov subspace using the Arnoldi method. In this work, we propose to compute (nonorthonormal) bases in a faster way and to use a fast randomized algorithm for least -squares problems to compute the compression of A onto the Krylov subspace. We present some numerical examples which show that our algorithms can be faster than the standard Arnoldi method while achieving comparable accuracy.

Recording physiological history of cells with chemical labeling

M-C. Huppertz; J. Wilhelm; V. Grenier; M. W. Schneider; T. Falt et al. 

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins that become labeled in the presence of both a specific cellular activity and a fluorescent substrate. The recording period is set by the presence of the substrate, whereas the cellular activity controls the degree of the labeling. The use of distinguishable substrates enabled the recording of successive periods of activity. We recorded protein-protein interactions, G protein-coupled receptor activation, and increases in intracellular calcium. Recordings of elevated calcium levels allowed selections of cells from heterogeneous populations for transcriptomic analysis and tracking of neuronal activities in flies and zebrafish.

Electronic structure and lattice dynamics of 1T-VSe2:Origin of the three-dimensional charge density wave

J. Diego; D. Subires; A. H. Said; D. A. Chaney; A. Korshunov et al. 

To characterize in detail the charge density wave (CDW) transition of 1T-VSe2, its electronic structure and lattice dynamics are comprehensively studied by means of x-ray diffraction, muon spectroscopy, angle resolved photoemission (ARPES), diffuse and inelastic x-ray scattering, and state-of-the-art first-principles density functional theory calculations. Resonant elastic x-ray scattering does not show any resonant enhancement at either V or Se, indicating that the CDW peak at the K edges describes a purely structural modulation of the electronic ordering. ARPES experiments identify (i) a pseudogap at T>T-CDW, which leads to a depletion of the density of states in the ML-M’L’ plane at T

Physical Review B

2024-01-16

DOI : 10.1103/PhysRevB.109.035133

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Q. Yang; Y. Li; C. Li; H. Wang; S. Yan et al. 

Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by jointly exploiting them, which is mainly due to the lack of audio-visual saliency datasets and insufficient exploitation of the multi-modality. In this article, we first construct an audio-visual saliency dataset with 57 360-degree videos watched by 63 viewers. Through a deep analysis of the constructed dataset, we find that the human gaze can be attracted by the auditory cues, resulting in a more concentrated saliency map if the sound source’s location is further provided. To jointly exploit the visual and audio features and their correlation, we further design a saliency prediction network for 360-degree videos (SVGC-AVA) based on spherical vector-based graph convolution and audio-visual attention. The proposed spherical vector-based graph convolution can process visual and audio features directly in the sphere domain, thus avoiding projection distortion incurred by traditional CNN-based predictors. In addition, the audio-visual attention scheme explores self-modal and cross-modal correlation for both modalities, which are further hierarchically processed with the U-Net’s multi-scale structure of SVGC-AVA. Evaluations on both our and public datasets validate that SVGC-AVA can achieve higher prediction accuracy, both qualitatively and subjectively.

High-κ Wide-Gap Layered Dielectric for Two-Dimensional van der Waals Heterostructures

A. Söll; E. Lopriore; A. K. Ottesen; J. Luxa; G. Pasquale et al. 

van der Waals heterostructures of two-dimensional materials have unveiled frontiers in condensed matter physics, unlocking unexplored possibilities in electronic and photonic device applications. However, the investigation of wide-gap, high-kappa layered dielectrics for devices based on van der Waals structures has been relatively limited. In this work, we demonstrate an easily reproducible synthesis method for the rare-earth oxyhalide LaOBr, and we exfoliate it as a 2D layered material with a measured static dielectric constant of 9 and a wide bandgap of 5.3 eV. Furthermore, our research demonstrates that LaOBr can be used as a high-kappa dielectric in van der Waals field-effect transistors with high performance and low interface defect concentrations. Additionally, it proves to be an attractive choice for electrical gating in excitonic devices based on 2D materials. Our work demonstrates the versatile realization and functionality of 2D systems with wide-gap and high-kappa van der Waals dielectric environments.

Linear-Covariance Loss for End-to-End Learning of 6D Pose Estimation

F. Liu; Y. Hu; M. Salzmann 

Most modern image-based 6D object pose estimation methods learn to predict 2D-3D correspondences, from which the pose can be obtained using a PnP solver. Because of the non-differentiable nature of common PnP solvers, these methods are supervised via the individual correspondences. To address this, several methods have designed differentiable PnP strategies, thus imposing supervision on the pose obtained after the PnP step. Here, we argue that this conflicts with the averaging nature of the PnP problem, leading to gradients that may encourage the network to degrade the accuracy of individual correspondences. To address this, we derive a loss function that exploits the ground truth pose before solving the PnP problem. Specifically, we linearize the PnP solver around the ground- truth pose and compute the covariance of the resulting pose distribution. We then define our loss based on the diagonal covariance elements, which entails considering the final pose estimate yet not suffering from the PnP averaging issue. Our experiments show that our loss consistently improves the pose estimation accuracy for both dense and sparse correspondence based methods, achieving state-of-the-art results on both Linemod-Occluded and YCB-Video.

MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency

Q. Wu; J. Yang; K. Sun; C. Zhang; Y. Zhang et al. 

3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Inspired by the great success of cycle tracking in unsupervised 2D SOT, we introduce the first semi-supervised approach to 3D SOT. Specifically, we introduce two cycle-consistency strategies for supervision: 1) Self tracking cycles, which leverage labels to help the model converge better in the early stages of training; 2) forward-backward cycles, which strengthen the tracker’s robustness to motion variations and the template noise caused by the template update strategy. Furthermore, we propose a data augmentation strategy named SOTMixup to improve the tracker’s robustness to point cloud diversity. SOTMixup generates training samples by sampling points in two point clouds with a mixing rate and assigns a reasonable loss weight for training according to the mixing rate. The resulting MixCycle approach generalizes to appearance matching-based trackers. On the KITTI benchmark, based on the P2B tracker [16], MixCycle trained with 10% labels outperforms P2B trained with 100% labels, and achieves a 28.4% precision improvement when using 1% labels. Our code will be released at https://github.com/Mumuqiao/MixCycle.

Learned Compressive Representations for Single-Photon 3D Imaging

F. Gutierrez-Barragan; F. Mu; A. Ardelean; A. Ingle; C. Bruschini et al. 

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that encodes distances along the time axis. As the spatio-temporal resolution of the histogram tensor increases, the in-pixel memory requirements and output data rates can quickly become impractical. To overcome this limitation, we propose a family of linear compressive representations of histogram tensors that can be computed efficiently, in an online fashion, as a matrix operation. We design practical lightweight compressive representations that are amenable to an in-pixel implementation and consider the spatio-temporal information of each timestamp. Furthermore, we implement our proposed framework as the first layer of a neural network, which enables the joint end-to-end optimization of the compressive representations and a downstream SPAD data processing model. We find that a well-designed compressive representation can reduce in-sensor memory and data rates up to 2 orders of magnitude without significantly reducing 3D imaging quality. Finally, we analyze the power consumption implications through an on-chip implementation.

AutoSynth: Learning to Generate 3D Training Data for Object Point Cloud Registration

Z. Dang; M. Salzmann 

In the current deep learning paradigm, the amount and quality of training data are as critical as the network architecture and its training details. However, collecting, processing, and annotating real data at scale is difficult, expensive, and time-consuming, particularly for tasks such as 3D object registration. While synthetic datasets can be created, they require expertise to design and include a limited number of categories. In this paper, we introduce a new approach called AutoSynth, which automatically generates 3D training data for point cloud registration. Specifically, AutoSynth automatically curates an optimal dataset by exploring a search space encompassing millions of potential datasets with diverse 3D shapes at a low cost. To achieve this, we generate synthetic 3D datasets by assembling shape primitives, and develop a meta-learning strategy to search for the best training data for 3D registration on real point clouds. For this search to remain tractable, we replace the point cloud registration network with a much smaller surrogate network, leading to a 4056.43 times speedup. We demonstrate the generality of our approach by implementing it with two different point cloud registration networks, BPNet [13] and IDAM [34]. Our results on TUDL [26], LINEMOD [23] and Occluded-LINEMOD [7] evidence that a neural network trained on our searched dataset yields consistently better performance than the same one trained on the widely used ModelNet40 dataset [65].

SoDaCam: Software-defined Cameras via Single-Photon Imaging

V. Sundar; A. Ardelean; T. Swedish; C. Brusschini; E. Charbon et al. 

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present “SoDaCam” that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon-cubes represent the spatio-temporal detections of photons as a sequence of binary frames, at frame-rates as high as 100 kHz. We show that simple transformations of the photon-cube, or photon-cube projections, provide the functionality of numerous imaging systems including: exposure bracketing, flutter shutter cameras, video compressive systems, event cameras, and even cameras that move during exposure. Our photon-cube projections offer the flexibility of being software-defined constructs that are only limited by what is computable, and shot-noise. We exploit this flexibility to provide new capabilities for the emulated cameras. As an added benefit, our projections provide camera-dependent compression of photon-cubes, which we demonstrate using an implementation of our projections on a novel compute architecture that is designed for single-photon imaging.

Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks

J. Qian; Y. Jiang; X. Liu; Q. Wang; T. Wang et al. 

With the growing popularity of electric vehicles (EVs), maintaining power grid stability has become a significant challenge. To address this issue, EV charging control strategies have been developed to manage the switch between vehicle-to-grid (V2G) and grid-to-vehicle (G2V) modes for EVs. In this context, multiagent deep reinforcement learning (MADRL) has proven its effectiveness in EV charging control. However, existing MADRL-based approaches fail to consider the natural power flow of EV charging/discharging in the distribution network and ignore driver privacy. To deal with these problems, this article proposes a novel approach that combines multi-EV charging/discharging with a radial distribution network (RDN) operating under optimal power flow (OPF) to distribute power flow in real time. A mathematical model is developed to describe the RDN load. The EV charging control problem is formulated as a Markov decision process (MDP) to find an optimal charging control strategy that balances V2G profits, RDN load, and driver anxiety. To effectively learn the optimal EV charging control strategy, a federated deep reinforcement learning algorithm named FedSAC is further proposed. Comprehensive simulation results demonstrate the effectiveness and superiority of our proposed algorithm in terms of the diversity of the charging control strategy, the power fluctuations on RDN, the convergence efficiency, and the generalization ability.

Nine lensed quasars and quasar pairs discovered through spatially extended variability in Pan-STARRS

F. Dux; C. A. C. Lemon; F. Courbin; F. Neira; T. Anguita et al. 

We present the proof of concept of a method for finding strongly lensed quasars using their spatially extended photometric variability through difference imaging in cadenced imaging survey data. We applied the method to Pan-STARRS, starting with an initial selection of 14 107 Gaia multiplets with quasar-like infrared colours from WISE. We identified 229 candidates showing notable spatially extended variability during the Pan-STARRS survey period. These include 20 known lenses and an additional 12 promising candidates for which we obtained long-slit spectroscopy follow-up. This process resulted in the confirmation of four doubly lensed quasars, four unclassified quasar pairs, and one projected quasar pair. Only three are pairs of stars or quasar + star projections. The false-positive rate accordingly is 25%. The lens separations are between 0.81 ” and 1.24 ”, and the source redshifts lie between z = 1 :47 and z = 2 :46. Three of the unclassified quasar pairs are promising dual-quasar candidates with separations ranging from 6.6 to 9.3 kpc. We expect that this technique is a particularly e fficient way to select lensed variables in the upcoming Rubin-LSST, which will be crucial given the expected limitations for spectroscopic follow-up.

Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback

T. Yeo; O. F. Kar; Z. Sodagar; A. Zamir 

We propose a method for adapting neural networks to distribution shifts at test-time. In contrast to training-time robustness mechanisms that attempt to anticipate and counter the shift, we create a closed-loop system and make use of test-time feedback signal to adapt a network on the fly. We show that this loop can be effectively implemented using a learning-based function, which realizes an amortized optimizer for the network. This leads to an adaptation method, named Rapid Network Adaptation (RNA), that is notably more flexible and orders of magnitude faster than the baselines. Through a broad set of experiments using various adaptation signals and target tasks, we study the generality, efficiency, and flexibility of this method. We perform the evaluations using various datasets (Taskonomy, Replica, ScanNet, Hypersim, COCO, ImageNet), tasks (depth, optical flow, semantic segmentation, classification), and distribution shifts (Cross-datasets, 2D and 3D Common Corruptions) with promising results.

Center-Based Decoupled Point Cloud Registration for 6D Object Pose Estimation

H. Jiang; Z. Dang; S. Gu; J. Xie; M. Salzmann et al. 

In this paper, we propose a novel center-based decoupled point cloud registration framework for robust 6D object pose estimation in real-world scenarios. Our method decouples the translation from the entire transformation by predicting the object center and estimating the rotation in a center- aware manner. This center offset-based translation estimation is correspondence-free, freeing us from the difficulty of constructing correspondences in challenging scenarios, thus improving robustness. To obtain reliable center predictions, we use a multi-view (bird’s eye view and front view) object shape description of the source-point features, with both views jointly voting for the object center. Additionally, we propose an effective shape embedding module to augment the source features, largely completing the missing shape information due to partial scanning, thus facilitating the center prediction. With the center-aligned source and model point clouds, the rotation predictor utilizes feature similarity to establish putative correspondences for SVD-based rotation estimation. In particular, we introduce a center-aware hybrid feature descriptor with a normal correction technique to extract discriminative, partaware features for high-quality correspondence construction. Our experiments show that our method outperforms the state-of-the-art methods by a large margin on realworld datasets such as TUD-L, LINEMOD, and OccludedLINEMOD. Code is available at https://github.com/JiangHB/CenterReg.

GECCO: Geometrically-Conditioned Point Diffusion Models

M. J. Tyszkiewicz; P. Fua; E. Trulls 

Diffusion models generating images conditionally on text, such as Dall-E 2 [51] and Stable Diffusion[53], have recently made a splash far beyond the computer vision community. Here, we tackle the related problem of generating point clouds, both unconditionally, and conditionally with images. For the latter, we introduce a novel geometrically-motivated conditioning scheme based on projecting sparse image features into the point cloud and attaching them to each individual point, at every step in the denoising process. This approach improves geometric consistency and yields greater fidelity than current methods relying on unstructured, global latent codes. Additionally, we show how to apply recent continuous-time diffusion schemes [59, 21]. Our method performs on par or above the state of art on conditional and unconditional experiments on synthetic data, while being faster, lighter, and delivering tractable likelihoods. We show it can also scale to diverse indoors scenes.

Data-Driven Behaviour Estimation in Parametric Games

A. M. Maddux; N. Pagan; G. Belgioioso; F. Doerfler 

A central question in multi-agent strategic games deals with learning the underlying utilities driving the agents’ behaviour. Motivated by the increasing availability of large data-sets, we develop an unifying data-driven technique to estimate agents’ utility functions from their observed behaviour, irrespective of whether the observations correspond to equilibrium configurations or to temporal sequences of action profiles. Under standard assumptions on the parametrization of the utilities, the proposed inference method is computationally efficient and finds all the parameters that rationalize the observed behaviour best. We numerically validate our theoretical findings on market share estimation problem under advertising competition, using historical data from the Coca-Cola Company and Pepsi Inc. duopoly.|Copyright (c) 2023 The Authors.

Object-oriented modelling of advanced computer cooling solutions

A. Leva; F. Terraneo; T. Cancelliere; M. Chioggi; W. Fornaciari et al. 

Modern computing systems are so energy- intensive to make efficient cooling vital for their operation. This is giving rise to a variety of innovative cooling solutions based on a mix of traditional and new techniques. The design and engineering of these solutions, as well as of the necessarily involved controls, requires dynamic simulation. Cooling simulation models must be capable of representing multi-physics cyber-physical systems, of connecting to specialised 3D chip simulators when high detail is needed, and at the same time of scaling up to the data centre – tailoring the detail level accordingly – when system-level studies need carrying out. In such a challenging scenario, an enabling technology is Object- Oriented Modelling (OOM). Along this approach we here present a Modelica library to serve the purposes just outlined, and that we are releasing as free software for the scientific and engineering community.Copyright (c) 2023 The Authors.

Automatic and high-precision microseismic monitoring of progressive failure prior, during, and after tunnel excavation

S. Momeni; M. Ziegler; C. Nussbaum; B. Lecampion 

Acoustic emission (AE) monitoring is commonly used to inspect the health of a structure continuously. During fracture processes elastic waves of AE are created and emitted, and sensors can capture these waves. The acquired signals can be processed to track and describe the spatio-temporal progression of fractures in solid materials in real-time using quantitative geophysics-based approaches. Typically, these data are processed manually due to the complex nature of the recorded signals mainly caused by heterogeneous medium conditions. This method hasn’t found many real-world applications due to its high processing costs of the acquired massive datasets, which may exceed terabytes. Therefore, for use in a structural health monitoring (SHM), an automated methodology that can lower costs while keeping high precision is required. We discuss the application of a new automated and high-precision AE monitoring algorithm and software called SIMORGH (Momeni et al., 2021a, b) suitable for SHM. The primary software has been created for monitoring laboratory-scale (i.e., cm-size specimen) hydraulic fracturing. The algorithm has been scaled up to work also for heterogeneous media at the meters scale. SIMORGH supports a number of common data formats and can handle both continuous and trigger-based data. We show some initial results of implementing SIMORGH for microseismic monitoring of rock mass damage evolution around a large-diameter experiment borehole in faulted Opalinus Clay shale in the Mont Terri rock laboratory, Switzerland. The AE data include time periods prior, during, and after borehole drilling and was produced in the frame of the so-called PF experiment (Progressive failure of structurally-controlled overbreaks; Ziegler & Loew, 2020). Eight piezoelectric sensors installed in four boreholes have been used to continually capture data at a sampling rate of 200 kHz, filling up more than 500 GB of memory per day. Active acoustic scanning measurements of body wave velocities showed a transversely isotropic medium with p-wave velocities varying from 2.5 km/s to 3.5 km/s in slow and fast orientations. Adopting the medium information, our software was able to locate over 2000 AE sources automatically for a monitoring period of two weeks, and with a localization precision of 2 mm. Several AEs were also localized manually and show comparable results with those obtained by SIMORGH. If enough processing units are provided, SIMORGH can perform the calculations in parallel and enable real-time SHM with excellent precision on fracture geometry imaging.

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

S. Momeni; T. Schumacher; L. Linzer; B. Lecampion 

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by sensors. Using quantitative geophysics-based methods, the recorded signals can be processed to monitor and describe the spatio-temporal growth of fracture in brittle materials such as concrete in real-time. Because of the complex nature of the recorded elastic signals and the non-homogeneous medium condition of concrete, data are usually processed manually. Combined with the high processing cost of the large datasets collected, which may exceed Terabytes, this approach has not found many real-world applications. Thus, an automated methodology is needed that can reduce costs, while maintaining high-precision, for implementation in a structural health monitoring (SHM) scheme. Here we discuss the application of a new automated and high-precision AE monitoring algorithm and software called SIMRGH [5,6] suitable for SHM of concrete structures. The core software has been developed for the laboratory-scale (in scale of centimeters) hydraulic fracture monitoring. It is up-scaled to the meters scale and works for heterogeneous media. The software works with various standard data formats and can handle trigger-based as well as continuous data. In this paper, we show some initial results of implementing the software for AE monitoring of two 4.88-meter-long concrete beams loaded in the laboratory and compare it with manually processed AE data. We were able to locate at least three up to 10 times more AE sources compared to when manual processing was used and with higher precision. If enough processing units are provided, the software can run in parallel and enable real-time SHM with excellent precision on crack geometry imaging. Future work will include implementing moment tensor inversion (MTI) to characterize AE source physics, providing valuable information for decision makers regarding the nature of the captured data.

Shaped Laser Pulses for Microsecond Time-Resolved Cryo-EM: Outrunning Crystallization during Flash Melting

C. R. Krüger; N. J. Mowry; M. Drabbels 

Water vitrifies if cooled at rates above 3 × 105 K/s. In contrast, when the resulting amorphous ice is flash heated, crystallization occurs even at a more than 10 times higher heating rate, as we have recently shown. This may present an issue for microsecond time-resolved cryo-electron microscopy experiments, in which vitreous ice samples are briefly melted with a laser pulse because transient crystallization could potentially alter the dynamics of the embedded proteins. Here, we demonstrate how shaped microsecond laser pulses can be used to increase the heating rate and outrun crystallization. Time-resolved electron diffraction experiments reveal that the critical heating rate for amorphous solid water (ASW) is about 108 K/s. Our experiments add to the toolbox of the emerging field of microsecond time-resolved cryo-electron microscopy by demonstrating a straightforward approach for avoiding crystallization during laser melting and for achieving significantly higher heating rates, which paves the way for nanosecond time-resolved experiments.

Electromagnetic time reversal for online partial discharge location in power cables: Influence of interfering reflections from grid components

A. Ragusa; P. A. A. F. Wouters; H. Sasse; A. Duffy; F. Rachidi-Haeri et al. 

In online single-sided partial discharge (PD) location, the measured PD reflection patterns are affected by the characteristics of all the components of the associated power network. This paper analyses the performance of a PD location method based on electromagnetic time reversal (EMTR) theory, when interfering reflections contribute to the transient signals emitted by the PD event. The topology analysed is formed from a ring main unit (RMU) in a medium voltage grid with mixed cross-linked polyethylene and paper-insulated lead-covered (PILC) cable sections. The PD reflection patterns, observed at the RMU, are disturbed by the reflections coming from the impedance discontinuities of the circuit and by the reflections coming from the cable ends of the PILC cables connected to the RMU. The simulated configuration is chosen such that classical location techniques tend to fail due to overlapping peaks and other signal distortion. This is because the classic techniques are based on identifying individual reflection peaks from which the PD source can be determined via differences in time of arrival. The numerical investigation shows that the accuracy of the EMTR-based location method is robust against these effects, achieving a PD localisation with an error less than the 0.1%. The results also show that the EMTR-based method can localise PDs using a PD monitoring point located somewhere along the network and not necessarily at the line termination.

Comparison of selected surface level ERA5 variables against in‐situ observations in the continental Arctic

J. B. Pernov; J. Gros-Daillon; J. Schmale 

In this study, data from 17 ground-based, continental Arctic observatories areused to evaluate the performance of the European Centre for Medium-RangeWeather Forecasts Reanalysis version 5 (ERA5) reanalysis model. Three aspectsare evaluated: (i) the overall reproducibility of variables at all stations for allseasons at one-hour time resolution; (ii) the seasonal performance; and (iii)performance between different temporal resolutions (one hour to one month).Performance is evaluated based on the slope,R2value, and root-mean-squarederror (RMSE). We focus on surface meteorological variables including 2-mair temperature (temperature), relative humidity (RH), surface pressure, windspeed, zonal and meridional wind speed components, and short-wave down-ward (SWD) radiation flux. The overall comparison revealed the best resultsfor surface pressure (0.98±0.02,R2mean±standard deviation [σR2]), followedby temperature (0.94±0.02), and SWD radiation flux (0.87±0.03) while windspeed (0.49±0.12), RH (0.42±0.20), zonal (0.163±0.15) and meridional windspeed (0.129±0.17) displayed poor results. We also found that certain variables(surface pressure, wind speed, meridional, and zonal wind speed) showed noseasonal dependency while others (temperature, RH, and SWD radiation flux)performed better during certain seasons. Improved results were observed whendecreasing the temporal resolution from one hour to one month for temper-ature, meridional and zonal wind speed, and SWD radiation flux. However,certain variables (RH and surface pressure) showed comparatively worse resultsfor monthly resolution. Overall, ERA5 performs well in the Arctic, but cautionneeds to be taken with wind speed and RH, which has implications for the useof ERA5 in global climate models. Our results are useful to the scientific com-munity as it assesses the confidence to be placed in each of the surface variablesproduced by ERA5.KEYWORDSArctic, ERA5, meteorology, reanalysis model/in-situ observation comparisonJakob Boyd Pernov and Jules Gros-Daillon contributed equally to this work.This is an open access article under the terms of theCreative Commons AttributionLicense, which permits use, distribution and reproduction in any medium, provided theoriginal work is properly cited.© 2024 The Authors.Quarterly Journal of the Royal Meteorological Societypublished by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.Q J R Meteorol Soc. 2024;1–24.wileyonlinelibrary.com/journal/qj1

Settlement Layout Optimization: Appropriate Communal Open Space

L. A. Herrera Quiroz; Y. Pedrazzini 

Settlement Layout Optimization: Appropriate Communal Open Space – Annex 1: Public Services & Facilities (PSF)

L. A. Herrera Quiroz; Y. Pedrazzini 

Settlement Layout Optimization: Appropriate Communal Open Space – Annex 2: Efficient Circulation Network (CN)

L. A. Herrera Quiroz; Y. Pedrazzini 

3D Geomechanical Modelling of CO2 Storage with Focus on Fault Stability

E. Gallyamov; B. Lecampion; N. Richart; G. Anciaux; J-F. Molinari 

3D Geomechanical Modelling of CO2 Storage with Focus on Fault Stability

E. Gallyamov; N. Richart; B. Lecampion; J-F. Molinari; G. Anciaux 

A digital twin of the subsurface is crucial for all performance and risks assessments of a CO2 storage activities. The goal of the project is to develop an efficient fully-coupled geomechanical simulator for CO2 storage capable to model fluid flow along cracks and faults and their associated opening and slip. To reach this goal, we extend the open-source finite element library Akantu to simulate the time-dependent hydro-mechanical changes associated with CO2 injection. Thanks to the high-performance computing capabilities of Akantu, the solver will allow representing the complete three-dimensional geological structure of a site including the presence of natural fractures and faults whose reactivation potential is critical to assess.

Un modèle pluraliste d’éducation numérique, l’expérience du canton de Vaud en Suisse

D. Boullier; F. Chessel-Lazzarotto; G. Liegeois; F. Mondada; N. Badoux et al. 

Le canton de Vaud en Suisse a lancé depuis 2019 un nouveau format d’éducation numérique pour tous les niveaux, de la maternelle au gymnase, qui associe étroitement informatique et sciences sociales. Dans ce compte-rendu d’expérience, nous présentons à la fois le modèle qui l’a inspiré, les références conceptuelles auxquelles il se rattache, des exemples de sa mise en œuvre ainsi que les conditions de sa réalisation. Le modèle est pluraliste car il combine plusieurs visées pédagogiques : comprendre l’algorithmie comme principe de modularité dans le traitement des problèmes, comprendre les environnements socio-techniques historiques et contemporains dans lesquels sil sont déployés, s’engager dans des décisions de délégation aux machines à divers niveaux, s’engager dans une autorégulation éthique dans ces choix. Dans ce cadre, une variante du modèle centrée sur les enjeux écologiques est présentée.

La Science Informatique au lycee : Comment assurer des ressources de qualite ?

C. Pulfrey 

La qualité des ressources disponibles pour l’enseignement de la Science Informatique au niveau du lycée est un facteur décisif dans la qualité de l’enseignement et la motivation des jeunes à poursuivre des études dans la matière. Dans cet atelier, nous avons l’occasion en premier d’échanger sur les défis qui confrontent les enseignants de Science Informatique au lycée. Par la suite nous découvrons et testons une collection de nouvelles ressources, spécialement conçus par des enseignants spécialistes et disponibles gratuitement en ligne. Ces ressources couvrent les grands thèmes de la Science informatique, c’est-à- dire la Représentation de l’Information, l’Algorithmique, l’Architecture des ordinateurs et la Programmation et en plus il y a une partie des ressources dédiée à l’enseignement de la Sociologie de la Science Informatique. Nous examinons également les retours des enseignants et des élèves qui les ont testées dans le cadre d’un projet pilote.

Activités débranchées ludiques pour l’enseignement de concepts d’édu- cation numérique au collège

A. C. Nicole; Y. Secq 

Cet article présente deux ressources pédagogiques permettant d’aborder de manière ludique des éléments d’éducation numérique avec des élèves de collège. La première activité, Captology, est un jeu de cartes inspiré de la mécanique du jeu des 1000 bornes, qui vise à sensibiliser aux techniques mises en œuvre par certains services numériques pour exploiter l’attention des utilisateurs à des fins publicitaires. La seconde activité, Les Cordées du Cervin, est un jeu de plateau permettant d’initier les élèves aux notions de variable et d’affectation. Ces deux ressources ont été développées dans le cadre de la réforme de l’éducation numérique menée au niveau de l’école obligatoire dans le canton de Vaud en Suisse, et sont diffusées sous licence Creative Commons.

Activités débranchées en Science Informatique pour les 3-8 ans

F. Chessel-Lazzarotto 

Au travers de deux activités phares du manuel Décodage 1-4P vaudois (élèves de 4 à 8 ans), l’atelier du mercredi 17 mai 2023 a proposé à 35 enseignants en formation initiale d’aborder les concepts de Science Informatique pour des élèves de classes primaires. Vous trouverez dans cet article un exposé de l’atelier réalisé en 2022 pour DIDAPRO d’une durée 45 minutes, qui a permis de manipuler quelques étapes des deux activités et de mettre en valeur les notions et les enjeux sous-jacents. La première activité, le jeu de la grue, concerne la création de séquences d’instructions et la formalisation du langage associé. La seconde activité Pixel Paravent concerne la représentation des données et leur encodage. Ensuite, quelques résultats provenant des sessions de formation pilotées dans le Canton de Vaud (Suisse) de 2018 à 2022 sont présentés.

Concevoir un robot avec des élèves de 10-12 ans Felipe

F. Martinez 

Cet atelier présente une activité débranchée visant la conception d’un robot en réponse à un besoin spécifique. Reposant sur une approche méthodique, elle est principalement destinée à des élèves de 10-12 ans. Avant d’entamer le processus de conception, plusieurs étapes préliminaires sont entreprises. Elles incluent notamment l’observation et la classification de robots selon différents critères, ainsi que la définition et le partage des avantages et des inconvénients associés à leur utilisation. La variété des composants embarqués dans un robot est également abordée afin de saisir l’articulation fonctionnelle “capteurs-programmes-actionneurs”. Ces différentes étapes conduisent les élèves à effectuer des choix réfléchis et à se positionner de façon critique quant à la place des robots dans notre société. Ils·elles sont finalement amené·e·s à concevoir leur robot à l’aide d’un plateau de conception et de cartes à agencer. La présente ressource a été développée dans le cadre du projet EduNum du Canton de Vaud, Suisse, et est diffusée sous licence Creative Common.

Jeu de rôle sur les enjeux de l’automatisation de la conduite

S. Agrebi 

Jeu de rôle sur les enjeux de l’automatisation de la conduite Des navettes autonomes dans ma commune ? Sonia AGREBI Centre LEARN, École Polytechnique Fédérale de Lausanne, Suisse Numéro thématique 4 / 2024 RÉSUMÉ Cet atelier présente une ressource pédagogique débranchée pour sensibiliser les élèves aux enjeux liés à la conduite autonome, tout en ajoutant une touche ludique à leur apprentissage. Pour cette activité, la classe se transforme en un conseil communal fictif, créant ainsi un jeu de rôle autour de l’introduction des navettes autonomes. Les élèves se voient attribuer divers rôles, ce qui contribue à leur engagement. Ils·elles débattent de l’adoption de ces navettes dans leur commune et explorent les différentes perspectives des acteurs impliqués de manière interactive. Les ressources nécessaires à cette activité ont été conçues dans le cadre de la formation CAS pour l’Enseignement de la Science Informatique en Secondaire 1 faisant partie du projet EduNum du Canton de Vaud, Suisse. Elles sont destinées aux élèves âgés de 12 à 15 ans. Cet atelier offre une opportunité aux participants de découvrir cette ressource pédagogique ainsi que sa mise en pratique en classe.

Jeux de cartes sérieux sur des notions de cybersécurité

F. Martinez; Y. Secq 

Cet article présente une modalité pédagogique débranchée à la croisée d’un escape game et d’un livre dont vous êtes le héros pour initier des élèves de 13 à 16 ans à des notions de culture informatique liées à la cybersécurité. L’objectif est de plonger les élèves dans un scénario les invitant à comprendre une situation en découvrant des notions de culture informatique lors de leur parcours. À travers deux jeux de cartes, les élèves plongent dans un scénario les invitant à réaliser des choix et à se confronter à une variété de problématiques : le premier jeu se centre principalement sur des situations pouvant être rencontrées quotidiennement par les élèves et le second sur d’autres plus complexes et propres à un contexte professionnel. L’atelier permettra aux participants d’expérimenter cette modalité avant de découvrir la conception scénaristique et technique de ces jeux sérieux. Cette modalité a été développée dans le cadre de la formation continue CAS pour l’Enseignement de la Science Informatique en Secondaire 1 au sein du projet pilote Edunum du canton de Vaud en Suisse.

Numérique et environnement : cartographie du cycle de vie de nos équipements numériques

S. Agrebi 

Cet article présente une activité pédagogique débranchée pour sensibiliser les élèves aux enjeux environnementaux et sociaux liés à l’utilisation des technologies du numérique sur la base d’une cartographie de leur cycle de vie : fabrication, utilisation et fin de vie. L’activité vise une prise de conscience de la matérialité du numérique et de ses multiples conséquences. Elle encourage également les élèves à réfléchir aux actions possibles, à la fois individuelles et collectives, pouvant être entreprises pour limiter voire réduire les impacts environnementaux du numérique. Les cartes servant à la réalisation de la cartographie ont été réalisées dans le cadre du projet EduNum du Canton de Vaud, Suisse. Elles sont destinées à des élèves de 12 à 15 ans. Des déclinaisons adaptées aux élèves plus jeunes et plus âgés existent également. Cet atelier offre aux participants l’occasion de découvrir cette activité ainsi que sa mise en œuvre avec des élèves.

Lithium tantalate photonic integrated circuits for volume manufacturing

C. Wang; T. Kippenberg 

Dataset for the manuscript “Lithium tantalate photonic integrated circuits for volume manufacturing”.  DOI: 10.1038/s41586-024-07369-1 Contains all raw data and code used to produce the Figures and Extended Data Figures in the manuscript. 

Bioengineering functional organoid models across scales

Scalable constrained optimization

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Design for demise applied to spacecraft structural panels and experiments for ClearSpace One platform

Toward Wearable Biosensing by Spectroscopy-free Raman Shift Detection and Soft Optofluidics

Numerical Study of the Attosecond Free-Electron Laser Pulse Generation in the Soft X-ray Regime at the SwissFEL

Shear and steel-fibre reinforcement for the punching resistance of flat slabs at internal and edge columns

Additively manufactured stretchable zipping electrostatic actuators

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Global fluid simulations of plasma turbulence in stellarators

Hearing structure in music: An empirical inquiry into listening as representation and processing

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures

On the Theory and Practice of Modern Secure Messaging

Secure and Efficient Cryptographic Algorithms in a Quantum World

Optimality principles for the analysis of biological processes across scales: From enzyme kinetics to microbiome dynamics

Experimental study and interpretative modelling of the Power Exhaust in Configurations with Multiple X-Points in TCV

Single-Photon Avalanche Diode Image Sensors for Harsh Radiation Environments

Gyrokinetic simulations of turbulence in magnetic fusion plasmas using a delta-f PIC scheme with evolving background

Advanced Silicon and SWIR Single-Photon Avalanche Diodes: Design, Simulation, and Characterization

Network time series forecasting in photovoltaics power production

Charge-Transfer States in Organic Nanowires

A Cavity-Microscope for Quantum Simulations with Locally-Controllable All-to-All Interactions

Beyond fine-tuning: LoRA modules boost near-OOD detection and LLM security

E. Salimbeni; F. Craighero; R. Khasanova; M. Vasic; P. Vandergheynst 

Under resource constraints, LLMs are usually fine- tuned with additional knowledge using Parameter Efficient Fine-Tuning (PEFT), using Low-Rank Adaptation (LoRA) modules. In fact, LoRA injects a new set of small trainable matrices to adapt an LLM to a new task, while keeping the latter frozen. At deployment, LoRA weights are subsequently merged with the LLM weights to speed up inference. In this work, we show how to exploit the unmerged LoRA’s embedding to boost the performance of Out-Of-Distribution (OOD) detectors, especially in the more challenging near- OOD scenarios. Accordingly, we demonstrate how improving OOD detection also helps in characterizing wrong predictions in downstream tasks, a fundamental aspect to improve the reliability of LLMs. Moreover, we will present a use-case in which the sensitivity of LoRA modules and OOD detection are employed together to alert stakeholders about new model updates. This scenario is particularly important when LLMs are out-sourced. Indeed, test functions should be applied as soon as the model changes the version in order to adapt prompts in the downstream applications. In order to validate our method, we performed tests on Multiple Choice Question Answering datasets, by focusing on the medical domain as a fine-tuning task. Our results motivate the use of LoRA modules even after deployment, since they provide strong features for OOD detection for fine-tuning tasks and can be employed to improve the security of LLMs.

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

M. V. Nallapareddy; F. Craighero; C. Gobet; F. Naef; P. Vandergheynst 

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome dwell times, and in turn, predict the speed of translation. The proposed method, RiboGL, combines graph and recurrent neural networks to account for both graph and sequence-based features. The model takes a mixed graph representing the secondary structure of the mRNA sequence as input, which incorporates both sequence and structure codon neighbors. In our experiments, RiboGL greatly outperforms the state-of-the-art RiboMIMO model for ribosome density prediction. We also conduct multiple ablation studies to justify the design choices made in building the pipeline. Additionally, we use gradient-based interpretability to understand how the codon context and the structural neighbors affect the ribosome dwell time at the A site. By individually analyzing the genes in the dataset, we elucidate how structure neighbors could also potentially play a role in defining the ribosome dwell times. Importantly, since structure neighbors can be far away in the sequence, a recurrent model alone could not easily extract this information. This study lays the foundation for understanding how the mRNA secondary structure can be exploited for dwell time prediction, and how in the future other graph modalities such as features from the nascent polypeptide can be used to further our understanding.

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

N. Kotluk; R. Tormey 

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compassion into engineering ethics cases influenced the intensity of compassion associated with the protagonists of the cases. We utilised modified versions of the Engineering and Science Issues Test (ESIT) cases, employing three methods to intensify compassion associated with the cases’ protagonists: (i) implicit induction, (ii) explicit expression, and (iii) through the description of severe consequences. The participants (n = 415), predominantly engineering students (90%), were divided into one control group and three experimental groups. Results indicated that all three methods increased the intensity of compassion in the cases. However, the implicit method had a relatively weaker impact than the other two methods which had similar effects on the intensity of compassion. Other emotions did not seem to be impacted by the changes. This study provides valuable insights into effective methods to increase the intensity of compassion in engineering ethics cases without affecting other emotions.

Catalytic Enantioselective Synthesis of Inherently Chiral Macrocycles by Dynamic Kinetic Resolution

Q-L. Lu; X-D. Wang; S. Tong; J. Zhu; M-X. Wang 

Kinetically fast racemization of chiral substrates through an achiral intermediate and enantioselective functionalization of one of the enantiomeric substrates forms the basis of the dynamic kinetic resolution (DKR) of centrally chiral molecules. We report herein DKR of inherently chiral macrocycles through enantioselective alkylation of one of the two rapidly interconverting conformers. Reaction of heteracalixaromatics with bromomethylarenes in the presence of a catalytic amount of Cinchonine- derived chiral phase transfer catalyst (PTC) affords inherently chiral O- alkylated products in 90%−99% yields with up to 95% enaniomeric excess. Density functional theory calculations indicate that a host−guest-like interaction between the macrocyclic substrate and catalyst effectively differentiates the reactivity of two enantiomers devoid of chiral elements.

Rock Anisotropy Promotes Hydraulic Fracture Containment at Depth

G. Lu; S. Momeni; C. Peruzzo; F-E. Moukhtari; B. Lecampion 

Lippmann Photography: Past, Present, and Future

A. Latty; A. Hoffet; N. Isaac; P. Prandoni 

The purpose of this project was to bring to a wider public an almost forgotten technique for color photography, invented by Gabriel Lippmann in 1892 and rewarded with a Nobel prize in 1908. The project was born out of a longstanding cooperation between EPFL and the Elysée photography museum in Lausanne, which holds the largest collection of original Lippmann plates, and it was crowned by an extremely successful Lippmann photography exhibition at Plateforme10 in March 2023. This work was made possible by an SNF Agora grant.

FLO:RE – A new floor system made of reused reinforced concrete and steel elements

N. J. Bertola; C. M. Küpfer; M. Bastien Masse; C. Fivet 

Carefully extracting reinforced concrete (RC) elements from soon-to-be demolished structures and reusing them as load-bearing components is an emerging circular low-carbon alternative to building new structures. As floor construction typically accounts for the most upfront carbon footprint of buildings, this paper presents the design, structural verifications and construction process of FLO:RE, a new floor system built with reused saw-cut RC slab elements and steel beams. To value all preexisting properties, the new system reuses the RC elements in bending, taking advantage of the existing steel reinforcement. The life-cycle assessment (LCA) shows that the upfront carbon footprint of the reused system can be as low as 5 kgCO2,eq/m2, reducing by up to 94 % compared to conventional RC flat slabs. The construction and monitoring of a 30-m2 mock-up demonstrate the new-system construction ease and structural performance. This study proves the technical feasibility of reusing old RC slab elements in new floor systems.

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

M. O. A. Abdelfattah; M. Hassan; A. Alahi 

Current transformer-based skeletal action recognition models tend to focus on a limited set of joints and low-level motion patterns to predict action classes. This results in significant performance degradation under small skeleton perturbations or changing the pose estimator between training and testing. In this work, we introduce MaskCLR, a new Masked Contrastive Learning approach for Robust skeletal action recognition. We propose an Attention-Guided Probabilistic Masking strategy to occlude the most important joints and encourage the model to explore a larger set of discriminative joints. Furthermore, we propose a Multi-Level Contrastive Learning paradigm to enforce the representations of standard and occluded skeletons to be class-discriminative, i.e., more compact within each class and more dispersed across different classes. Our approach helps the model capture the high-level action semantics instead of low-level joint variations, and can be conveniently incorporated into transformer based models. Without loss of generality, we combine MaskCLR with three transformer backbones: the vanilla transformer, DSTFormer, and STTFormer. Extensive experiments on NTU60, NTU120, and Kinetics400 show that MaskCLR consistently outperforms previous state-of-the-art methods on standard and perturbed skeletons from different pose estimators, showing improved accuracy, generalization, and robustness.

Social-Transmotion: Promptable Human Trajectory Prediction

S. Saadatnejad; Y. Gao; K. Messaoud Ben Amor; A. Alahi 

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating the space. To address this, we introduce Social-Transmotion, a generic Transformer-based model that exploits diverse and numerous visual cues to predict human behavior. We translate the idea of a prompt from Natural Language Processing (NLP) to the task of human trajectory prediction, where a prompt can be a sequence of x-y coordinates on the ground, bounding boxes in the image plane, or body poses in either 2D or 3D. This, in turn, augments trajectory data, leading to enhanced human trajectory prediction. Using masking technique, our model exhibits flexibility and adaptability by capturing spatiotemporal interactions between agents based on the available visual cues. We delve into the merits of using 2D versus 3D poses, and a limited set of poses. Additionally, we investigate the spatial and temporal attention map to identify which keypoints and frames of poses are vital for optimizing human trajectory prediction. Our approach is validated on multiple datasets, including JTA, JRDB, Pedestrians and Cyclists in Road Traffic, and ETH-UCY. The code is publicly available: https://github.com/vita-epfl/social-transmotion.

Modeling Mode-Dependent Lane Discipline in Hybrid Traffic

G. Anagnostopoulos; N. Geroliminis 

Complex interactions can be observed in hybrid transportation systems, where cars share the same road space with other modes such as motorcycles, bicycles or even e-scooters. In this work we further built upon the concept of mode dependent lane discipline. Mode dependent lane discipline means that motorcycles do not necessarily follow the predefined lanes and may form emergent, virtual lanes in the available free spaces without any prior agreement in a self-organized manner. The other modes, such as cars, follow the lanes as given by the infrastructure. This is different than the traditional dualism between lane-based and lane-free traffic. Motivated from empirical findings, our modelling approach draws inspiration both from vehicular, as well as from pedestrian dynamics literature. At the same time, we recognize that motorcycles are neither pedestrians nor cars, as they have their own special features. Therefore, there is a need for dedicated methods that are not available off-the-shelf. Also, given that our detailed observations come from an urban context, even standard car-following models that have been mainly developed with freeways in mind, are not adequate for reproducing the observed phenomena and consequently we make a first step towards revisiting traffic flow dynamics in general. We utilize high accuracy trajectories from the congested city center of Athens that have been collected from a swarm of drones through the pNEUMA experiment.

When Your AI Becomes a Target: AI Security Incidents and Best Practices

K. Grosse; L. Bieringer; T. R. Besold; B. Biggio; A. Alahi 

In contrast to vast academic efforts to study AI security, few real-world reports of AI security incidents exist. Released incidents prevent a thorough investigation of the attackers’ motives, as crucial information about the company and AI application is missing. As a consequence, it often remains unknown how to avoid incidents. We tackle this gap and combine previous reports with freshly collected incidents to a small database of 32 AI security incidents. We analyze the attackers’ target and goal, influencing factors, causes, and mitigations. Many incidents stem from non-compliance with best practices in security and privacy-enhancing technologies. In the case of direct AI attacks, access control may provide some mitigation, but there is little scientific work on best practices. Our paper is thus a call for action to address these gaps.

Adolescent Stress-Induced Ventral Hippocampus Redox Dysregulation Underlies Behavioral Deficits and Excitatory/Inhibitory Imbalance Related to Schizophrenia

T. Santos-Silva; C. F. B. Lopes; D. Hazar Ülgen; D. A. Guimarães; F. S. Guimarães et al. 

Background and hypothesis: Redox dysregulation has been proposed as a convergent point of childhood trauma and the emergence of psychiatric disorders, such as schizophrenia (SCZ). A critical region particularly vulnerable to environmental insults during adolescence is the ventral hippocampus (vHip). However, the impact of severe stress on vHip redox states and their functional consequences, including behavioral and electrophysiological changes related to SCZ, are not entirely understood. Study design: After exposing adolescent animals to physical stress (postnatal day, PND31-40), we explored social and cognitive behaviors (PND47-49), the basal activity of pyramidal glutamate neurons, the number of parvalbumin (PV) interneurons, and the transcriptomic signature of the vHip (PND51). We also evaluated the impact of stress on the redox system, including mitochondrial respiratory function, reactive oxygen species (ROS) production, and glutathione (GSH) levels in the vHip and serum. Study results: Adolescent-stressed animals exhibited loss of sociability, cognitive impairment, and vHip excitatory/inhibitory (E/I) imbalance. Genome-wide transcriptional profiling unveiled the impact of stress on redox system- and synaptic-related genes. Stress impacted mitochondrial respiratory function and changes in ROS levels in the vHip. GSH and glutathione disulfide (GSSG) levels were elevated in the serum of stressed animals, while GSSG was also increased in the vHip and negatively correlated with sociability. Additionally, PV interneuron deficits in the vHip caused by adolescent stress were associated with oxidative stress. Conclusions: Our results highlight the negative impact of adolescent stress on vHip redox regulation and mitochondrial function, which are partially associated with E/I imbalance and behavioral abnormalities related to SCZ.

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Q. Liu; D. Huang; L. M. Costero Valero; M. Zapater Sancho; D. Atienza Alonso 

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use of \textit{Accelerated Processing Units} (APUs), processors that incorporate both a \textit{central processing unit} (CPU) and an \textit{integrated graphics processing unit} (iGPU). However, the performance of both APU and CPU systems can be significantly hampered by address translation overhead, leading to a decline in overall performance, especially for cache-resident workloads. To address this issue, we propose the introduction of a new \textit{intermediate address space} (IAS) in both APU and CPU systems. IAS serves as a bridge between \textit{virtual address} (VA) spaces and \textit{physical address} (PA) spaces, optimizing the address translation process. In the case of APU systems, our research indicates that the iGPU suffers from significant \textit{translation look-aside buffer} (TLB) misses in certain workload situations. Using an IAS, we can divide the initial address translation into front- and back-end phases, effectively shifting the bottleneck in address translation from the cache side to the memory controller side, a technique that proves to be effective for cache-resident workloads. Our simulations demonstrate that implementing IAS in the CPU system can boost performance by up to 40\% compared to conventional CPU systems. Furthermore, we evaluate the effectiveness of APU systems, comparing the performance of IAS-based systems with traditional systems, showing up to a 185\% improvement in APU system performance with our proposed IAS implementation. Furthermore, our analysis indicates that over 90\% of TLB misses can be filtered by the cache, and employing a larger cache within the system could potentially result in even greater improvements. The proposed IAS offers a promising and practical solution to enhance the performance of both APU and CPU systems, contributing to state-of-the-art research in the field of computer architecture.

Self-catalysed frontal polymerisation enables fast and low-energy processing of fibre reinforced polymer composites

J. Staal; B. Caglar; V. Michaud 

Frontal polymerisation has the potential to bring unprecedented reductions in energy demand and process time to produce fibre reinforced polymer composites. Production of epoxy-based fibre reinforced polymer parts with high fibre volume content, commonly encountered in industry, is however hindered by the heat sink created by the fibres and the mould, overcoming the heat output of the chemical reaction, thus preventing front propagation. We propose a novel self-catalysed frontal polymerisation manufacturing method based on the integration of thin resin channels in thermal contact with the composite stack as a strategy for low-energy production of high fibre volume fraction polymer composites without the need for a continuous energy input. Frontal polymerisation inside the resin channel proceeds faster and preheats the fabric stack, thus catalysing the process. Parts with up to 60% fibre content are successfully produced independently of the sample thickness. Fillers added within the resin channels provide means to tailor the frontal polymerisation process kinetics. The parts have a significantly higher glass transition temperature than those produced in a conventional oven, and comparable mechanical properties while energy consumption is reduced by over 99.5%.

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

A. Amirshahi; J. Dan; J. A. Miranda Calero; A. Aminifar; D. Atienza Alonso 

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of electrodes that balances performance and usability constraints. The search for the optimal subset of electrodes from a larger set is a problem with combinatorial complexity. While existing research has primarily focused on search strategies that only explore limited combinations, our methodology proposes a computationally efficient way to explore all combinations. To avoid the computational burden associated with training the model for each combination, we leverage an innovative approach inspired by few-shot learning. Remarkably, this strategy covers all the wearable electrode combinations while significantly reducing training time compared to retraining the network on each possible combination. In the context of an epileptic seizure detection task, the proposed method achieves an AUC value of 0.917 with configurations using eight electrodes. This performance matches that of prior research but is achieved in significantly less time, transforming a process that would span months into a matter of hours on a single GPU device. Our work allows comprehensive exploration of electrode configurations in wearable biomedical device design, yielding insights that enhance performance and real-world feasibility.

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Y. Wu; T. Zhang; W. Ke; c. Qiu; S. Süsstrunk et al. 

In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely positioned and displaying notable inter-object correlations. This can create a tendency for neural networks to exploit these strong dependencies, bypassing the individual object patterns. To address this challenge, we introduce a novel self-supervised learning (SSL) strategy. Our approach leverages both object patterns and contextual cues to produce robust features. It begins with the formulation of an object-exchanging strategy, where pairs of objects with comparable sizes are exchanged across different scenes, effectively disentangling the strong contextual dependencies. Subsequently, we introduce a context-aware feature learning strategy, which encodes object patterns without relying on their specific context by aggregating object features across various scenes. Our extensive experiments demonstrate the superiority of our method over existing SSL techniques, further showing its better robustness to environmental changes. Moreover, we showcase the applicability of our approach by transferring pre-trained models to diverse point cloud datasets.

TTool: A Supervised Artificial Intelligence-Assisted Visual Pose Detector for Tool Heads in Augmented Reality Woodworking

A. Settimi; Chutisilp Naravich; F. Aymanns; J. Gamerro; Y. Weinand 

We present TimberTool (TTool v2.1.1), a software designed for woodworking tasks assisted by augmented reality (AR), emphasizing its essential function of the real-time localization of a tool head’s poses within camera frames. The localization process, a fundamental aspect of AR-assisted tool operations, enables informed integration with contextual tracking, facilitating the computation of meaningful feedback for guiding users during tasks on the target object. In the context of timber construction, where object pose tracking has been predominantly explored in additive processes, TTool addresses a noticeable gap by focusing on subtractive tasks with manual tools. The proposed methodology utilizes a machine learning (ML) classifier to detect tool heads, offering users the capability to input a global pose and utilizing an automatic pose refiner for final pose detection and model alignment. Notably, TTool boasts adaptability through a customizable platform tailored to specific tool sets, and its open accessibility encourages widespread utilization. To assess the effectiveness of TTool in AR-assisted woodworking, we conducted a preliminary experimental campaign using a set of tools commonly employed in timber carpentry. The findings suggest that TTool can effectively contribute to AR-assisted woodworking tasks by detecting the six-degrees-of-freedom (6DoF) pose of tool heads to a satisfactory level, with a millimetric positional error of 3.9 ± 1 mm with possible large room for improvement and 1.19 ± 0.6° for what concerns the angular accuracy.

Near-Zero Parasitic Shift Flexure Pivots Based on Coupled n-RRR Planar Parallel Mechanisms

L. B. Tissot-Daguette; F. Cosandier; E. Thalmann; S. Henein 

Flexure pivots, which are widely used for precision mechanisms, generally have the drawback of presenting parasitic shifts accompanying their rotation. The known solutions for canceling these undesirable parasitic translations usually induce a loss in radial stiffness, a reduction of the angular stroke, and nonlinear moment–angle characteristics. This article introduces a novel family of kinematic structures based on coupled n-RRR planar parallel mechanisms, which presents exact zero parasitic shifts while alleviating the drawbacks of some known pivoting structures. Based on this invention, three symmetrical architectures have been designed and implemented as flexure-based pivots. The performance of the newly introduced pivots has been compared with two known planar flexure pivots having theoretically zero parasitic shift via Finite Element models and experiments performed on plastic mockups. The results show that the newly introduced flexure pivots are an order of magnitude radially stiffer than the considered pivots from the state-of-the-art while having equivalent angular strokes. To experimentally evaluate the parasitic shift of the novel pivots, one of the architectures was manufactured in titanium alloy using wire-cut electrical discharge machining. This prototype exhibits a parasitic shift under 1.5 µm over a rotation stroke of ±15 deg, validating the near-zero parasitic shift properties of the presented designs. These advantages are key to applications such as mechanical time bases, surgical robotics, or optomechanical mechanisms.

Toward Reliable Human Pose Forecasting With Uncertainty

S. Saadatnejad; M. Mirmohammadi; M. Daghyani; P. Saremi; Y. Z. Benisi et al. 

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited uncertainty analysis have hindered progress in the field. To address this, we first develop an open-source library for human pose forecasting, including multiple models, supporting several datasets, and employing standardized evaluation metrics, with the aim of promoting research and moving toward a unified and consistent evaluation. Second, we devise two types of uncertainty in the problem to increase performance and convey better trust: 1) we propose a method for modeling aleatoric uncertainty by using uncertainty priors to inject knowledge about the pattern of uncertainty. This focuses the capacity of the model in the direction of more meaningful supervision while reducing the number of learned parameters and improving stability; 2) we introduce a novel approach for quantifying the epistemic uncertainty of any model through clustering and measuring the entropy of its assignments. Our experiments demonstrate up to 25% improvements in forecasting at short horizons, with no loss on longer horizons on Human3.6 M, AMSS, and 3DPW datasets, and better performance in uncertainty estimation. The code is available online.

Warum Unternehmen radikal umdenken müssen

S. Nick 

Greenwashing ist ein Ärgernis. Wie aber lassen sich die Prinzipien der Nachhaltigkeit in Projekten und Unternehmen wirklich umsetzen? Mit dieser Frage setzt sich EPFL-Dozent und Unternehmer Sascha Nick intensiv auseinander – bald auch an einem Workshop an der Universität Freiburg.

Anthropological Insights into the Cultural Heritage and Landscape Surrounding Beijing’s Forbidden City

F. Graezer Bideau 

On the influence of flow-front orientation on stringer stiffened composite panels in water impacts

C. Pearson; M. de Mourgues; M. Battley; V. Michaud; J. Little et al. 

Water impacts form the critical load case for high-performance carbon fibre reinforced polymer (CFRP) racing craft. Such events produce a peaked, non-uniform pressure distribution that travels along a hull panel as it is immersed. Current design standards are based on static, uniform pressure loads that do not account for the directional nature of water impacts. With recent trends towards the use of directionally stiffened hull structures in the form of stringer stiffened composite panels (SSCPs), such simplifications of the load case may no longer be valid. In this study, a marine-based SSCP was tested experimentally and numerically to investigate the effects of flow-front orientation on high-performance hull panels. Parallel and perpendicular impacts at constant velocity were carried out using the novel Servo-hydraulic Slam Testing System (SSTS) and the results were used to validate a one-way coupled computational fluid dynamics — finite element analysis (CFD-FEA) Fluent/Abaqus solution. The highest strains in the monolithic skin and stringer were observed for perpendicular impacts. A parameter sweep across a range of impact orientations between parallel and perpendicular impacts was carried out. An approximately linear relationship between flow orientation angle and key structural strains was observed, with the highest strains reported at 70–90°. Results indicate that the critical load case for SSCPs occurs at 75°orientation angles, where strains in the stringer capping are maximum.

A global framework for data-informed bridge examination

N. Bertola; P. Schiltz; E. Brühwiler 

Examining the performance of an existing bridge requires information on several aspects, such as design choices, material properties, and ongoing degradation processes. It often happens that some critical information is not available. The traditional approach in structural engineering is to take the most conservative assumption for each unknown, following new-design principles. It will often be concluded that structural safety is not ensured and that the bridge must be strengthened or replaced. This conclusion has important economic costs, impacts on users, and environmental burden associated. In this paper, a global data-informed framework is proposed to examine structural safety of existing bridges accurately. Multiple state-of-the-art methodologies are unified to provide a comprehensive framework for bridge examination. Observations, which can include visual inspection, non-destructive testing, and structural sensing, enable the development of more realistic models of structural behaviour. A case study of a reinforced-concrete bridge in Switzerland illustrates the potential of the novel framework. Although almost no information was initially available on the bridge, the monitoring results show that it can be rationally concluded that the bridge is safe. This framework supports engineers in examining existing structures when crucial information is missing based on observations and engineering judgment.

Opportunities and Challenges for Generative Adversarial Reconstruction by Distribution Matching (CryoGAN)

M. Unser; P. N. Bohra 

Development of a Flying Wing UAV and Stochastic Component Characterization of the Dahu4NAV R-IMU

E. Chelly 

Boosting Weakly Convex Ridge Regularizers with Spatial Adaptivity

S. J. Neumayer; M. Pourya; A. Goujon; M. Unser 

La realité augmenté au service de l’usinage de charpente

A. Settimi 

Presentation of the research Augmented Carpentry at the inauguration ceremony of the Forum Construction Bois France.

Performance gap in the building sector and its impact on investment decisions for heating requirements

L. C. N. Bernath 

Between the ideal and reality lies the decisive world of the performance gap. This project is conducted within the framework of a Master Thesis at the Industrial Processes and Energy Systems Engineering (IPESE) laboratory of Ecole Polytechnique F´ed´erale de Lausanne (EPFL). The objective is to evaluate the energy performance gap, with a static approach, of the building sector and understand its impact on the global energy system in the context of energy transition. The challenge lies in the conservative assumptions regarding the thermal transmission coefficients and construction details of existing buildings in modelling tools. This study is based on two detailed surveys, one on swiss architectural elements and the other on new thermal transmission coefficient ranges. A methodology is designed and integrated to the existing optimization model: Renewable Energy Hub Optimizer (REHO) for different types of buildings, each having particular features. The idea is to integrate to the REHO model a static approach by varying the thermal transmission coefficients and develop a new method concerning the link between the thermal envelope and energy reference area. In result, the impact of the thermal envelope and the form factor of buildings on space heating requirements is researched. The investment and operation uncertainties resulting from the modelling gap are assessed. Finally, the static model developed in this study is compared with a regulatory approach and real on site data from a clustered neighbourhood in Geneva. The results show an improvement of 13,4 % with a change of method.

Direct observations of X-rays produced by upward positive lightning

T. Oregel-Chaumont; A. Sunjerga; P. Hettiarachchi; V. Cooray; M. Rubinstein et al. 

X-rays have been observed in natural downward cloud-to-ground lightning for over 20 years and in rocket-triggered lightning for slightly less. In both cases, this energetic radiation has been detected during the stepped and dart leader phases of downward negative flashes. More recently, X-rays have also been reported during the dart leader phase of upward negative flashes. In this study, we present the observations of four upward positive lightning flashes from the Säntis Tower (2.5 km ASL) in Switzerland. These consist of the simultaneous records of electric current passing through the tower, and electric field strength and X-ray flux 20 m from the tower base. One of the flashes was captured by a high-speed camera operating at 24,000 frames per second, stills from which are also presented. We detected X-rays during the initial phase of upward negative leader propagation, which can be associated with the leader-stepping process from electric field and current waveforms. To the best of our knowledge, this is the first time that such measurements are reported in the literature. The obtained time-synchronised data confirm that the X-ray emissions detected are associated with the initial steps of the upward negative leader. The frequency and energy of X-ray pulses appear to decrease as functions of time, with pulses disappearing altogether within the first millisecond of the leader initiation. X-ray emission also appears to be correlated with the maximum current-derivative and the electric field change of leader steps, consistent with cold electron runaway. These observations contribute to improving our understanding of upward lightning, which is a primary source of damage to tall structures such as wind turbines and telecommunications towers, as well as aircraft during takeoff and landing.

Vibrio cholerae pathogenicity island 2 encodes two distinct types of restriction systems

G. Vizzarro; A. Lemopoulos; D. W. Adams; M. Blokesch 

In response to predation by bacteriophages and invasion by other mobile genetic elements such as plasmids, bacteria have evolved specialised defence systems that are often clustered together on genomic islands. The O1 El Tor strains of Vibrio cholerae responsible for the ongoing seventh cholera pandemic (7PET) contain a characteristic set of genomic islands involved in host colonisation and disease, many of which contain defence systems. Notably, Vibrio pathogenicity island 2 contains several characterised defence systems as well as a putative Type I restriction-modification system (T1RM), which, interestingly, is interrupted by two genes of unknown function. Here, we demonstrate that the T1RM system is active, methylates the host genomes of a representative set of 7PET strains, and identify a specific recognition sequence that targets non-methylated plasmids for restriction. We go on to show that the two genes embedded within the T1RM system encode a novel two-protein modification-dependent restriction system related to the GmrSD family of Type IV restriction enzymes. Indeed, we show that this system has potent anti-phage activity against diverse members of the Tevenvirinae, a subfamily of bacteriophages with hypermodified genomes. Taken together these results expand our understanding of how this highly conserved genomic island contributes to the defence of pandemic V. cholerae against foreign DNA.

DeepMesh: Differentiable Iso-Surface Extraction

B. Guillard; E. Remelli; A. Lukoaianov; P. Yvernay; S. Richter et al. 

Optimizing Dynamic Aperture Studies with Active Learning

D. Di Croce; M. Giovannozzi; E. Krymova; T. Pieloni; S. Redaelli et al. 

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle’s motion remains bounded over a given number of turns. Understanding the features of dynamic aperture is crucial for the design and operation of such accelerators, as it provides insights into nonlinear effects and the possibility of optimising beam lifetime. The standard approach to calculate the dynamic aperture requires numerical simulations of several initial conditions densely distributed in phase space for a sufficient number of turns to probe the time scale corresponding to machine operations. This process is very computationally intensive and practically outside the range of today’s computers. In our study, we introduced a novel method to estimate dynamic aperture rapidly and accurately by utilising a Deep Neural Network model. This model was trained with simulated tracking data from the CERN Large Hadron Collider and takes into account variations in accelerator parameters such as betatron tune, chromaticity, and the strength of the Landau octupoles. To enhance its performance, we integrate the model into an innovative Active Learning framework. This framework not only enables retraining and updating of the computed model, but also facilitates efficient data generation through smart sampling. Since chaotic motion cannot be predicted, traditional tracking simulations are incorporated into the Active Learning framework to deal with the chaotic nature of some initial conditions. The results demonstrate that the use of the Active Learning framework allows faster scanning of the configuration parameters without compromising the accuracy of the dynamic aperture estimates.

4 points sensibles/ Vier Angelpunkte

A concrete answer for circular construction: three prototypes reusing saw-cut elements

M. Bastien Masse; C. M. Küpfer; C. Fivet 

Existing concrete buildings should be retained for as long as possible to reduce the environmental burden of demolition and new construction. However, when urban pressure makes demolition unavoidable, salvaging and reusing concrete elements elsewhere in new structures, rather than reducing them to rubble, efficiently prolongs the use of existing resources at their highest structural value. Concrete reuse is not a new approach: pioneer cases have demonstrated its potential, but broader adoption has still not been seen across the wider industry. Three prototypes recently built by Ecole Polytechnique Fédérale de Lausanne researchers and students in Switzerland demonstrate the feasibility and potential of reusing elements saw-cut from cast in situ concrete structures. The prototypes deal with different scales of elements, from small blocks to large slab elements and 3D assemblies. Lifecycle assessments confirm that reusing concrete elements drastically reduces the upfront global warming potential of new construction, providing a new lower-bound benchmark for sustainable, circular construction.

Lumped Drag Model Identification and Real-Time External Force Detection for Rotary-Wing Micro Aerial Vehicles

L. C. Wälti; A. Martinoli 

This work focuses on understanding and identifying the drag forces applied to a rotary-wing Micro Aerial Vehicle (MAV). We propose a lumped drag model that concisely describes the aerodynamical forces the MAV is subject to, with a minimal set of parameters. We only rely on commonly available sensor information onboard a MAV, such as accelerometer data, pose estimate, and throttle commands, which makes our method generally applicable. The identification uses an offline gradient-based method on flight data collected over specially designed trajectories. The identified model allows us to predict the aerodynamical forces experienced by the aircraft due to its own motion in real-time and, therefore, will be useful to distinguish them from external perturbations, such as wind or physical contact with the environment. The results show that we are able to identify the drag coefficients of a rotary-wing MAV through onboard flight data and observe the close correlation between the motion of the MAV, the measured external forces, and the predicted drag forces.

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

E. Bumbacher; J. Brender; R. L. Davis 

How to measure students’ Computational Problem-Solving (CPS) competencies is an ongoing research topic. Prevalent approaches vary by measurement tools (e.g., interactive programming, multiple-choice tests, or programming-independent tests) and task types (e.g., debugging problems or Parson problems). However, few studies have examined the measurement tools of CPS competencies themselves: affordances and limitations of the measurement tools and how they compare, or whether different task types might elicit CPS competencies differently. Research needs to address these questions in order to better understand how to design robust, generalizable, and effective measurement tools for CPS competencies. This paper presents an exploratory study that contributes to this research direction. It is part of a larger international project to develop an open-access formative assessment platform for CPS, which includes a novel authoring tool for a wide range of task types for interactive block-based programming. We used the tool to create an interactive programming experience with multiple task types and gave it to more than 300 secondary school students from different countries. We also administered a validated multiple-choice measurement of Computational Thinking with block-based programs. We focused on task complexity as a characteristic of task type, using a classification scheme based on task design features. Comparing students’ performances on tasks of different complexity and using two distinct measurement tools, we found that the multiple-choice measurement only partially predicts performance in the interactive programming task. Additionally, its predictive capacity varies significantly between task types of differing complexity.

Energy-Efficient Particle Accelerators for Research

M. Seidel 

Particle accelerators are the drivers for large-scale research infrastructures for particle physics but also for many branches of condensed matter research. The types of accelerator-driven research infrastructures include particle colliders, neutron, muon or neutrino sources, synchrotron light sources and free-electron lasers, as well as medical applications. These facilities are often large and complex and have a significant carbon footprint, both in construction and operation. In all facilities grid power is converted to beam power and ultimately to the desired type of radiation for research. The energy efficiency of this conversion process can be optimized using efficient technologies, but also with optimal concepts for entire facilities.

Degrees of Separation: A Flexible Type System for Safe Concurrency

Y. Xu; A. S. Boruch-Gruszecki; M. Odersky 

Data races have long been a notorious problem in concurrent programming. They are subtle to detect, and lead to non-deterministic behaviours. There has been a lot of interest in type systems that statically guarantee data race freedom. Significant progress has been made in this area, and these type systems are increasingly usable and practical. However, their adoption in mainstream programming languages is still limited, which is largely attributed to their strict alias prevention principles that obstruct the usage of existing programming patterns. This is a deterrent to the migration of existing code bases. To tackle this problem, we propose Capture Separation Calculus (System CSC), which statically prevents data races while being compatible with established programming patterns. It follows a \emph{control-as-you-need} philosophy: by default, aliases are allowed, but they are tracked in the type system. When data races are a concern, the tracked aliases are controlled to prevent data-race-prone patterns. We study the formal properties of System CSC. Type soundness is proven via the standard progress and preservation theorems. Additionally, we formally verify the data race freedom property of System CSC by proving that the reduction of a well-typed program is confluent.

Numerical investigation of two-dimensional Mode-II delamination in composite laminates

C. Wang; A. Vassilopoulos; T. Keller 

Delamination in real composite structures, which generally tends to grow in two-dimensions, sometimes cannot be appropriately represented by the widely accepted test methods where one-dimensional (1D) beam specimens are typically employed. In order to compare and contrast the two-dimensional (2D) and 1D delamination behavior under Mode-II fracture condition, a numerical investigation was carried out in this work based on previous 2D experiments (Fig. 1) and end-loaded split (ELS) experiments. Three-dimensional finite element models (Fig. 2) were established for the simulation of the experiments, and a new cohesive zone model was developed to take into account the effects of a large-scale fracture process zone (FPZ) in the presence of resin plastic deformation, microcracking and fiber (bundle) bridging. The total strain energy release rate (SERR) for Mode-II delamination in 2D plates were found to be similar to that in 1D beams of the same bulk materials, whereas the cohesive relationship was significantly different. Membrane forces that originated in the 2D plates due to large deformation resulted in reduced mean shear tractions over the microcracking zone, which might lead to significant discrepancies in the fracture behavior compared to that in standardized beam specimens.

“But of course i’m going to look happy” or “He needed to know I was angry”? Comparing use of emotional labour in teamwork in engineering and hospitality students

R. Germanier; A. Darioly; N. Kotluk; R. Tormey 

Being able to work effectively in a team is a vital professional skill but how do students in different disciplines, engineering and hospitality, display their emotions when working together? We investigated their self-reported use of emotional labour strategies, exploring the circumstances (when) and reasons (why) for using or not using them. We also examined the limitations and effects of emotional labour on their well-being. A mixed-method approach was adopted using participants from two Swiss higher education institutions. Stage 1, a quantitative survey, determined that hospitality students used emotional dissonance strategies less than engineering students and that there was no statistically significant difference on the use of deep acting strategies between the two groups. Stage 2 involved using interpretative phenomenological analysis (IPA) on interview data from 14 students equally distributed across the institutions showing that both groups readily displayed their felt emotions in educational teamwork but used surface acting when in leadership roles, or “for the good of the team”. Undertaking surface acting was reported as more difficult when emotionally or physically drained and hospitality students were more reflective of their interactions. There is an indication that women dialled down their shown emotions in situations of sexism and not feeling respected. Deep acting strategies were dismissed by engineers but enacted by hospitality students through empathising with clients and anticipating their needs. Recommendations include teaching deep acting strategies and providing meaningful team projects enabling students, especially in engineering institutions, to learn how to interact effectively and healthily with others.

Beyond Quiescent and Active: Intermediate Microglial Transcriptomic States in a Mouse Model of Down Syndrome

A. Fernandez-Blanco; C. Sierra; C. Tejido; M. Dierssen 

Research on microglia in Down syndrome (DS) has shown that microglial activation, increased inflammatory gene expression, and oxidative stress occur at different ages in DS brains. However, most studies resulted in simplistic definitions of microglia as quiescent or active, ignoring potential intermediate states. Indeed, recent work on microglial cells in young DS brains indicated that those evolve through different intermediate activation phenotypes before reaching a fully activated state. Here we used single nucleus RNA sequencing, to examine how trisomy affects microglial states in the Ts65Dn mouse model of DS. Despite no substantial changes in the proportion of glial populations, differential expression analysis revealed cell type-specific gene expression changes, most notably in astroglia, microglia, and oligodendroglia. Focusing on microglia, we identified differential expression of genes associated with different microglial states, including disease-associated microglia (DAMs), activated response microglia (ARMs), and human Alzheimer’s disease microglia (HAMs), in trisomic microglia. Furthermore, pseudotime analysis reveals a unique reactivity profile in Ts65Dn microglia, with fewer in a homeostatic state and more in an intermediate aberrantly reactive state than in euploid microglia. This comprehensive understanding of microglial transcriptional dynamics sheds light on potential pathogenetic mechanisms but also possible avenues for therapy for neurodevelopmental disorders.

Machine Learning for Screening Small Molecules as Passivation Materials for Enhanced Perovskite Solar Cells

X. Zhang; B. Ding; Y. Wang; Y. Liu; G. Zhang et al. 

Utilization of small molecules as passivation materials for perovskite solar cells (PSCs) has gained significant attention recently, with hundreds of small molecules demonstrating passivation effects. In this study, a high-accuracy machine learning model is established to identify the dominant molecular traits influencing passivation and efficiently screen excellent passivation materials among small molecules. To address the challenge of limited available dataset, a novel evaluation method called random-extracted and recoverable cross-validation (RE-RCV) is proposed, which ensures more precise model evaluation with reduced error. Among 31 examined features, dipole moment is identified, hydrogen bond acceptor count, and HOMO-LUMO gap as significant traits affecting passivation, offering valuable guidance for the selection of passivation molecules. The predictions are experimentally validate with three representative molecules: 4-aminobenzenesulfonamide, 4-Chloro-2-hydroxy-5-sulfamoylbenzoic acid, and Phenolsulfonphthalein, which exhibit capability to increase absolute efficiency values by over 2%, with a champion efficiency of 25.41%. This highlights its potential to expedite advancements in PSCs.|A high-accuracy machine learning model is established to efficiently screen effective passivation small molecules, where random-extracted and recoverable cross-validation is introduced to enhance the model evaluation accuracy. This facilitated the identification of dominant molecular traits influencing passivation effects and the screening of excellent passivation materials. The consistency between predictions and experimental results confirmed the reliability of the machine learning model. image

Ion Adsorption Enhances Apparent Nonelectrostatic Attraction between Monomers in Polyelectrolyte Brushes

M. Li; X. Xu; S. Yasar; H-A. Klok; B. Zhuang et al. 

Polyelectrolyte brushes are responsive to salt in the environment, and this has found broad applications in antifouling, biolubrication, and drug delivery. Salt primarily influences the conformation of the polyelectrolytes through ion adsorption. While ion adsorption is typically associated with electrostatic interactions, our research reveals that in multivalent ion solutions, it also enhances nonelectrostatic interactions by bringing distant polyelectrolyte segments closer together. The finding is based on a comparative study between theoretical, simulation, and experimental data for monovalent, divalent, and trivalent cation solutions of sodium poly(styrenesulfonate) (PSS) and potassium poly(3-sulfopropyl methacrylate) (PSPMA) brushes. By incorporating an apparent Flory-Huggins parameter that is linearly dependent on the extent of ion adsorption, we developed a theoretical model for polyelectrolyte brushes that predicts brush heights in good agreement with experimental and simulation data. This work provides three major contributions to our understanding of polyelectrolyte brushes. (a) The theoretical framework reveals that while electrostatic interactions primarily drive the contraction of short-chain brushes (approximately 50 monomers), nonelectrostatic interactions arising from ion adsorption induce the collapse of long-chain brushes (approximately 500 monomers) in multivalent ion solutions. (b) Traditional scaling theory is applied only to long polymer chains in monovalent cation systems. Our modified framework broadens the scope to include both short and long chains in both monovalent and multivalent systems, while most of the traditional scaling theory can only be applied to long-chain systems. (c) We provided a comprehensive quantitative examination of the inter- and intrachain cross-links.

Structural Basis of Ligand Selectivity by a Bacterial Adhesin Lectin Involved in Multispecies Biofilm Formation

S. Guo; T. D. R. Vance; H. Zahiri; R. Eves; C. A. Stevens et al. 

Carbohydrate recognition by lectins governs critical host-microbe interactions. MpPA14 (Marinomonas primoryensis PA14 domain) lectin is a domain of a 1.5-MDa adhesin responsible for a symbiotic bacterium-diatom interaction in Antarctica. Here, we show that MpPA14 binds various monosaccharides, with L-fucose and N-acetylglucosamine being the strongest ligands (dissociation constant [K-d],similar to 150 mu M). High-resolution structures of MpPA14 with 15 different sugars bound elucidated the molecular basis for the lectin’s apparent binding promiscuity but underlying selectivity. MpPA14 mediates strong Ca2+-dependent interactions with the 3,4-diols of L-fucopyranose and glucopyranoses, and it binds other sugars via their specific minor isomers. Thus, MpPA14 only binds polysaccharides like branched glucans and fucoidans with these free end groups. Consistent with our findings, adhesion of MpPA14 to diatom cells was selectively blocked by L-fucose, but not by N-acetyl galactosamine. The MpPA14 lectin homolog present in a Vibrio cholerae adhesin was produced and was shown to have the same sugar binding preferences as MpPA14. The pathogen’s lectin was unable to effectively bind the diatom in the presence of fucose, thus demonstrating the antiadhesion strategy of blocking infection via ligand-based antagonists.|IMPORTANCE Bacterial adhesins are key virulence factors that are essential for the pathogen-host interaction and biofilm formation that cause most infections. Many of the adhesin-driven cell-cell interactions are mediated by lectins. Our study reveals for the first time the molecular basis underlying the binding selectivity of a common bacterial adhesin lectin from the marine bacterium Marinomonas primoryensis, homologs of which are found in both environmental and pathogenic species. The lectinligand interactions illustrated at the atomic level guided the identification of a ligand that serves as an inhibitor to block bacterium-host adhesion. With conventional bactericidal antibiotics losing their potency due to resistance, our work gives critical insight into an antiadhesion strategy to treat bacterial infections.

Harboring CAR-T cells using an injectable scaffold to treat solid tumors

L. Tang 

Dopant-Free Pyrene-Based Hole Transporting Material Enables Efficient and Stable Perovskite Solar Cells

X. Zhang; X. Liu; F. F. Tirani; B. Ding; J. Chen et al. 

Dopant-free hole transporting materials (HTMs) is significant to the stability of perovskite solar cells (PSCs). Here, we developed a novel star-shape arylamine HTM, termed Py-DB, with a pyrene core and carbon-carbon double bonds as the bridge units. Compared to the reference HTM (termed Py-C), the extension of the planar conjugation backbone endows Py-DB with typical intermolecular pi-pi stacking interactions and excellent solubility, resulting in improved hole mobility and film morphology. In addition, the lower HOMO energy level of the Py-DB HTM provides efficient hole extraction with reduced energy loss at the perovskite/HTM interface. Consequently, an impressive power conversion efficiency (PCE) of 24.33 % was achieved for dopant-free Py-DB-based PSCs, which is the highest PCE for dopant-free small molecular HTMs in n-i-p configured PSCs. The dopant-free Py-DB-based device also exhibits improved long-term stability, retaining over 90 % of its initial efficiency after 1000 h exposure to 25 % humidity at 60 degrees C. These findings provide valuable insights and approaches for the further development of dopant-free HTMs for efficient and reliable PSCs.|Py-DB with an extended conjugated structure is an effective dopant-free HTM when applied in n-i-p-type PSCs, affording an efficiency of 24.33 %, the highest PCE for a dopant-free small-molecule HTM. image

A critical perspective for emerging ultra-thin solar cells with ultra-high power-per-weight outputs

A. Panagiotopoulos; T. Maksudov; G. Kakavelakis; G. Perrakis; E. A. Alharbi et al. 

Ultrathin, solution-processed emerging solar cells with high power-per-weight (PPW) outputs demonstrate unique potential for applications where low weight, high power output, and flexibility are indispensable. The following perspective explores the literature of emerging PVs and highlights the maximum reported PPW values of perovskite solar cells (PSCs) 29.4 W/g, organic solar cells (OSCs) 32.07 W/g, and quantum dot solar cells 15.02 W/g, respectively. The record PPW values of OSCs and PSCs are approximately one order of magnitude higher compared to their inorganic ultrathin solar cells counterparts (approximately 3.2 W/g for CIGS and a-Si). This consists emerging PVs, very attractive for a variety of applications where the PPW is the key parameter. In particular, both OSCs and PSCs can be implemented in different scenarios of applications (indoor and biocompatible applications for OSCs and outdoor and high-energy radiation conversion conditions for the PSCs) due to their unique optoelectronic and physiochemical properties. Finally, our theoretical optical and electrical simulation and optimization study for the most promising and well-suited PV technologies showed an impressive maximum realistic theoretical PPW limit of 74.3 and 93.7 W/g for PSCs and OSCs, respectively. Our finding in the theoretical section shows that the experimental results achieved in the literature of PSCs and OSCs toward high PPW outputs is not quite close to the theoretical maximum (35% and 40% of the theoretical maximum for OSCs and PSCs, respectively), and thus, more work needs to be done to further increase the experimental PPWoutput of these promising PV technologies.

High-Work-Function 2D Perovskites as Passivation Agents in Perovskite Solar Cells

E. Shirzadi; F. Ansari; H. Jinno; S. Tian; O. Ouellette et al. 

Various approaches have been employed to passivate the defects in perovskite films used in perovskite solar cells (PSCs). However, the passivation mechanism is often unclear at a molecular level, and the reason for enhanced PSC performance often remains elusive. Here, we explore the impact of passivation with high-work-function two-dimensional (2D) perovskites in promoting the efficiency of PSCs. We realized that 4-halophenylethylammonium lead iodide possesses a high work function, causing band bending at the perovskite surface, thus suppressing charge carrier recombination at the perovskite/hole transporting material (HTM) interface by forming a barricade for electrons to recombine at the trap states. Utilizing this strategy leads to a similar to 100 mV improvement in voltage and a similar to 2.5% increase in power conversion efficiency (PCE).

Direct measurement of key exciton properties: Energy, dynamics, and spatial distribution of the wave function

S. Dong; M. Puppin; T. Pincelli; S. Beaulieu; D. Christiansen et al. 

Excitons, Coulomb-bound electron-hole pairs, are the fundamental excitations governing the optoelectronic properties of semiconductors. Although optical signatures of excitons have been studied extensively, experimental access to the excitonic wave function itself has been elusive. Using multidimensional photoemission spectroscopy, we present a momentum-, energy-, and time-resolved perspective on excitons in the layered semiconductor WSe2. By tuning the excitation wavelength, we determine the energy-momentum signature of bright exciton formation and its difference from conventional single-particle excited states. The multidimensional data allow to retrieve fundamental exciton properties like the binding energy and the exciton-lattice coupling and to reconstruct the real-space excitonic distribution function via Fourier transform. All quantities are in excellent agreement with microscopic calculations. Our approach provides a full characterization of the exciton properties and is applicable to bright and dark excitons in semiconducting materials, heterostructures, and devices.|Key points:|center dot The full life cycle of excitons is recorded with time- and angle-resolved photoemission spectroscopy.|center dot The real-space distribution of the excitonic wave function is visualized.|center dot Direct measurement of the exciton-phonon interaction.

Drosophila SPG12 ortholog, reticulon-like 1, governs presynaptic ER organization and Ca2+ dynamics

J. Jose Perez-Moreno; R. C. Smith; M. K. Oliva; F. Gallo; S. Ojha et al. 

Neuronal endoplasmic reticulum (ER) appears continuous throughout the cell. Its shape and continuity are influenced by ER-shaping proteins, mutations in which can cause distal axon degeneration in Hereditary Spastic Paraplegia (HSP). We therefore asked how loss of Rtnl1, a Drosophila ortholog of the human HSP gene RTN2 (SPG12), which encodes an ER-shaping protein, affects ER organization and the function of presynaptic terminals. Loss of Rtnl1 depleted ER membrane markers at Drosophila presynaptic motor terminals and appeared to deplete narrow tubular ER while leaving cisternae largely unaffected, thus suggesting little change in resting Ca2+ storage capacity. Nevertheless, these changes were accompanied by major reductions in activity-evoked Ca2+ fluxes in the cytosol, ER lumen, and mitochondria, as well as reduced evoked and spontaneous neurotransmission. We found that reduced STIM-mediated ER-plasma membrane contacts underlie presynaptic Ca2+ defects in Rtnl1 mutants. Our results show the importance of ER architecture in presynaptic physiology and function, which are therefore potential factors in the pathology of HSP.

Cellular nanomotion as a new signature of life

R. G. Willaert; S. Kasas 

Minkowski Distance Based Pilot Protection for Tie Lines Between Offshore Wind Farms and MMC

Z. Yang; R. Zhu; W. Liao 

Offshore wind farms (OWFs) with modular multilevel converter high-voltage dc (MMC-HVdc) have become an important form of renewable energy utilization. However, if a fault occurs at the tie line between the MMC and the OWF, the fault steady-state current at the fault point will be equal to zero when the negative-sequence current is suppressed, so traditional differential protection may fail to operate. To cope with this issue, this article proposes a new pilot protection method based on Minkowski distance. For internal faults, OWF and MMC will have different transient currents, so the Minkowski distance will be much higher than 0, but it will be equal to 0 for external faults and normal operation since the fault currents on both sides are the opposite. Therefore, the internal fault can be detected reliably. The proposed method does not depend on the power frequency phasor extraction, so it is not affected by the frequency offset in the transient process. In addition, this method operates quickly and has a strong ability to withstand fault resistance and environmental noise. Moreover, since there is always a transient process when a fault occurs, the proposed method applies to different fault ride-through strategies. PSCAD simulation and real-time digital simulator experiments show that the proposed method is suitable for different fault locations and types.

Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high-spatial resolution

J. Rue-Queralt; H. Fluhr; S. Tourbier; Y. Aleman-Gomez; D. Pascucci et al. 

Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual-evoked potentials, we provide evidence supporting that (i) CSET captures realistic neurophysiological patterns with better accuracy than state-of-the-art methods, (ii) CSET can reconstruct brain responses more accurately and with more robustness to intrinsic noise in the EEG signal. These results demonstrate that CSET offers high spatio-temporal accuracy, enabling neuroscientists to extend their research beyond the current limitations of low sampling frequency in functional MRI and the poor spatial resolution of M/EEG.|Connectome spectrum electromagnetic tomography (CSET) presents a method to reconstruct high-spatial resolution brain source-networks, leveraging diffusion MRI and graph signal processing tools. This study evidences CSET’s superior accuracy and robustness against intrinsic EEG noise, promising a revolution in neuroscience research by overcoming the limitations of current functional MRI and M/EEG technologies. image

White adipose tissue distribution and amount are associated with increased white matter connectivity

L. Okudzhava; S. Schulz; E. Fischi-Gomez; G. Girard; J. Machann et al. 

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a deeper characterization of body composition is required, especially considering the links between abdominal obesity and metabolic dysfunction. This study aims to enhance our understanding of the relationship between obesity and WM connectivity by directly assessing the amount and distribution of fat tissue. Whole-body magnetic resonance imaging (MRI) was employed to evaluate total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), while MR liver spectroscopy measured liver fat content in 63 normal-weight, overweight, and obese males. WM connectivity was quantified using microstructure-informed tractography. Connectome-based predictive modeling was used to predict body composition metrics based on WM connectomes. Our analysis revealed a positive dependency between BMI, TAT, SAT, and WM connectivity in brain regions involved in reward processing and appetite regulation, such as the insula, nucleus accumbens, and orbitofrontal cortex. Increased connectivity was also observed in cognitive control and inhibition networks, including the middle frontal gyrus and anterior cingulate cortex. No significant associations were found between WM connectivity and VAT or liver fat. Our findings suggest that altered neural communication between these brain regions may affect cognitive processes, emotional regulation, and reward perception in individuals with obesity, potentially contributing to weight gain. While our study did not identify a link between WM connectivity and VAT or liver fat, further investigation of the role of various fat depots and metabolic factors in brain networks is required to advance obesity prevention and treatment approaches.|Obesity and brain connectivity: Our study reveals increased connectivity in key brain regions involved in appetite, reward, and cognitive control, providing insights into mechanisms driving overeating and weight gain. image

Twenty years of irrigation acclimation is driven by denser canopies and not by plasticity in twig- and needle-level hydraulics in a Pinus sylvestris forest

A. Gauthey; C. Bachofen; A. Chin; H. Cochard; J. Gisler et al. 

Climate change is predicted to increase atmospheric vapor pressure deficit, exacerbating soil drought, and thus enhancing tree evaporative demand and mortality. Yet, few studies have addressed the longer-term drought acclimation strategy of trees, particularly the importance of morphological versus hydraulic plasticity. Using a long-term (20 years) irrigation experiment in a natural forest, we investigated the acclimation of Scots pine (Pinus sylvestris) morpho-anatomical traits (stomatal anatomy and crown density) and hydraulic traits (leaf water potential, vulnerability to cavitation (Psi(50)), specific hydraulic conductivity (K-s), and tree water deficit) to prolonged changes in soil moisture. We found that low water availability reduced twig water potential and increased tree water deficit during the growing season. Still, the trees showed limited adjustments in most branch-level hydraulic traits (Psi(50) and K-s) and needle anatomy. In contrast, trees acclimated to prolonged irrigation by increasing their crown density and hence the canopy water demand. This study demonstrates that despite substantial canopy adjustments, P. sylvestris may be vulnerable to extreme droughts because of limited adjustment potential in its hydraulic system. While sparser canopies reduce water demand, such shifts take decades to occur under chronic water deficits and might not mitigate short-term extreme drought events.

Toward Metantennas: Metamaterial-Based Antennas for Wireless Communications

Z. N. Chen; X. Qing; Y. Su; R. Xu 

Antennas have historically been the most common electromagnetic (EM) technology for wireless communication systems. Antenna as hardware is entirely dependent on the EM properties of the materials used, mostly related to the permittivity and permeability. In addition to natural materials, such as good conductors and low-loss dielectrics, metamaterials (MTMs) have been proposed as artificial structures engineered for unique EM properties that are not found in nature. MTMs have enabled new methods of controlling EM fields and wave propagation, resulting in the rapid development of innovative antennas based on MTMs, otherwise known as metantennas. Metantennas have been mostly developed to address critical challenges by increasing antenna gain and bandwidth while decreasing antenna volume and profile. This article presents three common metantenna designs that demonstrate how the metantenna technology addresses the most critical challenges in antenna design, that is, achieving a wide bandwidth and a high gain, as well as a miniaturized size. These designs include a low-profile wideband metantenna for 5G NR small cells using anisotropic high-permittivity MTM; a wideband antipodal antenna loaded with zero-index MTM for gain enhancement; and compact multiple-beam Luneburg lens antennas using transformation optics methods and MTM implementation. The designs demonstrate the advantages of metantennas over traditional antennas for the fifth and sixth generation communications as well as satellite communications.

Modified capillary number to standardize droplet generation in suction-driven microfluidics

J. Panwar; R. Roy 

In droplet microfluidic devices with suction-based flow control, the microchannel geometry and suction pressure at the outlet govern the dynamic properties of the two phases that influence the droplet generation. Therefore, it is critical to understand the role of geometry along with suction pressure in the dynamics of droplet generation to develop a predictive model. We conducted a comprehensive characterization of droplet generation in a flow focusing device with varying control parameters. We used these results to formulate a scaling argument and propose a governing parameter, called as modified capillary number (CaL), that combines normalized droplet volume with geometrical parameters (length of dispersed and continuous phase channels) and flow parameters (interfacial tension, phase viscosity and velocity) in a power law relationship. CaL effectively captures the transition from squeezing to dripping regimes of droplet generation, providing essential insights into the design requirements for suction-driven droplet generation. These findings are key to standardize microfluidic flow-focusing devices that can achieve the desired droplet generation behavior with optimal pressure consumption.

The AGORA High-resolution Galaxy Simulations Comparison Project. V. Satellite Galaxy Populations in a Cosmological Zoom-in Simulation of a Milky Way-Mass Halo

M. Jung; S. Roca-Fabrega; J-h. Kim; A. Genina; L. Hausammann et al. 

We analyze and compare the satellite halo populations at z similar to 2 in the high-resolution cosmological zoom-in simulations of a 1012 M circle dot target halo (z = 0 mass) carried out on eight widely used astrophysical simulation codes (Art-I, Enzo, Ramses, Changa, Gadget-3, Gear, Arepo-t, and Gizmo) for the AGORA High-resolution Galaxy Simulations Comparison Project. We use slightly different redshift epochs near z = 2 for each code (hereafter “z similar to 2”) at which the eight simulations are in the same stage in the target halo’s merger history. After identifying the matched pairs of halos between the CosmoRun simulations and the DMO simulations, we discover that each CosmoRun halo tends to be less massive than its DMO counterpart. When we consider only the halos containing stellar particles at z similar to 2, the number of satellite galaxies is significantly fewer than that of dark matter halos in all participating AGORA simulations and is comparable to the number of present-day satellites near the Milky Way or M31. The so-called “missing satellite problem” is fully resolved across all participating codes simply by implementing the common baryonic physics adopted in AGORA and the stellar feedback prescription commonly used in each code, with sufficient numerical resolution (less than or similar to 100 proper pc at z = 2). We also compare other properties such as the stellar mass-halo mass relation and the mass-metallicity relation. Our work highlights the value of comparison studies such as AGORA, where outstanding problems in galaxy formation theory are studied simultaneously on multiple numerical platforms.

A benchmark dataset for machine learning in ecotoxicology

C. Schuer; L. Gasser; F. Perez-Cruz; K. Schirmer; M. Baity-Jesi 

The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, which we consider a barrier of entry for this kind of research. Additionally, model performances can only be compared across studies when the same dataset, cleaning, and splittings were used. Therefore, we provide ADORE, an extensive and well-described dataset on acute aquatic toxicity in three relevant taxonomic groups (fish, crustaceans, and algae). The core dataset describes ecotoxicological experiments and is expanded with phylogenetic and species-specific data on the species as well as chemical properties and molecular representations. Apart from challenging other researchers to try and achieve the best model performances across the whole dataset, we propose specific relevant challenges on subsets of the data and include datasets and splittings corresponding to each of these challenge as well as in-depth characterization and discussion of train-test splitting approaches.

A comprehensive mathematical model for cardiac perfusion

A. Zingaro; C. Vergara; L. Dede; F. Regazzoni; A. Quarteroni 

The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, valve modeling, and a multicompartment Darcy model of perfusion. We consider a fully coupled electromechanical model of the left heart that provides input for a fully coupled Navier-Stokes-Darcy model for myocardial perfusion. The fluid dynamics problem is modeled in a left heart geometry that includes large epicardial coronaries, while the multicompartment Darcy model is set in a biventricular myocardium. Using a realistic and detailed cardiac geometry, our simulations demonstrate the biophysical fidelity of our model in describing cardiac perfusion. Specifically, we successfully validate the model reliability by comparing in-silico coronary flow rates and average myocardial blood flow with clinically established values ranges reported in relevant literature. Additionally, we investigate the impact of a regurgitant aortic valve on myocardial perfusion, and our results indicate a reduction in myocardial perfusion due to blood flow taken away by the left ventricle during diastole. To the best of our knowledge, our work represents the first instance where electromechanics, hemodynamics, and perfusion are integrated into a single computational framework.

A simplified version of rapid susceptibility testing of bacteria and yeasts using optical nanomotion detection

M. I. Villalba; V. Gligorovski; S. J. Rahi; R. G. Willaert; S. Kasas 

We present a novel optical nanomotion-based rapid antibiotic and antifungal susceptibility test. The technique consisted of studying the effects of antibiotics or antifungals on the nanometric scale displacements of bacteria or yeasts to assess their sensitivity or resistance to drugs. The technique relies on a traditional optical microscope, a video camera, and custom-made image analysis software. It provides reliable results in a time frame of 2-4 h and can be applied to motile, non-motile, fast, and slowly growing microorganisms. Due to its extreme simplicity and low cost, the technique can be easily implemented in laboratories and medical centers in developing countries.

Slowing gait during turning: how volition of modifying walking speed affects the gait pattern in healthy adults

J. Madrid; L. Benning; M. Selig; B. Ulrich; B. M. Jolles et al. 

Background Turning during walking and volitionally modulating walking speed introduces complexity to gait and has been minimally explored.Research question How do the spatiotemporal parameters vary between young adults walking at a normal speed and a slower speed while making 90 degrees, 180 degrees, and 360 degrees turns?Methods In a laboratory setting, the spatiotemporal parameters of 10 young adults were documented as they made turns at 90 degrees, 180 degrees, and 360 degrees. A generalized linear model was utilized to determine the effect of both walking speed and turning amplitude.Results Young adults volitionally reducing their walking speed while turning at different turning amplitudes significantly decreased their cadence and spatial parameters while increasing their temporal parameters. In conditions of slower movement, the variability of certain spatial parameters decreased, while the variability of some temporal parameters increased.Significance This research broadens the understanding of turning biomechanics in relation to volitionally reducing walking speed. Cadence might be a pace gait constant synchronizing the rhythmic integration of several inputs to coordinate an ordered gait pattern output. Volition might up-regulate or down-regulate this pace gait constant (i.e., cadence) which creates the feeling of modulating walking speed.

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems

I. Biazzo 

Autoregressive Neural Networks (ARNNs) have shown exceptional results in generation tasks across image, language, and scientific domains. Despite their success, ARNN architectures often operate as black boxes without a clear connection to underlying physics or statistical models. This research derives an exact mapping of the Boltzmann distribution of binary pairwise interacting systems in autoregressive form. The parameters of the ARNN are directly related to the Hamiltonian’s couplings and external fields, and commonly used structures like residual connections and recurrent architecture emerge from the derivation. This explicit formulation leverages statistical physics techniques to derive ARNNs for specific systems. Using the Curie-Weiss and Sherrington-Kirkpatrick models as examples, the proposed architectures show superior performance in replicating the associated Boltzmann distributions compared to commonly used designs. The findings foster a deeper connection between physical systems and neural network design, paving the way for tailored architectures and providing a physical lens to interpret existing ones.

Bright and dark Talbot pulse trains on a chip

J. Wu; M. Clementi; E. Nitiss; J. Hu; C. Lafforgue et al. 

Temporal Talbot effect, the intriguing phenomenon of the self-imaging of optical pulse trains, is extensively investigated using macroscopic components. However, the ability to manipulate pulse trains, either bright or dark, through the Talbot effect on integrated photonic chips to replace bulky instruments has rarely been reported. Here, we design and experimentally demonstrate a proof-of-principle integrated silicon nitride device capable of imprinting the Talbot phase relation onto in-phase optical combs and generating the two-fold self-images at the output. We show that the GHz-repetition-rate bright and dark pulse trains can be doubled without affecting their spectra as a key feature of the temporal Talbot effect. The designed chip can be electrically tuned to switch between pass-through and repetition-rate-multiplication outputs and is compatible with other related frequencies. The results of this work lay the foundations for the large-scale system-on-chip photonic integration of Talbot-based pulse multipliers, enabling the on-chip flexible up-scaling of pulse trains’ repetition rate without altering their amplitude spectra.

Technology challenges and integration of the plasma position reflectometer in RFX-mod2

G. De Masi; R. Cavazzana; F. Ruffini; G. Marchiori; M. Moresco et al. 

The integration of the new plasma position reflectometer in the RFX-mod2 experiment (the upgraded version of the previous RFX-mod that operated until 2015) is presented in this contribution. Particular attention has been devoted to the high field side subsystem where an antenna pair will be installed in the inner midplane. Waveguides, insulated through the application of a ZrO painting, will be routed in between the vacuum vessel and the conductive shell to a vertical port. The severe constraints in terms of physical space available guided the antennas design: a hoghorn antenna model was first numerically modeled and, due to the complex geometry, produced through metal additive manufacturing; then, a post -production surface treatment allowed achieving a surface with characteristic roughness and conductivity comparable to traditional manufactured antennas. Different bench tests are presented to assess the system performance.

Mott physics in the multiflavored age

F. Mila 

The multiflavor Mott insulators, whose local Hilbert space consists of multiple degrees of freedom, occur widely in both quantum materials and ultracold atom systems. This Comment recommends the review article by Chen and Wu that is, to the author’s knowledge, the first one to deal with all aspects and physical realizations of the multiflavor Mott insulators.

Fluid-structure interactions of bristled wings: the trade-off between weight and drag

Y. L. Lin; M. Pezzulla; P. M. Reis 

The smallest flying insects often have bristled wings resembling feathers or combs. We combined experiments and three-dimensional numerical simulations to investigate the trade-off between wing weight and drag generation. In experiments of bristled strips, a reduced physical model of the bristled wing, we found that the elasto-viscous number indicates when reconfiguration occurs in the bristles. Analysis of existing biological data suggested that bristled wings of miniature insects lie below the reconfiguration threshold, thus avoiding drag reduction. Numerical simulations of bristled strips showed that there exist optimal numbers of bristles that maximize the weighted drag when the additional volume due to the bristles is taken into account. We found a scaling relationship between the rescaled optimal numbers and the dimensionless bristle length. This result agrees qualitatively with and provides an upper bound for the bristled wing morphological data analysed in this study.

Nanofluidic logic with mechano-ionic memristive switches

T. Emmerich; Y. Teng; N. Ronceray; E. Lopriore; R. Chiesa et al. 

Neuromorphic systems are typically based on nanoscale electronic devices, but nature relies on ions for energy-efficient information processing. Nanofluidic memristive devices could thus potentially be used to construct electrolytic computers that mimic the brain down to its basic principles of operation. Here we report a nanofluidic device that is designed for circuit-scale in-memory processing. The device, which is fabricated using a scalable process, combines single-digit nanometric confinement and large entrance asymmetry and operates on the second timescale with a conductance ratio in the range of 9 to 60. In operando optical microscopy shows that the memory capabilities are due to the reversible formation of liquid blisters that modulate the conductance of the device. We use these mechano-ionic memristive switches to assemble logic circuits composed of two interactive devices and an ohmic resistor.

Thermal transport of glasses via machine learning driven simulations

P. Pegolo; F. Grasselli 

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the chemical and morphological complexity of glasses calls for atomistic simulations where the interatomic potentials are able to capture the variety of local environments, composition, and (dis)order that typically characterize glassy phases. Machine-learning potentials (MLPs) are emerging as a valid alternative to computationally expensive ab initio simulations, inevitably run on very small samples which cannot account for disorder at different scales, as well as to empirical force fields, fast but often reliable only in a narrow portion of the thermodynamic and composition phase diagrams. In this article, we make the point on the use of MLPs to compute the thermal conductivity of glasses, through a review of recent theoretical and computational tools and a series of numerical applications on vitreous silica and vitreous silicon, both pure and intercalated with lithium.

Synergistic Redox Modulation for High-Performance Nickel Oxide-Based Inverted Perovskite Solar Modules

Y. Liu; B. Ding; G. Zhang; X. Ma; Y. Wang et al. 

Nickel oxide (NiOx)-based inverted perovskite solar cells stand as promising candidates for advancing perovskite photovoltaics towards commercialization, leveraging their remarkable stability, scalability, and cost-effectiveness. However, the interfacial redox reaction between high-valence Ni4+ and perovskite, alongside the facile conversion of iodide in perovskite into I2, significantly deteriorates the performance and reproducibility of NiOx-based perovskite photovoltaics. Here, potassium borohydride (KBH4) is introduced as a dual-action reductant, which effectively avoids the Ni4+/perovskite interface reaction and mitigates the iodide-to-I2 oxidation within perovskite film. This synergistic redox modulation significantly suppresses nonradiative recombination and increases the carrier lifetime. As a result, an impressive power conversion efficiency of 24.17% for NiOx-based perovskite solar cells is achieved, and a record efficiency of 20.2% for NiOx-based perovskite solar modules fabricated under ambient conditions. Notably, when evaluated using the ISOS-L-2 standard protocol, the module retains 94% of its initial efficiency after 2000 h of continuous illumination under maximum power point at 65 degrees C in ambient air.|The dual-action reductant KBH4 is employed to suppress the harmful reaction between NiOx and perovskite while simultaneously avoiding iodide oxidation in perovskite. High-quality perovskite film with low-defect density on NiOx@KBH4 is achieved during the deposition in ambient conditions. This significantly improves the power conversion efficiency and stability of perovskite solar modules. image

Optical Monitoring of Water Side Permeation in Thin Film Encapsulation

K. Wu; M. Mariello; Y. Leterrier; S. P. Lacour 

The stability of long-term microfabricated implants is hindered by the presence of multiple water diffusion paths within artificially patterned thin-film encapsulations. Side permeation, defined as infiltration of molecules through the lateral surface of the thin structure, becomes increasingly critical with the trend of developing high-density and miniaturized neural electrodes. However, current permeability measurement methods do not account for side permeation accurately nor quantitatively. Here, a novel optical, magnesium (Mg)-based method is proposed to quantify the side water transmission rate (SWTR) through thin film encapsulation and validate the approach using micrometric polyimide (PI) and polyimide-silicon carbide (PI-SiC) multilayers. Through computed digital grayscale images collected with corroding Mg film microcells coated with the thin encapsulation, side and surface WTRs are quantified. A 4.5-fold ratio between side and surface permeation is observed, highlighting the crucial role of the PI-PI interface in lateral diffusion. Universal guidelines for the design of flexible, hermetic neural interfaces are proposed. Increasing encapsulation’s width (interelectrode spacing), creating stronger interfacial interactions, and integrating high-barrier interlayers such as SiC significantly enhance the lateral hermeticity.|This study introduces a magnesium-based optical technique to quantify water permeation in thin film encapsulation, which becomes crucial as devices miniaturize. It highlights that design rules, robust interfacial interactions, and the use of high-barrier materials like silicon carbide significantly enhance the encapsulation’s barrier effectiveness. This offers a novel approach to improving the durability of thin film coatings. image

Energy-dependent periodicities of LS I+61°303 in the GeV band

M. Chernyakova; D. Malyshev; A. Neronov; D. Savchenko 

LS I +61 degrees 303 is a rare representative of the gamma-ray binaries with a compact object known to be a pulsar. We report on the periodicity and spectral analysis of this source performed with more than 14 yr of Fermi/LAT data. The periodicity of LS I +61 degrees 303 is strongly energy dependent. Two periods P-1 = 26.932 +/- 0.004(stat) +/- 0.008(syst) and P-2 = 26.485 +/- 0.004(stat) +/- 0.007(syst) are detected only at E > 1 GeV and at E < 0.3 GeV correspondingly. Within 1 sigma (stat + syst) the periods are consistent with orbital (P-2) and beat orbital/superorbital (P-1) periods. We present the orbital light curves of the system in several energy bands and the results of the spectral analysis. We discuss the possible origin of the change in the variability pattern between 0.1 and 1 GeV energy.

Cosmological constraints with the linear point from the BOSS survey

M. He; C. Zhao; H. Shan 

The Linear Point (LP), defined as the mid-point between the baryon acoustic oscillation (BAO) peak and the associated left dip of the two-point correlation function (2PCF), xi(s), is proposed as a new standard ruler which is insensitive to non-linear effects. In this paper, we use a Bayesian sampler to measure the LP and estimate the corresponding statistical uncertainty, and then perform cosmological parameter constraints with LP measurements. Using the Patchy mock catalogues, we find that the measured LPs are consistent with theoretical predictions at 0.6 per cent level. We find constraints with mid-points identified from the rescaled 2PCF (s(2)xi) more robust than those from the traditional LP based on., as the BAO peak is not always prominent when scanning the cosmological parameter space, with the cost of 2-4 per cent increase of statistical uncertainty. This problem can also be solved by an additional data set that provides strong parameter constraints. Measuring LP from the reconstructed data slightly increases the systematic error but significantly reduces the statistical error, resulting in more accurate measurements. The 1 sconfidence interval of distance scale constraints from LP measurements are 20-30 per cent larger than those of the corresponding BAO measurements. For the reconstructed Sloan Digital Sky Survey Data Release 12 data, the constraints on H-0 and Omega(m) in a flat-Lambda cold dark matter framework with the LP are generally consistent with those from BAO. When combined with Planck cosmic microwave background data, we obtain H-0 = 68.02(-0.37)(+0.36) km s(-1) Mpc(-1) and Omega(m) = 0.3055(+-0.0048)(-0.0049) with the LP.

Vapor compression and energy dissipation in a collapsing laser-induced bubble

D. B. Preso; D. Fuster; A. B. Sieber; D. Obreschkow; M. FARHAT 

The composition of the gaseous phase of cavitation bubbles and its role on the collapse remains to date poorly understood. In this work, experiments of single cavitation bubbles in aqueous ammonia serve as a novel approach to investigate the effect of the vapor contained in a bubble on its collapse. We find that the higher vapor pressure of more concentrated aqueous ammonia acts as a resistance to the collapse, reducing the total energy dissipation. In line with visual observation, acoustic measurements, and luminescence recordings, it is also observed that higher vapor pressures contribute to a more spherical collapse, likely hindering the growth of interface instabilities by decreasing the collapse velocities and accelerations. Remarkably, we evidence a strong difference between the effective damping and the energy of the shock emission, suggesting that the latter is not the dominant dissipation mechanism at collapse as predicted from classical correction models accounting for slightly compressible liquids. Furthermore, our results suggest that the vapor inside collapsing bubbles gets compressed, consistently with previous studies performed in the context of single bubble sonoluminescence, addressing the question about the ability of vapors to readily condense during a bubble collapse in similar regimes. These findings provide insight into the identification of the influence of the bubble content and the energy exchanges of the bubble with its surrounding media, eventually paving the way to a more efficient use of cavitation in engineering and biomedical applications.

Frequent asymmetric migrations suppress natural selection in spatially structured populations

A. Abbara; A-F. Bitbol 

Natural microbial populations often have complex spatial structures. This can impact their evolution, in particular the ability of mutants to take over. While mutant fixation probabilities are known to be unaffected by sufficiently symmetric structures, evolutionary graph theory has shown that some graphs can amplify or suppress natural selection, in a way that depends on microscopic update rules. We propose a model of spatially structured populations on graphs directly inspired by batch culture experiments, alternating within-deme growth on nodes and migration-dilution steps, and yielding successive bottlenecks. This setting bridges models from evolutionary graph theory with Wright-Fisher models. Using a branching process approach, we show that spatial structure with frequent migrations can only yield suppression of natural selection. More precisely, in this regime, circulation graphs, where the total incoming migration flow equals the total outgoing one in each deme, do not impact fixation probability, while all other graphs strictly suppress selection. Suppression becomes stronger as the asymmetry between incoming and outgoing migrations grows. Amplification of natural selection can nevertheless exist in a restricted regime of rare migrations and very small fitness advantages, where we recover the predictions of evolutionary graph theory for the star graph.

Disorder and Halide Distributions in Cesium Lead Halide Nanocrystals as Seen by Colloidal 133Cs Nuclear Magnetic Resonance Spectroscopy

M. Aebli; C. J. Kaul; N. Yazdani; F. Krieg; C. Bernasconi et al. 

Colloidal nuclear magnetic resonance (cNMR) spectroscopy on inorganic cesium lead halide nanocrystals (CsPbX3 NCs) is found to serve for noninvasive characterization and quantification of disorder within these structurally soft and labile particles. In particular, we show that Cs-133 cNMR is highly responsive to size variations from 3 to 11 nm or to altering the capping ligands on the surfaces of CsPbX3 NCs. Distinct Cs-133 signals are attributed to the surface and core NC regions. Increased heterogeneous broadening of Cs-133 signals, observed for smaller NCs as well as for long-chain zwitterionic capping ligands (phosphocholines, phosphoethanol(propanol)amine, and sulfobetaines), can be attributed to more significant surface disorder and multifaceted surfaces (truncated cubes). On the contrary, capping with dimethyl-didodecyl-ammonium bromide (DDAB) successfully reduces signal broadening owing to better surface passivation and sharper (001)-bound cuboid shape. DFT calculations on various sizes of NCs corroborate the notion that the surface disorder propagates over several octahedral layers. Cs-133 NMR is a sensitive probe for studying halide gradients in mixed Br/Cl NCs, indicating bromide-rich surfaces and chloride-rich cores. On the contrary, mixed Br/I NCs exhibit homogeneous halide distributions.

Ion Spectroscopy Reveals Structural Difference for Proteins Microhydrated by Retention and Condensation of Water

A. Zviagin; O. V. Boyarkin 

Protein ubiquitin in its +7 charge state microhydrated by 5 and 10 water molecules has been interrogated in the gas phase by cold ion UV/IR spectroscopy. The complexes were formed either by condensing water onto the unfolded bare proteins in a temperature-controlled ion trap or by incomplete dehydration of the folded proteins. In the case of cryogenic condensation, the UV spectra of the complexes exhibit a resolved vibrational structure, which looks similar to the spectrum of bare unfolded ubiquitin. The spectra become, however, broad-band with no structure when complexes of the same size are produced by incomplete dehydration under soft conditions of electrospray ionization. We attribute this spectroscopic dissimilarity to the structural difference of the protein: condensing a few water molecules cannot refold the gas-phase structure of the bare ubiquitin, while the retained water preserves its solution-like folded motif through evaporative cooling. This assessment is firmly confirmed by IR spectroscopy, which reveals the presence of free NH and carboxylic OH stretching vibrations only in the complexes with condensed water.

Acetyl-CoA carboxylase 1 controls a lipid droplet-peroxisome axis and is a vulnerability of endocrine-resistant ER+ breast cancer

M. Bacci; N. Lorito; A. Smiriglia; A. Subbiani; F. Bonechi et al. 

Targeting aromatase deprives ER(+ )breast cancers of estrogens and is an effective therapeutic approach for these tumors. However, drug resistance is an unmet clinical need. Lipidomic analysis of long-term estrogen-deprived (LTED) ER+ breast cancer cells, a model of aromatase inhibitor resistance, revealed enhanced intracellular lipid storage. Functional metabolic analysis showed that lipid droplets together with peroxisomes, which we showed to be enriched and active in the LTED cells, controlled redox homeostasis and conferred metabolic adaptability to the resistant tumors. This reprogramming was controlled by acetyl-CoA-carboxylase-1 (ACC1), whose targeting selectively impaired LTED survival. However, the addition of branched- and very long-chain fatty acids reverted ACC1 inhibition, a process that was mediated by peroxisome function and redox homeostasis. The therapeutic relevance of these findings was validated in aromatase inhibitor-treated patient-derived samples. Last, targeting ACC1 reduced tumor growth of resistant patient-derived xenografts, thus identifying a targetable hub to combat the acquisition of estrogen independence in ER+ breast cancers.

Forward-forward training of an optical neural network

I. Oguz; J. Ke; Q. Weng; F. Yang; M. Yildirim et al. 

Neural networks (NNs) have demonstrated remarkable capabilities in various tasks, but their computation-intensive nature demands faster and more energy-efficient hardware implementations. Optics-based platforms, using technologies such as silicon photonics and spatial light modulators, offer promising avenues for achieving this goal. However, training multiple programmable layers together with these physical systems poses challenges, as they are difficult to fully characterize and describe with differentiable functions, hindering the use of error backpropagation algorithm. The recently introduced forward-forward algorithm (FFA) eliminates the need for perfect characterization of the physical learning system and shows promise for efficient training with large numbers of programmable parameters. The FFA does not require backpropagating an error signal to update the weights, rather the weights are updated by only sending information in one direction. The local loss function for each set of trainable weights enables low-power analog hardware implementations without resorting to metaheuristic algorithms or reinforcement learning. In this paper, we present an experiment utilizing multimode nonlinear wave propagation in an optical fiber demonstrating the feasibility of the FFA approach using an optical system. The results show that incorporating optical transforms in multilayer NN architectures trained with the FFA can lead to performance improvements, even with a relatively small number of trainable weights. The proposed method offers a new path to the challenge of training optical NNs and provides insights into leveraging physical transformations for enhancing the NN performance.

A 0.14-nJ/b 200-Mb/s 2.7-3.5-GHz Quasi-Balanced FSK Transceiver With PLL-Based Modulation and Sideband Energy Detection

B. Wang; C. Ding; Y. Nie; W. Rhee; Z. Wang 

This paper describes a balanced frequency shift keying (FSK) modulation, namely quasi-balanced FSK (QB-FSK), for energy-efficient high-data-rate communication. Not suffering from data-pattern dependency, the proposed modulation method enables frequency modulation (FM) over 100 Mb/s by utilizing a wideband phase-locked loop (PLL). The QB-FSK signal is generated with the same baseband clock frequency as the non-return zero (NRZ)-coded binary FSK (BFSK) signal, resulting in improved bandwidth efficiency compared to other balanced FSK signals. For demodulation, the receiver employs a sideband energy detection (SB-ED) method. A FM discriminator converts the QB-FSK signal to an on-off keying (OOK) signal. After that, a band-pass filter (BPF) is used to filter out 1/f noise and dc offset. Based on the proposed QB-FSK modulation and the SB-ED method, a prototype FSK transceiver is implemented in 65-nm CMOS for high-data-rate sub-6-GHz proprietary wireless connectivity. The receiver successfully demodulates data at a rate of 200 Mb/s with a sensitivity of -67 dBm, while the transmitter can achieve a maximum data rate of 400 Mb/s. The 200-Mb/s transceiver achieves an energy efficiency of 0.14 nJ/b.

Lateral medullary vascular compression manifesting as paroxysmal hypertension

L. Giammattei; G. Wuerzner; K. Theiler; P. Vollenweider; V. Dunet et al. 

Neurovascular compression of the rostral ventrolateral medulla (RVLM) has been described as a possible cause of refractory essential hypertension. We present the case of a patient affected by episodes of severe paroxysmal hypertension, some episodes associated with vago-glossopharyngeal neuralgia. Classical secondary forms of hypertension were excluded. Imaging revealed a neurovascular conflict between the posterior inferior cerebellar artery (PICA) and the ventrolateral medulla at the level of the root entry zone of the ninth and tenth cranial nerves (CN IX-X REZ). A MVD of a conflict between the PICA and the RVLM and adjacent CN IX-X REZ was performed, resulting in reduction of the frequency and severity of the episodes. Brain MRI should be performed in cases of paroxysmal hypertension. MVD can be considered in selected patients.

Mapping orthorhombic domains with geometrical phase analysis in rare-earth nickelate heterostructures

B. Mundet; M. Hadjimichael; J. Fowlie; L. Korosec; L. Varbaro et al. 

Most perovskite oxides belong to the Pbnm space group, composed of an anisotropic unit cell, A-site antipolar displacements, and oxygen octahedral tilts. Mapping the orientation of the orthorhombic unit cell in epitaxial heterostructures that consist of at least one Pbnm compound is often needed for understanding and controlling the different degrees of coupling established at their coherent interfaces and, therefore, their resulting physical properties. However, retrieving this information from the strain maps generated with high-resolution scanning transmission electron microscopy can be challenging, because the three pseudocubic lattice parameters are very similar in these systems. Here, we present a novel methodology for mapping the crystallographic orientation in Pbnm systems. It makes use of the geometrical phase analysis algorithm, as applied to aberration-corrected scanning transition electron microscopy images, but in an unconventional way. The method is fast and robust, giving real-space maps of the lattice orientations in Pbnm systems, from both cross section and plan-view geometries, and across large fields of view. As an example, we apply our methodology to rare-earth nickelate heterostructures, in order to investigate how the crystallographic orientation of these films depends on various structural constraints that are imposed by the underlying single crystal substrates. We observe that the resulting domain distributions and associated defect landscapes mainly depend on a competition between the epitaxial compressive/tensile and shear strains, together with the matching of atomic displacements at the substrate/film interface. The results point toward strategies for controlling these characteristics by appropriate substrate choice.

Photothermal spectroscopy on-chip sensor for the measurement of a PMMA film using a silicon nitride micro-ring resonator and an external cavity quantum cascade laser

G. Ricchiuti; A. Walsh; J. H. Mendoza-Castro; A. S. Vorobev; M. Kotlyar et al. 

Laser-based mid-infrared (mid-IR) photothermal spectroscopy (PTS) represents a selective, fast, and sensitive analytical technique. Recent developments in laser design permits the coverage of wider spectral regions in combination with higher power, enabling for qualitative reconstruction of broadband absorption features, typical of liquid or solid samples. In this work, we use an external cavity quantum cascade laser (EC-QCL) that emits in pulsed mode in the region between 5.7 and 6.4 mu m (1770-1560 cm-1), to measure the absorption spectrum of a thin film of polymethyl methacrylate (PMMA) spin-coated on top of a silicon nitride (Si3N4) micro-ring resonator (MRR). Being the PTS signal inversely proportional to the volume of interaction, in the classical probe-pump dual beam detection scheme, we exploit a Si3N4 transducer coated with PMMA, as a proof-of-principle for an on-chip photothermal sensor. By tuning the probe laser at the inflection point of one resonance, aiming for highest sensitivity, we align the mid-IR beam on top of the ring’s area, in a transversal configuration. To maximize the amplitude of the photoinduced thermal change, we focus the mid-IR light on top of the ring using a Cassegrain reflector enabling for an optimal match between ring size and beam waist of the excitation source. We briefly describe the transducer design and fabrication process, present the experimental setup, and perform an analysis for optimal operational parameters. We comment on the obtained results showing that PTS allows for miniaturized robust sensors opening the path for on-line/in-line monitoring in several industrial processes.

Measurement of the CKM angle γ in the B0→DK *0 channel using self-conjugate D→ KS0h+ h- decays

R. Aaij; A. S. W. Abdelmotteleb; C. A. Beteta; F. Abudinen; T. Ackernley et al. 

A model-independent study of CP violation in B-0 -> DK (*0) decays is presented using data corresponding to an integrated luminosity of 9 fb(-1) collected by the LHCb experiment at centre-of-mass energies of v s = 7, 8 and 13TeV. The CKM angle. is determined by examining the distributions of signal decays in phase-space bins of the self-conjugate D. K(S)(0)h(+) h(-) decays, where h = p, K. Observables related to CP violation are measured and the angle. is determined to be. = (49+22 -19).. Measurements of the amplitude ratio and strong-phase difference between the favoured and suppressed B-0 decays are also presented.

Multi-machine benchmark of the self-consistent 1D scrape-off layer model DIV1D from stagnation point to target with SOLPS-ITER

G. L. Derks; E. Westerhof; M. van Berkel; J. H. Jenneskens; J. T. W. Koenders et al. 

This paper extends a 1D dynamic physics-based model of the scrape-off layer (SOL) plasma, DIV1D, to include the core SOL and possibly a second target. The extended model is benchmarked on 1D mapped SOLPS-ITER simulations to find input settings for DIV1D that allow it to describe SOL plasmas from upstream to target-calibrating it on a scenario and device basis. The benchmark shows a quantitative match between DIV1D and 1D mapped SOLPS-ITER profiles for the heat flux, electron temperature, and electron density within roughly 50% on: (1) the Tokamak Configuration Variable (TCV) for a gas puff scan; (2) a single SOLPS-ITER simulation of the Upgraded Mega Ampere Spherical Tokamak; and (3) the Upgraded Axially Symmetric Divertor EXperiment in Garching Tokamak (AUG) for a simultaneous scan in heating power and gas puff. Once calibrated, DIV1D self-consistently describes dependencies of the SOL solution on core fluxes and external neutral gas densities for a density scan on TCV whereas a varying SOL width is used in DIV1D for AUG to match a simultaneous change in power and density. The ability to calibrate DIV1D on a scenario and device basis is enabled by accounting for cross field transport with an effective flux expansion factor and by allowing neutrals to be exchanged between SOL and adjacent domains.