cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Activation of Carboxylic Acids by using Sulfonyl Chloride Reagent: A Simple One Pot Conversion of Carboxylic Acids to Alcohols
Creators: name: Panigrahi, Ranjan Kumar
name: Jana, Samaresh
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Biochemistry
subject: Physical Sciences not elsewhere classified
subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Physiology
subject: Pharmacology
subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Chemical Sciences not elsewhere classified
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Mental Health
subject: Hematology

description: Activation of Carboxylic Acids by using Sulfonyl Chloride Reagent: A Simple One Pot Conversion of Carboxylic Acids to Alcohols
AirForUAppendix-12-15-2018_final – Supplemental material for Engagement With Air Quality Information: Stated Versus Revealed Preferences
Creators: name: Delmas, Magali A.
name: Aanchal Kohli
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 150310 Organisation and Management Theory
subject: FOS: Economics and business
subject: Sociology
subject: FOS: Sociology

description: Supplemental material, AirForUAppendix-12-15-2018_final for Engagement With Air Quality Information: Stated Versus Revealed Preferences by Magali A. Delmas and Aanchal Kohli in Organization & Environment
Additional file 1 of Retention time and fix acquisition rate of glued-on GPS transmitters in a semi-aquatic species
Creators: name: Pitman, John B.
name: Bastille-Rousseau, Guillaume
Publisher: name: figshare
Year: 2024
Subjects: subject: Neuroscience
subject: Evolutionary Biology
subject: FOS: Biological sciences
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Science Policy

description: Additional file 1. Boxplots displaying how retention time (number of days the transmitter remained attached to the beaver) varied across individuals.
title: NEPS-SC5-Erhebungsdaten verknüpft mit administrativen Daten des IAB (NEPS-SC5-ADIAB)
Creators: name: Bachbauer, Nadine
name: Wolf, Clara
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2021

description: Dieser Datenreport beschreibt die verknüpften Erhebungsdaten des Nationalen Bildungspanels der Startkohorte 5 'Hochschulstudium und Übergang in den Beruf' (NEPS-SC5) mit administrativen Daten des Instituts für Arbeitsmarkt- und Berufsforschung (IAB).
Supplemental material for Durability and notch sensitivity analysis of environmental ageing induced glass fibre mat and kenaf fibre mat-reinforced composites
Creators: name: Md Sohag Miah
name: Jianyong Yu
name: Yuqiu Yang
name: Hafeezullah Memon
name: Rashid, Muhammad A
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 91299 Materials Engineering not elsewhere classified
subject: FOS: Materials engineering

description: Supplemental Material for Durability and notch sensitivity analysis of environmental ageing induced glass fibre mat and kenaf fibre mat-reinforced composites by Md Sohag Miah, Jianyong Yu, Yuqiu Yang, Hafeezullah Memon and Muhammad A Rashid in Journal of Industrial Textiles
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
Creators: name: Chu, Mengyu
name: Liu, Lingjie
name: Zheng, Quan
name: Franz, Aleksandra
name: Seidel, Hans-Peter
name: Theobalt, Christian
name: Zayer, Rhaleb
Publisher: name: arXiv
Year: 2022
Subjects: subject: Graphics (cs.GR)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: High-fidelity reconstruction of fluids from sparse multiview RGB videos remains a formidable challenge due to the complexity of the underlying physics as well as complex occlusion and lighting in captures. Existing solutions either assume knowledge of obstacles and lighting, or only focus on simple fluid scenes without obstacles or complex lighting, and thus are unsuitable for real-world scenes with unknown lighting or arbitrary obstacles. We present the first method to reconstruct dynamic fluid by leveraging the governing physics (ie, Navier -Stokes equations) in an end-to-end optimization from sparse videos without taking lighting conditions, geometry information, or boundary conditions as input. We provide a continuous spatio-temporal scene representation using neural networks as the ansatz of density and velocity solution functions for fluids as well as the radiance field for static objects. With a hybrid architecture that separates static and dynamic contents, fluid interactions with static obstacles are reconstructed for the first time without additional geometry input or human labeling. By augmenting time-varying neural radiance fields with physics-informed deep learning, our method benefits from the supervision of images and physical priors. To achieve robust optimization from sparse views, we introduced a layer-by-layer growing strategy to progressively increase the network capacity. Using progressively growing models with a new regularization term, we manage to disentangle density-color ambiguity in radiance fields without overfitting. A pretrained density-to-velocity fluid model is leveraged in addition as the data prior to avoid suboptimal velocity which underestimates vorticity but trivially fulfills physical equations. Our method exhibits high-quality results with relaxed constraints and strong flexibility on a representative set of synthetic and real flow captures.
description: accepted to ACM Transactions On Graphics (SIGGRAPH 2022), further info:\url{https://people.mpi-inf.mpg.de/~mchu/projects/PI-NeRF/}
A Rapid and Environmentally Benign Access to Hantzsch’s Polyhydroquinolines
Creators: name: Tangade, A. D.
name: Jadhav, P. M.
name: Kauthale, S. S.
name: Pawar, R. P.
name: Tekale, S. U.
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Space Science
subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Evolutionary Biology
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Inorganic Chemistry
subject: FOS: Chemical sciences
subject: Infectious Diseases
subject: FOS: Health sciences

description: A Rapid and Environmentally Benign Access to Hantzsch’s Polyhydroquinolines
On a set of norm attaining operators and the strong Birkhoff-James orthogonality
Creators: name: Choi, Geunsu
name: Jung, Mingu
name: Kim, Sun Kwang
Publisher: name: arXiv
Year: 2022
Subjects: subject: Functional Analysis (math.FA)
subject: FOS: Mathematics
subject: Primary: 46B04, Secondary: 46B20, 46B25

description: Continuing the study of recent results on the Birkhoff-James orthogonality and the norm attainment of operators, we introduce a property namely the adjusted Bhatia-Šemrl property for operators which is weaker than the Bhatia-Šemrl property. The set of operators with the adjusted Bhatia-Šemrl property is contained in the set of norm attaining ones as it was in the case of the Bhatia-Šemrl property. It is known that the set of operators with the Bhatia-Šemrl property is norm-dense if the domain space $X$ of the operators has the Radon-Nikodým property like finite dimensional spaces, but it is not norm-dense for some classical spaces such as $c_0$, $L_1[0,1]$ and $C[0,1]$. In contrast with the Bhatia-Šemrl property, we show that the set of operators with the adjusted Bhatia-Šemrl property is norm-dense when the domain space is $c_0$ or $L_1[0,1]$. Moreover, we show that the set of functionals having the adjusted Bhatia-Šemrl property on $C[0,1]$ is not norm-dense but such a set is weak-$*$-dense in $C(K)^*$ for any compact Hausdorff $K$.
description: 18 pages
ADVANCING UNIVERSAL HEALTH COVERAGE IN CHINA: A COMPREHENSIVE REVIEW
Creators: name: Dr. Emily Grace, Mitchell
Publisher: name: continental journal
Year: 2024
Subjects: Universal health coverage, public health services, health interventions, global health, equity.

description: Universal health coverage (UHC) is a crucial component of global health aiming to provide individuals with the necessary health services without subjecting them to financial hardship. While UHC has made substantial progress, it currently lacks a focus on public health services, which play a significant role in improving population health. This paper examines the relationship between UHC and public health, emphasizing the importance of integrating public health services within the UHC framework. By recognizing the value of public health interventions and their potential to promote equitable health outcomes, this study advocates for the enhancement of UHC through an inclusive approach to public health services, aligning with the Sustainable Development Goals.
METODOLOGIA W.F.C PARA MITIGAR ALZHEIMER  DIMINUIR A EVOLUÇÃO DE UMA DOENÇA DEVASTADORA
Creators: name: Washington, Francisco Corrêa
Publisher: name: Zenodo
Year: 2024
Subjects: Alzheimer, método, PDCA, AVDs, AIVDs, mitigar, cognição, autonomia, multidisciplinar

description: Este artigo representa um viés aberto dentro da comunidade cientifica, sendo um leque sobre o que se refere ao resgate das sinapses cerebrais em pacientes com evolução do Alzheimer, usando uma metodologia nunca usada antes, iniciando então um campo de pesquisa dentro da área médica, difundindo todas as áreas e tornando um olhar só, método W.F.C junto ao ciclo PDCA, veio para nortear todos profissionais e familiares que entram e embalam Alzheimer, como não tendo ainda referência, desenvolver o método trará um rio de pesquisas mais detalhadas, tendo o antes e o depois da evolução, quanto do fator cognição e autonomia foi mantida, os arquivos com palavra-chave dos idosos e suas AVDs e AIVDs sendo usados em forma de vídeos, feito por eles mesmos, se dando aulas, retardando então e mitigando sofrimento humano que aflige, como a doença de Alzheimer.
Joint Trajectory and Resource Optimization of MEC-Assisted UAVs in Sub-THz Networks: A Resources-based Multi-Agent Proximal Policy Optimization DRL with Attention Mechanism
Creators: name: Park, Yu Min
name: Hassan, Sheikh Salman
name: Tun, Yan Kyaw
name: Han, Zhu
name: Hong, Choong Seon
Publisher: name: arXiv
Year: 2022
Subjects: subject: Networking and Internet Architecture (cs.NI)
subject: FOS: Computer and information sciences

description: THz band communication technology will be used in the 6G networks to enable high-speed and high-capacity data service demands. However, THz-communication losses arise owing to limitations, i.e., molecular absorption, rain attenuation, and coverage range. Furthermore, to maintain steady THz-communications and overcome coverage distances in rural and suburban regions, the required number of BSs is very high. Consequently, a new communication platform that enables aerial communication services is required. Furthermore, the airborne platform supports LoS communications rather than NLoS communications, which helps overcome these losses. Therefore, in this work, we investigate the deployment and resource optimization for MEC-enabled UAVs, which can provide THz-based communications in remote regions. To this end, we formulate an optimization problem to minimize the sum of the energy consumption of both MEC-UAV and MUs and the delay incurred by MUs under the given task information. The formulated problem is a MINLP problem, which is NP-hard. We decompose the main problem into two subproblems to address the formulated problem. We solve the first subproblem with a standard optimization solver, i.e., CVXPY, due to its convex nature. To solve the second subproblem, we design a RMAPPO DRL algorithm with an attention mechanism. The considered attention mechanism is utilized for encoding a diverse number of observations. This is designed by the network coordinator to provide a differentiated fit reward to each agent in the network. The simulation results show that the proposed algorithm outperforms the benchmark and yields a network utility which is $2.22\%$, $15.55\%$, and $17.77\%$ more than the benchmarks.
description: 13 pages, 12 figures
Multicomponent Synthesis of Novel 7H-Pyrrolo[3,2-f]quinoxaline Derivatives
Creators: name: Wei, Kai
name: Huang, Qi-Zhong
name: Liu, Jia-Yan
name: Chen, Dong-Sheng
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Medicine
subject: Molecular Biology
subject: Neuroscience
subject: Chemical Sciences not elsewhere classified
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Virology

description: Multicomponent Synthesis of Novel 7H-Pyrrolo[3,2-f]quinoxaline Derivatives
Shifted Contact Structures and Their Local Theory
Creators: name: Berktav, Kadri İlker
Publisher: name: arXiv
Year: 2022
Subjects: subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics
subject: 14A20, 14A30, 14F05

description: In this paper, we formally define the concept of shifted contact structures on derived (Artin) stacks and study their local properties in the context of derived algebraic geometry. In this regard, for negatively shifted contact derived $\mathbb{K}$-schemes, we develop a Darboux-like theorem and formulate the notion of symplectification.
description: V07: Example 3.10, the proof of Theorem 3.13, Observations 2.27 and 3.17 revisited; some edits on the published version. See Addendum on the author's webpage for details. Comments are welcome!
A policy gradient approach for Finite Horizon Constrained Markov Decision Processes
Creators: name: Guin, Soumyajit
name: Bhatnagar, Shalabh
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: The infinite horizon setting is widely adopted for problems of reinforcement learning (RL). These invariably result in stationary policies that are optimal. In many situations, finite horizon control problems are of interest and for such problems, the optimal policies are time-varying in general. Another setting that has become popular in recent times is of Constrained Reinforcement Learning, where the agent maximizes its rewards while it also aims to satisfy some given constraint criteria. However, this setting has only been studied in the context of infinite horizon MDPs where stationary policies are optimal. We present an algorithm for constrained RL in the Finite Horizon Setting where the horizon terminates after a fixed (finite) time. We use function approximation in our algorithm which is essential when the state and action spaces are large or continuous and use the policy gradient method to find the optimal policy. The optimal policy that we obtain depends on the stage and so is non-stationary in general. To the best of our knowledge, our paper presents the first policy gradient algorithm for the finite horizon setting with constraints. We show the convergence of our algorithm to a constrained optimal policy. We also compare and analyze the performance of our algorithm through experiments and show that our algorithm performs better than some other well known algorithms.
title: NEPS-SC5 survey data linked to administrative data of the IAB (NEPS-SC5-ADIAB)
Creators: name: Bachbauer, Nadine
name: Wolf, Clara Berufsforschung
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2021

description: This data report describes the linked survey data of Starting Cohort 5 'From Higher Education to the Labor Market' of the National Educational Panel Study (NEPS-SC5) with administrative data of the Institute for Employment Research (IAB).
GeoCode: Interpretable Shape Programs
Creators: name: Pearl, Ofek
name: Lang, Itai
name: Hu, Yuhua
name: Yeh, Raymond A.
name: Hanocka, Rana
Publisher: name: arXiv
Year: 2022
Subjects: subject: Graphics (cs.GR)
subject: FOS: Computer and information sciences

description: The task of crafting procedural programs capable of generating structurally valid 3D shapes easily and intuitively remains an elusive goal in computer vision and graphics. Within the graphics community, generating procedural 3D models has shifted to using node graph systems. They allow the artist to create complex shapes and animations through visual programming. Being a high-level design tool, they made procedural 3D modeling more accessible. However, crafting those node graphs demands expertise and training. We present GeoCode, a novel framework designed to extend an existing node graph system and significantly lower the bar for the creation of new procedural 3D shape programs. Our approach meticulously balances expressiveness and generalization for part-based shapes. We propose a curated set of new geometric building blocks that are expressive and reusable across domains. We showcase three innovative and expressive programs developed through our technique and geometric building blocks. Our programs enforce intricate rules, empowering users to execute intuitive high-level parameter edits that seamlessly propagate throughout the entire shape at a lower level while maintaining its validity. To evaluate the user-friendliness of our geometric building blocks among non-experts, we conducted a user study that demonstrates their ease of use and highlights their applicability across diverse domains. Empirical evidence shows the superior accuracy of GeoCode in inferring and recovering 3D shapes compared to an existing competitor. Furthermore, our method demonstrates superior expressiveness compared to alternatives that utilize coarse primitives. Notably, we illustrate the ability to execute controllable local and global shape manipulations.
description: project page: https://threedle.github.io/GeoCode/
APPENDIX_A_JULY_25_2019 – Supplemental material for Is Film as a Research Tool the Future of Public Health? A Review of Study Designs, Opportunities, and Challenges
Creators: name: Baumann, Sara E.
name: Merante, Monica
name: Folb, Barbara L.
name: Burke, Jessica G.
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 111099 Nursing not elsewhere classified
subject: FOS: Health sciences
subject: 111799 Public Health and Health Services not elsewhere classified
subject: 160807 Sociological Methodology and Research Methods
subject: FOS: Sociology

description: Supplemental material, APPENDIX_A_JULY_25_2019 for Is Film as a Research Tool the Future of Public Health? A Review of Study Designs, Opportunities, and Challenges by Sara E. Baumann, Monica Merante, Barbara L. Folb and Jessica G. Burke in Qualitative Health Research
Nested Dirichlet models for unsupervised attack pattern detection in honeypot data
Creators: name: Passino, Francesco Sanna
name: Mantziou, Anastasia
name: Ghani, Daniyar
name: Thiede, Philip
name: Bevington, Ross
name: Heard, Nicholas A.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Cryptography and Security (cs.CR)
subject: Applications (stat.AP)
subject: FOS: Computer and information sciences

description: Cyber-systems are under near-constant threat from intrusion attempts. Attacks types vary, but each attempt typically has a specific underlying intent, and the perpetrators are typically groups of individuals with similar objectives. Clustering attacks appearing to share a common intent is very valuable to threat-hunting experts. This article explores Dirichlet distribution topic models for clustering terminal session commands collected from honeypots, which are special network hosts designed to entice malicious attackers. The main practical implications of clustering the sessions are two-fold: finding similar groups of attacks, and identifying outliers. A range of statistical models are considered, adapted to the structures of command-line syntax. In particular, concepts of primary and secondary topics, and then session-level and command-level topics, are introduced into the models to improve interpretability. The proposed methods are further extended in a Bayesian nonparametric fashion to allow unboundedness in the vocabulary size and the number of latent intents. The methods are shown to discover an unusual MIRAI variant which attempts to take over existing cryptocurrency coin-mining infrastructure, not detected by traditional topic-modelling approaches.
Efficient lineshape estimation by ghost spectroscopy
Creators: name: Gianani, Ilaria
name: Soto, Luis L. Sanchez
name: Goldberg, Aaron Z.
name: Barbieri, Marco
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: Data Analysis, Statistics and Probability (physics.data-an)
subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: Recovering the original spectral lineshapes from data obtained by instruments with extended transmission profiles is a basic tenet in spectroscopy. By using the moments of the measured lines as basic variables, we turn the problem into a linear inversion. However, when only a finite number of these moments are relevant, the rest of them act as nuisance parameters. These can be taken into account with a semiparametric model, which allows us to establish the ultimate bounds on the precision attainable in the estimation of the moments of interest. We experimentally confirm these limits with a simple ghost spectroscopy demonstration.
Supplemental_Appendix_1_Final_R1 – Supplemental material for Urinary 11-nor-9-carboxy-tetrahydrocannabinol elimination in adolescent and young adult cannabis users during one month of sustained and biochemically-verified abstinence
Creators: name: Schuster, Randi Melissa
name: Potter, Kevin
name: Vandrey, Ryan
name: Hareli, Maya
name: Gilman, Jodi
name: Schoenfeld, David
name: A Eden Evins
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine
subject: 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified
subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology
subject: 110319 Psychiatry (incl. Psychotherapy)

description: Supplemental material, Supplemental_Appendix_1_Final_R1 for Urinary 11-nor-9-carboxy-tetrahydrocannabinol elimination in adolescent and young adult cannabis users during one month of sustained and biochemically-verified abstinence by Randi Melissa Schuster, Kevin Potter, Ryan Vandrey, Maya Hareli, Jodi Gilman, David Schoenfeld and A Eden Evins in Journal of Psychopharmacology
Identifying socio-ecological dynamics in water systems through adaptive cycles
Creators: name: da Silva, Maycon Breno Macena
name: Ribeiro, Márcia Maria Rios
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Space Science
subject: Medicine
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: FOS: Biological sciences
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Inorganic Chemistry
subject: FOS: Chemical sciences
subject: Science Policy

description: Investigating the dynamics of water systems is challenging but essential for identifying weaknesses and strengths that enhance adaptation and transformation, contributing to governance. We propose integrating approaches to the adaptive cycle framework to understand socio-ecological dynamics, system interactions, and variables that impact a water system as a reservoir in the Brazilian semi-arid region. Key findings include the identification of non-linearity in the socio-ecological dynamics and the simultaneous use of adaptation and transformation mechanisms to prevent water collapse. We also emphasize the role of institutions in creating resilience, which can steer the system towards desired or undesired regimes. Additionally, understanding relationships among systems at various planning levels and their variables is crucial, as they can influence water systems fast or slowly. The outcomes show the importance of considering a reservoir at the local planning level within a river basin, state, and nation. This consideration helps improve water governance and policymaking.
title: Codebuch und Dokumentation des Panel 'Arbeitsmarkt und soziale Sicherung' (PASS)
Creators: name: Berg, Marco
name: Cramer, Ralph
name: Dickmann, Christian
name: Gilberg, Reiner
name: Jesske, Birgit
name: Kleudgen, Martin
name: Beste, Jonas
name: Dummert, Sandra
name: Frodermann, Corinna
name: Wenzig, Claudia
name: Trappmann, Mark
name: Bähr, Sebastian
name: Collischon, Matthias
name: Coban, Mustafa
name: Friedrich, Martin
name: Gleiser, Patrick
name: Gundert, Stefanie
name: Malich, Sonja
name: Müller, Bettina
name: Schwarz, Stefan
name: Stegmaier, Jens
name: Teichler, Nils
name: Unger, Stefanie Berufsforschung
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2021

description: Die FDZ-Datenreporte beschreiben die Daten des FDZ im Detail. Diese Reihe hat somit eine doppelte Funktion: Zum einen stellen Nutzerinnen und Nutzer fest, ob die angebotenen Daten für das Forschungsvorhaben geeignet sind, zum anderen dienen sie zur Vorbereitung der Auswertungen.DieserDatenreportdokumentiertdie AufbereitungderWelle 14 vonPASS. Das Dokument basiert auf dem Datenreport der Welle 13: Marco Berg, Ralph Cramer, Christian Dickmann, Reiner Gilberg, Birgit Jesske, Martin Kleudgen (alle infas Institut für angewandte Sozialwissenschaft GmbH), Jonas Beste, Sandra Dummert, Corinna Frodermann, Stefan Schwarz, Mark Trappmann, Sebastian Bähr, Mustafa Coban, Martin Friedrich, Stefanie Gundert, BettinaMüller, NilsTeichler, StefanieUnger, Claudia Wenzig (alle InstitutfürArbeitsmarkt- und Berufsforschung (IAB)): Codebuch und Dokumentation des Panel „Arbeitsmarkt und soziale Sicherung“ (PASS) Band I: Datenreport Welle 13, FDZ Datenreport, 12/2020 (de), Nürnberg
Multiplicity of nontrivial zeros of primitive L-functions via higher-level correlations
Creators: name: Gonçalves, Felipe
name: de Laat, David
name: Leijenhorst, Nando
Publisher: name: arXiv
Year: 2023
Subjects: subject: Number Theory (math.NT)
subject: Optimization and Control (math.OC)
subject: FOS: Mathematics

description: We give universal bounds on the fraction of nontrivial zeros having given multiplicity for L-functions attached to a cuspidal automorphic representation of $\mathrm{GL}_m/\mathbb{Q}$. For this, we apply the higher-level correlation asymptotic of Hejhal and Rudnick & Sarnak in conjunction with semidefinite programming bounds.
description: 15 pages, revision based on suggestions by referee
Unimodal Distributions for Ordinal Regression
Creators: name: Cardoso, Jaime S.
name: Cruz, Ricardo
name: Albuquerque, Tomé
Publisher: name: arXiv
Year: 2023
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: In many real-world prediction tasks, class labels contain information about the relative order between labels that are not captured by commonly used loss functions such as multicategory cross-entropy. Recently, the preference for unimodal distributions in the output space has been incorporated into models and loss functions to account for such ordering information. However, current approaches rely on heuristics that lack a theoretical foundation. Here, we propose two new approaches to incorporate the preference for unimodal distributions into the predictive model. We analyse the set of unimodal distributions in the probability simplex and establish fundamental properties. We then propose a new architecture that imposes unimodal distributions and a new loss term that relies on the notion of projection in a set to promote unimodality. Experiments show the new architecture achieves top-2 performance, while the proposed new loss term is very competitive while maintaining high unimodality.
description: 17 pages
Precipitation recycling impacts on runoff in arid regions of China and Mongolia: a machine learning approach
Creators: name: Li, Ruolin
name: Feng, Qi
name: Cui, Yang
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Cell Biology
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: FOS: Biological sciences
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy
subject: Plant Biology

description: This study analyses the impact of precipitation recycling on runoff in the China–Mongolia Arid Region (CMAR) using European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data and a random forest model. We address the challenge of quantifying complex precipitation recycling effects in arid regions by combining reanalysis data with machine learning. Our approach reveals significant positive feedback between precipitation recycling rate (rr) and runoff (ro), with correlation coefficients of 0.40 in spring and 0.21 in summer. Scenario analyses demonstrate that neglecting rr underestimates runoff by 1123% in wet seasons, while doubling rr overestimates it by 819% during peak rainfall. The random forest model effectively captures rrro relationships, particularly for the prevalent low-runoff conditions in CMAR. These findings emphasize the crucial role of local water recycling in sustaining runoff and managing water scarcity in arid regions. We suggest incorporating recycling processes into hydrological models to improve runoff predictions in water-scarce environments.
Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling
Creators: name: Li, Haotian
name: Wang, Yun
name: Liao, Q. Vera
name: Qu, Huamin
Publisher: name: arXiv
Year: 2023
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Data storytelling plays an important role in data workers' daily jobs since it boosts team collaboration and public communication. However, to make an appealing data story, data workers spend tremendous efforts on various tasks, including outlining and styling the story. Recently, a growing research trend has been exploring how to assist data storytelling with advanced artificial intelligence (AI). However, existing studies may focus on individual tasks in the workflow of data storytelling and do not reveal a complete picture of humans' preference for collaborating with AI. To better understand real-world needs, we interviewed eighteen data workers from both industry and academia to learn where and how they would like to collaborate with AI. Surprisingly, though the participants showed excitement about collaborating with AI, many of them also expressed reluctance and pointed out nuanced reasons. Based on their responses, we first characterize stages and tasks in the practical data storytelling workflows and the desired roles of AI. Then the preferred collaboration patterns in different tasks are identified. Next, we summarize the interviewees' reasons why and why not they would like to collaborate with AI. Finally, we provide suggestions for human-AI collaborative data storytelling to hopefully shed light on future related research.
description: To be published in IEEE Transactions on Visualization and Computer Graphics
Improved streamflow simulations in hydrologically diverse basins using physically-informed deep learning models
Creators: name: Magotra, Bhanu
name: Saharia, Manabendra
name: Dhanya, C. T.
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Environmental Sciences not elsewhere classified
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified

description: Physically-informed deep learning models, especially long short-term memory (LSTM) networks, have shown promise in large-scale streamflow simulations. However, an in-depth understanding of the relative contribution of physical information in deep learning models has been missing. Using a large-sample testbed of 220 catchments in hydrologically diverse regions of the Indian sub-continent, we quantify the impact of incremental addition of physical information on model performance using multiple variants of the LSTM model based on various combinations of static catchment attributes and simulated land surface states. We found that LSTM models trained with catchment geophysics as additional input outperformed the base LSTM model in terms of the nationwide median Kling-Gupta efficiency (KGE) of in-sample catchments, increasing KGE from 0.32 to 0.60. Additionally, the model retained significant prediction skill in out-of-sample catchments, demonstrating that a pre-trained LSTM model can be a powerful tool to predict streamflow in data-scarce regions.
The effect of loops on the mean square displacement of Rouse-model chromatin
Creators: name: Yuan, Tianyu
name: Yan, Hao
name: Bailey, Mary Lou P.
name: Williams, Jessica F.
name: Surovtsev, Ivan
name: King, Megan C.
name: Mochrie, Simon G. J.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Biological Physics (physics.bio-ph)
subject: Soft Condensed Matter (cond-mat.soft)
subject: Subcellular Processes (q-bio.SC)
subject: FOS: Physical sciences
subject: FOS: Biological sciences

description: Many researchers have been encouraged to describe the dynamics of chromosomal loci in chromatin using the classical Rouse model of polymer dynamics by the agreement between the measured mean square displacement (MSD) versus time of fluorescently-labelled loci and the Rouse-model predictions. However, the discovery of intermediate-scale chromatin organization, known as topologically associating domains (TADs), together with the proposed explanation of TADs in terms of chromatin loops and loop extrusion, is at odds with the classical Rouse model, which does not contain loops. Accordingly, we introduce an extended Rouse model that incorporates chromatin loop configurations from loop-extrusion-factor-model simulations. Specifically, we extend the classical Rouse model by modifying the polymer's dynamical matrix to incorporate extra springs that represent loop bases. We also theoretically generalize the friction coefficient matrix so that the Rouse beads with non-uniform friction coefficients are compatible with our Rouse model simulation method. This extended Rouse model allowes us to investigate the impact of loops and loop extrusion on the dynamics of chromatin. We show that loops significantly suppress the averaged MSD of a chromosomal locus, consistent with recent experiments that track fluorescently-labelled chromatin loci in fission yeast [M. L. P. Bailey, I. Surovtsev, J. F. Williams, H. Yan, T. Yuan, S. G. Mochrie, and M. C. King, Mol. Biol. Cell (in press)]. We also find that loops slightly reduce the MSD's stretching exponent from the classical Rouse-model value of 0.5 to a loop-density-dependent value in the 0.45-0.40 range. Remarkably, stretching exponent values in this range have also been reported in recent experiments [S. C. Weber, A. J. Spakowitz, and J. A. Theriot, Phys. Rev. Lett. 104, 238102 (2010) and Bailey et al., Mol. Biol. Cell (in press)].
Improved streamflow simulations in hydrologically diverse basins using physically informed deep learning models
Creators: name: Magotra, Bhanu
name: Saharia, Manabendra
name: Dhanya, C.T.
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Environmental Sciences not elsewhere classified
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified

description: Physically informed deep learning models, especially Long Short-Term Memory (LSTM) networks, have shown promise in large-scale streamflow simulations. However, an in-depth understanding of the relative contribution of physical information in deep learning models has been missing. Using a large-sample testbed of 220 catchments in hydrologically diverse regions of the Indian subcontinent, we quantify the impact of incremental addition of physical information on model performance using multiple variants of the LSTM model based on various combinations of static catchment attributes and simulated land surface states. We found that LSTM models trained with catchment geophysics as additional input outperformed the base LSTM model in terms of the nationwide median Kling-Gupta Efficiency (KGE) of in-sample catchments, increasing KGE from 0.32 to 0.60. Additionally, the model retained significant prediction skill in out-of-sample catchments, demonstrating that a pre-trained LSTM model can be a powerful tool to predict streamflow in data-scarce regions.
Weyl laws for interacting particles
Creators: name: Nguyen, Ngoc Nhi
Publisher: name: arXiv
Year: 2023
Subjects: subject: Mathematical Physics (math-ph)
subject: Spectral Theory (math.SP)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: We study grand-canonical interacting fermionic systems in the mean-field regime, in a trapping potential. We provide the first order term of integrated and pointwise Weyl laws, but in the case with interaction. More precisely, we prove the convergence of the densities of the grand-canonical Hartree-Fock ground state to the Thomas-Fermi ground state in the semiclassical limit $\hbar\to 0$. For the proof, we write the grand-canonical version of the results of Fournais, Lewin and Solovej (Calc. Var. Partial Differ. Equ., 2018) and of Conlon (Commun. Math. Phys., 1983).
description: 37 pages
title: Codebuch und Dokumentation der Interviewernachbefragung des Panel "Arbeitsmarkt und soziale Sicherung" (PASS)
Creators: name: Dummert, Sandra Berufsforschung
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2021

description: Die FDZ-Datenreporte beschreiben die Daten des FDZ im Detail. Diese Reihe hat somit eine doppelte Funktion: Zum einen stellen Nutzerinnen und Nutzer fest, ob die angebotenen Daten für das Forschungsvorhaben geeignet sind, zum anderen dienen sie zur Vorbereitung der Auswertungen. Dieser Datenreport beschreibt die im Rahmen einer Interviewendennachbefragung (PASS-INT) erhobenen Daten. Diese Befragung, welche sich an die Interviewenden richtet, wurde ab der 4. Welle im Anschluss an jedes erfolgreich durchgeführte Personeninterview für das Panel Arbeitsmarkt und Soziale Sicherung (PASS) durchgeführt.
The concept of mapped coercivity for nonlinear operators in Banach spaces
Creators: name: Becker, Roland
name: Braack, Malte
Publisher: name: arXiv
Year: 2023
Subjects: subject: Analysis of PDEs (math.AP)
subject: Functional Analysis (math.FA)
subject: FOS: Mathematics
subject: 35J60, 35J61, 35J20, 46T99, 47H99, 47J05, 47J30

description: We provide a concise proof of existence for nonlinear operator equations in separable Banach spaces. Notably, the operator is not assumed to be monotone. Instead, our main hypotheses consist of a continuity assumption and a generalized coercivity property. Mapped coercivity is a generalization of the usual coercivity property for nonlinear operators. In the case of linear operators, we recover linear coercivity and the traditional inf-sup condition. To illustrate the applicability of this general concept, we apply it to semi-linear elliptic problems and the Navier-Stokes equations.
Nonlinear multi-state tunneling dynamics in a spinor Bose-Einstein condensate
Creators: name: Hardesty-Shaw, Z. N.
name: Guan, Q.
name: Austin-Harris, J. O.
name: Blume, D.
name: Lewis-Swan, R. J.
name: Liu, Y.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Gases (cond-mat.quant-gas)
subject: FOS: Physical sciences

description: We present an experimental realization of dynamic self-trapping and non-exponential tunneling in a multi-state system consisting of ultracold sodium spinor gases confined in moving optical lattices. Taking advantage of the fact that the tunneling process in the sodium spinor system is resolvable over a broader dynamic energy scale than previously observed in rubidium scalar gases, we demonstrate that the tunneling dynamics in the multi-state system strongly depends on an interaction induced nonlinearity and is influenced by the spin degree of freedom under certain conditions. We develop a rigorous multi-state tunneling model to describe the observed dynamics. Combined with our recent observation of spatially-manipulated spin dynamics, these results open up prospects for alternative multi-state ramps and state transfer protocols.
Estradiol is Pro-Nociceptive and Associated with a Small-Fiber Neuropathy Among Premenopausal Women with Sickle Cell Disease
Creators: name: Ramsay, Zachary
name: Sharma, Deva
name: Wisdom-Phipps, Margaret
name: Chin, Nicki
name: Campbell, Leroy
name: Knight-Madden, Jennifer
name: Asnani, Monika
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Physiology
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences

description: Vaso-occlusive crisis (VOC) pain episodes often occur with menses and concurrent hormonal contraceptive use may reduce their frequency. This study tested the hypothesis that among women with sickle cell disease (SCD), sex hormones are associated with pain detection thresholds. Women with SCD aged minimum 18 years with regular menses, and without acute illnesses, pregnancy, oophorectomy, or hormonal contraceptive use within three months prior were included. Pain detection thresholds for heat (HPT) and pressure (PPT), and serum estradiol, progesterone and testosterone were measured at follicular and luteal phases. The Adult Sickle Cell Quality-of-Life Measurement Information System assessed quality-of-life and VOC frequency and severity scores. Generalized linear mixed models were performed, including the day of the cycle standardized by cycle length. Among 125 participants, neither the day nor phase of the menstrual cycle was associated with PPT or HPT. In multivariate analyses, worse VOC scores (β = 1.7) and severe genotype (β = −46.0) were associated with higher and lower trapezius PPT, respectively. Older age was associated with lower forearm HPT (β = −0.1). Among leg measurements, ovulatory cycles (β = −1.1) and hydroxyurea use (β = −1.2) were associated with lower HPT, while worse VOC scores (β = 0.1) were associated with higher HPT. Higher estradiol was associated with lower HPT at the leg (β = −0.02), with an interaction with the cycle day (β = 0.001) predicting lower thresholds earlier in the cycle for the same estradiol level. Estradiol is associated with a time-varying, length-dependent small-fiber neuropathy among SCD women; and may be a potential therapeutic target and biomarker for SCD pain.
Probabilistic Risk Assessment of an Obstacle Detection System for GoA 4 Freight Trains
Creators: name: Gleirscher, Mario
name: Haxthausen, Anne E.
name: Peleska, Jan
Publisher: name: arXiv
Year: 2023
Subjects: subject: Systems and Control (eess.SY)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: In this paper, a quantitative risk assessment approach is discussed for the design of an obstacle detection function for low-speed freight trains with grade of automation (GoA)~4. In this 5-step approach, starting with single detection channels and ending with a three-out-of-three (3oo3) model constructed of three independent dual-channel modules and a voter, a probabilistic assessment is exemplified, using a combination of statistical methods and parametric stochastic model checking. It is illustrated that, under certain not unreasonable assumptions, the resulting hazard rate becomes acceptable for specific application settings. The statistical approach for assessing the residual risk of misclassifications in convolutional neural networks and conventional image processing software suggests that high confidence can be placed into the safety-critical obstacle detection function, even though its implementation involves realistic machine learning uncertainties.
title: Panel Arbeitsmarkt und Soziale Sicherung PASS-Erhebungswelle 14 - 2020 (Haupterhebung)
Creators: name: Jesske, Birgit
name: Schulz, Sabine Berufsforschung
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2021

description: Bereits in Erhebungswelle 10 hat PASS auf die Herausforderung reagiert, dass sich die Zusammensetzung der Zielgruppe der SGB-II-Empfänger verändert hat. Ausgelöst durch die verstärkte Flüchtlingszuwanderung seit 2014 in Deutschland finden sich unter den Leistungsempfängern größere Anteile aus arabischsprachigen Herkunftsländern, die über die nächsten Jahre im PASS befragt werden sollen. Dafür wurden in Welle 10 neben dem Einsatz eines arabischen Erhebungsinstruments verschiedene Maßnahmen zur Kontaktierung und Interviewführung getroffen und weiterentwickelt, die in den Folgewellen erneut zum Einsatz kamen. Während in Welle 10 ein Oversampling für Neuzugänge ins SGB II mit syrischer und irakischer Nationalität erfolgte, sind syrische/irakische Haushalte seit Welle 11 in den Auffrischungsstichproben auch ohne diese Maßnahme ausreichend vertreten. Die Erfahrungen aus den Vorwellen haben gezeigt, dass sich Kontaktierung und Interviewführung, aber auch Bearbeitungsergebnisse in dieser Gruppe noch deutlich von der üblichen SGB-II-Stichprobe unterscheiden. Vor diesem Hintergrund werden im Methodenbericht Ergebnisse nach Stichprobengruppen getrennt ausgewiesen, so dass syrische/irakische Haushalte sowohl im Panel als auch für die Auffrischungsstichprobe immer eine eigene Gruppe innerhalb der SGB-II-Stichproben bilden.