cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Strain of knockout rats SHR/Ola with deletion of Bdnf (brain derived neurotrophic factor) gene.
Creators: name: Mlejnek, Petr
name: Silhavy, Jan
name: Pravenec, Michal
Publisher: name: Zenodo
Year: 2024

description: Functional prototype

Supported by the project National Institute for Research of Metabolic and Cardiovascular Diseases (Programme EXCELES, ID Project No. LX22NPO5104) - Funded by the European Union – Next Generation EU.
_online_supp_-_Heft_et_al_Transnat_Right_News_Ecologies_Supplementary_information_file – Supplemental material for Toward a Transnational Information Ecology on the Right? Hyperlink Networking among Right-Wing Digital News Sites in Europe and the United States
Creators: name: Heft, Annett
name: Knüpfer, Curd
name: Reinhardt, Susanne
name: Mayerhöffer, Eva
Publisher: name: SAGE Journals
Year: 2020
Subjects: subject: 200199 Communication and Media Studies not elsewhere classified
subject: FOS: Media and communications
subject: 160607 International Relations
subject: FOS: Political science

description: Supplemental material, _online_supp_-_Heft_et_al_Transnat_Right_News_Ecologies_Supplementary_information_file for Toward a Transnational Information Ecology on the Right? Hyperlink Networking among Right-Wing Digital News Sites in Europe and the United States by Annett Heft, Curd Knüpfer, Susanne Reinhardt and Eva Mayerhöffer in The International Journal of Press/Politics
Spatial Patterns of Delivery Hospitalizations with Opioid Use Disorder in Pennsylvania
Creators: name: Frankeberger, Jessica
name: Jarlenski, Marian
name: Krans, Elizabeth E.
name: Coulter, Robert W. S.
name: Mair, Christina
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Space Science
subject: Medicine
subject: Cell Biology
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified
subject: Science Policy

description: Opioid use disorder (OUD) in pregnancy has substantially increased throughout the drug overdose crisis, but little is known about how local community environments are associated with OUD in pregnancy. This study investigates spatial patterns and residential ZIP code-level factors associated with delivery hospitalizations with OUD in Pennsylvania and compares these patterns to those for all delivery hospitalizations and all OUD-related hospitalizations. ZIP code-level inpatient hospitalizations based on patients’ residential ZIP codes in Pennsylvania were examined from 2016 to 2019. Using Bayesian hierarchical space-time conditional autoregressive models, we assessed the contributions of residential ZIP code-level factors to OUD delivery hospitalizations and compared these associations to those from models of all delivery hospitalizations and all OUD-related hospitalizations. Significant spatial autocorrelation was identified for all three types of hospitalizations. Higher unemployment, greater population density, higher overall hospitalization rate, and presence of an OUD treatment facility were associated with greater OUD delivery hospitalizations in residential ZIP codes, while higher median household income and a greater proportion of the population who were non-Hispanic Black and Hispanic were associated with lower OUD delivery hospitalizations. Findings were similar to those for all OUD-related hospitalizations. The effect of ZIP code-level unemployment rate differed between all delivery hospitalizations and those with OUD, with a positive association with OUD deliveries and a negative association with all deliveries. Areas with worse economic conditions and greater population density are associated with OUD at delivery, similar to all OUD-related hospitalizations. Community OUD programs may consider simultaneously targeting OUD concerns in pregnancy.
Additional file 1 of Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy
Creators: name: Cubillos, Gabriel
name: Monckeberg, Max
name: Plaza, Alejandra
name: Morgan, Maria
name: Estevez, Pablo A.
name: Choolani, Mahesh
name: Kemp, Matthew W.
name: Illanes, Sebastian E.
name: Perez, Claudio A.
Publisher: name: figshare
Year: 2024
Subjects: Cell Biology
Biotechnology
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
Mathematical Sciences not elsewhere classified

description: Additional file 1: Table S1. The Mean AUCROC bracketed values are at the 95% confidence interval, and standard deviation (STD) of the different models presented in Tables 5 and 6. STD uses four decimals.
Dynamics of large oscillator populations with random interactions
Creators: name: Pikovsky, Arkady
name: Smirnov, Lev A.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Adaptation and Self-Organizing Systems (nlin.AO)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: FOS: Physical sciences

description: We explore large populations of phase oscillators interacting via random coupling functions. Two types of coupling terms, the Kuramoto-Daido coupling and the Winfree coupling, are considered. Under the assumption of statistical independence of the phases and the couplings, we derive reduced averaged equations with effective non-random coupling terms. As a particular example, we study interactions that have the same shape but possess random coupling strengths and random phase shifts. While randomness in coupling strengths just renormalizes the interaction, a distribution of the phase shifts in coupling reshapes the coupling function.
sj-pdf-1-pul-10.1177_2045894020954158 - Supplemental material for Comparative effectiveness of endothelin receptor antagonists on mortality in patients with pulmonary arterial hypertension in a US Medicare population: a retrospective database analysis
Creators: name: Benza, Raymond L.
name: Lickert, Cassandra A.
name: Xie, Lin
name: Drake, William
name: Ogbomo, Adesuwa
name: Yuce, Huseyin
name: Cole, Michele R.
Publisher: name: SAGE Journals
Year: 2020
Subjects: Cardiology
Respiratory Diseases

description: Supplemental material, sj-pdf-1-pul-10.1177_2045894020954158 for Comparative effectiveness of endothelin receptor antagonists on mortality in patients with pulmonary arterial hypertension in a US Medicare population: a retrospective database analysis by Raymond L. Benza, Cassandra A. Lickert, Lin Xie, William Drake Adesuwa Ogbomo, Huseyin Yuce and Michele R. Cole in Pulmonary Circulation
Yoga_breast_ca_syst_rev_ICT_suppl_methods – Supplemental material for The Effect of Yoga Interventions on Cancer-Related Fatigue and Quality of Life for Women with Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Creators: name: O’Neill, Meagan
name: Samaroo, Dominic
name: Lopez, Christian
name: Tomlinson, George
name: Mina, Daniel Santa
name: Sabiston, Catherine
name: Culos-Reed, Nicole
name: Alibhai, Shabbir M. H.
Publisher: name: SAGE Journals
Year: 2020
Subjects: subject: 111708 Health and Community Services
subject: FOS: Health sciences
subject: 110306 Endocrinology
subject: FOS: Clinical medicine
subject: 111299 Oncology and Carcinogenesis not elsewhere classified
subject: 111702 Aged Health Care

description: Supplemental material, Yoga_breast_ca_syst_rev_ICT_suppl_methods for The Effect of Yoga Interventions on Cancer-Related Fatigue and Quality of Life for Women with Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials by Meagan O’Neill, Dominic Samaroo, Christian Lopez, George Tomlinson, Daniel Santa Mina, Catherine Sabiston, Nicole Culos-Reed and Shabbir M. H. Alibhai in Integrative Cancer Therapies
Is Complexity an Illusion?
Creators: name: Bennett, Michael Timothy
Publisher: name: arXiv
Year: 2024
Subjects: subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Simplicity is held by many to be the key to general intelligence. Simpler models tend to "generalise", identifying the cause or generator of data with greater sample efficiency. The implications of the correlation between simplicity and generalisation extend far beyond computer science, addressing questions of physics and even biology. Yet simplicity is a property of form, while generalisation is of function. In interactive settings, any correlation between the two depends on interpretation. In theory there could be no correlation and yet in practice, there is. Previous theoretical work showed generalisation to be a consequence of "weak" constraints implied by function, not form. Experiments demonstrated choosing weak constraints over simple forms yielded a 110-500% improvement in generalisation rate. Here we show that all constraints can take equally simple forms, regardless of weakness. However if forms are spatially extended, then function is represented using a finite subset of forms. If function is represented using a finite subset of forms, then we can force a correlation between simplicity and generalisation by making weak constraints take simple forms. If function is determined by a goal directed process that favours versatility (e.g. natural selection), then efficiency demands weak constraints take simple forms. Complexity has no causal influence on generalisation, but appears to due to confounding.
description: Accepted for publication in the Proceedings of the 17th Conference on Artificial General Intelligence, 2024. Definitions shared with arXiv:2302.00843
Transparency Materials for MIS Quarterly "Breached and Denied: The Cost of Data Breaches on Individuals as Mortgage Application Denials"
Creators: name: Min-Seok Pang
Publisher: name: OSF Registries
Year: 2024
Subjects: subject: Business
subject: Management Information Systems

description: Transparency Materials for MIS Quarterly "Breached and Denied: The Cost of Data Breaches on Individuals as Mortgage Application Denials"
Opportunistic Sensor-Based Authentication Factors in and for the Internet of Things
Creators: name: Saideh, Marc
name: Jamont, Jean-Paul
name: Vercouter, Laurent
Publisher: name: arXiv
Year: 2024
Subjects: subject: Cryptography and Security (cs.CR)
subject: FOS: Computer and information sciences

description: Communication between connected objects in the Internet of Things (IoT) often requires secure and reliable authentication mechanisms to verify identities of entities and prevent unauthorized access to sensitive data and resources. Unlike other domains, IoT offers several advantages and opportunities, such as the ability to collect real-time data through numerous sensors. These data contains valuable information about the environment and other objects that, if used, can significantly enhance authentication processes. In this paper, we propose a novel idea to building opportunistic sensor-based authentication factors by leveraging existing IoT sensors in a system of systems approach. The objective is to highlight the promising prospects of opportunistic authentication factors in enhancing IoT security. We claim that sensors can be utilized to create additional authentication factors, thereby reinforcing existing object-to-object authentication mechanisms. By integrating these opportunistic sensor-based authentication factors into multi-factor authentication schemes, IoT security can be substantially improved. We demonstrate the feasibility and effectivenness of our idea through illustrative experiments in a parking entry scenario, involving both mobile robots and cars, achieving high identification accuracy. We highlight the potential of this novel method to improve IoT security and suggest future research directions for formalizing and comparing our approach with existing techniques.
New Synthetic Routes to Next-Generation Organic P-Type Dopants for Improved Stretchable Transistors
Creators: name: Das, Arnob
Publisher: name: Stanford Digital Repository
Year: 2025
Subjects: subject: Organic FETs (Transistors)
subject: Stretchable semiconductors
subject: Organic dopants
subject: Small molecule synthesis

description: Intrinsically stretchable electronics have significant promise in revolutionizing bioelectronic health
interfaces and wearable consumer electronics due to viscoelastic matching with biological tissue. Despite the development of highly scalable process flows for the production of intrinsically stretchable
electronics that yield devices with high transistor density, the operating gate voltages reside between
∼30-60 V, well outside consumer/commercially applicable regimes of ∼1-5 V. Previously, thiol-ene
crosslinking chemistry was shown to initiate favorable dielectric behavior in stretchable semiconductors and reduce gate voltage to commercially applicable regimes, but currently thiol-ene chemistry is
not compatible with the azide-mediated crosslinking employed for the stretchable dielectric in highly
scalable process flows for intrinsically stretchable electronics. The design of a new p-type dopant
for stretchable diketopyrrolepyrrole (DPP) semiconductors that also incorporates thiol-ene reactive
moieties, would thus be compatible with azide-mediated processing and enable high transistor density and scalability for the next-generation improvements in stretchable transistors. Therefore, this
thesis proposes four new synthetic routes for new organic p-type dopants, generates a novel contribution to the literature - oxidized allyl-F4TCNQ - that incorporates thiol-ene reactive moieties, and
successfully dopes a DPP-type material (DPP-SVS) by an increase in output current of a DPP-type
polymer by ∼3 orders of magnitude. Synthetic considerations and insights gained from the novel
production of oxidized allyl-F4TCNQ in this thesis thus function as an important starting material to propose improved synthetic routes for next-generation organic p-type dopants in stretchable transistors.
Additional file 1 of Comparison of guideline concordant antibiotic prophylaxis in Veterans Affairs and non-Veterans Affairs dental settings among those with cardiac conditions or prosthetic joints
Creators: name: Ramanathan, Swetha
name: Evans, Charlesnika T.
name: Hershow, Ronald C.
name: Calip, Gregory S.
name: Rowan, Susan
name: Hubbard, Colin
name: Suda, Katie J.
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Neuroscience
subject: Physiology
subject: FOS: Biological sciences
subject: Pharmacology
subject: Biotechnology
subject: Biological Sciences not elsewhere classified
subject: Cancer

description: Additional file 1: Supplemental Table 1. Distribution of characteristics by dental setting.
Supplementary_file – Supplemental material for A randomized controlled trial of cognitive behavioral therapy compared with diabetes education for diabetic peripheral neuropathic pain
Creators: name: Higgins, Diana M
name: Heapy, Alicia A
name: Buta, Eugenia
name: LaChappelle, Kathryn M
name: Serowik, Kristin L
name: Czlapinski, Rebecca
name: Kerns, Robert D
Publisher: name: SAGE Journals
Year: 2020
Subjects: subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology
subject: 110319 Psychiatry (incl. Psychotherapy)
subject: FOS: Clinical medicine
subject: 111799 Public Health and Health Services not elsewhere classified
subject: FOS: Health sciences

description: Supplemental material, Supplementary_file for A randomized controlled trial of cognitive behavioral therapy compared with diabetes education for diabetic peripheral neuropathic pain by Diana M Higgins, Alicia A Heapy, Eugenia Buta, Kathryn M LaChappelle, Kristin L Serowik, Rebecca Czlapinski and Robert D Kerns in Journal of Health Psychology
Data Collection of Real-Life Knowledge Work in Context: The RLKWiC Dataset
Creators: name: Bakhshizadeh, Mahta
name: Jilek, Christian
name: Schröder, Markus
name: Maus, Heiko
name: Dengel, Andreas
Publisher: name: arXiv
Year: 2024
Subjects: subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Over the years, various approaches have been employed to enhance the productivity of knowledge workers, from addressing psychological well-being to the development of personal knowledge assistants. A significant challenge in this research area has been the absence of a comprehensive, publicly accessible dataset that mirrors real-world knowledge work. Although a handful of datasets exist, many are restricted in access or lack vital information dimensions, complicating meaningful comparison and benchmarking in the domain. This paper presents RLKWiC, a novel dataset of Real-Life Knowledge Work in Context, derived from monitoring the computer interactions of eight participants over a span of two months. As the first publicly available dataset offering a wealth of essential information dimensions (such as explicated contexts, textual contents, and semantics), RLKWiC seeks to address the research gap in the personal information management domain, providing valuable insights for modeling user behavior.
description: Accepted and presented at the 10th International Conference on Information Management (ICIM2024), will be published in Springer CCIS series Conference Proceedings (Electronic ISSN: 1865-0937; Print ISSN: 1865-0929)
Variations of supersymmetric quantum mechanics and superconformal indices
Creators: name: Spiridonov, Vyacheslav P.
Publisher: name: arXiv
Year: 2024
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: Old studies on supersymmetric quantum mechanics and its deformations, that were initiated by the 1988 joint paper with V. Rubakov, are retrospectively discussed. In the modern circumstances, corresponding results can be related to computations of superconformal indices and associated special functions.
description: 12 pages, 1 figure, Contribution to the Proceedings of the V.A. Rubakov memorial conference, October 02-07, 2023, Yerevan, Armenia
Konstruktivismus In Der Führung: Die Innere Haltung Als Zentraler Aspekt In Der Arbeit Einer Führungsperson
Creators: name: Meier, Prisca
Publisher: name: Zenodo
Year: 2012

description: Keine Beschreibung.
description: + Code Diss LU: hslusa mas lko + Fussnote: Master-Arbeit MAS of Advanced Studies in Lösungs- und Kompetenzorientierung, Hochschule Luzern, 2012
Supplemental_Material - How Are We Testing Interactions in Latent Variable Models? Surging Forward or Fighting Shy?
Creators: name: Cortina, Jose M.
name: Markell-Goldstein, Hannah M.
name: Green, Jennifer P.
name: Chang, Yingyi
Publisher: name: SAGE Journals
Year: 2021
Subjects: subject: 150310 Organisation and Management Theory
subject: FOS: Economics and business
subject: 160807 Sociological Methodology and Research Methods
subject: FOS: Sociology

description: Supplemental_Material for How Are We Testing Interactions in Latent Variable Models? Surging Forward or Fighting Shy? by Jose M. Cortina, Hannah M. Markell-Goldstein, Jennifer P. Green and Yingyi Chang in Organizational Research Methods
Microwave dependent quantum transport characteristics in GaN/AlGaN FETs
Creators: name: Shinozaki, Motoya
name: Abe, Takaya
name: Matsumura, Kazuma
name: Aizawa, Takumi
name: Kumasaka, Takashi
name: Otsuka, Tomohiro
Publisher: name: arXiv
Year: 2024
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: Defects in semiconductors, traditionally seen as detrimental to electronic device performance, have emerged as potential assets in quantum technologies due to their unique quantum properties. This study investigates the interaction between defects and quantum electron transport in GaN/AlGaN field-effect transistors, highlighting the observation of Fano resonances at low temperatures. We observe the resonance spectra and their dependence on gate voltage and magnetic fields. To explain the observed behavior, we construct the possible scenario as a Fano interferometer with finite width. Our findings reveal the potential of semiconductor defects to contribute to the development of quantum information processing, providing their role to key components in next-generation quantum devices.
description: 14 pages, 6 figures
title: LPP – Linked Personnel Panel 1221: Arbeitsqualität und wirtschaftlicher Erfolg
Creators: name: Ruf, Kevin
name: Mackeben, Jan
name: Wolter, Stefanie
name: Grunau, Philipp
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2022
Subjects: subject: Linked-Employer-Employee-Datensatz
subject: Datendokumentation
subject: Arbeitsqualität
subject: Personalarbeit
subject: Unternehmenskultur
subject: Betriebsbefragung
subject: Beschäftigtenbefragung

description: Dieser Datenreport beschreibt die fünfte Welle des Linked Personnel Panels (LPP 1221). Das LPP – ein Linked-Employer-Employee Datensatz – entsteht im Projekt 'Arbeitsqualität und wirtschaftlicher Erfolg' und erfasst Informationen zu Themen wie Personalarbeit, Unternehmenskultur und Managementinstrumenten bei in Deutschland ansässigen Betrieben. Die bisherigen Befragungswellen enthalten Informationen von 1.219 Betrieben und 7.508 Beschäftigten (Welle 1), 771 Betrieben und 7.282 Beschäftigten (Welle 2), 846 Betrieben und 6.779 Beschäftigten (Welle 3),769 Betrieben und 6.494 Beschäftigten (Welle 4), sowie 770 Betriebe und 7.397 Beschäftigte (Welle 5). Auf der Betriebsebene ist das LPP repräsentativ für privatwirtschaftliche Betriebe in Deutschland mit mindestens 50 sozialversicherungspflichtigen Beschäftigten. Durch die Verknüpfung mit dem IAB-Betriebspanel entsteht ein Datenprodukt, das Längsschnittanalysen zu Personalstrategie und Arbeitsqualität in Deutschland ermöglicht.
description: FDZ-Datenreport
Additional file 1 of Association study between drug prescriptions and Alzheimer’s disease claims in a commercial insurance database
Creators: name: Hu, Eric
name: Li, Tong Shu
name: Wineinger, Nathan E.
name: Su, Andrew I.
Publisher: name: figshare
Year: 2024
Subjects: Medicine
Pharmacology
Biotechnology
Cancer
Science Policy
Mental Health

description: Additional file 1: Supplementary Methods. Figure S1. Diagram representation of the sorting process based on coverage history. Figure S2. A pictorial representation of the propensity matching process. Figure S3. Selection of segmented portions from non-users based on coverage during the claim count analysis.
A need for better data sharing policies: a review of data sharing policies in biomedical journals
Creators: name: Vasilevsky, Nicole
name: Minnier, Jessica
name: Haendel, Melissa
name: Champieux, Robin
Publisher: name: F1000Research
Year: 2017

description: There is agreement in the biomedical research community that data sharing is key to making science more transparent, reproducible, and reusable. Publishers could play an important role in facilitating data sharing; however, many journals have not yet implemented data sharing policies and the requirements vary across journals. To assess the pervasiveness and quality of data sharing policies, we curated the author instructions of 318 biomedical journals. The policies were reviewed and coded according to a rubric. We determined if if data sharing was required, recommended, or not addressed at all. The data sharing method and licensing recommendations were examined, as well any mention of reproducibility. The data was analyzed for patterns relating to publishing volume, Journal Impact Factor, and publishing models (Open Access or subscription). 11.9% of the journals stated that data sharing was required as a condition of publication; 9.1% of the journals required data sharing, but did not make clear it would affect publication decisions; 23.3% of the journals only encouraged authors to share data; 9.1% of journals mentioned data sharing indirectly; and 14.8% only addressed protein, proteomic and/or genomic data sharing. There was no mention of data sharing in 31.8% of the journals. Impact factors were significantly higher for journals with the strongest data sharing policies compared to all other data sharing mark categories. Open access journals were not more likely to require data sharing. Our study showed only a minority of biomedical journals require data sharing, and a significant association between higher Impact Factors and journals with a data sharing requirement. We found that most data sharing policies did not provide specific guidance on the practices that ensure data is maximally available and reusable. As a continuation of this work, we plan to build a curated public database of journal data sharing policies, and convene a community of stakeholders to further work on recommendations for strengthening and communicating journal data sharing policies.
Chiral-vacuum excited replicae in QCD modeling
Creators: name: Garnacho-Velasco, Eduardo
name: Bicudo, Pedro J. de A.
name: Ribeiro, J. Emilio F. T.
name: Llanes-Estrada, Felipe J.
name: Molina, Lucas Pérez
name: Herreros, Victor Serrano
name: Fernández, Jorge Vallejo
Publisher: name: arXiv
Year: 2024
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Lattice (hep-lat)
subject: FOS: Physical sciences

description: We present a detailed study of the Bardeen-Cooper-Schrieffer (BCS) gap equation ``replicae'' or excited vacuum states, orthogonal to the ground-state one, in the chiral-quark sector of the Hamiltonian Coulomb-gauge model of chromodynamics. Analyzing the number of negative eigenmodes of the energy density's Hessian we believe that we have identified all of the (negative energy-density) vacua of this nonlinear system, namely the ground BCS state and two (or one) replicae for slightly massive (or massless) quarks, given the interaction strength typical of the strong interactions. The meson spectrum over each of the replicae looks similar, so the differences are not significant enough given model uncertainties, but matrix elements are more sensitive and allow to distinguish them. We propose to look for such excited vacua in lattice gauge theory by trying to identify excitations with scalar quantum numbers which have energies proportional to the lattice volume (unlike conventional mesons for which the mass stabilizes to a constant upon taking the infinite volume limit).
description: 10 pages, 26 plots
Chat2Scenario: Scenario Extraction From Dataset Through Utilization of Large Language Model
Creators: name: Zhao, Yongqi
name: Xiao, Wenbo
name: Mihalj, Tomislav
name: Hu, Jia
name: Eichberger, Arno
Publisher: name: arXiv
Year: 2024
Subjects: subject: Robotics (cs.RO)
subject: FOS: Computer and information sciences

description: The advent of Large Language Models (LLM) provides new insights to validate Automated Driving Systems (ADS). In the herein-introduced work, a novel approach to extracting scenarios from naturalistic driving datasets is presented. A framework called Chat2Scenario is proposed leveraging the advanced Natural Language Processing (NLP) capabilities of LLM to understand and identify different driving scenarios. By inputting descriptive texts of driving conditions and specifying the criticality metric thresholds, the framework efficiently searches for desired scenarios and converts them into ASAM OpenSCENARIO and IPG CarMaker text files. This methodology streamlines the scenario extraction process and enhances efficiency. Simulations are executed to validate the efficiency of the approach. The framework is presented based on a user-friendly web app and is accessible via the following link: https://github.com/ftgTUGraz/Chat2Scenario.
description: IEEE Intelligent Vehicles Symposium (IV 2024)
Additional file 2 of Association study between drug prescriptions and Alzheimer’s disease claims in a commercial insurance database
Creators: name: Hu, Eric
name: Li, Tong Shu
name: Wineinger, Nathan E.
name: Su, Andrew I.
Publisher: name: figshare
Year: 2024
Subjects: Medicine
Pharmacology
Biotechnology
Cancer
Science Policy
Mental Health

description: Additional file 2: Supplementary Results. Figure 1. Log 10 Hazard Ratio Distribution Graph from the survival analysis of partial coverage individuals. Supplementary Results Figure 2. Log 10 Hazard Ratio Cumulative Graph from the survival analysis of partial coverage individuals. Supplementary Results Figure 3. QQ plot for raw P values from the survival analysis of partial coverage individuals.
Training future biocurators through data science trainings and open educational resources
Creators: name: Vasilevsky, Nicole
name: Laderas, Ted
name: Wirz, Jackie
name: Pederson, Bjorn
name: Dorr, David A.
name: Hersh, William
name: McWeeney, Shannon
name: Haendel, Melissa
Publisher: name: F1000Research
Year: 2017

description: With the exponentially increasing volume and complexity of biomedical data, and conversely, our increasing ability to use the data, or misuse it; the need to train researchers in biocuration is key. As part of the National Institute of Health Big Data to Knowledge (BD2K) initiative, a research team at Oregon Health & Science University is developing a set of Skills Courses and Open Educational Resources (OERs) that includes training researchers to make data structured, discoverable and reusable. At OHSU, basic science and medical students are not formally trained in data management or biocuration, so these optional trainings are valuable for students to learn these important skills. To date, we have offered five in-person skills courses; the initial skills course functioned as a testing ground for creating the OERs. One skills course course titled ‘Data After Dark’ course was offered over two evenings (for a total of 8 hours) and was sponsored by a micro-grant from the Biocuration Society. The Skills Courses are offered to learners at different levels, with some courses targeted towards beginner/novice students and focused on basic research data management and biocuration, and other courses were targeted towards more advanced students that focused on interactive visualization, scripting and analysis skills. In addition to offering the in-person Skills Courses, we created 20 OER modules that are available online for use by both learners and educators. The materials include slide decks, video tutorials, exercises, and recommended readings. Some of the modules especially relevant to biocuration are Data Annotation and Curation (BDK12), Ontologies 101 (BDK14), Team Science (BDK07), Basic Research Data Standards (BDK05), and Guidelines for Reporting, Publications, And Data Sharing (BDK22). The OERs and Skills Course materials are intended to be flexible and customizable and we encourage others to use or repurpose these materials for training, workshops, and professional development or for dissemination to instructors in various fields. The OERs and other materials are available here: www.dmice.ohsu.edu/bd2k; we welcome comments, requests, and contributions.
Deep Learning Based Solar Radiation Prediction Models for the Pacific Northwest
Creators: name: Guha Neogi, Pinaki Prasad
Publisher: name: Washington State University
Year: 2025

description: Over the past few decades, as a consequence of the depleting fossil fuels and increasing environmental pollution, renewable energy resources have acquired remarkable attention. Though renewable energy resources are available in various forms, solar energy undoubtedly tops the list in terms of convenience, reliability, and recently, affordability. As of 2023, the Guardian, a world news publication, reports that it is now cheaper in 99% of the United States to build new solar or wind generation capability than to continue to run existing coal-fired power plants. However, whereas the US has the domestic capability to produce significant amounts of coal and natural gas, and thus provide generation capacity that meets consumer demand, solar and wind generation capacity is subject to ever-changing weather patterns. Thus, introducing these renewable resources adds the complexity of determining for any given period of time, how much generation capacity is available, and whether that capacity will meet demand so that additional generation resources (coal, natural gas, hydro-energy) can be brought online. In our work, we have developed a number of deep-learning models to predict solar generation capacity in the near future term, so that appropriate actions can be taken well ahead of time to balance this power generation and use in real time. These models are targeted to the Pacific Northwest region of the United States of America, where the availability of sunlight is relatively unpredictable due to year-round rainfall and frequent wildfires. The proposed models, especially the seasonal and the monthly model, show a significant improvement in short-term solar radiation forecasting over other related works, and existing standard machine learning and recurrent neural network models, thus proving their efficacy.
Telehealth Disparities in Outpatient Substance Use Disorder (SUD) Treatment among Medicaid Beneficiaries during COVID-19
Creators: name: Choi, Sugy
name: Hussain, Shazia
name: Wang, Yichuan
name: D’Aunno, Thomas
name: Mijanovich, Tod
name: Neighbors, Charles J.
Publisher: name: Taylor & Francis
Year: 2025
Subjects: Medicine
Biotechnology
Science Policy
Mental Health
Hematology

description: We investigated racial and ethnic disparities in telehealth counseling among Medicaid-insured patients in outpatient substance use disorder (SUD) treatment clinics and assessed whether the clinic-level proportion of Medicaid-insured patients moderated these disparities. Using New York State (NYS) Medicaid and statewide treatment registry data, we analyzed 24,814 admission episodes across 399 outpatient SUD clinics during the first 6 months of COVID-19 (April–September 2020). Our outcome measure was the number of tele-counseling sessions within the first 90 days of treatment. Key independent variables included beneficiary race/ethnicity and the clinic-level proportion of Medicaid-insured patients, divided into four quartiles: lowest, second, third, and highest. Mixed effects negative binomial models assessed the associations between race/ethnicity, Medicaid proportions, and telehealth use, with interaction terms evaluating the moderating role of Medicaid proportions. Black and Latinx patients received fewer telehealth sessions than non-Latinx White patients, with adjusted incidence rate ratios (aIRRs) of 0.86 (95% CI: 0.82, 0.91) for Black patients and 0.93 (95% CI: 0.88, 0.98) for Latinx patients. Black patients at clinics with the highest Medicaid proportions had higher telehealth usage rates compared to those at clinics with the lowest Medicaid proportions (aIRR, 1.20; 95% CI, 1.03–1.41). Patients in clinics with the highest Medicaid proportions were more likely to use individual telehealth counseling (aIRR, 1.02–1.88; 95% CI, 1.01–3.04). Significant racial disparities in telehealth use exist, with variations persisting across clinics with different Medicaid proportions. Targeted interventions are needed to address these access gaps.
title: LPP – Linked Personnel Panel 1221: Quality of work and economic success
Creators: name: Ruf, Kevin
name: Mackeben, Jan
name: Wolter, Stefanie
name: Grunau, Philipp
Publisher: name: Forschungsdatenzentrum der Bundesagentur für Arbeit (BA) im Institut für Arbeitsmarkt- und Berufsforschung (IAB)
Year: 2022
Subjects: subject: Linked employer/employee data
subject: data documentation
subject: quality of work
subject: HR work
subject: corporate culture
subject: establishment survey
subject: employee survey

description: This data report describes the fifth wave of the Linked Personnel Panel (LPP 1221). The LPP is a linked-employer-employee data set on human resources (HR) work, corporate culture and management instruments in German establishments that evolved within the framework of the project ‘Quality of work and economic success’. The survey waves contain information from 1,219 establishments, 7,508 employees (wave 1), 771 establishments and 7,282 employees (wave 2), 846 establishments and 6,779 employees (wave 3), 769 establishments and 6,494 employees (wave 4) and 770 establishments and 7,397 employees (wave 5) The LPP is representative for German private sector establishments with at least 50 employees subject to social security. The linkage with the IAB Establishment Panel yields a data product that enables longitudinal analyses regarding HR strategies and quality of work in Germany.
description: FDZ-Datenreport
Detectability of axisymmetric magnetic fields from the core to the surface of oscillating post-main sequence stars
Creators: name: Bhattacharya, Shatanik
name: Das, Srijan Bharati
name: Bugnet, Lisa
name: Panda, Subrata
name: Hanasoge, Shravan M.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: Magnetic fields in the stellar interiors are key candidates to explain observed core rotation rates inside solar-like stars along their evolution. Recently, asteroseismic estimates of radial magnetic field amplitudes near the hydrogen-burning shell (H-shell) inside about 24 red-giants (RGs) have been obtained by measuring frequency splittings from their power spectra. Using general Lorentz-stress (magnetic) kernels, we investigated the potential for detectability of near-surface magnetism in a 1.3 $M_{\odot}$ star of super-solar metallicity as it evolves from a mid sub-giant to a late sub-giant into an RG. Based on these sensitivity kernels, we decompose an RG into three zones - deep core, H-shell, and near-surface. The sub-giants instead required decomposition into an inner core, an outer core, and a near-surface layer. Additionally, we find that for a low-frequency g-dominated dipolar mode in the presence of a typical stable magnetic field, ~25% of the frequency shift comes from the H-shell and the remaining from deeper layers. The ratio of the subsurface tangential field to the radial field in H-burning shell decides if subsurface fields may be potentially detectable. For p-dominated dipole modes close to $ν_\rm{max}$, this ratio is around two orders of magnitude smaller in subgiant phases than the corresponding RG. Further, with the availability of magnetic kernels, we propose lower limits of field strengths in crucial layers in our stellar model during its evolutionary phases. The theoretical prescription outlined here provides the first formal way to devise inverse problems for stellar magnetism and can be seamlessly employed for slow rotators.
description: Accepted for publication in The Astrophysical Journal, 34 pages, 22 figures, 3 tables
Architecture of Rammed Earth: Implications of surface geometry on design variability for contemporary formations of thermally performative rammed earth wall panels
Creators: name: Gupta, Pragya
Publisher: name: Carnegie Mellon University
Year: 2023
Subjects: Built Environment and Design not elsewhere classified

description: Buildings contribute to approximately a third of the world’s greenhouse gas emissions. The residential sector contributes to 13% of the world’s total delivered energy.(United Nations Environment Programme, 2009) With such a high impact on global energy consumption and greenhouse gas emissions, it is imperative that we find solutions that would minimize the carbon footprint of new construction over the entire lifecycle of the building – construction, operation and demolition. 
Rammed earth construction is an environmentally benign alternative to current construction materials. It utilizes locally sourced materials, requires minimal processing, and is a healthy, non-toxic material providing greater indoor air quality. The use of Rammed Earth as a thermal storage device has the potential to reduce the energy associated with heating and cooling a building while reconnecting with vernacular practices of architecture.
This study explores the effectiveness of rammed earth as wall panels in hot and arid climates. It aims at identifying digital tools and processes to introduce greater design variability in Rammed Earth.
Cycling into the workshop: predictive maintenance for Barcelona's bike-sharing system
Creators: name: Grau-Escolano, Jordi
name: Bassolas, Aleix
name: Vicens, Julian
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computers and Society (cs.CY)
subject: Machine Learning (cs.LG)
subject: Physics and Society (physics.soc-ph)
subject: FOS: Computer and information sciences
subject: FOS: Physical sciences

description: Bike-sharing systems have emerged as a significant element of urban mobility, providing an environmentally friendly transportation alternative. With the increasing integration of electric bikes alongside mechanical bikes, it is crucial to illuminate distinct usage patterns and their impact on maintenance. Accordingly, this research aims to develop a comprehensive understanding of mobility dynamics, distinguishing between different mobility modes, and introducing a novel predictive maintenance system tailored for bikes. By utilising a combination of trip information and maintenance data from Barcelona's bike-sharing system, Bicing, this study conducts an extensive analysis of mobility patterns and their relationship to failures of bike components. To accurately predict maintenance needs for essential bike parts, this research delves into various mobility metrics and applies statistical and machine learning survival models, including deep learning models. Due to their complexity, and with the objective of bolstering confidence in the system's predictions, interpretability techniques explain the main predictors of maintenance needs. The analysis reveals marked differences in the usage patterns of mechanical bikes and electric bikes, with a growing user preference for the latter despite their extra costs. These differences in mobility were found to have a considerable impact on the maintenance needs within the bike-sharing system. Moreover, the predictive maintenance models proved effective in forecasting these maintenance needs, capable of operating across an entire bike fleet. Despite challenges such as approximated bike usage metrics and data imbalances, the study successfully showcases the feasibility of an accurate predictive maintenance system capable of improving operational costs, bike availability, and security.
description: 25 pages, 9 figures, 7 tables
Usability Testing of Five Fentanyl Test Strip Brands in Real-World Settings
Creators: name: Childerhose, Janet E.
name: Myers, John V.
name: Dzurec, Megan E.
name: Gault, Caroline
name: Lieberman, Marya
name: Stenger, Sarah G.
name: Munch, Fabienne
name: Niles, Kaleigh T.
name: Fernandez, Soledad A.
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Medicine
subject: Neuroscience
subject: Pharmacology
subject: Chemical Sciences not elsewhere classified
subject: Sociology
subject: FOS: Sociology
subject: Information Systems not elsewhere classified
subject: Mental Health

description: Fentanyl test strips (FTS) are a forensic tool designed for laboratory testing of urine samples. They have been adapted into a point-of-consumption drug-checking tool to detect illegally manufactured fentanyl in local drug supply. This creates unknown usability challenges for people who use drugs (PWUD). To assess ease of use in real-world settings, we conducted usability testing of five FTS brands. Six researchers independently completed a REDCap survey to evaluate usability of five FTS brands before and after testing a baking soda sample prepared in their homes. The survey first assessed ease of use of specific brand features, then usability of each brand as an interactive system with the System Usability Scale (SUS). DanceSafe scored highest on ease of use ratings and highest on the SUS (above the usability threshold of ≤68). Dosetest scored lowest on ease of use ratings and below the SUS usability threshold. Respondents identified usability challenges with all brands, including difficulty opening single-strip envelopes, complex instruction design, and instruction discrepancies. Design of all brands assumes users have required testing resources (e.g. water, measuring tools, an Internet connection, and a timer), yet no brand provides these. FTS are complex interactive systems not fully adapted for testing in real-world settings. The complexity of FTS may lead to testing error or limit their adoption by PWUD. We encourage manufacturers to design FTS directly for PWUD by considering resource limitations of real-world testing settings, human factors, and local supply complexity.
Recovery Capital Is Associated with a Greater Likelihood of NIAAA-Defined Recovery for Adults with Prior Alcohol Problems
Creators: name: LaBarre, Charles
name: Bowen, Elizabeth
name: Knapp, Kyler S.
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Medicine
subject: Cell Biology
subject: Neuroscience
subject: Ecology
subject: FOS: Biological sciences
subject: Sociology
subject: FOS: Sociology
subject: Science Policy
subject: Mental Health

description: Background: The National Institute on Alcohol Abuse and Alcoholism (NIAAA) finalized a definition of alcohol use disorder (AUD) recovery requiring (1) remission from DSM-5 AUD symptoms except craving and (2) cessation of heavy drinking. The literature suggests that recovery capital, which encapsulates the resources that influence substance use recovery, is an important determinant of AUD recovery outcomes. However, little research has examined potential relationships between recovery capital and the NIAAA recovery definition. Objectives: This study examined associations between recovery capital and NIAAA-defined recovery. Data were drawn from a project that developed and tested a new recovery capital measure, the Multidimensional Inventory of Recovery Capital. Participants self-identifying as having resolved a prior alcohol problem for at least 30 days (N = 477, 49% cisgender female, Mage = 42.6 years) completed surveys assessing recovery capital, heavy drinking (per NIAAA guidelines), and DSM-5 AUD symptoms. Logistic regression modeling examined associations between recovery capital scores and the odds of meeting the NIAAA recovery criteria. Results: Most of the sample (80.3%) met both NIAAA recovery criteria. Total recovery capital scores were associated with greater odds of NIAAA recovery (OR = 1.61; p = .001). When examined separately, individual recovery capital domains were differentially associated with NIAAA recovery depending on recovery duration. Conclusion: Overall, findings suggest that greater recovery capital may be linked to a greater likelihood of meeting NIAAA recovery criteria.
supplement_material – Supplemental material for STABLE-2007 Demonstrates Predictive and Incremental Validity in Assessing Risk-Relevant Propensities for Sexual Offending: A Meta-Analysis
Creators: name: Brankley, Andrew E.
name: Babchishin, Kelly M.
name: R. Karl Hanson
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 160299 Criminology not elsewhere classified
subject: FOS: Law
subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology

description: Supplemental material, supplement_material for STABLE-2007 Demonstrates Predictive and Incremental Validity in Assessing Risk-Relevant Propensities for Sexual Offending: A Meta-Analysis by Andrew E. Brankley, Kelly M. Babchishin and R. Karl Hanson in Sexual Abuse: A Journal of Research and Treatment