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arXiv 2024年

作者： Idnay, Betina Xu, Zihan Adams, William G. Adibuzzaman, Mohammad Anderson, Nicholas R. Bahroos, Neil Bell, Douglas S. Bumgardner, Cody Campion, Thomas Castro, Mario Cimino, James J. Cohen, I. Glenn Dorr, David Elkin, Peter L. Fan, Jungwei W. Ferris, Todd Foran, David J. Hanauer, David Hogarth, Mike Huang, Kun Kalpathy-Cramer, Jayashree Kandpal, Manoj Karnik, Niranjan S. Katoch, Avnish Lai, Albert M. Lambert, Christophe G. Li, Lang Lindsell, Christopher Liu, Jinze Lu, Zhiyong Luo, Yuan McGarvey, Peter Mendonca, Eneida A. Mirhaji, Parsa Murphy, Shawn Osborne, John D. Paschalidis, Ioannis C. Harris, Paul A. Prior, Fred Shaheen, Nicholas J. Shara, Nawar Sim, Ida Tachinardi, Umberto Waitman, Lemuel R. Wright, Rosalind J. Zai, Adrian H. Zheng, Kai Lee, Sandra Soo-Jin Malin, Bradley A. Natarajan, Karthik Price, W. Nicholson Zhang, Rui Zhang, Yiye Xu, Hua Bian, Jiang Weng, Chunhua Peng, Yifan Department of Biomedical Informatics Columbia University Irving Medical Center New YorkNY United States Department of Population Health Sciences Weill Cornell Medicine New YorkNY United States Department of Pediatrics Boston Medical Center BostonMA United States Chobanian & Avedisian School of Medicine Boston University BostonMA United States Oregon Clinical and Translational Research Institute Oregon Health and Science University PortlandOR United States Department of Public Health Sciences University of California Davis DavisCA United States Keck School of Medicine University of Southern California Los AngelesCA United States Department of Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine University of Kentucky College of Medicine LexingtonKY United States Division of Pulmonary Critical Care and Sleep Medicine University of Kansas School of Medicine Kansas CityKS United States Department of Biomedical Informatics and Data Science Heersink School of Medicine University of Alabama BirminghamAL United States Harvard Law School Petrie-Flom Center for Health Law Policy Biotechnology and Bioethics Harvard University CambridgeMA United States Department of Biomedical Informatics University at Buffalo BuffaloNY United States Center for Clinical and Translational Science Mayo Clinic RochesterMN United States Technology and Digital Solutions Stanford Medicine Stanford University StanfordCA United States Center for Biomedical Informatics Rutgers Cancer Institute New BrunswickNJ United States Department of Learning Health Sciences University of Michigan Medical School Ann ArborMI United States University of California San Diego La Jolla CA United States Department of Biostatistics and Health Data Science School of Medicine Indiana University IndianapolisIN United States Division of Artificial Medical Intelligence in Ophthalmology Univ

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational science Award (CTSA) Program led by the National Center for Advancing Translational sciences (NCATS) of the National Institutes of Health (NIH) at the United States. With the rapid advancement of GenAI technologies, including large language models (LLMs), healthcare institutions face unprecedented opportunities and challenges. This research explores the current status of GenAI integration, focusing on stakeholder roles, governance structures, and ethical considerations by administering a survey among leaders of health institutions (i.e., representing academic medical centers and health systems) to assess the institutional readiness and approach towards GenAI adoption. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The study highlights significant variations in governance models, with a strong preference for centralized decision-making but notable gaps in workforce training and ethical oversight. Moreover, the results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis also reveals concerns regarding GenAI bias, data security, and stakeholder trust, which must be addressed to ensure the ethical and effective implementation of GenAI technologies. This study offers valuable insights into the challenges and opportunities of GenAI integration in healthcare, providing a roadmap for institutions aiming to leverage GenAI for improved quality of care and operational efficiency. © 2024, CC BY.

关键词： Electronic health record

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Strong coupling in (2+1+1)-flavor QCD

arXiv

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arXiv 2025年

作者： Leino, Viljami Bazavov, Alexei Brambilla, Nora Kronfeld, Andreas S. Mayer-Steudte, Julian Petreczky, Peter Steinbeißer, Sebastian Vairo, Antonio Weber, Johannes H. Helmholtz Institute Mainz Staudingerweg 18 Mainz55128 Germany Institut für Kernphysik Johannes Gutenberg-Universität Mainz Johann-Joachim-Becher-Weg 48 Mainz55128 Germany Department of Computational Mathematics Science and Engineering Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Physics Department TUM School of Natural Sciences Technical University of Munich James-Franck-Straße 1 Garching b. München85748 Germany Munich Data Science Institute Technical University of Munich Walther-von-Dyck-Straße 10 Garching b. München85748 Germany Institute for Advanced Study Technical University of Munich Lichtenbergstraße 2a Garching b. München85748 Germany Particle Theory Department Theory Division Fermi National Accelerator Laboratory BataviaIL60510-5011 United States Physics Department Brookhaven National Laboratory UptonNY11973-5000 United States Leibniz-Rechenzentrum der Bayerischen Akademie der Wissenschaften Boltzmannstraße 1 Garching b. München85748 Germany Institut für Physik & IRIS Adlershof Humboldt-Universität zu Berlin Zum Großen Windkanal 2 BerlinD-12489 Germany Institut für Kernphysik Technische Universität Darmstadt Schlossgartenstraße 2 DarmstadtD-64289 Germany

The strong coupling αs can be obtained from the static energy as shown in previous lattices studies. For short distances, the static energy can be calculated both on the lattice with the use of Wilson line correlators, and with the perturbation theory up to three loop accuracy with leading ultrasoft log resummation. Comparing the perturbative expression and lattice data allows for precise determination of αs(mZ). We will present preliminary results for the determination of αs(MZ) in (2+1+1)-flavor QCD using the configurations made available by the MILC-collaboration with smallest lattice spacing reaching 0.0321 fm. Copyright © 2025, The Authors. All rights reserved.

关键词： Perturbation techniques

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Analysis of node2vec random walks on networks

arXiv

引用

arXiv 2020年

作者： Meng, Lingqi Masuda, Naoki Department of Mathematics University at Buffalo State University of New York BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Random walks have been proven to be useful for constructing various algorithms to gain information on networks. Algorithm node2vec employs biased random walks to realize embeddings of nodes into low-dimensional spaces, which can then be used for tasks such as multi-label classification and link prediction. The performance of the node2vec algorithm in these applications is considered to depend on properties of random walks that the algorithm uses. In the present study, we theoretically and numerically analyze random walks used by the node2vec. Those random walks are second-order Markov chains. We exploit the mapping of its transition rule to a transition probability matrix among directed edges to analyze the stationary probability, relaxation times in terms of the spectral gap of the transition probability matrix, and coalescence time. In particular, we show that node2vec random walk accelerates diffusion when walkers are designed to avoid both back-tracking and visiting a neighbor of the previously visited node but do not avoid them completely. Copyright © 2020, The Authors. All rights reserved.

关键词： Relaxation time

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Lessons Learned from Assessing Trustworthy AI in Practice

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Digital Society 2023年第3期2卷 1-25页

作者： Vetter, Dennis Amann, Julia Bruneault, Frédérick Coffee, Megan Düdder, Boris Gallucci, Alessio Gilbert, Thomas Krendl Hagendorff, Thilo van Halem, Irmhild Hickman, Eleanore Hildt, Elisabeth Holm, Sune Kararigas, Georgios Kringen, Pedro Madai, Vince I. Wiinblad Mathez, Emilie Tithi, Jesmin Jahan Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Computational Vision and Artificial Intelligence Lab Goethe University Frankfurt Frankfurt Am Main Germany Z-Inspection® Initiative Venice Italy Health Ethics and Policy Lab ETH Zurich Zurich Switzerland Strategy and Innovation Careum Foundation Zurich Switzerland Philosophie Departement Collège André-Laurendeau Montréal Canada École Des Médias Université du Québec À Montréal Montréal Canada Department of Medicine Division of Infectious Diseases and Immunology New York University Grossman School of Medicine New York City USA Department of Computer Science University of Copenhagen Copenhagen Denmark Digital Life Initiative Cornell Tech New York City USA Cluster of Excellence “Machine Learning: New Perspectives for Science” University of Tuebingen Tuebingen Germany School of Law University of Bristol Bristol UK Center for the Study of Ethics in the Professions Illinois Institute of Technology Chicago USA Department of Business Management and Analytics Arcada University of Applied Sciences Helsinki Finland Department of Food & Resource Economics University of Copenhagen Copenhagen Denmark Department of Physiology Faculty of Medicine University of Iceland Reykjavik Iceland QUEST Centre for Responsible Research Berlin Institute of Health Charité Universitätsmedizin Berlin Berlin Germany Faculty of Computing Engineering and the Built Environment School of Computing and Digital Technology Birmingham City University Birmingham UK Parallel Computing Labs Intel Santa Clara USA School of Economics Innovation and Technology Kristiania University College Oslo Norway Data Science Graduate School Seoul National University Seoul South Korea

Building artificial intelligence (AI) systems that adhere to ethical standards is a complex problem. Even though a multitude of guidelines for the design and development of such trustworthy AI systems exist, these guidelines focus on high-level and abstract requirements for AI systems, and it is often very difficult to assess if a specific system fulfills these requirements. The Z-Inspection® process provides a holistic and dynamic framework to evaluate the trustworthiness of specific AI systems at different stages of the AI lifecycle, including intended use, design, and development. It focuses, in particular, on the discussion and identification of ethical issues and tensions through the analysis of socio-technical scenarios and a requirement-based framework for ethical and trustworthy AI. This article is a methodological reflection on the Z-Inspection® process. We illustrate how high-level guidelines for ethical and trustworthy AI can be applied in practice and provide insights for both AI researchers and AI practitioners. We share the lessons learned from conducting a series of independent assessments to evaluate the trustworthiness of real-world AI systems, as well as key recommendations and practical suggestions on how to ensure a rigorous trustworthiness assessment throughout the lifecycle of an AI system. The results presented in this article are based on our assessments of AI systems in the healthcare sector and environmental monitoring, where we used the framework for trustworthy AI proposed in the Ethics Guidelines for Trustworthy AI by the European Commission’s High-Level Expert Group on AI. However, the assessment process and the lessons learned can be adapted to other domains and include additional frameworks.

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Comparison of immune profiles between hepatocellular carcinoma subtypes

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Biophysics Reports 2020年第1期6卷 19-32页

作者： Xuemin Pan Ping Lin Fangyoumin Feng Jia Li Yuan-Yuan Li Wentao Dai Bo Hu Xin-Rong Yang Jia Fan Hong Li Yixue Li School of Life Sciences and Biotechnology Shanghai Jiao Tong University Bio-Med Big Data Center Key Laboratory of Computational Biology CAS-MPG Partner Institute for Computational Biology Shanghai Institute of Nutrition and Health Shanghai Institutes for Biological Sciences University of Chinese Academy of Sciences Chinese Academy of Sciences University of the Chinese Academy of Sciences School of Life Science and Techonology Shanghai Tech University Shanghai Center for Bioinformation Technology Shanghai Academy of Science & Technology Shanghai Engineering Research Center of Pharmaceutical Translation Department of Liver Surgery Liver Cancer Institute Zhongshan Hospital Fudan University Key Laboratory of Carcinogenesis and Cancer Invasion Ministry of Education Collaborative Innovation Center of Genetics and Development Fudan University

Immunotherapy, especially immune checkpoint inhibitors, is becoming a promising treatment for hepatocellular carcinoma(HCC). However, the response rate remains limited due to the heterogeneity of HCC samples. Molecular subtypes of HCC vary in genomic background, clinical features, and prognosis. This study aims to compare the immune profiles between HCC subtypes and find subtype-specific immune characteristics that might contribute to the prognosis and potential of immunotherapy. The immune profiles consist of immune-related genes, cytolytic activity, immune pathways, and tumorinfiltrating lymphocytes. HCC-c1 samples showed an overall higher activation level of immune genes and pathways, and this pattern was consistent in validation sets. We associated the difference in immune profiles with the activation level of cancer hallmarks and genomic mutations. There was a negative correlation between most of the metabolism pathway and immune-related pathways in HCC samples. CTNNB1/WNT signaling pathway mutation, one of the common mutations in HCC, appears to be associated with the expression of immune genes as well. These results reveal the difference of immune profiles between HCC subtypes and possible reasons and influence, which may also deepen our understanding of the carcinogenesis process.

关键词： Hepatocellular carcinoma Immune Tumor-infiltrating lymphocytes Metabolism CTNNB1 mutation

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HPV-CCDC106 integration alters local chromosome architecture and hijacks an enhancer by three-dimensional genome structure remodeling in cervical cancer

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Journal of Genetics and Genomics 2020年第8期47卷 435-448页

作者： Canhui Cao Ping Hong Xingyu Huang Da Lin Gang Cao Liming Wang Bei Feng Ping Wu Hui Shen Qian Xu Ci Ren Yifan Meng Wenhua Zhi Ruidi Yu Juncheng Wei Wencheng Ding Xun Tian Qinghua Zhang Wei Li Qinglei Gao Gang Chen Kezhen Li Wing-Kin Sung Zheng Hu Hui Wang Guoliang Li Peng Wu Department of Gynecologic Oncology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China Cancer Biology Research Center(Key Laboratory of the Ministry of Education) Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China National Key Laboratory of Crop Genetic Improvement Huazhong Agricultural UniversityWuhan430070China Agricultural Bioinformatics Key Laboratory of Hubei Province Hubei Engineering Technology Research Center of Agricultural Big DataCollege of InformaticsHuazhong Agricultural UniversityWuhan430070China State Key Laboratory of Agricultural Microbiology Huazhong Agricultural UniversityWuhan430070China Bio-Medical Center Huazhong Agricultural UniversityWuhan430070China College of Veterinary Medicine Huazhong Agricultural UniversityWuhan430070China Department of Obstetrics and Gynecology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430022China Department of Obstetrics and Gynecology Key Laboratory for Molecular Diagnosis of Hubei ProvinceThe Central Hospital of WuhanTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430010China Department of Computational and Systems Biology Genome Institute of SingaporeSingapore Department of Gynecological Oncology The First Affiliated Hospital of Sun Yat-sen UniversityGuangzhou510080China

Integration of human papillomavirus(HPV)DNA into the human genome is a reputed key driver of cervical ***,the effects of HPV integration on chromatin structural organization and gene expression are largely *** studied a cohort of 61 samples and identified an integration hot spot in the CCDC106 gene on chromosome *** then selected fresh cancer tissue that contained the unique integration loci at CCDC106 with no HPV episomal DNA and performed whole-genome,RNA,chromatin immunoprecipitation and high-throughput chromosome conformation capture(Hi-C)sequencing to identify the mechanisms of HPV integration in cervical *** analyses indicated that chromosome 19 exhibited significant genomic variation and differential expression densities,with correlation found between three-dimensional(3D)structural change and gene ***,HPV integration divided one topologically associated domain(TAD)into two smaller TADs and hijacked an enhancer from PEG3 to CCDC106,with a decrease in PEG3 expression and an increase in CCDC106 *** expression dysregulation was further confirmed using 10 samples from our cohort,which exhibited the same HPV-CCDC106 *** summary,we found that HPV-CCDC106 integration altered local chromosome architecture and hijacked an enhancer via 3D genome structure ***,this study provides insight into the 3D structural mechanism underlying HPV integration in cervical carcinogenesis.

关键词： Cervical cancer HPV integration Fusion gene Hi-C Enhancer TAD

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Ethical Aspects of computational Modelling in science, Decision Support and Communication 15th

Ethical Aspects of Computational Modelling in Science, Decis...

引用

15th International Workshop on Artificial Life and Evolutionary Computation, WIVACE 2021

作者： Füchslin, Rudolf Marcel Ambühl, Jacques Faggian, Alessia Fellermann, Harold M. Flumini, Dandolo Geller, Armando Hanczyc, Martin M. Klinkert, Andreas Krütli, Pius Matuttis, Hans-Georg Ott, Thomas Scheidegger, Stephan Schmid, Gary Bruno Smieszek, Timo Schneider, Johannes J. Steiner, Albert Weyland, Mathias S. Institute of Applied Mathematics and Physics Zurich University of Applied Sciences Zurich Technikumstrasse 9 Winterthur8400 Switzerland European Centre for Living Technology Ca’ Bottacin Dorsoduro 3911 Calle Crosera Venice30123 Italy World Bank Group Geneva Switzerland University of Trento Trento38123 Italy School of Computing Newcastle University Science Square 1 Newcastle Upon TyneNE4 5TG United Kingdom GmbH Fraumünsterstrasse 11 Zurich8001 Switzerland Institute of Data Analysis and Process Design Zurich University of Applied Sciences Rosenstrasse 3 Winterthur8400 Switzerland Transdisciplinarity Lab ETH Zurich Zurich8092 Switzerland Department of Mechanical Engineering and Intelligent Systems The University of Electrocommunications Tokyo182-8585 Japan Institute of Computational Life Sciences Zurich University of Applied Sciences Schloss 1 Wädenswil8820 Switzerland Swiss NeuroCreations GmbH Hambergersteig 25 Zurich8008 Switzerland Muesmattweg 70 Allschwil4123 Switzerland

ISBN: (纸本)9783031239281

The development of data science, the increase of computational power, the availability of the internet infrastructure for data exchange and the urgency for an understanding of complex systems require a responsible and ethical use of computational models in science, communication and decision-making. Starting with a discussion of the width of different purposes of computational models, we first investigate the process of model construction as an interplay of theory and experimentation. We emphasise the different aspects of the tension between model variables and experimentally measurable observables. The resolution of this tension is a prerequisite for the responsible use of models and an instrumental part of using models in the scientific processes. We then discuss the impact of models and the responsibility that results from the fact that models support and may also guide experimentation. Further, we investigate the difference between computational modelling in an interdisciplinary science project and computational models as tools in transdisciplinary decision support. We regard the communication of model structures and modelling results as essential;however, this communication cannot happen in a technical manner, but model structures and modelling results must be translated into a "narrative." We discuss the role of concepts from disciplines such as literary theory, communication science, and cultural studies and the potential gains that a broader approach can obtain. Considering concepts from the liberal arts, we conclude that there is, besides the responsibility of the model author, also a responsibility of the user/reader of the modelling results. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Scalable matched-filtering pipeline for gravitational-wave searches of compact binary mergers

arXiv

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arXiv 2024年

作者： Huang, Yun-Jing Hanna, Chad Ewing, Becca Godwin, Patrick Gonsalves, Joshua Magee, Ryan Messick, Cody Tsukada, Leo Yarbrough, Zach Joshi, Prathamesh Kennington, James Niu, Wanting Rollins, Jameson Shah, Urja Department of Physics The Pennsylvania State University University ParkPA16802 United States Institute for Gravitation and the Cosmos The Pennsylvania State University University ParkPA16802 United States Department of Astronomy and Astrophysics The Pennsylvania State University University ParkPA16802 United States Institute for Computational and Data Sciences The Pennsylvania State University University ParkPA16802 United States LIGO Laboratory California Institute of Technology MS 100-36 PasadenaCA91125 United States Department of Computer Science and Engineering The Pennsylvania State University University ParkPA16802 United States LIGO Laboratory California Institute of Technology PasadenaCA91125 United States Leonard E. Parker Center for Gravitation Cosmology and Astrophysics University of Wisconsin-Milwaukee MilwaukeeWI53201 United States Department of Physics and Astronomy University of Nevada Las Vegas 4505 South Maryland Parkway Las VegasNV89154 United States Nevada Center for Astrophysics University of Nevada Las VegasNV89154 United States Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States School of Physics Georgia Institute of Technology AtlantaGA30332 United States

As gravitational-wave observations expand in scope and detection rate, the data analysis infrastructure must be modernized to accommodate rising computational demands and ensure sustainability. We present a scalable gravitational-wave search pipeline which modernizes the GstLAL pipeline by adapting the core filtering engine to the PyTorch framework, enabling flexible execution on both Central Processing Units (CPUs) and Graphics Processing Units (GPUs). Offline search results on the same 8.8 day stretch of public gravitational-wave data indicate that the GstLAL and the PyTorch adaptation demonstrate comparable search performance, even with float16 precision. Lastly, computational benchmarking results show that the GPU float16 configuration of the PyTorch adaptation executed on an A100 GPU can achieve a speedup factor of up to 169 times compared to GstLAL’s performance on a single CPU core. © 2024, CC BY.

关键词： Matched filters

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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

arXiv

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arXiv 2024年

作者： Evans, Matthew L. Bergsma, Johan Merkys, Andrius Andersen, Casper W. Andersson, Oskar B. Beltrán, Daniel Blokhin, Evgeny Boland, Tara M. Balderas, Rubén Castañeda Choudhary, Kamal Díaz, Alberto Díaz García, Rodrigo Domínguez Eckert, Hagen Eimre, Kristjan Montero, María Elena Fuentes Krajewski, Adam M. Mortensen, Jens Jørgen Duarte, José Manuel Nápoles Pietryga, Jacob Qi, Ji de Jesús Trejo Carrillo, Felipe Vaitkus, Antanas Yu, Jusong Zettel, Adam de Castro, Pedro Baptista Carlsson, Johan Cerqueira, Tiago F.T. Divilov, Simon Hajiyani, Hamidreza Hanke, Felix Jose, Kevin Oses, Corey Riebesell, Janosh Schmidt, Jonathan Winston, Donald Xie, Christen Yang, Xiaoyu Bonella, Sara Botti, Silvana Curtarolo, Stefano Draxl, Claudia Cobas, Luis Edmundo Fuentes Hospital, Adam Liu, Zi-Kui Marques, Miguel A.L. Marzari, Nicola Morris, Andrew J. Ong, Shyue Ping Orozco, Modesto Persson, Kristin A. Thygesen, Kristian S. Wolverton, Chris Scheidgen, Markus Toher, Cormac Conduit, Gareth J. Pizzi, Giovanni Gražulis, Saulius Rignanese, Gian-Marco Armiento, Rickard Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium Matgenix SRL 185 Rue Armand Bury Gozée6534 Belgium École Polytechnique Fédérale de Lausanne Avenue de Forel 3 Lausanne1015 Switzerland Institute of Biotechnology Life Sciences Center Vilnius University Sauletekio av. 7 VilniusLT-10257 Lithuania SINTEF P.O. Box 4760 Torgarden TrondheimNO-7465 Norway Materials Design and Informatics unit Department of Physics Chemistry and Biology Linköping University Sweden Baldiri i Reixac 10-12 Barcelona08028 Spain Tilde Materials Informatics Straßmannstraße 25 Berlin10249 Germany Materials Platform for Data Science Sepapaja 6 Tallinn15551 Estonia Computational Atomic-Scale Materials Design Technical University of Denmark Kgs. Lyngby Denmark Av. Miguel de Cervantes 120 Complejo Industrial Chihuahua Chihuahua Chih. 31136 Mexico Material Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Center for Extreme Materials Duke University DurhamNC27708 United States École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Universidad Autónoma de Chihuahua Facultad de Ciencias Quimicas Chihuahua31125 Mexico Department of Materials Science and Engineering The Pennsylvania State University University ParkPA16802 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of NanoEngineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093-0448 United States National Institute for Materials Science 1-2-1 Sengen Ibaraki Tsukuba305-0047 Japan Dassault Systèmes Germany GmbH Am Kabellager 11-13 Cologne51063 Germany CFisUC Department of Physics University of Coimbra Rua Larga Coimbra3004-516 Portugal Dassault Systèmes 22 Science Park CB4 0FJ United Kingdom Theory of Condensed Matter Cavendis

The Open databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development. © 2024, CC BY.

关键词： Electronic data interchange

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Here There Be (Dusty) Monsters: High Redshift AGN are Dustier Than Their Hosts

arXiv

引用

arXiv 2024年

作者： Brooks, Madisyn Simons, Raymond C. Trump, Jonathan R. Taylor, Anthony J. Backhaus, Bren Davis, Kelcey Buat, Véronique Cleri, Nikko J. de la Vega, Alexander Finkelstein, Steven L. Hirschmann, Michaela Holwerda, Benne W. Kocevski, Dale D. Koekemoer, Anton M. Lucas, Ray A. Pacucci, Fabio Seillé, Lise-Marie Department of Physics Unit 3046 University of Connecticut 196A Auditorium Road StorrsCT06269 United States Department of Engineering and Physics Providence College 1 Cunningham Sq ProvidenceRI02918 United States Department of Astronomy The University of Texas at Austin AustinTX United States Department of Physics and Astronomy University of Kansas LawrenceKS66045 United States Aix Marseille Univ CNRS CNES LAM Marseille France Paris France Department of Astronomy and Astrophysics The Pennsylvania State University University ParkPA16802 United States Institute for Computational and Data Sciences The Pennsylvania State University University ParkPA16802 United States Institute for Gravitation and the Cosmos The Pennsylvania State University University ParkPA16802 United States Department of Physics and Astronomy University of California 900 University Ave RiversideCA92521 United States Cosmic Frontier Center The University of Texas at Austin AustinTX United States Observatoire de Sauverny Versoix1290 Switzerland Department of Physics University of Louisville Natural Science Building 102 Louisville40292 KY United States Department of Physics and Astronomy Colby College WatervilleME04901 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Center for Astrophysics Harvard & Smithsonian 60 Garden St CambridgeMA02138 United States Black Hole Initiative Harvard University 20 Garden St CambridgeMA02138 United States

JWST spectroscopy has discovered a population of z 3.5 galaxies with broad Balmer emission lines, and narrow forbidden lines, that are consistent with hosting active galactic nuclei (AGN). Many of these systems, now known as "little red dots" (LRDs), are compact and have unique colors that are very red in the optical/near-infrared and blue in the ultraviolet. The relative contribution of galaxy starlight and AGN to these systems remains uncertain, especially for the galaxies with unusual blue+red spectral energy distributions. In this work, we use Balmer decrements to measure the independent dust attenuation of the broad and narrow emission-line components of a sample of 29 broad-line AGN identified from three public JWST spectroscopy surveys: CEERS, JADES, and RUBIES. Stacking the narrow components from the spectra of 25 sources with broad Hα and no broad Hβ results in a median narrow Hα/Hβ = 2.47+0−0.0505 (consistent with Av = 0) and broad Hα/Hβ > 8.85 (Av > 3.63). The narrow and broad Balmer decrements imply little-to-no attenuation of the narrow emission lines, which are consistent with being powered by star formation and located on larger physical scales. Meanwhile, the lower limit in broad Hα/Hβ decrement, with broad Hβ undetected in the stacked spectrum of 25 broad-Hα AGN, implies significant dust attenuation of the broad-line emitting region that is presumably associated with the central AGN. Our results indicate that these systems, on average, are consistent with heavily dust-attenuated AGN powering the red parts of their SED while their blue UV emission is powered by unattenuated star formation in the host galaxy. © 2024, CC BY.

关键词： Stars

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