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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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1873. Next Steps in Predicting Anti-MRSA Antibiotic Prescribing

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Open Forum Infectious Diseases 2018年第SUPPL_1期5卷 S535–S536页

作者： Holmer, Haley K Pakyz, Amy Tallman, Gregory B Elman, Miriam R Hohmann, Samuel Fu, Rochelle Kuper, Kristi McGregor, Jessina C Epidemiology Oregon Health and Science University/Portland State University School of Public Health Portland Oregon Department of Pharmacotherapy and Outcomes Science Virginia Commonwealth University Richmond Virginia Department of Pharmacy Practice Oregon State University/Oregon Health and Science University College of Pharmacy Portland Oregon Biostatistics and Design Program Oregon Health and Science University-Portland State University School of Public Health Portland Oregon Center for Advanced Analytics Vizient Chicago Illinois Department of Health Systems Management Rush University Chicago Illinois Vizient Inc. Houston Texas

Background Antibiotic use metrics are utilized by antimicrobial stewardship programs to benchmark performance against peer institutions and inform stewardship efforts. Benchmarking requires risk adjustment for patient- and facility-level factors so that remaining differences are attributable only to prescribing practices. Antibiotics for the treatment of methicillin-resistant Staphylococcus aureus (MRSA) are one of the most frequently used drug classes. Our objective was to identify predictors of anti-MRSA antibiotic use in a nationwide network of hospitals. Methods We used data from inpatient encounters at facilities participating in the Vizient data repository between January 1, 2016 and December 31, 2016. The outcome, anti-MRSA antibiotic use, was calculated as days of therapy per patient-days present for each encounter. We constructed a multivariable negative binomial regression model and assessed the following predictors for inclusion: age, sex, race, ethnicity, diagnosis related groups (DRGs), ICU days, admit month, facility bed size, facility teaching status, and region. A clinical framework was used to categorize DRGs based on risk of anti-MRSA antibiotic use. A backwards stepwise approach was used to identify the final model. We evaluated predictor effect size and significance, and assessed model fit using a deviance-based pseudo- R 2 . Results One hundred forty-five facilities representing 3,608,711 encounters met inclusion criteria. All predictors considered in our model were significant. Predictors with the greatest magnitude of association included DRG categories and patient age. The DRG categories with the strongest associations were DRGs for infections likely due to Staphylococcus aureus (RR = 1.66, P < 0.0001) or for diagnoses likely to receive long-term MRSA coverage (RR = 1.49, P < 0.0001). The age group with the strongest association was age 2–10 years (RR = 1.64; P < 0.001). The deviance-based pseudo- R 2 of the final model was 0.19, indicating g

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NWChem: Past, present, and future

arXiv

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arXiv 2020年

作者： Aprà, E. Bylaska, E.J. de Jong, W.A. Govind, N. Kowalski, K. Straatsma, T.P. Valiev, M. van Dam, H.J.J. Alexeev, Y. Anchell, J. Anisimov, V. Aquino, F.W. Atta-Fynn, R. Autschbach, J. Bauman, N.P. Becca, J.C. Bernholdt, D.E. Bhaskaran-Nair, K. Bogatko, S. Borowski, P. Boschen, J. Brabec, J. Bruner, A. Cauët, E. Chen, Y. Chuev, G.N. Cramer, C.J. Daily, J. Deegan, M.J.O. Dunning, T.H. Dupuis, M. Dyall, K.G. Fann, G.I. Fischer, S.A. Fonari, A. Früchtl, H. Gagliardi, L. Garza, J. Gawande, N. Ghosh, S. Glaesemann, K. Götz, A.W. Hammond, J. Helms, V. Hermes, E.D. Hirao, K. Hirata, S. Jacquelin, M. Jensen, L. Johnson, B.G. Jónsson, H. Kendall, R.A. Klemm, M. Kobayashi, R. Konkov, V. Krishnamoorthy, S. Krishnan, M. Lin, Z. Lins, R.D. Littlefield, R.J. Logsdail, A.J. Lopata, K. Ma, W. Marenich, A.V. Martin del Campo, J. Mejia-Rodriguez, D. Moore, J.E. Mullin, J.M. Nakajima, T. Nascimento, D.R. Nichols, J.A. Nichols, P.J. Nieplocha, J. Otero-de-la-Roza, A. Palmer, B. Panyala, A. Pirojsirikul, T. Peng, B. Peverati, R. Pittner, J. Pollack, L. Richard, R.M. Sadayappan, P. Schatz, G.C. Shelton, W.A. Silverstein, D.W. Smith, D.M.A. Soares, T.A. Song, D. Swart, M. Taylor, H.L. Thomas, G.S. Tipparaju, V. Truhlar, D.G. Tsemekhman, K. van Voorhis, T. Vázquez-Mayagoitia, Á. Verma, P. Villa, O. Vishnu, A. Vogiatzis, K.D. Wang, D. Weare, J.H. Williamson, M.J. Windus, T.L. Woliński, K. Wong, A.T. Wu, Q. Yang, C. Yu, Q. Zacharias, M. Zhang, Z. Zhao, Y. Harrison, R.J. Pacific Northwest National Laboratory RichlandWA99352 United States Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Brookhaven National Laboratory UptonNY11973 United States Argonne Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Intel Corporation Santa ClaraCA95054 United States QSimulate CambridgeMA02139 United States Department of Physics University of Texas at Arlington ArlingtonTX76019 United States Department of Chemistry University at Buffalo State University of New York BuffaloNY14260 United States Department of Chemistry Pennsylvania State University University ParkPA16802 United States Oak Ridge National Laboratory Oak RidgeTN37831 United States Washington University St. LouisMO63130 United States 4G Clinical WellesleyMA02481 United States Faculty of Chemistry Maria Curie-Sklodowska University in Lublin Lublin20-031 Poland Department of Chemistry Iowa State University AmesIA50011 United States J. Heyrovský Institute of Physical Chemistry Academy of Sciences of the Czech Republic Prague 818223 Czech Republic Department of Chemistry and Physics University of Tennessee at Martin MartinTN38238 United States Université libre de Bruxelles BrusselsB-1050 Belgium Facebook Menlo ParkCA94025 United States Institute of Theoretical and Experimental Biophysics Russian Academy of Science Pushchino Moscow142290 Russia Department of Chemistry Chemical Theory Center Supercomputing Institute University of Minnesota MinneapolisMN55455 United States SKAO Jodrell Bank Observatory MacclesfieldSK11 9DL United Kingdom Department of Chemistry University of Washington SeattleWA98195 United States Dirac Solutions PortlandOR97229 United States Chemistry Division U. S. Naval Research Laboratory WashingtonDC20375 United States School of Chemistry and Biochemis

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the last few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach and outlook. Copyright © 2020, The Authors. All rights reserved.

关键词： Computational chemistry

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NextGen VOICES: A postdoc's purpose

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science (New York, N.Y.) 2018年第6384期360卷 26-27页

作者： Carolyn Adams Brotherton Saima Naz Syed Shan-E-Ali Zaidi Allison F Dennis Anni Hämäläinen Wadim Strielkowski Ming-Ju Amy Lyu J K Wenderott Cristina Espinosa-Diez Kyle Isaacson Yifan Li Ebrahim Hassan J Steen Hoyer Joseph Michael Cusimano Department of Microbiology University of Washington Seattle WA 98195 USA. Lahore Punjab Pakistan. eLife Ambassador Gembloux Agro-Bio Tech University of Liège Gembloux 5030 Namur Belgium. The Program in Cell Molecular Developmental Biology and Biophysics (CMDB) Johns Hopkins University Baltimore MD 21218 USA. École d'Optométrie University of Montréal Montréal QC H3T 1P1 Canada and Canadian Association of Postdoctoral Scholars. Department of Agricultural and Resource Economics University of California Berkeley Berkeley CA 94720 USA. Department of Plant Systems Biology Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences Shanghai 200032 China. Department of Materials Science and Engineering University of Michigan Ann Arbor MI 48109 USA. Oregon Health and Science University Portland OR 97239 USA. Department of Bioengineering University of Utah Salt Lake City UT 84112 USA. Berkeley CA 94703 USA. Institute of Virology Medical Center University of Freiburg 79104 Freiburg Germany. Department of Ecology Evolution and Natural Resources Rutgers University New Brunswick NJ 08901 USA. College of Pharmacy The Ohio State University Columbus OH 43210 USA.

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Publisher Correction: Brain charts for the human lifespan

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Nature 2022年第7931期610卷 E6页

作者： R A I Bethlehem J Seidlitz S R White J W Vogel K M Anderson C Adamson S Adler G S Alexopoulos E Anagnostou A Areces-Gonzalez D E Astle B Auyeung M Ayub J Bae G Ball S Baron-Cohen R Beare S A Bedford V Benegal F Beyer J Blangero M Blesa Cábez J P Boardman M Borzage J F Bosch-Bayard N Bourke V D Calhoun M M Chakravarty C Chen C Chertavian G Chetelat Y S Chong J H Cole A Corvin M Costantino E Courchesne F Crivello V L Cropley J Crosbie N Crossley M Delarue R Delorme S Desrivieres G A Devenyi M A Di Biase R Dolan K A Donald G Donohoe K Dunlop A D Edwards J T Elison C T Ellis J A Elman L Eyler D A Fair E Feczko P C Fletcher P Fonagy C E Franz L Galan-Garcia A Gholipour J Giedd J H Gilmore D C Glahn I M Goodyer P E Grant N A Groenewold F M Gunning R E Gur R C Gur C F Hammill O Hansson T Hedden A Heinz R N Henson K Heuer J Hoare B Holla A J Holmes R Holt H Huang K Im J Ipser C R Jack A P Jackowski T Jia K A Johnson P B Jones D T Jones R S Kahn H Karlsson L Karlsson R Kawashima E A Kelley S Kern K W Kim M G Kitzbichler W S Kremen F Lalonde B Landeau S Lee J Lerch J D Lewis J Li W Liao C Liston M V Lombardo J Lv C Lynch T T Mallard M Marcelis R D Markello S R Mathias B Mazoyer P McGuire M J Meaney A Mechelli N Medic B Misic S E Morgan D Mothersill J Nigg M Q W Ong C Ortinau R Ossenkoppele M Ouyang L Palaniyappan L Paly P M Pan C Pantelis M M Park T Paus Z Pausova D Paz-Linares A Pichet Binette K Pierce X Qian J Qiu A Qiu A Raznahan T Rittman A Rodrigue C K Rollins R Romero-Garcia L Ronan M D Rosenberg D H Rowitch G A Salum T D Satterthwaite H L Schaare R J Schachar A P Schultz G Schumann M Schöll D Sharp R T Shinohara I Skoog C D Smyser R A Sperling D J Stein A Stolicyn J Suckling G Sullivan Y Taki B Thyreau R Toro N Traut K A Tsvetanov N B Turk-Browne J J Tuulari C Tzourio É Vachon-Presseau M J Valdes-Sosa P A Valdes-Sosa S L Valk T van Amelsvoort S N Vandekar L Vasung L W Victoria S Villeneuve A Villringer P E Vértes K Wagstyl Y S Wang S K Warfield V Warrier E Westman M L Westwater H C Whalley A V Witte N Yang B Yeo H Y Autism Research Centre Department of Psychiatry University of Cambridge Cambridge UK. rb643@medschl.cam.ac.uk. Brain Mapping Unit Department of Psychiatry University of Cambridge Cambridge UK. rb643@medschl.cam.ac.uk. Department of Psychiatry University of Pennsylvania Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Department of Child and Adolescent Psychiatry and Behavioral Science The Children's Hospital of Philadelphia Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Lifespan Brain Institute The Children's Hospital of Philadelphia and Penn Medicine Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Department of Psychiatry University of Cambridge Cambridge UK. MRC Biostatistics Unit University of Cambridge Cambridge UK. Department of Psychiatry University of Pennsylvania Philadelphia PA USA. Lifespan Informatics & Neuroimaging Center University of Pennsylvania Philadelphia PA USA. Department of Psychology Yale University New Haven CT USA. Developmental Imaging Murdoch Children's Research Institute Melbourne Victoria Australia. Department of Medicine Monash University Melbourne Victoria Australia. UCL Great Ormond Street Institute for Child Health London UK. Weill Cornell Institute of Geriatric Psychiatry Department of Psychiatry Weill Cornell Medicine New York USA. Department of Pediatrics University of Toronto Toronto Canada. Holland Bloorview Kids Rehabilitation Hospital Toronto Canada. The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for NeuroInformation University of Electronic Science and Technology of China Chengdu China. University of Pinar del Río "Hermanos Saiz Montes de Oca" Pinar del Río Cuba. MRC Cognition and Brain Sciences Unit University of Cambridge Cambridge UK. Autism Research Centre Department of Psychiatry University of Cambridge Cambridge UK. Department of Psychology School of Philosophy Psychology and Language Sciences University of Edinburgh Edinburgh UK. Queen's

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Comment on "Global pattern of nest predation is disrupted by climate change in shorebirds"

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science 2019年第6445期364卷 1041-+页

作者： Bulla, Martin Reneerkens, Jeroen Weiser, Emily L. Sokolov, Aleksandr Taylor, Audrey R. Sittler, Benoit McCaffery, Brian J. Ruthrauff, Dan R. Catlin, Daniel H. Payer, David C. Ward, David H. Solovyeva, Diana V. Santos, Eduardo S. A. Rakhimberdiev, Eldar Nol, Erica Kwon, Eunbi Brown, Glen S. Hevia, Glenda D. Gates, H. River Johnson, James A. van Gils, Jan A. Hansen, Jannik Lamarre, Jean-Francois Rausch, Jennie Conklin, Jesse R. Liebezeit, Joe Bety, Joel Lang, Johannes Alves, Jose A. Fernandez-Elipe, Juan Michael-Exo, Klaus Bollache, Loic Bertellotti, Marcelo Giroux, Marie-Andree van de Pol, Martijn Johnson, Matthew Boldenow, Megan L. Valcu, Mihai Soloviev, Mikhail Sokolova, Natalya Senner, Nathan R. Lecomte, Nicolas Meyer, Nicolas Schmidt, Niels Martin Gilg, Olivier Smith, Paul A. Machin, Paula McGuire, Rebecca L. Cerboncini, Ricardo A. S. Ottvall, Richard van Bemmelen, Rob S. A. Swift, Rose J. Saalfeld, Sarah T. Jamieson, Sarah E. Brown, Stephen Piersma, Theunis Albrecht, Tomas D'Amico, Veronica Lanctot, Richard B. Kempenaers, Bart Department of Behavioural Ecology and Evolutionary Genetics Max Planck Institute for Ornithology 82319 Seewiesen Germany. NIOZ Royal Netherlands Institute for Sea Research Department of Coastal Systems and Utrecht University 1790 AB Den Burg Texel Netherlands. Faculty of Environmental Sciences Czech University of Life Sciences 16521 Prague Czech Republic. Conservation Ecology Group Groningen Institute for Evolutionary Life Sciences (GELIFES) University of Groningen 9700 CC Groningen Netherlands. Upper Midwest Environmental Sciences Center U.S. Geological Survey La Crosse WI 54603 USA. Arctic Research Station Institute of Plant and Animal Ecology 629400 Labytnangi Russia. Department of Geography and Environmental Studies University of Alaska Anchorage AK 99508 USA. Nature Conservation and Landscape Ecology University of Freiburg 79106 Freiburg Germany. Arctic Ecology Research Group (GREA) F-21440 Francheville France. Yukon Delta National Wildlife Refuge U.S. Fish and Wildlife Service Grand View WI 54839 USA. Alaska Science Center U.S. Geological Survey Anchorage AK 99508 USA. Department of Fish and Wildlife Conservation Virginia Tech Blacksburg VA 24061 USA. Natural Resource Sciences National Park Service Anchorage AK 99501 USA. Institute of Biological Problems of the North FEB RAS Magadan 685000 Russia. BECO do Departamento de Zoologia Rua do Matão Universidade de São Paulo 05508-090 São Paulo Brazil. Department of Vertebrate Zoology Lomonosov Moscow State University 119234 Moscow Russia. Biology Department Trent University Peterborough ON K9J 7B8 Canada. Wildlife Research and Monitoring Ministry of Natural Resources and Forestry Peterborough ON K9L 1Z8 Canada. Grupo de Ecofisiología Aplicada al Manejo y Conservación de Fauna Silvestre Centro para el Estudio de Sistemas Marinos (CESIMAR)-CCT CONICET-CENPAT 9120 Puerto Madryn Argentina. Pacific Flyway Program National Audubon Society Anchorage AK 99501 USA. Migratory Bird Management U.S. Fish

Kubelka et al. (Reports, 9 November 2018, p. 680) claim that climate change has disrupted patterns of nest predation in shorebirds. They report that predation rates have increased since the 1950s, especially in the Arctic. We describe methodological problems with their analyses and argue that there is no solid statistical support for their claims.

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Mind and Life: Is the Materialist Neo-Darwinian Conception of Nature False?

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Biological Theory 2015年第1期11卷 25-38页

作者： Zwick, Martin Systems Science Graduate Program Portland State University Portland USA

A partial review of Thomas Nagel’s book, Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost Certainly False is used to articulate some systems-theoretic ideas about the challenge of understanding subjective experience. The article accepts Nagel’s view that reductionist materialism fails as an approach to this challenge, but argues that seeking an explanation of mind based on emergence is more plausible than seeking one based on panpsychism, which Nagel favors. However, the article proposes something similar to Nagel’s neutral monism by positing a hierarchy of information processes that spans the domains of matter, life, and mind. As depicted in this hierarchy, subjective experience is emergent, but also continuous with informational phenomena at lower levels.

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Levels of Altruism

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Biological Theory 2014年第1期9卷 100-107页

作者： Zwick, Martin Fletcher, Jeffrey A. Systems Science Graduate Program Portland State University Portland OR United States

The phenomenon of altruism extends from the biological realm to the human sociocultural realm. This article sketches a coherent outline of multiple types of altruism of progressively increasing scope that span these two realms and are grounded in an ever-expanding sense of “self.” Discussion of this framework notes difficulties associated with altruism at different levels. It links scientific ideas about the evolution of cooperation and about hierarchical order to perennial philosophical and religious concerns. It offers a conceptual background for inquiry into societal challenges that call for altruistic behavior, especially the challenge of environmental and social sustainability. © 2013, Konrad Lorenz Institute for Evolution and Cognition Research.

关键词： Altruism Evolution of cooperation Kin selection Multilevel selection Reciprocal altruism Self

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Bargaining for your privacy in the information age: Systematic factors undermining the equity of user-company online information transactions

Bargaining for your privacy in the information age: Systemat...

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portland International Conference on Management of Engineering and Technology (PICMET)

作者： Peter Glazer Jonathan Straus Portland State University School of Business Administration Portland OR USA Portland State University Systems Science PhD Program Portland OR USA

Consumer privacy and protection of personal information are among the forefront of emerging complex social issues in the internet age. This growing threat to consumers' safety and security is framed as a systemic problem of structural inequality, specifically one where consumers are situated in positions of inferior bargaining power compared to the online service providers they engage in personal information transactions with. We propose a host of vestigial societal factors interacting with the turbulently transitional information-based economy, including outdated legal and economic regulations as well as cognitive limitations and cultural preferences among public users, reinforce and exacerbate these inequitable consumer-company relationships. Potential implications on future policy, social changes and directions for future research are discussed.

关键词： Safety Security Privacy Companies Internet Law

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