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Identification of Sumatera Butterfly species by using deep learning with data augmentation

AIP Conference Proceedings 2024年第1期2970卷

作者： Rico Andrian Admi Syarif Favorisen Rosyking Lumbanraja Emantis Rosa Doctoral Program of Mathematics and Natural Sciences Lampung University Jl. Prof. Dr. Sumantri Brojonegoro No. 1 Bandar Lampung 35145 Indonesia Department of Computer Science Lampung University Jl. Prof. Dr. Sumantri Brojonegoro No. 1 Bandar Lampung 35145 Indonesia Department of Biology Lampung University Jl. Prof. Dr. Sumantri Brojonegoro No. 1 Bandar Lampung 35145 Indonesia

Butterflies are members of the Lepidoptera order. The complexity of the Sumatera Butterfly’s patterns and hues makes it difficult to identify with the naked eye. Gita Persada Butterfly Park is always crowded with people who want to see and learn about the different species of Sumatera butterfly. The Sumatera Butterfly, which humans can see with the naked eye, is quite difficult to identify without the assistance of certain technologies due to its diverse patterns and colors and the fact that there are nearly several species. AlexNet is one of the deep learning architectures that can detect images of the Sumatera Butterfly, functioning similarly to the human brain in object recognition. Deep learning employs artificial neural networks for learning. The first stage of this research consisted of collecting the Sumatera Butterfly dataset and identifying the butterfly species with AlexNet. The second step is identifying Sumatera butterfly species using AlexNet with additional data augmentation, flip data augmentation, and rotate data augmentation. The comparison between pre- and post-augmentation performance will reveal the difference. AlexNet’s accuracy without boost is 98.12 percent. After adding data augmentation to AlexNet architecture, the accuracy ratio is 99.06 percent, while AlexNet’s highest accuracy is 99.37 percent with flip augmentation.

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MIS: A tool for planning and evaluation

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New Directions for Student Services 1980年第9期1980卷

作者： Vincent C. Racippo Cecelia H. Foxley Vincent C. Racioppo is a doctoral student in the Division of Counselor Education's Student Development Program at the University of Iowa. As a member of the planning staff at Youngstown State University he was responsible for overseeing information collection validation and dissemination. He is presently a graduate assistant in the University of Iowa's Office of Academic Affairs where he combines his training and experience in both computer science and student development. Cecilia H. Foxley is associate professor in the Division of Counselor Education (Student Development Program) and acting assistant dean of the College of Education at the University of Iowa.

Even the simplest form of a management information system can assist the student services administrator in organization and program planning and evaluation of desired results.

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Out on the Land: Income, Subsistence Activities, and Food Sharing Networks in Nain, Labrador

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Journal of Anthropology 2013年第1期2013卷

作者： Kirk Dombrowski Emily Channell Bilal Khan Joshua Moses Evan Misshula Department of Anthropology John Jay College City University of New York 524 West 59th Street New York NY 10019 USAcuny.edu Doctoral Program in Anthropology CUNY Graduate Center 365 5th Avenue New York NY 10016 USAcuny.edu Department of Mathematics and Computer Science John Jay College City University of New York 524 West 59th Street New York NY 10019 USAcuny.edu Culture and Mental Health Research Unit 4333 Chemin de la Cote Ste-Catherine Montreal QC Canada H3T 1E4 Doctoral Program in Criminal Justice CUNY Graduate Center 365 5th Avenue New York NY 10016 USAcuny.edu

In recent Inuit ethnography, a major concern has been how and to what extent contemporary Inuit participate in and depend on subsistence activities, particularly in the context of increasing wage employment and growing participation in the cash economy. This paper provides an analysis of these activities in the predominately Inuit community of Nain, Labrador. Using social network data and demographic information collected between January and June 2010, we examine the interconnections between subsistence activities—obtaining “country food” through activities such as hunting, fishing, and collecting—with access to the means of obtaining subsistence resources (such as snow mobiles, cabins, and boats), employment status, and income. Our data indicate that individuals with higher employment status and income tend to be more central to the network of subsistence food sharing, but not because they have greater access to hunting tools or equipment (they do not). We conclude that those individuals who play the most central role in the network are those who are financially able to do so, regardless of access to hunting tools/means.

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The Biodiversity of Flora and Fauna in the Re-vegetation Area in The Post-Mining Area of Pongkor

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IOP Conference Series: Earth and Environmental science 2020年第1期501卷

作者： A Kusumoarto A Gunawan Machfud A Hikmat Doctoral Student Program Natural Resource and Environmental Management Science School of Post-Graduate IPB University Jl. Raya Pajajaran Bogor Indonesia 16143 Lecturer in Architecture Study Program Faculty of Technic and Computer Science Indraprasta PGRI University Jl. Raya Nangka No. 58C RT.5/RW.5 Tanjung Barat Kecamatan Jagakarsa Kota Jakarta Selatan Daerah Khusus Ibukota Jakarta 12530 Lecturer in Landscape Architecture Department IPB University Jl. Raya Darmaga Bogor Indonesia 16680 Lecturer in AgroIndustrial Technology Department IPB University Jl.Raya Darmaga Bogor Indonesia 16680 Lecturer in Conservation of Forest and Ecotourism Department IPB University Jl. Raya Darmaga Bogor Indonesia 16680

The Pongkor post-mining area is designated as one of the ecotourism areas in Bogor. This area has biodiversity of flora and fauna. This study aims to: (1) analysis the importance value index (IVI) of flora types; (2) analysis species richness index, species diversity index, and relative species abundance index; (3) analysis the beauty, the uniqueness and the rarity of the flora and fauna types. The method used in this research is quantitative descriptive. Based on the identification results, 185 species of flora are distributed in this region. During the rainy season, 15 species of herpetofauna were identified, 32 types of aves, and 4 types of mammals, while in the dry season 19 species of herpetofauna were identified, 23 types of aves, and 2 types of mammals. Based on the results of the analysis conducted on these flora and fauna, there are flora species that have high IVI values and some beautiful and unique flora species that are in the category of endangered species. Besides that, there are also fauna species which have a value of species richness index, species diversity index, and relative species abundance index, as well as some beautiful, unique, and fauna species that are in the category of endangered species.

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Correction: Secondary outcomes and qualitative findings of an open-label feasibility trial of lisdexamfetamine dimesylate for adults with bulimia nervosa

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Journal of eating disorders 2023年第1期11卷 205页

作者： Laura Dixon Sara Bartel Victoria Brown Sarrah I Ali Susan Gamberg Andrea Murphy Katherine L Brewer Susan L McElroy Allan Kaplan Abraham Nunes Aaron R Keshen Eating Disorder Program Nova Scotia Health Authority Halifax NS Canada. Department of Psychiatry Dalhousie University Halifax NS Canada. College of Pharmacy Dalhousie University Halifax NS Canada. College of Doctoral Studies University of Phoenix Tempe AZ USA. Lindner Center of HOPE Mason OH USA. Department of Psychiatry and Behavioral Neuroscience University of Cincinnati College of Medicine Cincinnati OH USA. Department of Psychiatry Centre for Addiction and Mental Health Institute of Medical Science University of Toronto Toronto ON Canada. Faculty of Computer Science Dalhousie University Halifax NS Canada. Eating Disorder Program Nova Scotia Health Authority Halifax NS Canada. aaron.keshen@nshealth.ca. Department of Psychiatry Dalhousie University Halifax NS Canada. aaron.keshen@nshealth.ca.

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Effectiveness of expository based on digital learning repository for critical thinking skills of vocational students in digital simulation and communication subjects

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AIP Conference Proceedings 2023年第1期2590卷

作者： Basori Sajidan Muhammad Akhyar Wiranto Department of Education Science Doctoral Program Universitas Sebelas Maret Rd. Ir. Sutami 36A Kentingan Surakarta Indonesia Department of Informatics and Computer Engineering Education Universitas Sebelas Maret Rd. Ir. Sutami 36A Kentingan Surakarta Indonesia Department of Biology Education Universitas Sebelas Maret Rd. Ir. Sutami 36A Kentingan Surakarta Indonesia Department of Mechanical Engineering Education Universitas Sebelas Maret Rd. Ir. Sutami 36A Kentingan Surakarta Indonesia Department of Informatics Universitas Sebelas Maret Rd. Ir. Sutami 36A Kentingan Surakarta Indonesia

The competency to think critically is one of the skills that students must possess in the 21st century. This study aims to determine vocational students' critical thinking skills (CTs) in digital simulation and communication subjects using expository based on digital learning repository. This research uses quantitative descriptive. The samples of this study were students of class X SMK N 2 Surakarta. The instrument used is a multiple-choice test that developed based on indicators of CTs, according to Facione, which consist of interpretation, analysis, evaluation, inference, explanation, and self-regulation. The results of this study showed that the average percentage of students' CTs is in the sufficient category. The results of each indicator can be described as follows: (1) The interpretation indicator is 46.8% in the sufficient category, (2) The analysis indicator is 49.5% in the sufficient category, (3) The evaluation indicator is 60.5% in the sufficient category, (4) The inference indicator is 48, 4% in the sufficient category, (5) About 56.5% for the explanation indicator in the sufficient category, and (6) The self-regulation indicator is 64.5% in the high category. The results showed that students' CTs were still quite or moderate. Students' CTs need to be improved with innovative learning models and methods that will affect learning motivation and critical thinking skills towards various student problems in teaching and learning activities.

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Unveiling long COVID symptomatology, co-occurrence trends, and symptom distress post SARS-CoV-2 infection

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Journal of infection and public health 2024年第7期17卷 102464页

作者： Shikha Kukreti Chun-Yin Yeh Yi-Jhen Chen Meng-Ting Lu Ming-Chi Li Yi-Yin Lai Chung-Yi Li Nai-Ying Ko Department of Nursing College of Medicine National Cheng Kung University Tainan Taiwan Department of Public Health College of Medicine National Cheng Kung University Taiwan. Department of Computer Science and Information Engineering National Cheng Kung University Taiwan. Department of Internal Medicine National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan Taiwan. Centre of Infection Control College of Medicine National Cheng Kung University and Hospital Tainan Taiwan. Department of Public Health College of Medicine National Cheng Kung University Taiwan Department of Public Health College of Public Health China Medical University Taichung Department of Healthcare Administration College of Medical and Health Science Asia University Taichung Taiwan. International Doctoral Program in Nursing Department of Nursing College of Medicine National Cheng Kung University Tainan Taiwan. Electronic address: nyko@mail.ncku.edu.tw.

BACKGROUND:Long COVID, an emerging public health issue, is characterized by persistent symptoms following SARS-CoV-2 infection. This study aims to explore the relationship between post-COVID-19 symptomatology and patient distress employing Latent Class Analysis to uncover symptom co-occurrence patterns and their association with distress. METHODS:A cross-sectional study was conducted using an online survey among 240 participants from a university and affiliated hospital of southern Taiwan. The survey quantified distress due to persistent symptoms and assessed the prevalence of Long COVID, symptom co-occurrence, and latent symptom classes. Latent Class Analysis (LCA) identified distinct symptom patterns, and multiple regression models evaluated associations between symptom patterns, distress, and demographic factors. RESULTS:The study found that 80 % of participants experienced Long COVID, with symptoms persisting for over three months. Individuals with multiple COVID-19 infections showed a significant increase in general (β = 1.79), cardiovascular (β = 0.61), and neuropsychological symptoms (β = 2.18), and higher total distress scores (β = 6.35). Three distinct symptomatology classes were identified: "Diverse", "Mild", and "Severe" symptomatology. The "Mild Symptomatology" class was associated with lower distress (-10.61), while the "Severe Symptomatology" class showed a significantly higher distress due to symptoms (13.32). CONCLUSION:The study highlights the significant impact of Long COVID on individuals, with distinct patterns of symptomatology and associated distress. It emphasizes the cumulative effect of multiple COVID-19 infections on symptom severity and the importance of tailored care strategies.

关键词： Co-occurrence Distress Latent class Long COVID

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"So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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International Journal of Information Management 2023年 71卷

作者： Dwivedi, Yogesh K. Kshetri, Nir Hughes, Laurie Slade, Emma Louise Jeyaraj, Anand Kar, Arpan Kumar Baabdullah, Abdullah M. Koohang, Alex Raghavan, Vishnupriya Ahuja, Manju Albanna, Hanaa Albashrawi, Mousa Ahmad Al-Busaidi, Adil S. Balakrishnan, Janarthanan Barlette, Yves Basu, Sriparna Bose, Indranil Brooks, Laurence Buhalis, Dimitrios Carter, Lemuria Chowdhury, Soumyadeb Crick, Tom Cunningham, Scott W. Davies, Gareth H. Davison, Robert M. Dé, Rahul Dennehy, Denis Duan, Yanqing Dubey, Rameshwar Dwivedi, Rohita Edwards, John S. Flavián, Carlos Gauld, Robin Grover, Varun Hu, Mei-Chih Janssen, Marijn Jones, Paul Junglas, Iris Khorana, Sangeeta Kraus, Sascha Larsen, Kai R. Latreille, Paul Laumer, Sven Malik, F. Tegwen Mardani, Abbas Mariani, Marcello Mithas, Sunil Mogaji, Emmanuel Nord, Jeretta Horn O'Connor, Siobhan Okumus, Fevzi Pagani, Margherita Pandey, Neeraj Papagiannidis, Savvas Pappas, Ilias O. Pathak, Nishith Pries-Heje, Jan Raman, Ramakrishnan Rana, Nripendra P. Rehm, Sven-Volker Ribeiro-Navarrete, Samuel Richter, Alexander Rowe, Frantz Sarker, Suprateek Stahl, Bernd Carsten Tiwari, Manoj Kumar van der Aalst, Wil Venkatesh, Viswanath Viglia, Giampaolo Wade, Michael Walton, Paul Wirtz, Jochen Wright, Ryan Digital Futures for Sustainable Business & Society Research Group School of Management Swansea University Bay Campus Fabian Bay Wales Swansea United Kingdom Maharashtra Pune India Bryan School of Business and Economics University of North Carolina at Greensboro United States University of Bristol Business School University of Bristol BS8 1SD United Kingdom Professor of Information Systems Raj Soin College of Business Wright State University 3640 Colonel Glenn Highway DaytonOH45435 United States School of Artificial Intelligence Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Studies Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Information Systems Faculty of Economics and Administration King Abdulaziz University Jeddah Saudi Arabia School of Computing Middle Georgia State University MaconGA United States Client Advisory and Transformation Stackroute NIIT Limited India Department of Information Systems Analytics and Operations College of Business University of Louisville United States Northumbria University London United Kingdom IRC-FDE KFUPM Saudi Arabia ISOM KFUPM Business School KFUPM Saudi Arabia Innovation and Technology Transfer Center Sultan Qaboos University Oman Department of Business Communication Sultan Qaboos University Oman Department of Management Studies National Institute of Technology Tiruchirappalli India Montpellier France FORE School of Management New Delhi India Indian Institute of Management Ahmedabad Vastrapur Ahmedabad380015 India Information School University of Sheffield United Kingdom Bournemouth University Business School Poole United Kingdom School of Information Systems and Technology Management University of New South Wales Sydney Australia Information Operations and Management Sciences Department TBS Business School 1 Place Alphonse Jourdain Toulouse31068 France Department of Education & Childhood Studies Swansea Univers

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics;digital transformation of organisations and societies;and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI;examining biases of generative AI attributable to training datasets and processes;exploring business and societal contexts best suited for generative AI implementation;determining optimal combinations of human and generative AI for various tasks;identifying ways to assess accuracy of text produced by generative AI;and uncovering the ethical and legal issues in using generative AI across different contexts. © 2023 The Authors

关键词： Marketing

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Author Correction: The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

npj biodiversity

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npj biodiversity 2024年第1期3卷 31页

作者： Ann M Mc Cartney Giulio Formenti Alice Mouton Diego De Panis Luísa S Marins Henrique G Leitão Genevieve Diedericks Joseph Kirangwa Marco Morselli Judit Salces-Ortiz Nuria Escudero Alessio Iannucci Chiara Natali Hannes Svardal Rosa Fernández Tim De Pooter Geert Joris Mojca Strazisar Jonathan M D Wood Katie E Herron Ole Seehausen Phillip C Watts Felix Shaw Robert P Davey Alice Minotto José M Fernández Astrid Böhne Carla Alegria Tyler Alioto Paulo C Alves Isabel R Amorim Jean-Marc Aury Niclas Backstrom Petr Baldrian Laima Baltrunaite Endre Barta Bertrand BedHom Caroline Belser Johannes Bergsten Laurie Bertrand Helena Bilandija Mahesh Binzer-Panchal Iliana Bista Mark Blaxter Paulo A V Borges Guilherme Borges Dias Mirte Bosse Tom Brown Rémy Bruggmann Elena Buena-Atienza Josephine Burgin Elena Buzan Alessia Cariani Nicolas Casadei Matteo Chiara Sergio Chozas Fedor Čiampor Angelica Crottini Corinne Cruaud Fernando Cruz Love Dalen Alessio De Biase Javier Del Campo Teo Delic Alice B Dennis Martijn F L Derks Maria Angela Diroma Mihajla Djan Simone Duprat Klara Eleftheriadi Philine G D Feulner Jean-François Flot Giobbe Forni Bruno Fosso Pascal Fournier Christine Fournier-Chambrillon Toni Gabaldon Shilpa Garg Carmela Gissi Luca Giupponi Jessica Gomez-Garrido Josefa González Miguel L Grilo Björn Grüning Thomas Guerin Nadege Guiglielmoni Marta Gut Marcel P Haesler Christoph Hahn Balint Halpern Peter W Harrison Julia Heintz Maris Hindrikson Jacob Höglund Kerstin Howe Graham M Hughes Benjamin Istace Mark J Cock Franc Janžekovič Zophonias O Jonsson Sagane Joye-Dind Janne J Koskimäki Boris Krystufek Justyna Kubacka Heiner Kuhl Szilvia Kusza Karine Labadie Meri Lähteenaro Henrik Lantz Anton Lavrinienko Lucas Leclère Ricardo Jorge Lopes Ole Madsen Ghislaine Magdelenat Giulia Magoga Tereza Manousaki Tapio Mappes Joao Pedro Marques Gemma I Martinez Redondo Florian Maumus Shane A McCarthy Hendrik-Jan Megens Jose Melo-Ferreira Sofia L Mendes Matteo Montagna Joao Moreno Mai-Britt Mosbech Mónica Moura Zuzana Musilova Eugene Myers Will J N Genomics Institute University of California Santa Cruz CA USA. anmmccar@ucsc.edu. The Vertebrate Genome Laboratory The Rockefeller University New York NY USA. Department of Biology University of Florence Sesto Fiorentino Italy. InBios-Conservation Genetics Laboratory University of Liege Liege Belgium. Leibniz Institut für Zoo und Wildtierforschung Berlin Germany. Berlin Center for Genomics in Biodiversity Research Berlin Germany. Department of Biology University of Antwerp Antwerp Belgium. Institute of Zoology University of Cologne Cologne Germany. Department of Chemistry Life Sciences and Environmental Sustainability University of Parma Parma Italy. Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra) Barcelona Spain. Naturalis Biodiversity Center Leiden The Netherlands. Neuromics Support Facility VIB Center for Molecular Neurology VIB Antwerp Belgium. Neuromics Support Facility Department of Biomedical Sciences University of Antwerp Antwerp Belgium. Tree of Life Wellcome Sanger Institute Hinxton Cambridge UK. School of Biology and Environmental Science University College Dublin Belfield Ireland. Aquatic Ecology & Evolution Institute of Ecology & Evolution University of Bern Bern Switzerland. Department of Fish Ecology & Evolution Eawag Kastanienbaum Switzerland. Department of Biological and Environmental Science University of Jyvaskyla Jyvaskyla Finland. The Earlham Institute Norwich Research Park Norwich UK. Digital Science London UK. Barcelona Supercomputing Center Spanish National Bioinformatics Institute ELIXIR Spain Getafe Spain. Leibniz Institute for the Analysis of Biodiversity Change Museum Koenig Bonn Bonn Germany. CE3C-Centre for Ecology Evolution and Environmental Changes & CHANGE-Global Change and Sustainability Institute Faculdade de Ciências Universidade de Lisboa Campo Grande Lisboa Portugal. Centro Nacional de Análisis Genómico (CNAG) Barcelona Spain. Universitat de Barcelona (UB) Barcelona Spain. CIBIO C

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