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Publisher Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

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Nature genetics 2023年第1期55卷 166页

作者： Huipeng Li Elise T Courtois Debarka Sengupta Yuliana Tan Kok Hao Chen Jolene Jie Lin Goh Say Li Kong Clarinda Chua Lim Kiat Hon Wah Siew Tan Mark Wong Paul Jongjoon Choi Lawrence J K Wee Axel M Hillmer Iain Beehuat Tan Paul Robson Shyam Prabhakar Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India. Synthetic Biology Genome Institute of Singapore Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. Department of Pathology Singapore General Hospital Singapore Singapore. Department of Colorectal Surgery Singapore General Hospital Singapore Singapore. Data Analytics Department Institute for Infocomm Research Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. paul.robson@***. The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA. paul.robson@***. Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA. paul.robson@***. Department of Biological Sciences National University of Singapore Singapore Singapore. paul.robson@***. Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. prabhakars@gis.a-star.edu.sg.

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Publisher Correction: Comprehensive molecular characterization of mitochondrial genomes in human cancers

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Nature genetics 2023年第5期55卷 893页

作者： Yuan Yuan Young Seok Ju Youngwook Kim Jun Li Yumeng Wang Christopher J Yoon Yang Yang Inigo Martincorena Chad J Creighton John N Weinstein Yanxun Xu Leng Han Hyung-Lae Kim Hidewaki Nakagawa Keunchil Park Peter J Campbell Han Liang Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon Korea. Department of Health Science and Technology Samsung Advanced Institute for Health Science and Technology Sungkyunkwan University School of Medicine Seoul Korea. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. Division of Biostatistics The University of Texas Health Science Center at Houston School of Public Health Houston TX USA. Department of Medicine and Dan L. Duncan Cancer Center Division of Biostatistics Baylor College of Medicine Houston TX USA. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD USA. Department of Biochemistry and Molecular Biology The University of Texas Health Science Center at Houston McGovern Medical School Houston TX USA. Department of Biochemistry Ewha Womans University School of Medicine Seoul Korea. Laboratory for Cancer Genomics RIKEN Center for Integrative Medical Sciences Yokohama Japan. Division of Hematology/Oncology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Korea. kpark@skku.edu. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. pc8@sanger.ac.uk. Cambridge University Hospitals NHS Foundation Trust Cambridge UK. pc8@sanger.ac.uk. Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@***. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. hliang1@***. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@mdanderson

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Author Correction: Comprehensive molecular characterization of mitochondrial genomes in human cancers

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Nature genetics 2023年第6期55卷 1078页

作者： Yuan Yuan Young Seok Ju Youngwook Kim Jun Li Yumeng Wang Christopher J Yoon Yang Yang Inigo Martincorena Chad J Creighton John N Weinstein Yanxun Xu Leng Han Hyung-Lae Kim Hidewaki Nakagawa Keunchil Park Peter J Campbell Han Liang Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon Korea. Department of Health Science and Technology Samsung Advanced Institute for Health Science and Technology Sungkyunkwan University School of Medicine Seoul Korea. Samsung Genome Institute Samsung Medical Center Seoul Korea. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. Division of Biostatistics The University of Texas Health Science Center at Houston School of Public Health Houston TX USA. Department of Medicine and Dan L. Duncan Cancer Center Division of Biostatistics Baylor College of Medicine Houston TX USA. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD USA. Department of Biochemistry and Molecular Biology The University of Texas Health Science Center at Houston McGovern Medical School Houston TX USA. Department of Biochemistry Ewha Womans University School of Medicine Seoul Korea. Laboratory for Cancer Genomics RIKEN Center for Integrative Medical Sciences Yokohama Japan. Division of Hematology/Oncology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Korea. kpark@skku.edu. Samsung Advanced Institute for Health Sciences and Technology Sungkyunkwan University School of Medicine Seoul South Korea. kpark@skku.edu. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. pc8@sanger.ac.uk. Department of Haematology University of Cambridge Cambridge UK. pc8@sanger.ac.uk. Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@mdanderson.org. Quantitative and Comp

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Quantum Simulation for High-Energy Physics

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PRX Quantum 2023年第2期4卷 027001-027001页

作者： Christian W. Bauer Zohreh Davoudi A. Baha Balantekin Tanmoy Bhattacharya Marcela Carena Wibe A. de Jong Patrick Draper Aida El-Khadra Nate Gemelke Masanori Hanada Dmitri Kharzeev Henry Lamm Ying-Ying Li Junyu Liu Mikhail Lukin Yannick Meurice Christopher Monroe Benjamin Nachman Guido Pagano John Preskill Enrico Rinaldi Alessandro Roggero David I. Santiago Martin J. Savage Irfan Siddiqi George Siopsis David Van Zanten Nathan Wiebe Yukari Yamauchi Kübra Yeter-Aydeniz Silvia Zorzetti Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics Maryland Center for Fundamental Physics and the NSF Institute for Robust Quantum Simulation University of Maryland College Park Maryland 20742 USA Department of Physics University of Wisconsin Madison Wisconsin 53706 USA T-2 Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Fermi National Accelerator Laboratory Batavia Illinois 60510 USA Enrico Fermi Institute University of Chicago Chicago Illinois 60637 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Physics University of Chicago Chicago Illinois 60637 USA Department of Physics and Illinois Center for the Advanced Study of the Universe and Illinois Quantum Information Science and Technology Center University of Illinois Urbana Illinois 61801 USA QuEra Computing Inc Boston Massachusetts 02135 USA Department of Mathematics University of Surrey Guildford Surrey GU2 7XH United Kingdom Center for Nuclear Theory Department of Physics and Astronomy Stony Brook University New York 11794-3800 USA Department of Physics Brookhaven National Laboratory Upton New York 11973 USA Peng Huanwu Center for Fundamental Theory Hefei Anhui 230026 China Interdisciplinary Center for Theoretical Study University of Science and Technology of China Hefei Anhui 230026 China Pritzker School of Molecular Engineering Chicago Quantum Exchange and Kadanoff Center for Theoretical Physics University of Chicago Illinois 60637 USA qBraid Co. Harper Court 5235 Chicago Illinois 60615 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA Department of Physics and Astronomy University of Iowa Iowa City Iowa 52242 USA Duke Quantum Center Duke University Durham North Carolina 27701 USA Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA Department of Physics Duke University

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community. This fact speaks of a remarkable rate of growth of this subfield over the past few years, stimulated by the impressive advancements in quantum information sciences (QIS) and associated technologies over the past decade, and the significant investment in this area by the government and private sectors in the U.S. and other countries. High-energy physicists have quickly identified problems of importance to our understanding of nature at the most fundamental level, from tiniest distances to cosmological extents, that are intractable with classical computers but may benefit from quantum advantage. They have initiated, and continue to carry out, a vigorous program in theory, algorithm, and hardware co-design for simulations of relevance to the HEP mission. This Roadmap is an attempt to bring this exciting and yet challenging area of research to the spotlight, and to elaborate on what the promises, requirements, challenges, and potential solutions are over the next decade and beyond.

关键词： Quantum simulation

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An Early Warning Approach to Monitor COVID-19 Activity with Multiple Digital Traces in Near Real-Time

arXiv

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arXiv 2020年

作者： Kogan, Nicole E. Clemente, Leonardo Liautaud, Parker Kaashoek, Justin Link, Nicholas B. Nguyen, Andre T. Lu, Fred S. Huybers, Peter Resch, Bernd Havas, Clemens Petutschnig, Andreas Davis, Jessica Chinazzi, Matteo Mustafa, Backtosch Hanage, William P. Vespignani, Alessandro Santillana, Mauricio Computational Health Informatics Program Boston Children’s Hospital BostonMA United States Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Department of Earth and Planetary Sciences Harvard University CambridgeMA United States School of Engineering and Applied Sciences Harvard University CambridgeMA United States University of Maryland Baltimore County BaltimoreMD United States Booz Allen Hamilton ColumbiaMD United States Department of Statistics Stanford University StanfordCA United States Department of Geoinformatics - Z GIS University of Salzburg Salzburg Austria Center for Geographic Analysis Harvard University CambridgeMA United States Northeastern University BostonMA United States Department of Pediatrics Harvard Medical School BostonMA United States University Medical Center Hamburg-Eppendorf Hamburg Germany

Non-pharmaceutical interventions (NPIs) have been crucial in curbing COVID-19 in the United States (US). Consequently, relaxing NPIs through a phased re-opening of the US amid still-high levels of COVID-19 susceptibility could lead to new epidemic waves. This calls for a COVID-19 early warning system. Here we evaluate multiple digital data streams as early warning indicators of increasing or decreasing state-level US COVID-19 activity between January and June 2020. We estimate the timing of sharp changes in each data stream using a simple Bayesian model that calculates in near real-time the probability of exponential growth or decay. Analysis of COVID-19-related activity on social network microblogs, Internet searches, point-of-care medical software, and a metapopulation mechanistic model, as well as fever anomalies captured by smart thermometer networks, shows exponential growth roughly 2-3 weeks prior to comparable growth in confirmed COVID-19 cases and 3-4 weeks prior to comparable growth in COVID-19 deaths across the US over the last 6 months. We further observe exponential decay in confirmed cases and deaths 5-6 weeks after implementation of NPIs, as measured by anonymized and aggregated human mobility data from mobile phones. Finally, we propose a combined indicator for exponential growth in multiple data streams that may aid in developing an early warning system for future COVID-19 outbreaks. These efforts represent an initial exploratory framework, and both continued study of the predictive power of digital indicators as well as further development of the statistical approach are needed. Copyright © 2020, The Authors. All rights reserved.

关键词： Search engines

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Low-temperature electron-phonon interaction of quantum emitters in hexagonal boron nitride

arXiv

引用

arXiv 2019年

作者： Grosso, Gabriele Moon, Hyowon Ciccarino, Christopher J. Flick, Johannes Mendelson, Noah Toth, Milos Aharonovich, Igor Narang, Prineha Englund, Dirk R. Advanced Science Research Center City University of New York Photonics Initiative New YorkNY United States Physics Program Graduate Center City University of New York New YorkNY United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States School of Mathematical and Physical Sciences University of Technology Sydney UltimoNSW2007 Australia Center for Computational Quantum Physics Flatiron Institute New YorkNY United States

关键词： Electron-phonon interactions

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Data-augmented modeling of intracranial pressure

arXiv

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arXiv 2018年

作者： Wang, Jian-Xun Hu, Xiao Shadden, Shawn C. Mechanical Engineering University of California BerkeleyCA United States Aerospace and Mechanical Engineering Center of Informatics and Computational Science University of Notre Dame Notre DameIN United States Department of Physiological Nursing Department of Neurological surgery Institute of Computational Health Sciences UCSF Joint Bio-Engineering Graduate Program University of California San FranciscoCA United States

Precise management of patients with cerebral diseases often requires intracranial pressure (ICP) monitoring, which is highly invasive and requires a specialized ICU setting. The ability to noninvasively estimate ICP is highly compelling as an alternative to, or screening for, invasive ICP measurement. Most existing approaches for noninvasive ICP estimation aim to build a regression function that maps noninvasive measurements to an ICP estimate using statistical learning techniques. These data-based approaches have met limited success, likely because the amount of training data needed is onerous for this complex applications. In this work, we discuss an alternative strategy that aims to better utilize noninvasive measurement data by leveraging mechanistic understanding of physiology. Specifically, we developed a Bayesian framework that combines a multiscale model of intracranial physiology with noninvasive measurements of cerebral blood flow using transcranial Doppler. Virtual experiments with synthetic data are conducted to verify and analyze the proposed framework. A preliminary clinical application study on two patients is also performed in which we demonstrate the ability of this method to improve ICP prediction. Copyright © 2018, The Authors. All rights reserved.

关键词： Diagnosis

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Paralog-divergent Features May Help Reduce Off-target Effects of Drugs:Hints from Glucagon Subfamily Analysis

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Genomics, Proteomics & Bioinformatics 2017年第4期15卷 246-254页

作者： Zhining Sa Jingqi Zhou Yangyun Zou Zhixi Su Xun Gu State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology School of LifeSciencesFudan UniversityShanghai 200433China Department of Genetics Development and Cell BiologyProgram of Bioinformatics and Computational BiologyIowa State UniversityAmesIA 50011USA

Side effects from targeted drugs remain a serious conccrn. One reason is the nonselective binding of a drug to unintended proteins such as its paralogs, which arc highly homologous in sequences and have similar structures and drug-binding pockets. To identify targctablc differences between paralogs, we analyzed two types （type-I and type-ll） of functional divergence between two paralogs in the known target protein receptor family G-protein coupled receptors （GPCRs） at the amino acid level. Paralogous protein receptors in glucagon-like subfamily, glucagon receptor （GCGR） and glucagon-like peptide-I receptor （GLP-I R）, exhibit divergence in ligands and are clinically validated drug targets for type 2 diabetes. Our data showed that type-ll alnino acids were significantly enriched in the binding sites of antagonist MK-0893 to GCGR. which had a radical shift in physicochemical properties between GCGR and GLP-1R. We also examined the role of type-I amino acids between GCGR and GLP-IR. The divergent features between GCGR and GLP-I R paralogs may be helpful in their discrimination, thus enabling the identification of binding sites to reduce undesirable side effects and increase the target specificity of drugs.

关键词： Paralog Functional divergence Functional site Drug specificity Evolutionary conservation

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Native diversity buffers against severity of non-native tree invasions ( vol 621,pg 773 , 2023 )

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NATURE 2023年第7982期622卷 E2-E2页

作者： Delavaux, Camille S. Crowther, Thomas W. Zohner, Constantin M. Robmann, Niamh M. Lauber, Thomas van den Hoogen, Johan Kuebbing, Sara Liang, Jingjing de-Miguel, Sergio Nabuurs, Gert-Jan Reich, Peter B. Abegg, Meinrad Yao, Yves C. Adou Alberti, Giorgio Zambrano, Angelica M. Almeyda Alvarado, Braulio Vilchez Alvarez-Davila, Esteban Alvarez-Loayza, Patricia Alves, Luciana F. Ammer, Christian Anton-Fernandez, Clara Araujo-Murakami, Alejandro Arroyo, Luzmila Avitabile, Valerio Aymard, Gerardo A. Baker, Timothy R. Balazy, Radomir Banki, Olaf Barroso, Jorcely G. Bastian, Meredith L. Bastin, Jean-Francois Birigazzi, Luca Birnbaum, Philippe Bitariho, Robert Boeckx, Pascal Bongers, Frans Bouriaud, Olivier Brancalion, Pedro H. S. Brandl, Susanne Brienen, Roel Broadbent, Eben N. Bruelheide, Helge Bussotti, Filippo Gatti, Roberto Cazzolla Cesar, Ricardo G. Cesljar, Goran Chazdon, Robin Chen, Han Y. H. Chisholm, Chelsea Cho, Hyunkook Cienciala, Emil Clark, Connie Clark, David Colletta, Gabriel D. Coomes, David A. Valverde, Fernando Cornejo Corral-Rivas, Jose J. Crim, Philip M. Cumming, Jonathan R. Dayanandan, Selvadurai de Gasper, Andre L. Decuyper, Mathieu Derroire, Geraldine DeVries, Ben Djordjevic, Ilija Dolezal, Jiri Dourdain, Aurelie Obiang, Nestor Laurier Engone Enquist, Brian J. Eyre, Teresa J. Fandohan, Adande Belarmain Fayle, Tom M. Feldpausch, Ted R. Ferreira, Leandro V. Fischer, Markus Fletcher, Christine Frizzera, Lorenzo Gamarra, Javier G. P. Gianelle, Damiano Glick, Henry B. Harris, David J. Hector, Andrew Hemp, Andreas Hengeveld, Geerten Herault, Bruno Herbohn, John L. Herold, Martin Hillers, Annika Coronado, Euridice N. Honorio Hui, Cang Ibanez, Thomas T. Amaral, Ieda Imai, Nobuo Jagodzinski, Andrzej M. Jaroszewicz, Bogdan Johannsen, Vivian Kvist Joly, Carlos A. Jucker, Tommaso Jung, Ilbin Karminov, Viktor Kartawinata, Kuswata Kearsley, Elizabeth Kenfack, David Kennard, Deborah K. Kepfer-Rojas, Sebastian Keppel, Gunnar Khan, Mohammed Latif Killeen, Timothy J. Kim, Hyun Seok Kitayama, Kanehiro Kohl, Michael Korju Institute of Integrative Biology ETH Zurich (Swiss Federal Institute of Technology) Zurich Switzerland Department of Genetics Evolution and Environment University College London London UK The Forest School at The Yale School of the Environment Yale University New Haven CT USA Department of Forestry and Natural Resources Purdue University West Lafayette IN USA Department of Agriculture Forestry and Bioresources Seoul National University Seoul South Korea Department of Crop and Forest Sciences University of Lleida Lleida Spain Joint Research Unit CTFC–AGROTECNIO–CERCA Solsona Spain Wageningen University and Research Wageningen The Netherlands World Agroforestry (ICRAF) Nairobi Kenya Department of Forest Resources University of Minnesota St Paul MN USA Hawkesbury Institute for the Environment Western Sydney University Penrith New South Wales Australia Institute for Global Change Biology and School for Environment and Sustainability University of Michigan Ann Arbor MI USA Swiss Federal Institute for Forest Snow and Landscape Research WSL Birmensdorf Switzerland UFR Biosciences University Félix Houphouët-Boigny Abidjan Côte d’Ivoire Department of Agricultural Food Environmental and Animal Sciences University of Udine Udine Italy Faculty of Science and Technology Free University of Bolzano Bolzano Italy Spatial Ecology and Conservation Laboratory Department of Tourism Recreation and Sport Management University of Florida Gainesville FL USA Forestry School Tecnológico de Costa Rica TEC Cartago Costa Rica Fundacion ConVida Universidad Nacional Abierta y a Distancia UNAD Medellin Colombia Field Museum of Natural Histiory Chicago IL USA Center for Tropical Research Institute of the Environment and Sustainability UCLA Los Angeles CA USA Silviculture and Forest Ecology of the Temperate Zones University of Göttingen Göttingen Germany Division of Forest and Forest Resources Norwegian Institute of Bioeconomy Research (NIBIO) Ås Norway Museo de Hi

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