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Estimating wetland CH4 emissions on the Qinghai-Tibetan Plateau based on a processed model coupled with inundation dynamics between 1960 and 2100

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Science of the Total Environment 2024年 955卷 177169页

作者： Zhang, Jiang Chen, Huai Peng, Changhui Huang, Yuanyuan Wang, Yike Liu, Xinwei Wang, Meng Wang, Le Yu, Dongxue Zhu, Qiuan Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Chengdu Institute of Biology Chinese Academy of Sciences Chengdu610041 China Institute of Environment Sciences Department of Biology Sciences University of Quebec at Montreal Case Postale 8888 Succursale Centre-Ville MontrealQCH3C 3P8 Canada School of Geography Science Hunan Normal University Changsha410081 China Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains Ministry of Education School of Geographical Sciences Northeast Normal University Changchun130024 China Key Laboratory of Soil and Water Processes in Watershed College of Geography and Remote Sensing Hohai University Nanjing210098 China National Earth System Science Data Center National Science & Technology Infrastructure of China Beijing100101 China

Quantifying the impacts of climate change and wetland area dynamics on methane (CH4) emissions in the Qinghai-Tibetan Plateau (QTP) is crucial for enhancing our understanding of regional and global CH4 budgets. However, a major source of uncertainty in estimating wetland methane emissions stems from the limited delineation of wetland area dynamics. In this study, we integrated dynamic wetland inundation schemes into a process-based model to quantify the contributions of wetland area variations to natural wetland CH4 emissions on the QTP, both historically and in the future. The results revealed that climate change significantly influenced the spatiotemporal distribution of wetland CH4 emissions, with wetland inundation dynamics contributing between 21.84 % and 27.18 % of the increase in CH4 emissions from 1960 to 2020. Under future climate change scenarios, wetland CH4 emissions are projected to exhibit a more pronounced increasing trend, with wetland inundation dynamics projected to contribute 18.94 % to 21.80 % of the increase in CH4 emissions in the QTP under seven Shared Socioeconomic Pathways scenarios. © 2024 Elsevier B.V.

关键词： Greenhouse gas emissions

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An Early Detection Model of Prostate Cancer Based on MRI

An Early Detection Model of Prostate Cancer Based on MRI

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IEEE International Conference on data Science in Cyberspace (DSC)

作者： Yuankun Liu Lumin Xing Di Wang Xin Nie Xueyan Zhang Di Wu Wenjian Liu Faculty of Data Science City University of Macau China Shandong Provincial Qianfoshan Hospital The First Affiliated Hospital of Shandong First Medical University Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Chongqing Jianzhu College Chongqing China School of Information Work Office Shandong Youth University of Political Science Jinan China School of Mathematics Physics and Computing University of Southern Queensland Queensland Australia

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

Prostate cancer is a prevalent form of cancer among men, with a high rate of occurrence but relatively lower mortality compared to other types of cancer. Early detection is crucial because it allows for earlier intervention, potentially preventing progression to more severe stages, and improving patient outcomes. However, human diagnosis is time-consuming and inefficient, an autonomous early detection system is essential for saving lives. To address this challenge, we propose a novel MoE-MRIViT framework that uses advanced machine learning and computer vision techniques to analyze MRI images and identify features indicative of prostate cancer. The system processes the data using a vision transformer to extract precise prostate cancer features from MRI scans, and uses attention mechanisms to focus on significant areas. Through the MoE-MRIViT intervention in two stages, we have achieved superior results compared to the state-of-the-art (SOTA) methods. Experimental results demonstrate that our model achieves an impressive accuracy of 94.84%, outperforming the ResNet-101 and the basic ViT models, which achieve accuracies of 89.4% and 92.31%, respectively.

关键词： Computer vision Visualization Accuracy Magnetic resonance imaging Mortality Transformers Feature extraction Reliability Prostate cancer Medical diagnostic imaging

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Exploiting Gabor Feature Extraction Method for Chinese Character Writing Quality Evaluation

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Journal of Physics: Conference Series 2020年第1期1575卷

作者： Zhixiao Wang Wenyao Yan Mingtao Guo Jiulong Zhang School of Computer Science and Engineering Xi'an University of Technology Xi'an 710048 China Shaanxi Key Laboratory Xi'an of Network Computing and Security Technology China School of Data Science and Computer Xi'an innovation college of Yan'an University Xi'an 710100 China

The automatic evaluation of Chinese character writing quality has a wide application prospect. Most of the existing evaluation methods of Chinese character writing quality are based on radical segmentation and feature judgment, which require the high accuracy of Chinese character segmentation. However, there are many problems in the real handwriting, such as continuous writing, uneven strength of writing, personalized writing style and so on, which lead to the difficulty of segmentation in the ordinary handwriting. To solve the above problems, we propose an effective method based on image texture where the uniformity of writing lines and writing style is taken as an effective criterion. In our method, Gabor transform is used to extract the image features of writing samples, and finally the statistical learning method of support vector machine is used to effectively evaluate the writing quality. Experiments on multiple real datasets including CHAED show that our method is effective and accurate. The advantage of this method is that it does not need to segment fonts, and the cost of global feature extraction is small.

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Artificial Intelligence System for Detection and Screening of Cardiac Abnormalities using Electrocardiogram Images

arXiv

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arXiv 2023年

作者： Zhang, Deyun Geng, Shijia Zhou, Yang Xu, Weilun Wei, Guodong Wang, Kai Yu, Jie Zhu, Qiang Li, Yongkui Zhao, Yonghong Chen, Xingyue Zhang, Rui Fu, Zhaoji Zhou, Rongbo Yanqi, E. Fan, Sumei Zhao, Qinghao Cheng, Chuandong Peng, Nan Zhang, Liang Zheng, Linlin Chu, Jianjun Xu, Hongbin Tan, Chen Liu, Jian Tao, Huayue Liu, Tong Chen, Kangyin Jiang, Chenyang Liu, Xingpeng Hong, Shenda HeartVoice Medical Technology Hefei China HeartRhythm-HeartVoice Joint Laboratory Beijing China Heart Center Beijing Chao-Yang Hospital Capital Medical University Beijing China HeartRhythm Medical Beijing China Division of Life Sciences and Medicine University of Science and Technology of China Hefei China Department of Physiology School of Basic Medical Sciences Anhui Medical University Hefei China Department of Anatomy and Histoembryology School of Basic Medical Sciences Anhui Medical University Hefei China Department of Cardiology Peking University People's Hospital Beijing China Department of Neurosurgery The First Affiliated Hospital University of Science and Technology of China Hefei China Heart Center Anhui Chest Hospital Anhui Medical University Hefei China Department of Electrocardiography The First Affiliated Hospital Anhui Medical University Hefei China The Second People's Hospital of Hefei City Hefei China Information Center/Medical Big Data Office The First Affiliated Hospital Anhui Medical University Hefei China Department of Cardiology Hebei Yan Da Hospital Langfang China Network Information Center Second Hospital of Tianjin Medical University Tianjin China Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease Department of Cardiology Tianjin Institute of Cardiology Second Hospital of Tianjin Medical University Tianjin China Key Laboratory of Cardiovascular Intervention and Regenerative Medicine of Zhejiang Province Department of Cardiology Sir Run Run Shaw Hospital Zhejiang University School of Medicine Hangzhou China National Institute of Health Data Science Peking University Beijing China Institute of Medical Technology Health Science Center Peking University Beijing China

The artificial intelligence (AI) system has achieved expert-level performance in electrocardiogram (ECG) signal analysis. However, in underdeveloped countries or regions where the healthcare information system is imperfect, only paper ECGs can be provided. Analysis of real-world ECG images (photos or scans of paper ECGs) remains challenging due to complex environments or interference. In this study, we present an AI system developed to detect and screen cardiac abnormalities (CAs) from real-world ECG images. The system was evaluated on a large dataset of 52,357 patients from multiple regions and populations across the world. On the detection task, the AI system obtained area under the receiver operating curve (AUC) of 0.996 (hold-out test), 0.994 (external test 1), 0.984 (external test 2), and 0.979 (external test 3), respectively. Meanwhile, the detection results of AI system showed a strong correlation with the diagnosis of cardiologists (cardiologist 1 (R=0.794, p Copyright © 2023, The Authors. All rights reserved.

关键词： Electrocardiograms

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Revisiting Cloud Migration: Strategies and Methods

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Journal of Physics: Conference Series 2020年第1期1575卷

作者： Zhixiao Wang Wenyao Yan Wendong Wang School of Computer Science and Engineering Xi'an University of Technology Xi'an 710048 China Shaanxi Key Laboratory Xi'an of Network Computing and Security Technology China School of Data Science and Computer Xi'an innovation college of Yan'an University Xi'an 710100 China Yan'an University Xi'an 716000 China

Cloud computing attracts users with its advantage of unlimited resource supply where resources can be elastically expanded on demand and balanced-load at the same time. This means that the application in the cloud environment should run in the way of elastic expansion cluster. At present, most of the elastic expansion and load balancing technologies provided by IaaS level are oriented to virtual machines (VM), with little consideration of application level, which does not fundamentally meet the needs of users. Based on this, starting from the motivation of cloud migration, we first analyse the cloud migration technology from three aspects: migration object, migration means and migration objectives, then explore the cloud migration criteria and four cloud migration strategies at the application level in the cloud environment, and point out that cloud migration should be optimized and maintained in terms of elastic expansion, load balancing, security, etc.

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Transferring knowledge distillation for multilingual social event detection

arXiv

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arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

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Front Cover: International Journal of Intelligent Systems, Volume 37 Issue 11 November 2022

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International Journal of Intelligent Systems 2022年第11期37卷

作者： Xianjia Meng Yong Yang Ximeng Liu Nan Jiang School of Information Science and Technology Northwest University Xi'an People's Republic of China Fujian Province Key Laboratory of Information Security of Network System and College of Computer and Data Science Fuzhou University Fuzhou People's Republic of China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen People's Republic of China Department of Internet of Things School of Information Engineering East China Jiao Tong University Nanchang People's Republic of China

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Analysis of COVID-19 Guideline Quality and Change of Recommendations:A Systematic Review

健康数据科学（英文）

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健康数据科学（英文） 2022年第2期 3-24页

作者： Siya Zhao Shuya Lu Shouyuan Wu Zijun Wang Qiangqiang Guo Qianling Shi Hairong Zhang Juanjuan Zhang Hui Liu Yunlan Liu Xianzhuo Zhang Ling Wang Mengjuan Ren Ping Wang Hui Lan Qi Zhou Yajia Sun Jin Cao Qinyuan Li Janne Estill Joseph L.Mathew Hyeong Sik Ahn Myeong Soo Lee Xiaohui Wang Chenyan Zhou Yaolong Chen School of Public Health Lanzhou UniversityLanzhouChina Institute of Health Data Science Lanzhou UniversityLanzhouChina Department of Pediatric Sichuan Provincial People's HospitalUniversity of Electronic Science and Technology of ChinaChengduChina Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital ChengduChina School of Public Health Lanzhou UniversityLanzhouChina Evidence-Based Medicine Center School of Basic Medical SciencesLanzhou UniversityLanzhouChina The First School of Clinical Medicine Lanzhou UniversityLanzhouChina National Clinical Research Center for Child Health and Disorders Ministry of Education Key Laboratory of Child Development and DisordersChina International Science and Technology Cooperation Base of Child Development and Critical DisordersChildren's Hospital of Chongqing Medical UniversityChongqingChina Institute of Global Health University of GenevaGenevaSwitzerland Institute of Mathematical Statistics and Actuarial Science University of BernBernSwitzerland Advanced Pediatrics Centre PGIMER ChandigarhChandigarhIndia Department of Preventive Medicine Korea UniversitySeoulRepublic of Korea Korea Cochrane Centre SeoulRepublic of Korea Evidence Based Medicine SeoulRepublic of Korea Korea University School of Medicine SeoulRepublic of Korea Korea Institute of Oriental Medicine DaejeonRepublic of Korea University of Science and Technology DaejeonRepublic of Korea London Southbank University LondonUK Tianjin University of Traditional Chinese Medicine TianjinChina Institute of Health Data Science Lanzhou UniversityLanzhouChina Evidence-Based Medicine Center School of Basic Medical SciencesLanzhou UniversityLanzhouChina WHO Collaborating Centre for Guideline Implementation and Knowledge Translation LanzhouChina Guideline International Network Asia China Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province Lanzhou UniversityLanzhouChina Lanzhou University GRADE Center China

*** of coronavirus disease 2019(COVID-19)clinical practice guidelines(CPGs)and expert consensus statements have been developed and published since the outbreak of the ***,these CPGs are of widely variable ***,this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs,exploring factors that may influence their quality,and analyzing the change of recommendations in CPGs with evidence *** searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 *** assessment of the methodological and reporting qualities of CPGs was performed using the AGREE Ⅱinstrument and RIGHT *** and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19(remdesivir,glucocorticoids,hydroxychloroquine/chloroquine,interferon,and lopinavir-ritonavir)were also systematically *** the statistical inference was performed to identify factors associated with the quality of *** included a total of 92 COVID-19 CPGs developed by 19 ***,the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0％,and the AGREE Ⅱ domain score was 30.4％.The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year *** associated with high methodological and reporting qualities included the evidence-based development process,management of conflicts of interest,and use of established rating systems to assess the quality of evidence and strength of *** recommendations of only seven(7.6％)CPGs were informed by a systematic review of evidence,and these seven CPGs have relatively high methodological and reporting qualities,in which six of them fully meet the Institute of Medicine(IOM)criteria of ***,a rapid advice CPG developed by the World Health Organization(WHO)of the seven CPGs got the highest overall

关键词： covid-19 analysis quality review change guideline recommendations systematic

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Worldwide Soundscapes: A Synthesis of Passive Acoustic Monitoring Across Realms

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Global Ecology and Biogeography 2025年第5期34卷

作者： Kevin F. A. Darras Rodney A. Rountree Steven L. Van Wilgenburg Anna F. Cord Frederik Pitz Youfang Chen Lijun Dong Agnès Rocquencourt Camille Desjonquères Patrick Mauritz Diaz Tzu-Hao Lin Théophile Turco Louise Emmerson Tom Bradfer-Lawrence Amandine Gasc Sarah Marley Marcus Salton Laura Schillé Paul J. Wensveen Shih-Hung Wu Adriana C. Acero-Murcia Orlando Acevedo-Charry Matyáš Adam Jacopo Aguzzi Irmak Akoglu M. Clara P. Amorim Mina Anders Michel André Alexandre Antonelli Leandro Aparecido Do Nascimento Giulliana Appel Stephanie Archer Christos Astaras Andrey Atemasov Jamieson Atkinson Joël Attia Emanuel Baltag Luc Barbaro Fritjof Basan Carly Batist Julio Ernesto Baumgarten Just T. Bayle Sempere Kristen Bellisario Asaf Ben David Oded Berger-Tal Frédéric Bertucci Matthew G. Betts Iqbal S. Bhalla Thiago Bicudo Marta Bolgan Sara Bombaci Gerard Bota Martin Boullhesen Robert A. Briers Susannah Buchan Michal Budka Katie Burchard Giuseppa Buscaino Alice Calvente Marconi Campos-Cerqueira Maria Isabel Carvalho Gonçalves Maria Ceraulo Maite Cerezo-Araujo Gunnar Cerwén Adams A. Chaskda Maria Chistopolova Christopher W. Clark Kieran D. Cox Benjamin Cretois Chapin Czarnecki Luis P. da Silva Wigna da Silva Laurence H. De Clippele David de la Haye Ana Silvia de Oliveira Tissiani Devin de Zwaan M. Eugenia Degano Jessica Deichmann Joaquin del Rio Christian Devenish Ricardo Díaz-Delgado Pedro Diniz Dorgival Diógenes Oliveira-Júnior Thiago Dorigo Saskia Dröge Marina Duarte Adam Duarte Kerry Dunleavy Robert Dziak Simon Elise Hiroto Enari Haruka S. Enari Florence Erbs Britas Klemens Eriksson Pınar Ertör-Akyazi Nina C. Ferrari Luane Ferreira Abram B. Fleishman Paulo J. Fonseca Bárbara Freitas Nicholas R. Friedman Jérémy S. P. Froidevaux Svetlana Gogoleva Carolina Gonzaga José Miguel González Correa Eben Goodale Benjamin Gottesman Ingo Grass Jack Greenhalgh Jocelyn Gregoire Samuel Haché Jonas Hagge William Halliday Antonia Hammer Tara Hanf-Dressler Sylvain Haupert Samara Haver Becky Heath Daniel Hending Jose Hernandez-Blanco Dennis Higgs EFNO ECODIV INRAE Domaine des Barres Nogent-sur-Vernisson France Sustainable Agricultural Systems & Engineering Lab School of Engineering Westlake University Hangzhou Zhejiang China Chair of Computational Landscape Ecology Faculty of Environmental Sciences Dresden University of Technology Dresden Germany Biology Department University of Victoria Victoria British Columbia Canada The Fish Listener Waguoit Massachusetts USA Terrestrial Unit Prairie Region Canadian Wildlife Service Environment & Climate Change Canada Prairie & Northern Wildlife Research Centre Saskatoon Saskatchewan Canada Agro-ecological Modeling Group Faculty of Agriculture University of Bonn Bonn Germany Marine Mammal and Marine Bioacoustics Laboratory Department of Deep Sea Science Institute of Deep-sea Science and Engineering Chinese Academy of Sciences Sanya Hainan China Institut de Systématique Évolution Biodiversité Muséum National d’Histoire Naturelle Paris France Université Grenoble Alpes Université Savoie Mont Blanc CNRS LECA Grenoble France Climate Change and Biodiversity Hanns R. Neumann Stiftung Indonesia Muaradua Indonesia Biodiversity Research Center Academia Sinica Nankang Taipei Taiwan ENES Bioacoustics Research Laboratory University of Saint-Etienne CRNL CNRS UMR 5292 Inserm UMR_S 1028 Saint-Etienne France Australian Antarctic Division Science Branch Department of Climate Change Energy Environment and Water Channel Highway Kingston Tasmania Australia Biological and Environmental Sciences University of Stirling Stirling Scotland Centre for Conservation Science RSPB Edinburgh UK IMBE Aix Marseille Univ Avignon Univ CNRS IRD Aix-en-Provence France Scotland's Rural College Craibstone Estate Aberdeen UK BIOGECO INRAE University of Bordeaux Cestas France Westman Islands Research Centre University of Iceland Vestmannaeyjar Iceland Qigu Research Center Taiwan Biodiversity Research Institute Nantou County Taiwan Programa de Pós-graduação em Ecologia

Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location Worldwide, 12,343 sites, all ecosystem types. Time Period 1991 to present. Major Taxa Studied All soniferous taxa. Methods We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm 2 ) than aquatic sampling (0.3 and 1.8 sites/Mkm 2 in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio-temporal replication in freshwater habitats. Overall, this

关键词： ARU automated sound recorder biodiversity conservation biology ecoacoustics IUCN GET realm Passive Acoustic Monitoring phenology soundscape ecology

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