检索结果-内蒙古大学图书馆

LONG-TERM RECAPTURE OF WESTERN PAINTED TURTLE (CHRYSEMYS PICTA BELLII): LONGEVITY IMPLICATIONS

Northwestern Naturalist 2023年第1期104卷 72-76页

作者： Laura B Guderyahn Elaine M Stewart Sue G Beilke Catherine de Rivera Marc P Hayes Earth Environment and Society PhD Program Department of Environmental Science and Management Portland State University Portland OR 97207 USA (LBG) Metro – Conservation Program Portland OR 97232 USA (EMS) Independent Ecologist Tigard OR 97223 USA (SGB) Department of Environmental Science and Management Portland State University Portand OR 97207 USA (CDR) Aquatic and Herpetological Research LLC Eagle Point OR 97524 USA (MPH) .

Western Painted Turtles (Chrysemys picta bellii) are 1 of only 2 native turtles in the Pacific Northwest. In October 2021, we recaptured an adult male 21 y after it was initially marked. In 2000, it had at least 9 annuli, indicating an age of at least 30 y in 2021. This approximates only half the maximum known age for the larger C. picta species complex east of the continental divide (61 y). Further, in 2000, this adult male was 37–43 mm larger than the largest or oldest males recorded from eastern populations of C. p. bellii, which suggests that fundamental differences may exist in growth between eastern and western populations that may reflect different age-size relationships. These relationships, along with longevity data, are foundational to conservation that seeks to understand demography and survival in western populations. Study of eastern populations shows that determination of age limits may span decades, so collaboration for data-sharing over long timelines to understand the patterns in western populations will be crucial.

关键词： age Chrysemys picta bellii longevity marked recapture western North America Western Painted Turtle

来源：评论

学校读者我要写书评

暂无评论

An Interactive Dashboard to Study the Impact of Hurricane Florence on Food Bank Operations

An Interactive Dashboard to Study the Impact of Hurricane Fl...

引用

2020 International Conference on Computational science and Computational Intelligence, CSCI 2020

作者： Enyew, Bantwale Odubela, Kehinde Jiang, Steven Davis, Lauren North Carolina at State University Applied Science Technology Phd Program Greensboro United States North Carolina at State University Department of Industrial and Systems Engineering Greensboro United States

ISBN: (纸本)9781728176246

North Carolina is the third most hurricane-prone states in the US. In 2018, Hurricane Florence caused a lot of damages to households in North Carolina. The Food Bank of Central and Eastern North Carolina (FBCENC) serves 34 counties in North Carolina, and 22 of them were affected by Hurricane Florence. This research aims to investigate the impact of Hurricane Florence on the operations of FBCENC. We developed interactive dashboards to visualize food bank operational data and other relevant data and studied the trends and patterns of food distribution in three key stages: preparedness, response, and recovery. These dashboards enable food bank operations managers to explore and interact with the data with ease to explore the operational data at different stages, at different branch level, and on a different time scale (monthly, weekly, or daily). The impact on the operations of affected service areas vs. not affected areas could be investigated as well. The findings of this research will provide insight into how humanitarian relief agencies can better prepare for, respond to, and recover from the disruptions caused by hurricanes. © 2020 IEEE.

关键词： Hurricanes

来源：评论

学校读者我要写书评

暂无评论

A computational model for recovery from traumatic brain injury 63

A computational model for recovery from traumatic brain inju...

引用

63rd Annual Meeting of the International Society for the systems sciences, ISSS 2019

作者： Wakeland, Wayne Kenzie, Erin Systems Science Program Portland State University United States

A computational simulation model calculates estimated recovery trajectories following traumatic brain injury (TBI). Prior publications include a multi-scale conceptual framework for studying concussion, a systems-level causal loop diagram (CLD) and an analysis of key feedback processes. A set of first order ordinary differential equations and their associated parameters determines recovery trajectories. The model contains 15 state variables, 73 auxiliary variables, and 50 parameters describing TBI pathology in an aggregate fashion at the cellular, network, cognitive and social levels. There are 1200 feedback loops, which give rise to a variety of behavior modes, many of which are highly nonlinear. Exogenous parameters include patient and injury characteristics, treatments, and time constants for recovery processes. Model testing has focused on reviewing the causal diagram with subject matter experts and determining sensitivity of model results to injury severity and patient characteristics, especially the time constants associated with healing/recovery processes. The model produces outcome trajectories that represent quick or slow recovery with no deficits, partial recovery, and the patient remaining indefinitely in a pathological state. While highly speculative, the model serves to demonstrate the potential utility of computational models in this context and to further discussion about the complex dynamics involved in recovery from TBI. The model also generates counterintuitive results, as is characteristic of complex systems. Much more research will be needed to create a properly supported research model that could be used or for precision medicine or to aid clinical trial design. © Copyright Wayne Wakeland 2019. All rights reserved.

关键词： Recovery

来源：评论

学校读者我要写书评

暂无评论

Melatonin and the Skin: Current Progress and Perspectives for Human Health

引用

Journal of Investigative Dermatology 2025年第6期145卷 1345-1360.e2页

作者： Slominski, Andrzej T. Kim, Tae-Kang Janjetovic, Zorica Slominski, Radomir M. Ganguli-Indra, Gitali Athar, Mohammad Indra, Arup K. Reiter, Russel J. Kleszczyński, Konrad Department of Dermatology Heersink School of Medicine The University of Alabama at Birmingham Birmingham AL United States Cancer Chemoprevention Program Comprehensive Cancer Center The University of Alabama at Birmingham Birmingham AL United States Pathology and Laboratory Medicine Service VA Medical Center Birmingham AL United States Department of Medicine-Immunology/Rheumatology The University of Alabama at Birmingham Birmingham AL United States Informatics Institute The University of Alabama at Birmingham Birmingham AL United States Department of Pharmaceutical Sciences College of Pharmacy Oregon State University Corvallis OR United States Knight Cancer Institute Oregon Health & Science University Portland OR United States Department of Dermatology Oregon Health & Science University Portland OR United States Department of Cell Systems and Anatomy Long School of Medicine UT Health San Antonio San Antonio TX United States Department of Dermatology University of Münster Münster Germany

Skin has the capacity to produce and metabolize melatonin into biologically active metabolites. These metabolites exert phenotypic activities through receptor-dependent and receptor-independent action, including direct antioxidant activity, interaction with regulatory proteins, and regulation of mitochondrial function. They can act on G-protein–coupled melatonin receptors (MT1 and MT2) as well as nuclear aryl hydrocarbon receptor and peroxisome proliferator–activated receptor γ receptors. These metabolic pathways, together with receptor- and nonreceptor-mediated phenotypic activities of its intermediates, has been identified as a cutaneous melatoninergic system. Its pharmacological modulation and topical application of melatonin or its metabolites can be used to prevent and treat skin disorders and cutaneous aging. © 2024 The Authors

关键词： Human skin Melatonin Melatonin metabolites Melatonin receptors Photoprotection

来源：评论

学校读者我要写书评

暂无评论

How Microbes Shape Their Communities? A Microbial Community Model Based on Functional Genes

引用

Genomics, Proteomics & Bioinformatics 2019年第1期17卷 91-105页

作者： Xiaoqing Jiang Xin Li Longshu Yang Chunhong Liu Qi Wang Weilai Chi Huaiqiu Zhu State Key Laboratory for Turbulence and Complex Systems Department of Biomedical Engineering College of Engineering Peking University Center for Quantitative Biology Peking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Biological (PTN) PhD Program and College of Life Sciences Peking University Center for Protein Science Peking University

Exploring the mechanisms of maintaining microbial community structure is important to understand biofilm development or microbiota dysbiosis. In this paper, we propose a functional gene-based composition prediction(FCP) model to predict the population structure composition within a microbial community. The model predicts the community composition well in both a low-complexity community as acid mine drainage(AMD) microbiota, and a complex community as human gut microbiota. Furthermore, we define community structure shaping(CSS) genes as functional genes crucial for shaping the microbial community. We have identified CSS genes in AMD and human gut microbiota samples with FCP model and find that CSS genes change with the conditions. Compared to essential genes for microbes, CSS genes are significantly enriched in the genes involved in mobile genetic elements, cell motility, and defense mechanisms, indicating that the functions of CSS genes are focused on communication and strategies in response to the environment factors. We further find that it is the minority, rather than the majority, which contributes to maintaining community structure. Compared to health control samples, we find that some functional genes associated with metabolism of amino acids, nucleotides, and lipopolysaccharide are more likely to be CSS genes in the disease group. CSS genes may help us to understand critical cellular processes and be useful in seeking addable gene circuitries to maintain artificial self-sustainable communities. Our study suggests that functional genes are important to the assembly of microbial communities.

关键词： Metagenomics Dynamics model Community structure Acid mine drainage Human gut microbiota

来源：评论

学校读者我要写书评

暂无评论

Agricultural All-Terrain Vehicle Safety: Hazard Control Methods Using the Haddon Matrix

引用

Journal of Agromedicine 2021年第4期26卷 420-435页

作者： Farzaneh Khorsandi Paul Ayers Gerene Denning Charles Jennissen Dee Jepsen Melvin Myers Stephen Oesch Michael Pate David J. White a Agricultural Safety and Health Engineering Assistant Specialist in Cooperative Extension Defpartment of Biological and Agricultural Engineering University of California Davis b Professor Department of Biosystems Engineering and Soil Science University of Tennessee Knoxville c Emeritus Research Scientist in Emergency Medicine Department of Emergency Medicine University of Iowa Carver College of Medicine d MD Clinical Professor of Pediatrics and Emergency Medicine Department of emergency medicine University of Iowa Carver College of Medicine e Associate Professor / State Agricultural Safety Leader Department of Food Agricultural and Biological Engineering agricultural safety and health program The Ohio State University f Associate Professor (Adjunct) Environmental Health Emory University Emory Rollins School of Public Health Atlanta Georgia g Retired highway and motor vehicle safety attorney h Associate Professor Applied Sciences Technology & Education Agricultural Systems Technology and Education program Utah State University i PhD Professor of Social and Behavioral Health Sciences College of Public Health and Human Sciences School of Social and Behavioral Health Sciences and Extension 4-H Youth Development Oregon State University

ABSTRACTABSTRACTAll-terrain vehicle (ATV) crashes are one of the leading causes of death and injury in agriculture across the United states. Use of ATVs is highly prevalent in rural areas and has seen an increase in their application for a variety of agricultural work tasks. Empirical research on the use of these vehicles for agricultural tasks and associated injuries is limited, especially in the United states. Moreover, little is known about the risk factors associated with ATV-related injuries while doing farm work. A comprehensive review was conducted to evaluate the current injury burden of ATV use in agriculture, the need for future research, and possible solutions related to agricultural ATV safety. Potential injury prevention approaches are evaluated based on the hierarchy of control, including elimination or substitution (using side-by-side vehicles instead of ATVs or modifying ATV design), engineering control (operator protection devices), administrative authority (regulations and standards in the United states and around the world), training, and use of personal protective equipment. In addition, vehicle nomenclature, risk factors, and crash mechanisms are reviewed. Recommendations to decrease the likelihood of ATV crashes and injuries are provided.

关键词： Agriculture all-terrain vehicle ATV quad bike safety

来源：评论

学校读者我要写书评

暂无评论

Atlas of Gray Matter Volume Differences Across Psychiatric Conditions: A Systematic Review With a Novel Meta-Analysis That Considers Co-Occurring Disorders

引用

Biological Psychiatry 2025年第1期98卷 76-90页

作者： Fortea, Lydia Ortuño, Maria De Prisco, Michele Oliva, Vincenzo Albajes-Eizagirre, Anton Fortea, Adriana Madero, Santiago Solanes, Aleix Vilajosana, Enric Yao, Yuanwei Del Fabro, Lorenzo Solé, Eduard Verdolini, Norma Farré-Colomés, Alvar Serra-Blasco, Maria Picó-Pérez, Maria Lukito, Steve Wise, Toby Carlisi, Christina Arnone, Danilo Kempton, Matthew J. Hauson, Alexander Omar Wollman, Scott Soriano-Mas, Carles Rubia, Katya Norman, Luke Fusar-Poli, Paolo Mataix-Cols, David Valentí, Marc Via, Esther Cardoner, Narcis Solmi, Marco Zhang, Jintao Pan, Pinglei Shin, Jae Il Fullana, Miquel A. Vieta, Eduard Radua, Joaquim Institut d'Investigacions Biomèdiques August Pi I Sunyer Barcelona Spain Department of Medicine University of Barcelona Institute of Neuroscience Barcelona Spain Centro de Investigación Biomédica en Red de Salud Mental Instituto de Salud Carlos III Madrid Spain Bipolar and Depressive Disorders Unit Hospital Clínic Barcelona Spain Department of Biomedical and Neuromotor Sciences University of Bologna Bologna Italy Psychiatric and Psychology Service Hospital Clínic Barcelona Spain Schizophrenia Unit Hospital Clínic Barcelona Spain Department of Psychology The University of Hong Kong Hong Kong Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Pathophysiology and Transplantation University of Milan Milan Italy Local Health Unit Umbria 1 Department of Mental Health Mental Health Center of Perugia Perugia Italy Department of Addictive Behaviour and Addiction Medicine Central Institute of Mental Health Medical Faculty of Mannheim Heidelberg University Mannheim Germany eHealth ICOnnecta't Program and Psycho-Oncology Service Institut Català d'Oncologia L'Hospitalet de Llobregat Spain Psycho-oncology and Digital Health Group Health Services Research in Cancer Institut d'Investigació Biomèdica de Bellvitge L'Hospitalet del Llobregat Spain Live and Health Sciences Research Institute University of Minho Braga Portugal ICVS/3B's PT Government Associate Laboratory Guimarães Braga Portugal Departamento de Psicología Básica Universitat Jaume I Castelló de la Plana Spain Department of Child and Adolescent Psychiatry Institute of Psychology Psychiatry and Neuroscience King's College London London United Kingdom Department of Neuroimaging Institute of Psychiatry Psychology & Neurosciences King's College London London United Kingdom Division of Psychology and Language Sciences University College London London United Kingdom Centre for Affective Disorders Psychological Medicine King's College London Londo

Background: Regional gray matter volume (GMV) differences between individuals with mental disorders and comparison participants may be confounded by co-occurring disorders. To disentangle disorder-specific GMV correlates, we conducted a large-scale multidisorder meta-analysis using a novel approach that explicitly models co-occurring disorders. Methods: We systematically reviewed voxel-based morphometry studies indexed in PubMed and Scopus up to January 2023 that compared adults with major mental disorders (anorexia nervosa, schizophrenia spectrum, anxiety, bipolar, major depressive, obsessive-compulsive, and posttraumatic stress disorders plus attention-deficit/hyperactivity, autism spectrum, and borderline personality disorders) with comparison participants. Two authors independently extracted data and assessed quality using the Newcastle-Ottawa Scale. We derived GMV correlates for each disorder using: 1) a multidisorder meta-analysis that accounted for all co-occurring mental disorders simultaneously and 2) separate standard meta-analyses for each disorder in which co-occurring disorders were ignored. We assessed the alterations’ extent, intensity (effect size), and specificity (interdisorder correlations and transdiagnostic alterations) for both approaches. Results: We included 433 studies (499 datasets) involving 19,718 patients and 16,441 comparison participants (51% female, ages 20–67 years). We provide GMV correlate maps for each disorder using both approaches. The novel approach, which accounted for co-occurring disorders, produced GMV correlates that were more focal and disorder specific (less correlated across disorders and fewer transdiagnostic abnormalities). Conclusions: This work offers the most comprehensive atlas of GMV correlates across major mental disorders. Modeling co-occurring disorders yielded more specific correlates, supporting this approach's validity. The atlas NIfTI maps are available online. © 2024 Society of Biological Psychiatry

关键词： Anxiety disorders Comorbidity Gray matter volume Major depressive disorder Meta-analysis Psychiatric conditions

来源：评论

学校读者我要写书评

暂无评论

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

arXiv

引用

arXiv 2023年

作者： Eastman, Peter Galvelis, Raimondas Peláez, Raúl P. Abreu, Charlles R.A. Farr, Stephen E. Gallicchio, Emilio Gorenko, Anton Henry, Michael M. Hu, Frank Huang, Jing Krämer, Andreas Michel, Julien Mitchell, Joshua A. Pande, Vijay S. Rodrigues, João P.G.L.M. Rodriguez-Guerra, Jaime Simmonett, Andrew C. Singh, Sukrit Swails, Jason Turner, Philip Wang, Yuanqing Zhang, Ivy Chodera, John D. De Fabritiis, Gianni Markland, Thomas E. Department of Chemistry Stanford University StanfordCA94305 United States Acellera Labs C Dr Trueta 183 Barcelona08005 Spain C Dr. Aiguader 88 Barcelona08003 Spain Chemical Engineering Department School of Chemistry Federal University of Rio de Janeiro Rio de Janeiro68542 Brazil Redesign Science Inc. 180 Varick St. New YorkNY10014 United States EaStCHEM School of Chemistry University of Edinburgh EH9 3FJ United Kingdom Department of Chemistry and Biochemistry Brooklyn College The City University of New York NY United States Ph.D. Program in Chemistry Ph.D. Program in Biochemistry The Graduate Center of the City University of New York New YorkNY United States Stream HPC Koningin Wilhelminaplein 1 - 40601 Amsterdam1062 HG Netherlands Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University 18 Shilongshan Road Zhejiang Hangzhou310024 China Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 12 Berlin14195 Germany The Open Force Field Initiative Open Molecular Software Foundation DavisCA95616 United States Andreessen Horowitz 2865 Sand Hill Rd Menlo ParkCA94025 United States Department of Structural Biology Stanford University StanfordCA94305 United States Charité Universitätsmedizin Berlin In silico Toxicology and Structural Bioinformatics Virchowweg 6 Berlin10117 Germany Laboratory of Computational Biology National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Entos Inc. 9310 Athena Circle La Jolla CA92037 United States College of Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States Simons Center for Computational Physical Chemistry Center for Data Science New York University 24 Waverly Place New YorkNY10004 United States T

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Correction to: CpG‑creating mutations are costly in many human viruses

引用

Evolutionary Ecology 2020年第3期34卷 361-362页

作者： Caudill, Victoria R. Qin, Sarina Winstead, Ryan Kaur, Jasmeen Tisthammer, Kaho Pineda, E. Geo Solis, Caroline Cobey, Sarah Bedford, Trevor Carja, Oana Eggo, Rosalind M. Koelle, Katia Lythgoe, Katrina Regoes, Roland Roy, Scott Allen, Nicole Aviles, Milo Baker, Brittany A. Bauer, William Bermudez, Shannel Carlson, Corey Castellanos, Edgar Catalan, Francisca L. Chemel, Angeline Katia Elliot, Jacob Evans, Dwayne Fiutek, Natalie Fryer, Emily Goodfellow, Samuel Melvin Hecht, Mordecai Hopp, Kellen Hopson, E. Deshawn Jaberi, Amirhossein Kim, Jennifer Kinney, Christen Lao, Derek Le, Adrienne Lo, Jacky Lopez, Alejandro G. López, Andrea Lorenzo, Fernando G. Luu, Gordon T. Mahoney, Andrew R. Melton, Rebecca L. Nascimento, Gabriela Do Pradhananga, Anjani Rodrigues, Nicole S. Shieh, Annie Sims, Jasmine Singh, Rima Sulaeman, Hasan Thu, Ricky Tran, Krystal Tran, Livia Winters, Elizabeth J. Wong, Albert Pennings, Pleuni S. Department of Biology San Francisco State University San Francisco USA Department of Biology University of Oregon Eugene USA Quantitative Systems Biology Univeristy of California Merced USA Department of Ecology and Evolution University of Chicago Chicago USA Vaccine and Infectious Disease Division Fred Hutchinson Cancer Research Center Seattle USA Department of Computational Biology School of Computer Science Carnegie Mellon University Pittsburgh USA Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine London UK Department of Biology Emory University Atlanta USA Big Data Institute University of Oxford Oxford UK Department of Environmental Systems Science ETH Zurich Zurich Switzerland Department of Neurological Surgery University of California San Francisco USA Department of Organismic and Evolutionary Biology Harvard University Cambridge USA Department of Plant Biology Carnegie Institution for Science Stanford USA Health Sciences Center University of New Mexico Albuquerque USA UCSD Biomed Sciences PhD Program University of California San Diego USA Biochemistry Molecular Cellular and Developmental Biology Graduate Group University of California Davis USA UCSF Tetrad Graduate Program University of California San Francisco USA

In the original article, the co-author name "Jennifer Kim" has been inadvertently missed during the publication process. The complete author group is given in this correction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

引用

NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：