检索结果-内蒙古大学图书馆

Organ-on-a-Chip: Ex vivo Dynamics of Human Glioblastoma Cells in a Microvasculature-on-a-Chip System Correlates with Tumor Heterogeneity and Subtypes (Adv. Sci. 8/2019)

引用

Advanced science 2019年第8期6卷 1970046-1970046页

作者： Yang Xiao Dongjoo Kim Burak Dura Kerou Zhang Runchen Yan Huamin Li Edward Han Joshua Ip Pan Zou Jun Liu Ann Tai Chen Alexander O. Vortmeyer Jiangbing Zhou Rong Fan Department of Biomedical Engineering Yale University New Haven CT 06520 USA School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 USA Applied Math Program Yale University New Haven CT 06520 USA Department of Neurosurgery Yale School of Medicine New Haven CT 06520 USA Department of Pathology Indiana University Health Pathology Laboratory Indianapolis IN 46202 USA Yale Comprehensive Cancer Center New Haven CT 06520 USA

来源：评论

学校读者我要写书评

暂无评论

DEA and Fuzzy Simple Additive Weighting for Benchmarking Qualitative Data

引用

Journal of Physics: Conference Series 2019年第1期1361卷

作者： Dahlan Abdullah H Hartono Erianto Ongko Cut Ita Erliana Defi Irwansyah Akbar Iskandar Ayu Esteka Sari Abdussakir Yuniningsih Nurintan Asyiah Siregar Muhammad Syahrul Kahar Raditya Faisal Waliulu Ainna Amalia Nuning Kurniasih Muhammad Arifin Syafiul Muzid Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Akademi Teknologi Industri Immanuel Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Mathematics Education State Islamic University of Malang MalangIndonesia Department of Economic and Business Universitas Pembangunan Nasional 'Veteran' Surabaya Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Mathematics Education Department Universitas Muhammadiyah Sorong Sorong Indonesia Informatics Engineering Department Universitas Muhammadiyah Sorong Sorong Indonesia Islamic Institut of Miftahul Ula Kertosono Nganjuk East Java Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Information System Faculty of Engineering Universitas Muria Kudus Indonesia Information System Department Universitas Muria Kudus Indonesia

Data Envelopment Analysis (DEA) is one method that is often used in the benchmarking process. The benchmarking process with DEA is often faced with problems where there is a Decision Making Unit (DMU) both Input and Output which is not in the form of qualitative data but in the form of qualitative data. Qualitative data requires an assessment from the appraiser so that it can become quantitative data. This study will use the Fuzzy Simple Additive Weighting method to convert qualitative data into quantitative. The results of this study will produce a model that integrates DEA with Fuzzy Simple Additive Weighting.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Verbalization: Narration of autonomous robot experience 25

Verbalization: Narration of autonomous robot experience

引用

25th International Joint Conference on Artificial Intelligence, IJCAI 2016

作者： Rosenthal, Stephanie Selvaraj, Sai P. Veloso, Manuela Software Engineering Institute United States Robotics Institute United States Computer Science Department Carnegie Mellon University Pittsburgh United States

Autonomous mobile robots navigate in our spaces by planning and executing routes to destinations. When a mobile robot appears at a location, there is no clear way to understand what navigational path the robot planned and experienced just by looking at it. In this work, we address the generation of narrations of autonomous mobile robot navigation experiences. We contribute the concept of verbalization as a parallel to the well-studied concept of visualization. Through verbalizations, robots can describe through language what they experience, in particular in their paths. For every executed path, we consider many possible verbalizations that could be generated. We introduce the verbalization space that covers the variability of utterances that the robot may use to narrate its experience to different humans. We present an algorithm for segmenting a path and mapping each segment to an utterance, as a function of the desired point in the verbalization space, and demonstrate its application using our mobile service robot moving in our buildings. We believe our verbalization space and algorithm are applicable to different narrative aspects for many mobile robots, including autonomous cars.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Author Correction: RADICL-seq identifies general and cell type-specific principles of genome-wide RNA-chromatin interactions

引用

Nature communications 2021年第1期12卷 3128页

作者： Alessandro Bonetti Federico Agostini Ana Maria Suzuki Kosuke Hashimoto Giovanni Pascarella Juliette Gimenez Leonie Roos Alex J Nash Marco Ghilotti Christopher J F Cameron Matthew Valentine Yulia A Medvedeva Shuhei Noguchi Eneritz Agirre Kaori Kashi Joachim Luginbühl Riccardo Cazzoli Saumya Agrawal Nicholas M Luscombe Mathieu Blanchette Takeya Kasukawa Michiel de Hoon Erik Arner Boris Lenhard Charles Plessy Gonçalo Castelo-Branco Valerio Orlando Piero Carninci RIKEN Center for Integrative Medical Sciences Yokohama Kanagawa 230-0045 Japan. alessandro.bonetti@riken.jp. Laboratory of Molecular Neurobiology Department Medical Biochemistry and Biophysics Karolinska Institutet Stockholm Sweden. alessandro.bonetti@riken.jp. The Francis Crick Institute 1 Midland Road London NW1 1AT UK. RIKEN Center for Integrative Medical Sciences Yokohama Kanagawa 230-0045 Japan. Department of Medicine (H7) Karolinska Institutet Stockholm 141 86 Sweden. Epigenetics and Genome Reprogramming Laboratory IRCCS Fondazione Santa Lucia Rome Italy. Faculty of Medicine Imperial College London Institute of Clinical Sciences London W12 0NN UK. MRC London Institute of Medical Sciences London W12 0NN UK. School of Computer Science McGill University Montréal QC Canada. Department of Biochemistry and Goodman Cancer Research Centre McGill University Montréal QC Canada. Institute of Bioengineering Research Centre of Biotechnology Russian Academy of Science 117312 Moscow Russia. Department of Computational Biology Vavilov Institute of General Genetics Russian Academy of Science 119991 Moscow Russia. Department of Biological and Medical Physics Moscow Institute of Physics and Technology 141701 Dolgoprudny Moscow Region Russia. Laboratory of Molecular Neurobiology Department Medical Biochemistry and Biophysics Karolinska Institutet Stockholm Sweden. Department of Experimental Oncology IEO European Institute of Oncology IRCCS Milan Italy. UCL Genetics Institute University College London London WC1E 6BT UK. Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha Onna-son Kunigami-gun Okinawa 904-0495 Japan. Sars International Centre for Marine Molecular Biology University of Bergen 5008 Bergen Norway. Epigenetics and Genome Reprogramming Laboratory IRCCS Fondazione Santa Lucia Rome Italy. valerio.orlando@kaust.edu.sa. KAUST Environmental Epigenetics Program King Abdullah University of Science and Technology (KAUS

来源：评论

学校读者我要写书评

暂无评论

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

引用

NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

来源：评论

学校读者我要写书评

暂无评论

Ambient-pressure CVD of graphene on low-index Ni surfaces using methane: A combined experimental and first-principles study

引用

Physical Review Materials 2018年第7期2卷 073404-073404页

作者： Daniela L. Mafra Jimena A. Olmos-Asar Fabio R. Negreiros Alfonso Reina Ki Kang Kim Mildred S. Dresselhaus Jing Kong Gary J. Mankey Paulo T. Araujo Department of Electrical Engineering and Computer Sciences Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Centro de Ciências Naturais e Humanas Universidade Federal do ABC Santo André 09210-580 SP Brazil INFIQC CONICET Departamento de Química Teórcia y Computacional Facultad de Ciencias Químicas Universidad Nacional de Córdoba X5000HUA Argentina Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Energy and Materials Engineering Dongguk University-Seoul Seoul 04620 Republic of Korea Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Astronomy The University of Alabama Tuscaloosa Alabama 35487 USA Center for Materials for Information Technology (MINT Center) The University of Alabama Tuscaloosa Alabama 35401 USA Natural Sciences Institute Graduate Program in Physics - Federal University of Para Belem PA 66075-110 Brazil

The growth of large area single-layer graphene (1-LG) is studied using ambient pressure chemical vapor deposition on single-crystal Ni(111), Ni(110), and Ni(100). By varying both the furnace temperature in the range of 800–1100 °C and the gas flow through the growth chamber, uniform, high-quality 1-LG is obtained for Ni(111) and Ni(110) single crystals and for Ni(100) thin films. Surprisingly, only multilayer graphene growth could be obtained for single-crystal Ni(100). The experimental results are analyzed to determine the optimum combination of temperature and gas flow. Characterization with optical microscopy, Raman spectroscopy, and optical transmission support our findings. Density-functional theory calculations are performed to determine the energy barriers for diffusion, segregation, and adsorption, and model the kinetic pathways for formation of different carbon structures on the low-index surfaces of Ni.

关键词： Growth Synthesis 2-dimensional systems Carbon-based materials Atomic force microscopy Chemical vapor deposition Density functional calculations Density functional theory Raman spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Encouraging student innovation in a freshman-level computer science course 123

Encouraging student innovation in a freshman-level computer ...

引用

123rd ASEE Annual Conference and Exposition

作者： Fry, Cynthia C. Van Treuren, Kenneth W. Computer Science Fellows Program Baylor University United States Department of Engineering Baylor University United States

In a world where the demand is high for employees who can think creatively and apply entrepreneurial behaviors and thought processes to their work, it is critically important for engineering and computer science programs to provide more educational opportunities that take the essential basics of the disciplines and add to that content the experiences that will also encourage the development of entrepreneurial behaviors in students development of solutions to the challenges they face. In a second-semester project-based learning course in computer science at Baylor University, the students were introduced to an idea-generation technique called Painstorming chosen to encourage opportunity recognition, and asked to develop their own idea for a semester project. This paper will cover the success of project-based learning in engineering and computer science courses, show a method of idea generation called Painstorming, the application of Painstorming to software applications as a means to generate group project ideas, the adjustments necessary for the successful implementation of this approach in an already busy course, and the preliminary results of the experiment. © American Society for engineering Education, 2016.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Data-driven model reduction and transfer operator approximation

arXiv

引用

arXiv 2017年

作者： Klus, Stefan Nüske, Feliks Koltai, Péter Wu, Hao Kevrekidis, Ioannis Schütte, Christof Noé, Frank Department of Mathematics and Computer Science Freie Universität Berlin Germany Department of Chemical and Biological Engineering & Program in Applied and Computational Mathematics Princeton University United States Zuse Institute Berlin Germany

In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to approximate transfer operators and their eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out similarities and differences between methods developed independently by the dynamical systems, fluid dynamics, and molecular dynamics communities such as time-lagged independent component analysis (TICA), dynamic mode decomposition (DMD), and their respective generalizations. As a result, extensions and best practices developed for one particular method can be carried over to other related methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

The role of artificial intelligence in achieving the Sustainable Development Goals

arXiv

引用

arXiv 2019年

作者： Vinuesa, Ricardo Azizpour, Hossein Leite, Iolanda Balaam, Madeline Dignum, Virginia Domisch, Sami Felländer, Anna Langhans, Simone Tegmark, Max Nerini, Francesco Fuso Linné FLOW Centre KTH Mechanics StockholmSE-100 44 Sweden School of Electrical Engineering and Computer Science KTH Royal Institute Of Technology Stockholm Sweden Division of Robotics Perception and Learning School of EECS KTH Royal Institute Of Technology Stockholm Sweden Division of Media Technology and Interaction Design KTH Royal Institute of Technology Lindstedtsvägen 3 Stockholm Sweden Responsible AI Lab Umeå University UmeåSE-90358 Sweden Leibniz-Institute of Freshwater Ecology and Inland Fisheries Müggelseedamm 310 Berlin12587 Germany Division of Media Technology and Interaction Design KTH Royal Institute of Technology Lindstedtsvägen 3 Stockholm Sweden Leioa Spain Department of Zoology University of Otago 340 Great King Street Dunedin9016 New Zealand Center for Brains Minds & Machines Massachusetts Institute of Technology CambridgeMA02139 United States KTH Royal Institute of Technology Brinellvagen 68 StockholmSE-100 44 Sweden

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors across the society requires an assessment of its effect on sustainable development. Here we analyze published evidence of positive or negative impacts of AI on the achievement of each of the 17 goals and 169 targets of the 2030 Agenda for Sustainable Development. We find that AI can support the achievement of 128 targets across all SDGs, but it may also inhibit 58 targets. Notably, AI enables new technologies that improve efficiency and productivity, but it may also lead to increased inequalities among and within countries, thus hindering the achievement of the 2030 Agenda. The fast development of AI needs to be supported by appropriate policy and regulation. Otherwise, it would lead to gaps in transparency, accountability, safety and ethical standards of AI-based technology, which could be detrimental towards the development and sustainable use of AI. Finally, there is a lack of research assessing the medium- and long-term impacts of AI. It is therefore essential to reinforce the global debate regarding the use of AI and to develop the necessary regulatory insight and oversight for AI-based technologies. Copyright © 2019, The Authors. All rights reserved.

关键词： Planning

来源：评论

学校读者我要写书评

暂无评论

First Searches for Dark Matter with the KM3NeT Neutrino Telescopes

arXiv

引用

arXiv 2024年

作者： Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Alves Garre, S. Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Martino, B. De Wasseige, G. Decoene, V. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi Ibnsalih, W. Illuminati, G. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazar, J. Lazo, A. Le Stum, S. Lehaut, G. Lemaître, V. Leonora, E. Lessing, N. Levi, G. Lindsey Clark, M. Longhitano, F. Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Khalifa University Department of Physics PO Box 127788 Abu Dhabi0000 United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli Federico II Dip. Scienze Fisiche E. Pancini Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain Subatech IMT Atlantique IN2P3-CNRS Nantes Université 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università degli Studi della Campania Luigi Vanvitelli Dipartimento di Matematica e Fisica viale Lincoln 5 Caserta81100 Italy LPC Campus des Cézeaux 24 avenue des Landais BP 80026

Indirect dark matter detection methods are used to observe the products of dark matter annihilations or decays originating from astrophysical objects where large amounts of dark matter are thought to accumulate. With neutrino telescopes, an excess of neutrinos is searched for in nearby dark matter reservoirs, such as the Sun and the Galactic Centre, which could potentially produce a sizeable flux of Standard Model particles. The KM3NeT infrastructure, currently under construction, comprises the ARCA and ORCA undersea Čerenkov neutrino detectors located at two different sites in the Mediterranean Sea, offshore of Italy and France, respectively. The two detector configurations are optimised for the detection of neutrinos of different energies, enabling the search for dark matter particles with masses ranging from a few GeV/c2 to hundreds of TeV/c2. In this work, searches for dark matter annihilations in the Galactic Centre and the Sun with data samples taken with the first configurations of both detectors are presented. No significant excess over the expected background was found in either of the two analyses. Limits on the velocity-averaged self-annihilation cross section of dark matter particles are computed for five different primary annihilation channels in the Galactic Centre. For the Sun, limits on the spin-dependent and spin-independent scattering cross sections of dark matter with nucleons are given for three annihilation channels. © 2024, CC BY.

关键词： Neutrons

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：