检索结果-内蒙古大学图书馆

IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

来源：评论

学校读者我要写书评

暂无评论

Multivalent assembly of nucleolin-targeted F3 peptide potentiates TRAIL's tumor penetration and antitumor effects

引用

Journal of controlled Release 2025年 383卷 113835页

作者： Tao, Ze Li, Yingying Huang, Yunchuan Hu, Liqiang Wang, Shisheng Wan, Lin She, Tianshan Shi, Qiuxiao Lu, Sifen Wang, Xinyue Zhong, Yi Su, Tao Wang, Xinyuan Long, Dan Li, Yan Zhang, Jie Wang, Lijun Long, Tingting Zhu, Hong Lu, Xiaofeng Yang, Hao Division of Liver surgery and NHC Key Lab of Transplant Engineering and Immunology Institutes for Systems Genetics Frontiers Science Center for Disease-Related Molecular Network West China Hospital Sichuan University Chengdu610041 China Sichuan Provincial Engineering Laboratory of Pathology in Clinical Application West China Hospital Sichuan University Chengdu610041 China Department of Laboratory Medicine the West China Second University Hospital Sichuan University Chengdu610041 China West China-California Research Center for Predictive Intervention Medicine Chengdu610041 China Regenerative Medical Research Center West China Hospital Sichuan University Chengdu610041 China Proteomics-Metabolomics Platform Core facilities West China Hospital Sichuan University Chengdu610041 China Precision Medicine Key Laboratory of Sichuan Province and Precision Medicine Center West China Hospital Sichuan University Chengdu610041 China Lung Cancer Center West China Hospital Sichuan University Chengdu610041 China SCMPA Key Laboratory for Quality Research and Control of Chemical Medicine Chengdu Institute for Drug Control Chengdu610041 China Department of Ophthalmology The Third People's Hospital of Chengdu The Affiliated Hospital of Southwest Jiaotong University Chengdu610031 China Department of Laboratory Medicine West China Hospital Sichuan University Chengdu610041 China Division of Abdominal Tumor Multimodality Treatment Cancer Center West China Hospital Sichuan University Chengdu610041 China

Tumor-targeting drug delivery holds great promise for cancer treatment but faces significant challenges in penetrating solid tumors to achieve optimal therapeutic efficacy. By harnessing the natural tissue-penetration effect conferred by the CendR motif, we identified that the nucleolin (NCL)-targeted peptide F3 possesses tumor-penetrating capabilities. Co-administration of F3 with doxorubicin and the apoptosis-inducing protein TRAIL enhanced effective tumor penetration and improved antitumor activity. Taking advantage of TRAIL's natural self-trimerization, we developed a novel fusion protein, F3-TRAIL. This design enabled the trivalent assembly of F3 when fused with TRAIL, significantly enhancing its binding to NCL-positive tumor endothelial and parenchymal cells, resulting in deeper tumor penetration and superior antitumor effects compared to TRAIL alone. Mechanistic studies revealed that the multivalent F3-enhanced engagement with tumor cells potentiated TRAIL to trigger death receptor-dependent apoptosis signaling, even in TRAIL-resistant tumor cells. Building on this success, we constructed F3-HexaTR using the SpyCatcher/SpyTag superglue ligation system to generate a hexameric TRAIL, further amplifying cytotoxicity and antitumor efficacy. Combined analysis of data from TCGA and GTEx revealed significantly elevated NCL expression across 18 solid tumor types, underscoring the clinical potential of F3-directed targeted therapy. These findings highlight that F3-mediated NCL targeting is an effective strategy to overcome tumor penetration barriers, particularly for protein drug delivery. This multivalent assembly approach represents an innovative avenue for enhancing the therapeutic efficacy of various agents in the treatment of solid tumors. © 2025 Elsevier B.V.

关键词： Targeted drug delivery

来源：评论

学校读者我要写书评

暂无评论

Effective Source Camera Identification based on MSEPLL Denoising Applied to Small Image Patches

Effective Source Camera Identification based on MSEPLL Denoi...

引用

Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Wen-Na Zhang Yun-Xia Liu Ze-Yu Zou Yun-Li Zang Yang Yang Bonnie Ngai-Fong Law Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China School of Control Science and Engineering Shandong University Jinan China Integrated Electronic Systems Lab Co. Ltd Jinan China School of Information Science and Engineering Shandong University Qingdao China The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

Sensor Pattern Noise (SPN) has proven to be an effective fingerprint for source camera identification, while its estimation accuracy heavily relies on denoising algorithm. In this paper, an effective source camera identification scheme based on Multi-Scale Expected Patch Log Likelihood (MSEPLL) denoising algorithm is proposed, firstly. With enhanced prior modeling across multiple scales, MSEPLL can accurately restore the original image. As a consequence, estimated SPN is less influenced by image content. Secondly, the source camera identification problem is formulated by hypothesis testing, where normalized correlation coefficient is adopted for SPN detection. Finally, the effectiveness of the proposed method is verified by abundant experiments in terms of identification accuracy as well as receiver operating characteristic. Performance improvement is more prominent for small image patches, which is more conducive to real forensics applications.

关键词： Cameras Maximum likelihood estimation Gaussian processes Wiener filters Image denoising Image restoration

来源：评论

学校读者我要写书评

暂无评论

Mechatronic Design of a Human Robot Coupling Interface for Teaching by Demonstration

引用

IFAC-PapersOnLine 2016年第21期49卷 675-680页

作者： Liang P. Yang C. Wang N. Li Z. Li R. State Key Lab of Robotics Systems Harbin Institute of Technology Harbin China Zienkiewicz Centre for Computational Engineering Swansea University Swansea United Kingdom Centre for Robotics and Neural Systems Plymouth University United Kingdom The MOE Key Laboratory of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China

In this paper, we have developed a mechatronic human-robot coupling interface for kinaesthetic guidance based human robot teaching interface, by integration of a 6-axis force sensor, a coupling mechanism and wearable electromyography (EMG) arrays. Our design aims to transfer human operator's arm kinematics, force as well as human upper limb stiffness estimated from EMG signals to robot manipulators. Experiments have been carried out to test the teaching by demonstration performance of the coupling system in two scenarios: i) human teaching a robot for lifting up task; ii) human-robot skill transfer for one joint motion. Experimental results indicated that the coupling design nearly caused no disturbance to human upper limb stiffness estimation. Moreover, human arm kinematics and force/torque in task space can be transferred to the robot in a natural way with guaranteed safety. This coupling interface design can be easily extended to other robot platforms and has great potentials in application of human robot skill transfer. © 2016

关键词： electromyography (EMG) human robot coupling teaching by demonstration

来源：评论

学校读者我要写书评

暂无评论

Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

引用

The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

关键词：

来源：评论

学校读者我要写书评

暂无评论

Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

引用

15th Annual Conference on Advances in Autonomous Robotics systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

来源：评论

学校读者我要写书评

暂无评论

Reputation-Based Participant Incentive Approach in Opportunistic Cognitive networks

Reputation-Based Participant Incentive Approach in Opportuni...

引用

10th Annual Conference of Advanced Computer Architecture, ACA 2014

作者： Li, Jie Liu, Rui Yu, Ruiyun Wang, Xingwei Zhao, Zhijie Computing Center Northeastern University Shenyang China Key Lab of Network Control Systems Chinese Acad. of Sci. Shenyang China Department of Computing Hong Kong Polytechnic University Hong Kong Software College Northeastern University Shenyang China College of Information Sci. and Eng. Northeastern University Shenyang China Info. and Tech. Center of China Mobile Group Liaoning Co. LTD China

ISBN: (纸本)9783662444900

Sufficient reputable participants are critical to effective data collections and data disseminations in opportunistic cognitive networks. However, it is difficult to identify reputable or malicious participants in opportunistic networks. Cognitive network technology can be applied to the communication system of opportunistic networks to provide reputation-aware schemes of the participants. Furthermore, keeping participants enthusiasm for activities of networks is also important. In this work, we propose a Reputation-Based Participant Incentive Approach (RBPIA) to motivate reputable participants. RBPIA scores participants using reputation degree according to their sensing data and bid price respectively and encourage them to keep interested in the activities with rewards. Simulations are performed in different scenarios to evaluate efficiency of the approach. The results show that RBPIA can identify participant types well, and remarkably reduce the incentive cost. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

引用

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

来源：评论

学校读者我要写书评

暂无评论

Adaptive control of unmanned surface vessels matching an optimized reference model

Adaptive control of unmanned surface vessels matching an opt...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Chenguang Yang Rongxin Cui Zhijun Li Sanjay Sharma Xingang Zhao Center for Robotics and Neural Systems Plymouth University Ply-mouth UK The MOE Key Lab of Autonomous System and Network Control South China University of Technology Guangzhou China School of Marine Science and Technology Northwestern Polytechnical University Xi'an China School of Marine Science and Engineering University of Plymouth Plymouth UK Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781479973989

In this paper, adaptive control of unmanned marine surface vessel has been investigated in the presence of uncertain dynamics as well as external disturbance. Variable structure technique has been utilized in the control design to make the dynamic response and desired motion tracking as quickly as possible. In practice, usually the desired trajectories are given as step points, such that direct immediate tracking would cause large acceleration and huge control effort, while the latter may be out of the actuators' limitation. Therefore, a reference model approach is employed, such that instead of direct tracking of the desired set point, the control objective becomes to shape the closed-loop dynamics to match a reference model. The reference model is built using optimization technique which tries to minimizes both tracking error and motion acceleration, and subsequently control effort. The smooth tracking is thus guaranteed in an optimal manner.

关键词： Tracking Acceleration Trajectory Adaptation models Performance analysis Mathematical model Dynamics

来源：评论

学校读者我要写书评

暂无评论

Motion vehicles tracking in intelligent transportation visual surveillance systems

引用

Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2012年第SUPPL.2期36卷 216-222页

作者： Wu, Lin-Feng Xiong, Gang Qian, Shou-Yi Xie, Li Zhejiang Provincial Key Lab. of Information Network Technology Department of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Cloud Computing Industrial Technology Innovation and Incubation Center Dongguan Research Institute of CASIA Chinese Academy of Sciences Dongguan 523808 China Wenzhou Research Institute of Electronics and Information Wenzhou 325003 China

In terms of the difficulty of vehicle tracking in complex environment of the visual surveillance system, an object tracking algorithm is proposed for the applications in practical visual surveillance systems for intelligent traffic. A block-based Gaussian mixture background modeling method for object detection is presented to reduce the computational complexity of moving vehicle object abstraction. An adaptive tracking algorithm fused with color features and texture features is described to better adapt the traffic scene variation. The experimental results show that the proposed algorithm can effectively deal with the complex urban traffic conditions and the tracking performance is better than the conventional particle filter method and single feature based non-adaptive object tracking method.

关键词： Tracking (position)

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：