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arXiv 2018年

作者： Terashima, S. Yu, L. Ong, H.J. Tanihata, I. Adachi, S. Aoi, N. Chan, P.Y. Fujioka, H. Fukuda, M. Geissel, H. Gey, G. Golak, J. Haettner, E. Iwamoto, C. Kawabata, T. Kamada, H. Le, X.Y. Sakaguchi, H. Sakaue, A. Scheidenberger, C. Skibinski, R. Sun, B.H. Tamii, A. Tang, T.L. Tran, D.T. Topolnicki, K. Wang, T.F. Watanabe, Y.N. Weick, H. Witala, H. Zhang, G.X. Zhu, L.H. School of Physics and Nuclear Energy Engineering Beihang University Beijing100191 China International Research Center for Nuclei and Particles in Cosmos Beihang University Beijing100191 China RCNP Osaka University 10-1 Mihogaoka Ibaraki Osaka567-0047 Japan Department of Physics Kyoto University Kyoto606-8502 Japan Osaka University 1-5 Machikaneyama-cho Toyonaka Osaka560-0043 Japan GSI Helmholtzzentrum für Schwerionenforschung GmbH Planskstraße 1 Darmstadt64291 Germany Justus-Liebig-Universität Gießen Heinrich-Buff-Ring 16 Gießen35392 Germany M. Smoluchowski Institute of Physics Jagiellonian University KrakówPL-30348 Poland Department of Physics Faculty of Engineering Kyushu Institute of Technology Kitakyushu804-8550 Japan Beijing Advanced Innovation Center for Big Data based Precision Medicine Beihang University Beijing100083 China Institute of Physics Vietnam Academy of Science and Technology Hanoi100000 Viet Nam Department of Physics University of Tokyo Tokyo113-0033 Japan

The isospin character of p-n pairs at large relative momentum has been observed for the first time in the 16O ground state. A strong population of the J,T=1,0 state and a very weak population of the J,T=0,1 state were observed in neutron pick up domain of 16O(p,pd) at 392 MeV. This strong isospin dependence at large momentum transfer is not reproduced by the distorted-wave impulse approximation calculations with known spectroscopic amplitudes. The results indicate the presence of high-momentum protons and neutrons induced by the tensor interactions in ground state of 16O. Copyright © 2018, The Authors. All rights reserved.

关键词： Momentum

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Whole-Genome Sequencing and Analysis of the Chinese Herbal Plant Panax notoginseng

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Molecular Plant 2017年第6期10卷 899-902页

作者： Wei Chen Ling Kui Guanghui Zhang Shusheng Zhu Jing Zhang Xiao Wang Min Yang Huichuan Huang Yixiang Liu Yong Wang Yahe Li Lipin Zeng Wen Wang Xiahong He Yang Dong Shengchao Yang Biological Big Data College Yunnan Agricultural University yunnan Research Institute for Local Plateau Agriculture and Industry Kunming 650201 China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of Zoology Chinese Academy of Sciences Kunming 650223 China University of Chinese Academy of Sciences Beijing 100049 China National-Local Joint Engineering Research Center on Germplasm Utilization and Innovation of Chinese Medicinal Materials in Southwest China Yunnan Agricultural University Kunming 650201 China State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education Yunnan Agricultural University Kunming 650201 China NOWBIO Technology Co. Ltd Kunming 650202 China Institute of Panax notoginseng Wenshan University Wenshan 663000 China Longjing Pharmaceutical Co. Ltd Kunming 650228 China Farlong Pharmaceutical Walnut CA 91789 USA College of Life Science Kunming University of Science and Technology Kunming 650504 China

Dear Editor Panax notoginseng （Burk.） F.H. Chen （2n = 2x = 24, common name sanqi or tianql）, belonging to the Araliaceae family, is a slow-growing plant species documented in the ancient Chinese medical literatures for its ability to ameliorate hemostasis and improve blood circulation （Wang et al., 2016）. After decades of pharmacological research, a variety of P. notoginseng-specific secondary metabolites （notably ginsenosides, notoginsenosides and gypenosides） were isolated, identified, and implicated in conferring medicinal properties （Wang et al., 2016）.

关键词： Whole-Genome Sequencing Chinese Herbal Plant Panax notoginseng

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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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A hybrid-integrated external cavity laser with ultra-wide wavelength tuning range and high side-mode suppression

A hybrid-integrated external cavity laser with ultra-wide wa...

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Optical Fiber Communication Conference, OFC 2016

作者： Guo, Yuyao Li, Xinhang Xu, Weihan Liu, Chuxin Jin, Minhui Lu, Liangjun Xie, Jingya Stroganov, Anton Chen, Jianping Zhou, Linjie State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation Center Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology Shanghai200093 China LIGENTEC SA EPFL Innovation Park Bâtiment L Ecublens1024 Switzerland

We present a III-V/Si3N4 hybrid-integrated tunable laser. The laser shows a record of ~170-nm tuning range with a side mode suppression ratio above 64 dB and an intrinsic linewidth below 2.8 kHz. © 2022 The Autho...

ISBN: (纸本)9781943580071

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Analysis of Recommendation Algorithms for Internet of Things

Analysis of Recommendation Algorithms for Internet of Things

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IEEE Wireless Communications and Networking Conference

作者： Ibrahim Mashal Osama Alsaryrah Tein-Yaw Chung Innovation Center for Big Data and Digital Convergence Department of Computer Science and Engineering Yuan Ze University

ISBN: (纸本)9781467398152

Internet of Things (IoT) is a new paradigm that refers to a world-wide network of interconnected physical things using standardized communication protocols to provide human useful services such as personal health care and green energy monitoring. Nowadays, many third party service providers are providing a large number of IoT services. Recommending IoT services to users based on objects they own will become very crucial for the success of IoT. In this paper, we investigate the possibilities of leveraging recommendation algorithms, especially graph-based, to IoT. We propose a hyper-graph model for IoT systems in which each hyper-edge connects users, objects, and services. Next, we conduct experiment to analyze and explore correlations between performances of different algorithms on IoT Service Recommendation (IoTSRS) based on existing well known metrics. Results show that the graph-based recommendation algorithm can be used to develop an effective recommender system for IoT. Moreover, we show that some algorithms perform reasonably well and produce high quality results. However, further extension of existing approaches is required for IoTSRS.

关键词： Internet of Things Service Recommendation Tripartite Graph Collaborative Filtering Hyper-Edge

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Lightweight streaming authenticated data structures 22

Lightweight streaming authenticated data structures

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22nd ACM SIGSAC Conference on Computer and Communications Security, CCS 2015

作者： Yu, Chia-Mu Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan Innovation Center for Big Data and Digital Convergence Taoyuan Taiwan

ISBN: (纸本)9781450338325

We develop two novel techniques, FHMT and HWMT, for streaming authenticated data structures to achieve the streaming verifiable computation. By leveraging the computing capability of fully homomorphic encryption, FHMT shifts almost all of the computation tasks to the server, reaching nearly no overhead for the client. HWMT strikes the performance balance between the client and server via the proposed tree decomposition technique over the Merkle tree. We also report our research attempt, SAMT, to construct a more efficient data structure for extremely resource-limited clients without the heavy computation burden on the server.

关键词： Cryptography

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Distance learning by treating negative samples differently and exploiting impostors with symmetric triplet constraint for person re-identification

Distance learning by treating negative samples differently a...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoke Zhu Xiao-Yuan Jing Fei Wu Weishi Zheng Ruimin Hu Chunxia Xiao Chao Liang School of Computer and Information Engineering Henan University State Key Laboratory of Software Engineering Wuhan University College of Automation Nanjing University of Posts and Telecommunications School of Data and Computer Science Sun Yat-sen University National Engineering Research Center for Multimedia Software Computer School of Wuhan Univ. Collaborative Innovation Center of Geospatial Technology China

ISBN: (纸本)9781467372596

Distance learning (DL) is an effective technique for person reidentification (PR-ID). DL based methods learn the distance metric by exploiting the discriminative information contained in samples. In PR-ID, different types of negative samples own different amounts of discriminative information, and impostor samples usually own more than other well separable negative samples (WSN-samples). Therefore, how to make full use of the different discriminative information conveyed by all negative samples in the DL process is a critical issue to be investigated. In this paper, we propose a novel DL approach for PR-ID. Specifically, for each target sample, we divide its negative samples into impostors and WSN-samples. Then we learn the distance metric by utilizing impostors and WSN-samples differently. For impostors, we design a symmetric triplet constraint, which requires the impostor to be far away from both samples of its corresponding positive sample pair simultaneously; for WSN-samples, we require them to keep their favorable separability. Experimental results on three benchmark datasets demonstrate the effectiveness and efficiency of our approach.

关键词： Wireless sensor networks Measurement Thyristors Computer aided instruction Cameras Linear programming Computers

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Magnetic frustration driven by itinerancy in spinel CoV2O4

arXiv

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arXiv 2017年

作者： Lee, J.H. Ma, J. Hahn, S.E. Cao, H.B. Hong, Tao Okamoto, S. Zhou, H.D. Matsuda, M. Fishman, R.S. School of Energy and Chemical Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Key Laboratory of Artificial Structures and Quantum Control Department of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Collaborative Innovation Center of Advanced Microstructures Nanjing Jiangsu210093 China Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Neutron Data Analysis and Visualization Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Quantum Condensed Matter Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

Localized spins and itinerant electrons rarely coexist in geometrically-frustrated spinel lattices. We show that the spinel CoV2O4 stands at the crossover from insulating to itinerant behavior and exhibits a complex interplay between localized spins and itinerant electrons. In contrast to the expected paramagnetism, localized spins supported by enhanced exchange couplings are frustrated by the effects of delocalized electrons. This frustration produces a non-collinear spin state and may be responsible for macroscopic spin-glass behavior. Competing phases can be uncovered by external perturbations such as pressure or magnetic field, which enhance the frustration. Copyright © 2017, The Authors. All rights reserved.

关键词： Cobalt compounds

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Who will pass? Analyzing learner behaviors in MOOCs 23

Who will pass? Analyzing learner behaviors in MOOCs

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23rd International Conference on Computers in Education, ICCE 2015

作者： Tseng, Shu-Fen Tsao, Yen-Wei Yu, Liang-Chih Chan, Chien-Lung Lai, K. Robert Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801472

Massive Open Online Courses (MOOCs) have gained worldwide attention recently because of their great potential to reach learners. MOOCs provide a new option for learning, yet the impacts of MOOCs usage on learning still need to be clarified and empirically examined. By collecting data of three MOOCs at Yuan Ze University (YZU), this paper presented a study that classified learning behaviors among 1,230 students on MOOC platform at YZU. In addition, this study examined the impacts of learner behaviors in MOOCs on course completion. The effectiveness of online learning features was examined to expand our knowledge about how students respond to these learning tools. In this study, we used the Ward's and K-means clustering algorithms to determine number of cluster and to classify different types of learners in MOOCs. By cluster analysis, we classified three types of MOOC learners-Active learner, passive learner, and bystander. While most students were classified as bystanders (90%), there were only 1% of students labelled as active learner. In these courses, whether a student handed in assignments greatly determined his/her odds of completing course. The results of descriptive analysis indicated that students with various types of learning behaviors in MOOCs did reveal different levels of learning outcome. Active learners who handed in assignments on time and frequently watched videos have significantly shown higher rates of passing the course than the others. Additionally, those who actively participated in online discussion forum received a much higher grade in the class than inactive users.

关键词： Students

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Avatar as open student model to enhance student learning 23

Avatar as open student model to enhance student learning

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23rd International Conference on Computers in Education, ICCE 2015

作者： Chen, Zhi-Hong Chien, Chih-Hao Chou, Chih-Yueh Department of Information Communication Yuan Ze University Taiwan Department of Computer Engineering and Science Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801489

In this paper, we describe My-Hero system that is an open student model system developed to enhance student learning, including promoting their awareness, improving, and interaction. Since awareness is a key element for triggering behavior change (e.g., improving and interaction), enhancing students' learning awareness is the first step to change their behaviors. Thus, the learning process of the My-Hero system is initiated by enhancing learning awareness via open student model. In this way, students' effort can be guided in improving their current status and peer interaction.

关键词： Students

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