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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： J. Choi J. Yoo M. Lee E.-G. Kim J. S. Lee S. Lee S. Joo S. H. Song E.-C. Kim J. C. Lee H. C. Kim Y.-G. Jung S. Kwon Department of Electrical Engineering and Computer Science Seoul National University Seoul Republic of Korea QuantaMatrix Inc. Republic of Korea Interdisciplinary Program of Bioengineering Seoul National University Graduate School Seoul Republic of Korea Department of Laboratory Medicine School of Medicine” Incheon Republic of Korea Department of Laboratory Medicine Seoul National-University Hospital Seoul Republic of Korea Institute of Medical and Biological Engineering Seoul National University Seoul Republic of Korea

A rapid antibiotic susceptibility test (AST) is desperately needed in clinical settings for fast and appropriate antibiotic administration. Traditional ASTs, which rely on cell culture, are not suitable for urgent cases of bacterial infection and antibiotic resistance owing to their relatively long test times. Here, we describe a novel AST called single-cell morphological analysis (SCMA) that can determine antimicrobial susceptibility by automatically analyzing and categorizing morphological changes in single bacterial cells under various antimicrobial conditions. The SCMA was tested with four Clinical and Laboratory Standards Institute standard bacterial strains and 189 clinical samples from hospitals. The results were compared with the gold standard broth microdilution test. The SCMA results were obtained in less than 4 hours with 91.5% categorical agreement and 6.51% minor, 2.56% major, and 1.49% very major discrepancies. Thus, SCMA provides rapid and accurate antimicrobial susceptibility data.

关键词： Microorganisms Antibiotics Strain Immune system Microfluidics Standards Imaging

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Frontispiece: Quantum Crystallography: Current Developments and Future Perspectives

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Chemistry – A European Journal 2018年第43期24卷

作者： Alessandro Genoni Lukas Bučinský Nicolas Claiser Julia Contreras-García Birger Dittrich Paulina M. Dominiak Enrique Espinosa Carlo Gatti Paolo Giannozzi Jean-Michel Gillet Dylan Jayatilaka Piero Macchi Anders Ø. Madsen Lou Massa Chérif F. Matta Kenneth M. Merz Jr. Philip N. H. Nakashima Holger Ott Ulf Ryde Karlheinz Schwarz Marek Sierka Simon Grabowsky Université de Lorraine CNRS Laboratoire LPCT 1 Boulevard Arago F-57078 Metz France Institute of Physical Chemistry and Chemical Physics Slovak University of Technology FCHPT SUT Radlinského 9 SK-812 37 Bratislava Slovakia Université de Lorraine CNRS Laboratoire CRM2 Boulevard des Aiguillettes BP 70239 F-54506 Vandoeuvre-lès-Nancy France Sorbonne Universités UPMC Université Paris 06 CNRS Laboratoire de Chimie Théorique (LCT) 4 Place Jussieu F-75252 Paris Cedex 05 France Anorganische und Strukturchemie II Heinrich-Heine-Universität Düsseldorf Universitätsstraße 1 40225 Düsseldorf Germany Biological and Chemical Research Centre Department of Chemistry University of Warsaw ul. Żwirki i Wigury 101 02-089 Warszawa Poland CNR-ISTM Istituto di Scienze e Tecnologie Molecolari via Golgi 19 Milano I-20133 Italy Istituto Lombardo Accademia di Scienze e Lettere via Brera 28 20121 Milano Italy Department of Mathematics Computer Science and Physics University of Udine Via delle Scienze 208 I-33100 Udine Italy Structure Properties and Modeling of Solids Laboratory CentraleSupelec Paris-Saclay University 3 rue Joliot-Curie 91191 Gif-sur-Yvette France School of Molecular Sciences University of Western Australia 35 Stirling Highway Perth WA 6009 Australia Department of Chemistry and Biochemistry University of Bern Freiestrasse 3 CH-3012 Bern Switzerland Department of Pharmacy University of Copenhagen Universitetsparken 2 2100 Copenhagen Denmark Hunter College & the Ph.D. Program of the Graduate Center City University of New York New York USA Department of Chemistry and Physics Mount Saint Vincent University Halifax Nova Scotia B3M 2J6 Canada Department of Chemistry Dalhousie University Halifax Nova Scotia B3H 4J3 Canada Department of Chemistry Saint Mary's University Halifax Nova Scotia B3H 3C3 Canada Département de Chimie Université Laval Québec QC G1V 0A6 Canada Department of Chemistry and Department of Biochemistry and Molecular Biology Michigan Stat

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Dirichlet tessellation for high-dimensional RSS clustering in Wi-Fi environment

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ICIC Express Letters 2014年第7期8卷 2043-2048页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nanan District Chongqing 400065 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunication and Networking Program School of Information Science University of Pittsburgh PA 15260 United States

The received signal strength (RSS) clustering has played a significant role in site surveying and data pre-processing for the location tracking in Wi-Fi environment. To this end, this paper presents a novel clustering algorithm to cluster the raw RSS vectors with large similarities in both the RSS and physical locations together. The clusters of RSS vectors are determined by the cells which are generated by the Dirichlet tessellation in a transformed low-dimensional space. Our algorithm consists of two steps. We first use the Laplacian embedding to transform the raw measurements into a low-dimensional space, while preserving the RSS and location neighborhood relations. Second, after the seeds of cells are carefully selected, we will tessellate the low-dimensional space by the Dirichlet cells to obtain the clustering results. The experiments conducted in an actual public Wi-Fi environment prove that our algorithm can achieve the smallest cluster scattering in both the RSS and locations compared with the existing affinity propagation clustering, K-means clustering and binary support vector classifier (SVC) algorithms. © 2014 ISSN 1881-803X.

关键词： Wi-Fi

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Floor plan construction via anonymous Wi-Fi signal fragment matching

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ICIC Express Letters, Part B: Applications 2014年第4期5卷 981-987页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Wang, Zhuoran Chongqing Key Lab of Mobile Communications Technology School of Communication and Information Engineering Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nan'an Dist. Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh PA 15260 United States

Floor plan construction is the basis for fingerprint-based localization and people's activity learning, especially in the environments where the geometrical map is not available or does not exist. To this end, we propose a new received signal strength (RSS) fragment matching approach to identify the location points (LPs) in floor plan as the overlapped pieces between the fragments. Then, by means of the Smith-Waterman alignment, each LP can be recognized as a winning path in scoring space. Finally, we use the Allen's interval algebra to assemble the time-stamped LPs into a floor plan in target area. The experiments with the actual Wi-Fi RSS measurements recorded in HKUST campus demonstrate that our proposed approach performs better than the conventional K-means clustering and spectral clustering in floor plan construction. © 2014 ICIC International.

关键词： Algebra

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Construction of time-stamped mobility map for path tracking via smith-waterman measurement matching

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Mathematical Problems in engineering 2014年第1期2014卷 1-17页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Wu, Haibo Pu, Qiaolin Yu, Xiang Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

Path tracking in wireless and mobile environments is a fundamental technology for ubiquitous location-based services (LBSs). In particular, it is very challenging to develop highly accurate and cost-efficient tracking systems applied to the anonymous areas where the floor plans are not available for security and privacy reasons. This paper proposes a novel path tracking approach for large Wi-Fi areas based on the time-stamped unlabeled mobility map which is constructed from Smith-Waterman received signal strength (RSS) measurement matching. Instead of conventional location fingerprinting, we construct mobility map with the technique of dimension reduction from the raw measurement space into a low-dimensional embedded manifold. The feasibility of our proposed approach is verified by the real-world experiments in the HKUST campus Wi-Fi networks, sMobileNet. The experimental results prove that our approach is adaptive and capable of achieving an adequate precision level in path tracking. © 2014 Mu Zhou et al.

关键词： Wi-Fi

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Erratum to: The real cost of sequencing: scaling computation to keep pace with data generation

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Genome biology 2016年第1期17卷 78页

作者： Paul Muir Shantao Li Shaoke Lou Daifeng Wang Daniel J Spakowicz Leonidas Salichos Jing Zhang George M Weinstock Farren Isaacs Joel Rozowsky Mark Gerstein Department of Molecular Cellular and Developmental Biology Yale University New Haven CT 06520 USA. Systems Biology Institute Yale University West Haven CT 06516 USA. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. The Jackson Laboratory for Genomic Medicine Farmington CT 06032 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. mark@***. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. mark@***. Department of Computer Science Yale University New Haven CT 06520 USA. mark@***.

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Fungal diversity notes 253-366:taxonomic and phylogenetic contributions to fungal taxa

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Fungal Diversity 2016年第3期78卷 1-237页

作者： Guo Jie Li Kevin D.Hyde Rui Lin Zhao Sinang Hongsanan Faten Awad Abdel-Aziz Mohamed A.Abdel-Wahab Pablo Alvarado Genivaldo Alves-Silva Joseph F.Ammirati Hiran A.Ariyawansa Abhishek Baghela Ali Hassan Bahkali Michael Beug D.Jayarama Bhat Dimitar Bojantchev Thitiya Boonpratuang Timur S.Bulgakov Erio Camporesi Marcela CBoro Oldriska Ceska Dyutiparna Chakraborty Jia Jia Chen K.W.Thilini Chethana Putarak Chomnunti Giovanni Consiglio Bao Kai Cui Dong Qin Dai Yu Cheng Dai Dinushani A.Daranagama Kanad Das Monika C.Dayarathne Eske De Crop Rafael J.V.De Oliveira Carlos Alberto Fragoso de Souza JoséIde Souza Bryn T.M.Dentinger Asha J.Dissanayake Mingkwan Doilom E.Ricardo Drechsler-Santos Masoomeh Ghobad-Nejhad Sean P.Gilmore Aristóteles Góes-Neto MichałGorczak Charles H.Haitjema Kalani Kanchana Hapuarachchi Akira Hashimoto Mao Qiang He John K.Henske Kazuyuki Hirayama Maria J.Iribarren Subashini C.Jayasiri Ruvishika S.Jayawardena Sun Jeong Jeon Gustavo H.Jerônimo Ana L.Jesus E.B.Gareth Jones Ji Chuan Kang Samantha C.Karunarathna Paul M.Kirk Sirinapa Konta Eric Kuhnert Ewald Langer Haeng Sub Lee Hyang Burm Lee Wen Jing Li Xing Hong Li Kare Liimatainen Diogo Xavier Lima Chuan Gen Lin Jian Kui Liu Xings Zhong Liu Zuo Yi Liu J.Jennifer Luangsa-ard Robert Lücking H.Thorsten Lumbsch Saisamorn Lumyong Eduardo M.Leaño Agostina V.Marano Misato Matsumura Eric H.C.McKenzie Suchada Mongkolsamrit Peter E.Mortimer Thi Thuong Thuong Nguyen Tuula Niskanen Chada Norphanphoun Michelle A.O’Malley Sittiporn Parnmen Julia Pawłowska Rekhani H.Perera Rungtiwa Phookamsak Chayanard Phukhamsakda Carmen L.A.Pires-Zottarelli Olivier Raspé Mateus A.Reck Sarah C.O.Rocha AndréL.C.M.Ade Santiago Indunil C.Senanayake Ledo Setti Qiu Ju Shang Sanjay K.Singh Esteban B.Sir Kevin V.Solomon Jie Song Prasert Srikitikulchai Marc Stadler Satinee Suetrong Hayato Takahashi Takumasa Takahashi Kazuaki Tanaka Li Ping Tang Kasun M.Thambugala Donnaya Thanakitpipattana Michael K.Theodorou Benjarong Thongbai Tuksaporn Thummarukcharoen Qing Tian Saowaluck Tibpromma Annemieke State Key Laboratory of Mycology Institute of MicrobiologyChinese Academy of SciencesNo 31st West Beichen RoadChaoyang DistrictBeijing 100101People’s Republic of China Centre of Excellence in Fungal Research and School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box:2455Riyadh 1145Saudi Arabia Department of Botany and Microbiology Faculty of ScienceSohag UniversitySohag 82524Egypt ALVALAB C/La Rochela nº47E-39012 SantanderSpain Micolab Programa de Pós-Graduação em Biologia de FungosAlgas e PlantasDepartamento de BotânicaUniversidade Federal de Santa CatarinaCampus Universitário TrindadeCEP:88040-900 FlorianópolisSanta CatarinaBrazil Department of Biology University of WashingtonBox 351800SeattleWA 98195-1800USA Guizhou Key Laboratory of Agricultural Biotechnology Guizhou Academy of Agricultural SciencesGuiyang 550006GuizhouPeople’s Republic of China National Fungal Culture Collection of India(NFCCI) Biodiversity and Palaeobiology GroupMACS’Agharkar Research InstituteG.G.Agarkar RoadPune 411004India PO Box 116 HusumWA 98623-0116USA Formerly Department of BotanyGoa UniversityGoaIndia No.128/1-J Azad Housing SocietyCurcaP.O.Goa Velha 403108India *** 345 Shipwatch LaneHerculesCA 94547USA Microbe Interaction Laboratory(BMIT) BIOTECNational Science and Technology Development Agency(NSTDA)113 Thailand Science ParkThanon PhahonyothinTombon Khlong NuengAmphoeKhlong LuangPathum Thani 12120Thailand Academy of Biology and Biotechnology Southern Federal UniversityRostov-on-Don 344090Rostov regionRussia A.M.B.Gruppo Micologico Forlivese BAntonio“Cicognani” Via Roma Forlì Italy 18 A.M.B.Circolo Micologico“Giovanni Carini”C.P.314BresciaItaly Societàper gli Studi Naturalistici della Romagna C.P.144Bagnacavallo

Notes on 113 fungal taxa are compiled in this paper,including 11 new genera,89 new species,one new subspecies,three new combinations and seven reference *** geographic and taxonomic range of fungal taxa are *** the Ascomycota the new genera Angustospora(Testudinaceae),Camporesia(Xylariaceae),Clematidis,Crassiparies(Pleosporales genera incertae sedis),Farasanispora,Longiostiolum(Pleosporales genera incertae sedis),Multilocularia(Parabambusicolaceae),Neophaeocryptopus(Dothideaceae),Parameliola(Pleosporales genera incertae sedis),and Towyspora(Lentitheciaceae)are *** introduced species are Angustospora nilensis,Aniptodera aquibella,Annulohypoxylon albidiscum,Astrocystis thailandica,Camporesia sambuci,Clematidis italica,Colletotrichum menispermi,***,Comoclathris pimpinellae,Crassiparies quadrisporus,Cytospora salicicola,Diatrype thailandica,Dothiorella rhamni,Durotheca macrostroma,Farasanispora avicenniae,Halorosellinia rhizophorae,Humicola koreana,Hypoxylon lilloi,Kirschsteiniothelia tectonae,Lindgomyces okinawaensis,Longiostiolum tectonae,Lophiostoma pseudoarmatisporum,Moelleriella phukhiaoensis,***,Mucoharknessia anthoxanthi,Multilocularia bambusae,Multiseptospora thysanolaenae,Neophaeocryptopus cytisi,Ocellularia arachchigei,***,Ochronectria thailandica,Ophiocordyceps karstii,Parameliola acaciae,***,Parastagonospora cumpignensis,Pseudodidymosphaeria phlei,Polyplosphaeria thailandica,Pseudolachnella brevifusiformis,Psiloglonium macrosporum,Rhabdodiscus albodenticulatus,Rosellinia chiangmaiensis,Saccothecium rubi,Seimatosporium pseudocornii,***,Sigarispora ononidis and Towyspora *** combinations are provided for Eutiarosporella dactylidis(sexual morph described and illus trated)and Pseudocamarosporium ***,illustrations and/or reference specimens are designated for Aposphaeria corallinolutea,Cryptovalsa ampelina,Dothiorella vidmadera,Ophiocordyceps formosana,P

关键词： Ascomycota Basidiomycota Neocallimastigomycota Oomycota.Zygomycota Phylogeny Taxonomy New genus New species

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Design and numerical analysis of surface plasmon-enhanced fin Ge-Si light-emitting diode

Design and numerical analysis of surface plasmon-enhanced fi...

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作者： Jeong, Intae Kwon, Jooseong Kim, Changsoon Park, Young June Program in Nano Science and Technology Graduate School of Convergence Science and Technology Seoul National University Seoul 151-742 Korea Republic of Department of Electrical and Computer Engineering School of Engineering Seoul National University Seoul 151-747 Korea Republic of Advanced Institutes of Convergence Technology Suwon Gyeonggi 443-270 Korea Republic of

Heavily-doped strained germanium (Ge) can emit light efficiently thanks to its pseudo direct band gap characteristic. This makes Ge a good candidate for on-chip monolithic light sources in silicon (Si) photonics systems. We propose fin-shaped Ge-Si heterojunction lightemitting diode (LED) with metal gates, which can enhance light emission by coupling with surface plasmon resonant modes and modulate light emission from the LED. We verify these two aspects through numerical analysis and device simulations. We develop the method to find the optimal device structure and specific device dimensions to maximize the spontaneous emission rate enhancement. Also we find that the LED can be modulated by a gate voltage bias. © 2014 Optical Society of America.

关键词： Surface plasmons

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Calibrationless parallel imaging reconstruction based on structured low-rank matrix completion

Calibrationless parallel imaging reconstruction based on str...

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作者： Shin, Peter J. Larson, Peder E. Z. Ohliger, Michael A. Elad, Michael Pauly, John M. Vigneron, Daniel B. Lustig, Michael Department of Radiology and Biomedical Imaging University of California at San Francisco San FranciscoCA United States UC Berkeley-UCSF Graduate Program in Bioengineering CA United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA United States Department of Computer Science Technion'Israel Institute of Technology Haifa Israel Magnetic Resonance Systems Research Laboratory Department of Electrical Engineering Stanford University StanfordCA United States

Purpose: A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k-space estimation (SAKE), is presented. It is a data-driven, coil-by-coil reconstruction method that does not require a separate calibration step for estimating coil sensitivity information. Methods: In SAKE, an undersampled, multichannel dataset is structured into a single data matrix. The reconstruction is then formulated as a structured low-rank matrix completion problem. An iterative solution that implements a projection-ontosets algorithm with singular value thresholding is described. Results: Reconstruction results are demonstrated for retrospectively and prospectively undersampled, multichannel Cartesian data having no calibration signals. Additionally, non-Cartesian data reconstruction is presented. Finally, improved image quality is demonstrated by combining SAKE with wavelet-based compressed sensing. Conclusion: Because estimation of coil sensitivity information is not needed, the proposed method could potentially benefit MR applications where acquiring accurate calibration data is limiting or not possible at all. © 2013 Wiley Periodicals, Inc.

关键词： Compressed sensing

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Comparative study of leaf image recognition with a novel learning-based approach

Comparative study of leaf image recognition with a novel lea...

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science and Information Conference (SAI)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chih-Yang Lin Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a comparative study on leaf image recognition and propose a novel learning-based leaf image recognition technique via sparse representation (or sparse coding) for automatic plant identification. In our learning-based method, in order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. Moreover, we also implement a general bag-of-words (BoW) model-based recognition system for leaf images, used for comparison. We experimentally compare the two approaches and show unique characteristics of our sparse coding-based framework. As a result, efficient leaf recognition can be achieved on public leaf image dataset based on the two evaluated methods, where the proposed sparse coding-based framework can perform better.

关键词： Image recognition Dictionaries Training Feature extraction Shape Vectors Image coding

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