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Lattice vibration modes in type-II superlattice InAs/GaSb with no-common-atom interface and overlapping vibration spectra

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Physical Review B 2015年第23期91卷 235317-235317页

作者： Henan Liu Naili Yue Yong Zhang Pengfei Qiao Daniel Zuo Ben Kesler Shun Lien Chuang Jae-Hyun Ryou James D. Justice Russell Dupuis Optical Science and Engineering Graduate Program University of North Carolina at Charlotte Charlotte North Carolina USA Department of Electrical and Computer Engineering University of North Carolina at Charlotte Charlotte North Carolina USA Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Champaign Illinois USA Center for Compound Semiconductors and School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia USA

Heterostructures like InAs/GaSb superlattices (SLs) are distinctly different from well-studied ones like GaAs/AlAs SLs in terms of band alignment, common interface atom, and phonon spectrum overlapping of the constituents, which manifests as stark differences in their electronic and vibrational properties. This paper reports a comprehensive examination of all four types of phonon modes (confined, quasiconfined, extended, and interface) that have long been predicted for the InAs/GaSb SL, with the observation and interpretation of a set of phonon modes by performing cleaved edge μ-Raman study with polarization analysis. Furthermore, we show a signature of symmetry reduction from D2d for GaAs/AlAs SL to C2v for InAs/GaSb SL revealed as a phonon-polariton effect.

关键词： SUPERLATTICES HETEROJUNCTIONS VIBRATIONAL spectra PHONON spectra RAMAN spectroscopy

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Optimization Process of Glycerol Esterification Using Real Time Adaptive Control

Optimization Process of Glycerol Esterification Using Real T...

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International Conference on Advanced computer science and Information Systems

作者： Iwan Aang Soenandi Ani Suryani Taufik Djatna Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural University Dramaga Indonesia Lecturer Faculty of Engineering and Computer Science Krida Wacana Christian University Post Graduate Program of Agro-industrial Technology Bogor Agricultural University. Dramaga Indonesia Post Graduate Program of Agro-industrial Technology and Graduate Program of Computer Science Bogor Agricultural University. Dramaga Indonesia Department of Physics Faculty Mathematics and Natural Sciences Bogor Agricultural University. Dramaga Indonesia

ISBN: (纸本)9781509003648

The synthesis reaction used in esterification needs high energy consumption and a precise processing time to get the best yield of target. In this study, a model was formulated to optimize glycerol esterification process by minimizing the time needed for the process and maximizing the yield of Mono-glycerides. This optimization has gained importance for boosting the esterification industry and improving the production efficiency. Optimization through adaptive monitoring and control has provided significant advances in the process efficiency, a lower energy consumption and a better product quality. This paper presents the optimization with a computational algorithm in real time and adaptive control (RTAC), as compared to the conventional (traditional) methods to monitor and control of glycerol esterification processes. The identification of esterification status based on temperature and time are evaluated to strengthen the optimization. An adaptive method as feature selection to select wavelength IR sensors at specified intervals was carried out with Relief algorithm and Adaptive Pillar K-means clustering method to set the parameter control was proposed in this paper. Many combinations were evaluated from real time condition process, to achieve the best optimization results. The experimental results demonstrate that real time adaptive control can be achieved by using three clusters, which are heating up, stabilizing and finishing. In RTAC, each cluster has its own parameter to set the control point by the servo motor that was attached to magnetic stirrer-heater. By using optimization parameter for each cluster, esterification process time can be shortened by 15-20 minutes with a higher yield (7% or more), lower range stirrer rotation (300rpm-450 rpm) and a lower final temperature of 200℃ - 210℃.

关键词： Optimization Real Time Adaptive Control Glycerol Esterification

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Erratum: An intrinsic mechanism controls reactivation of neural stem cells by spindle matrix proteins

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Nature communications 2017年第1期8卷 1298页

作者： Song Li Chwee Tat Koe Su Ting Tay Angie Lay Keng Tan Shenli Zhang Yingjie Zhang Patrick Tan Wing-Kin Sung Hongyan Wang Neuroscience and Behavioural Disorders Program Duke-NUS Medical School 8 College Road Singapore 169857 Singapore. Cancer and Stem Cell Biology Program Duke-NUS Medical School 8 College Road Singapore 169857 Singapore. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore 28 Medical Drive Singapore 117456 Singapore. Cellular and Molecular Research National Cancer Centre Singapore 169610 Singapore. Cancer Science Institute of Singapore National University of Singapore Singapore 119074 Singapore. Genome Institute of Singapore 60 Biopolis Street Genome 02-01 Singapore 138672 Singapore. Department of Computer Science National University of Singapore Singapore 117417 Singapore. Neuroscience and Behavioural Disorders Program Duke-NUS Medical School 8 College Road Singapore 169857 Singapore. hongyan.wang@duke-nus.edu.sg. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore 28 Medical Drive Singapore 117456 Singapore. hongyan.wang@duke-nus.edu.sg. Department of Physiology Yong Loo Lin School of Medicine National University of Singapore Singapore 117597 Singapore. hongyan.wang@duke-nus.edu.sg.

A correction to this article has been published and is linked from the HTML version of this article.

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Conference on Advances in Signal Processing (CASP)

作者： Shri Promoad Gorhe Pradeep K. Sinha Madhuri A. Joshi M. B. Khambete Prachi Mukherji James L Garrison Pramod Kale Hemant A. Patil Aditya Abhyankar Arnab Das Maharshi Karve Stree Shikshan Samstha New Raipur University FIET (U.K.) FIE (I) FIETE (I) IET Pune Local Network College of Engineering Pune CCEW General Chair CASP-2016 (E&TC) CCEW Co Chair CASP-2016 Aeronautics and Astronautics Electrical and Computer Engineering (by courtesy) Ecological Sciences & Engineering Interdisciplinary Graduate Program Purdue University USA ICIT Pvt. Ltd. Pune Former Director ISRO DA-IICT Gandhinagar Gujarat State Faculty of Technology University of Pune Department of Technology University of Pune Acoustic Research Lab of the Tropical Marine Science Institute at the National University of Singapore Retd. Electrical Officer Indian Navy (1994 - 2015) Adjunct Faculty at IIT Delhi and DIAT Pune

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

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Distributed keyword vector representation for document categorization

Distributed keyword vector representation for document categ...

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International Conference on Technologies and Applications of Artificial Intelligence (TAAI)

作者： Yu-Lun Hsieh Shih-Hung Liu Yung-Chun Chang Wen-Lian Hsu Department of Computer Science National Chengchi University Taiwan Social Networks and Human-Centered Computing Program Academia Sinica Taiwan Institute of Information Science Academia Sinica Taiwan Graduate Institute of Electrical Engineering National Taiwan University Taiwan Departmem of Information Management National Taiwan University Taiwan

ISBN: (纸本)9781467396073

In the age of information explosion, efficiently categorizing the topic of a document can assist our organization and comprehension of the vast amount of text. In this paper, we propose a novel approach, named DKV, for document categorization using distributed real-valued vector representation of keywords learned from neural networks. Such a representation can project rich context information (or embedding) into the vector space, and subsequently be used to infer similarity measures among words, sentences, and even documents. Using a Chinese news corpus containing over 100,000 articles and five topics, we provide a comprehensive performance evaluation to demonstrate that by exploiting the keyword embeddings, DKV paired with support vector machines can effectively categorize a document into the predefined topics. Results demonstrate that our method can achieve the best performances compared to several other approaches.

关键词： Computational modeling Manuals

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Galvanotactic control of collective cell migration in epithelial monolayers (vol 13, pg 409, 2014)

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NATURE MATERIALS 2014年第5期13卷 530-530页

作者： Cohen, Daniel J. Nelson, W. James Maharbiz, Michel M. Joint Graduate Program in Bioengineering University of California at Berkeley Berkeley California 94720 USA Department of Biology Molelcular Cellular Physiology Stanford University Stanford California 94305 USA Department of Electrical Engineering Computer Science University of California at Berkeley Berkeley California 94720 USA

Many normal and pathological biological processes involve the migration of epithelial cell sheets. This arises from complex emergent behaviour resulting from the interplay between cellular signalling networks and the forces that physically couple the cells. Here, we demonstrate that collective migration of an epithelium can be interactively guided by applying electric fields that bias the underlying signalling networks. We show that complex, spatiotemporal cues are locally interpreted by the epithelium, resulting in rapid, coordinated responses such as a collective U-turn, divergent migration, and unchecked migration against an obstacle. We observed that the degree of external control depends on the size and shape of the cell population, and on the existence of physical coupling between cells. Together, our results offer design and engineering principles for the rational manipulation of the collective behaviour and material properties of a tissue.

关键词： CELL migration EPITHELIUM EPITHELIAL cells CELL populations SPATIOTEMPORAL processes

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Using Bipartite Graphs for 3D Cardiac Model Retrieval

Using Bipartite Graphs for 3D Cardiac Model Retrieval

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Leila C.C. Bergamasco Hellyan Oliveira Helton Bíscaro Harry Wechsler Fátima L.S. Nunes Polytechnic School - Graduate Program in Electrical Engineering University of Sao Paulo São Paulo SP Brasil Laboratory of Health Informatics Applications University of Sao Paulo São Paulo SP Brasil Department of Computer Science George Mason University Fairfax VA USA

Three-dimensional models have been used to aid medical diagnoses, using images generated by modalities like Magnetic Resonance Imaging. They can provide a more complete vision of objects since their depth is taken into account. Content-based Image Retrieval (CBIR) has also been used to aid the diagnosis. One important step in Three-dimensional CBIR (Model Retrieva) systems is the comparison between two models by using a set of features extracted and stored in a database. In this paper we present a novel method to compare two models, using the Bipartite graphs technique, with the aim to improve the retrieval precision. This technique retrieves 3D medical models of the left ventricle in order to aid the diagnosis of Congestive Heart Failure. Results showed that the novel method improved the precision by 10% when compared to the Similarity Function of Euclidean and Manhattan distance. These results confirmed that bipartite graph techniques can be used to improve the accuracy of Model Retrieval systems.

关键词： Solid modeling Three-dimensional displays Computational modeling Medical diagnostic imaging Feature extraction Bipartite graph

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Metadata Correction: Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey

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Journal of medical Internet research 2017年第6期19卷 e209页

作者： Hsiao-Hsien Rau Yi-Syuan Wu Chi-Ming Chu Fu-Chung Wang Min-Huei Hsu Chi-Wen Chang Kang-Hua Chen Yen-Liang Lee Senyeong Kao Yu-Lung Chiu Hsyien-Chia Wen Anis Fuad Chien-Yeh Hsu Hung-Wen Chiu Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan. Administration Department Healthconn Corp Taipei Taiwan. Institute of Medical Informatics Department of Computer Science of Information Engineering National Cheng Kung University Tainan Taiwan. School Of Public Health National Defense Medical Center Taiepi Taiwan. National Health Insurance Administration Ministry of Health and Welfare Taiepi Taiwan. School of Nursing College of Medicine Chang Gung University Linkou Taiwan. Division of Endocrinology Department of Pediatrics Linkou Chang Gung Memorial Hospital Linkou Taiwan. Internet of Things Laboratory Chunghwa Telecom Laboratories TaoYuen Taiwan. School of Health Care Administration Taipei Medical University Taipei Taiwan. Department of Biostatistics Epidemiology and Population Health Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia. Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan. Master Program in Global Health and Development Taipei Medical University Taipei Taiwan.

[This corrects the article DOI: .].

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Parametric sensitivity analysis of cOptBees optimal clustering algorithm 14

Parametric sensitivity analysis of cOptBees optimal clusteri...

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2014 14th International Conference on Intelligent Systems Design and Applications, ISDA 2014

作者： Cruz, Dávila Patrícia Ferreira Maia, Renato Dourado De Castro, Leandro Nunes Graduate Program in Electrical Engineering Mackenzie University São Paulo Brazil Computer Science Department State University of Montes Claros Montes Claros MG Brazil

ISBN: (纸本)9781479979387

Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same group are more similar to one another than to objects belonging to other groups. Many algorithms to solve data clustering problems have been presented in the literature. Recently, bee-inspired clustering algorithms have been proposed, presenting good performance to find groups in data. This paper aims to present the parametric sensitivity analysis of cOptBees, a bee-inspired clustering algorithm designed to find optimal clusters in datasets. The algorithm was run for different parameter configurations to assess the influence of each parameter in its performance. © 2014 IEEE.

关键词： Clustering algorithms

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Proceedings of the 23rd Paediatric Rheumatology European Society Congress: part three Abstracts

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PEDIATRIC RHEUMATOLOGY 2017年第1期15卷 203-259页

作者： [Anonymous] Pediatria II Reumatologia Istituto Giannina Gaslini Genoa Italy Radiologia Istituto Giannina Gaslini Genoa Italy University of Trieste Trieste Italy Division of Rheumatology Ospedale Pediatrico Bambino Gesù IRCCS Roma Italy Institute for Maternal and Child Health - IRCCS “Burlo Garofolo” Trieste Italy Pediatric Rheumatology Uludag University Medical Faculty Bursa Turkey Department of Pediatrics Nippon Medical School Tokyo Japan Division of Physiotherapy and Rehabilitaiton Faculty of Health Sciences Istanbul University Istanbul Turkey Department of Computer Engineering Gebze Institute of Technology Kocaeli Turkey Department of Pediatric Rheumatology Medical Faculty of Cerrahpasa Istanbul University Istanbul Turkey Department of Paediatric Rheumatology and Psychology Alder Hey Children’s NHS Foundation Trust Liverpool UK Department of Women’s and Children’s Health Institute of Translational Medicine Liverpool UK UK Experimental Arthritis Treatment Centre for Children University of Liverpool Liverpool UK Rheumatology Hospital for Sick Children Toronto Canada Pediatrics University of Toronto Toronto Canada Child Evaluative Health Sciences The Hospital for Sick Children Toronto Canada Lawrence S. Bloomberg Faculty of Medicine University of Toronto Toronto Canada Psychology University of Kansas Medical Center Lawrence USA Rheumatology IWK Health Center Halifax Canada Rheumatology Alberta children’s Hospital Calgary Canada Ingram School of Nursing Mcgill University Montreal Canada Child Health Evaluative Sciences Hospital for Sick Children Toronto Canada Rheumatology Children’s Hospital of Western Ontario London Canada Rheumatology CHU Ste-Justine Montreal Canada Rheumatology Montreal Children’s Hospital Montreal Canada Pediatrics Memorial University of Newfoundland St John’s Canada Pediatrics Children’s Hospital of Eastern Ontario Ottawa Canada Research Innovation and Knowledge Translation IWK Health Center Halifax Canada Pediatrics

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