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Author Correction: A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response

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Nature genetics 2021年第12期53卷 1722页

作者： Yang Luo Masahiro Kanai Wanson Choi Xinyi Li Saori Sakaue Kenichi Yamamoto Kotaro Ogawa Maria Gutierrez-Arcelus Peter K Gregersen Philip E Stuart James T Elder Lukas Forer Sebastian Schönherr Christian Fuchsberger Albert V Smith Jacques Fellay Mary Carrington David W Haas Xiuqing Guo Nicholette D Palmer Yii-Der Ida Chen Jerome I Rotter Kent D Taylor Stephen S Rich Adolfo Correa James G Wilson Sekar Kathiresan Michael H Cho Andres Metspalu Tonu Esko Yukinori Okada Buhm Han Paul J McLaren Soumya Raychaudhuri Center for Data Sciences Brigham and Women's Hospital Harvard Medical School Boston MA USA. yangluo@***. Division of Rheumatology Immunology and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA USA. yangluo@***. Division of Genetics Brigham and Women's Hospital Harvard Medical School Boston MA USA. yangluo@***. Department of Biomedical Informatics Harvard Medical School Boston MA USA. yangluo@***. Broad Institute of MIT and Harvard Cambridge MA USA. yangluo@***. Department of Biomedical Informatics Harvard Medical School Boston MA USA. Broad Institute of MIT and Harvard Cambridge MA USA. Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA. Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Department of Biomedical Sciences Seoul National University College of Medicine Seoul South Korea. Committee on Genetics Genomics and Systems Biology University of Chicago Chicago IL USA. Center for Data Sciences Brigham and Women's Hospital Harvard Medical School Boston MA USA. Division of Rheumatology Immunology and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA USA. Division of Genetics Brigham and Women's Hospital Harvard Medical School Boston MA USA. Department of Pediatrics Osaka University Graduate School of Medicine Osaka Japan. Department of Neurology Osaka University Graduate School of Medicine Osaka Japan. The Robert S. Boas Center for Genomics and Human Genetics Feinstein Institute for Medical ResearchNorth Short LIJ Health System Manhasset NY USA. Department of Dermatology University of Michigan Ann Arbor MI USA. Ann Arbor Veterans Affairs Hospital Ann Arbor MI USA. Institute of Genetic Epidemiology Department of Genetics and Pharmacology Medical University of Innsbruck Innsbruck Austria. Department of Biostatistics

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LUC Algorithm in Visual Cryptography

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Ratnadewi Christian Dio Alpha G Darmawan Napitupulu Heri Nurdiyanto Nuning Kurniasih Abdurrozaq Hasibuan GS Achmad Daengs Rosida Tiurma Manurung Indrya Mulyaningsih Robbi Rahim Castaka Agus Sugianto Dahlan Abdullah Department of Electrical Engineering Universitas Kristen Maranatha Bandung Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Banten Indonesia STMIK Dharma Wacana Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Universitas Islam Sumatera Utara Indonesia University of 45 Surabaya Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Bandung Indonesia Department of Education Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Politeknik TEDC Bandung Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia

Nowadays, messaging technology in digital data form more often used and not less messages that confidentially wanted. Then it should be modified so that can be understood only by the sender and the intended recipients. All of this system can be realization by using cryptography. LUC algorithms are introduced by Smith and Lennon in 1993. LUC algorithm is an algorithm that based on the use of Lucas sequence (specific arithmetic operations derived from Lucas row) that rarely used to enhance the security of the messages. In this research, LUC algorithm is combined with visual cryptography to process the encryption and the description of a colored image. Four different images were used in the trial here. The performance of the system is assessed using Structural similarity (SSIM) which has an assessment similar to human eye. If the image quality is the same as the original image, then the SSIM value is one. Whereas if the quality of decryption image is very different from the original image then the value of SSIM is zero.

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Abstracts and Workshops 7th National Spinal Cord Injury Conference November 9-11, 2017 Fallsview Casino Resort Niagara Falls, Ontario, Canada Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2017年第6期40卷 813-869页

作者： [Anonymous] a NET Team Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. fo Neural Engineering and Therapeutic Team Lyndhurst Centre Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. c Rick Hansen Institute Vancouver BC Canada. ev Rick Hansen Institute Vancouver BC Canada. fc Stan Cassidy Hospital University of New Brunswick Fredericton NB Canada. fd Dalhousie University Halifax NS Canada. e University of Saskatchewan Saskatoon SK Canada. aa University of Calgary Calgary AB Canada. y Dalhousie University Halifax NS Canada. fa Health Sciences Centre Winnipeg MB Canada. fb University of Manitoba Winnipeg MB Canada. h University of Alberta Edmonton AB Canada. i Universite Laval Quebe c City QC Canada. bd Rick Hansen Institute Vancouver BC Canada. fz Clinician Investigator Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto. v University of Toront o Toronto ON Canada. n Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada. o Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. ga Clinical Scientist Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Physical Therapy University of Toronto. dx Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. fm Lawson Health Research Institute London ON Canada. r Parkwood Institute London ON Canada. bi Parkwood Institute London ON Canada. s University of British Columbia Vancouver BC Canada. t Simon Fraser University Burnaby BC Canada. u DeltaQuest Foundation Concord MA USA. z Institut national d'excellence en santé et en services sociaux (INESSS) Quebec City QC Ca

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Author Correction: Post-treatment with PT302, a long-acting Exendin-4 sustained release formulation, reduces dopaminergic neurodegeneration in a 6-Hydroxydopamine rat model of Parkinson's disease

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Scientific reports 2018年第1期8卷 13953页

作者： Shuchun Chen Seong-Jin Yu Yazhou Li Daniela Lecca Elliot Glotfelty Hee Kyung Kim Ho-Il Choi Barry J Hoffer Nigel H Greig Dong Seok Kim Yun Wang Center for Neuropsychiatric Research National Health Research Institutes Zhunan Taiwan. Graduate Institute of Applied Science and Engineering Fu-Jen Catholic University New Taipei Taiwan. Drug Design and Development Section Translational Gerontology Branch Intramural Research Program National Institute on Aging National Institutes of Health Baltimore MD USA. Peptron Inc. Yuseong-gu Daejeon Republic of Korea. Department of Neurosurgery Case Western Reserve University School of Medicine Cleveland OH USA. Drug Design and Development Section Translational Gerontology Branch Intramural Research Program National Institute on Aging National Institutes of Health Baltimore MD USA. Greign@mail.nih.gov. Center for Neuropsychiatric Research National Health Research Institutes Zhunan Taiwan. ywang@nhri.org.tw.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

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Analysis of trunk movement for pregnant women with lumbopelvic pain using inertial measurement unit 16

Analysis of trunk movement for pregnant women with lumbopelv...

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4th International Conference on Control, Mechatronics and Automation, ICCMA 2016

作者： Morino, Saori Umezaki, Fumiko Hatanaka, Hiroko Aoyama, Tomoki Yamashita, Mamoru Takahashi, Masaki Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa Japan Kishokai Medical Corporation 2-4-15 Nishiki Naka-ku Nagoya Aichi Japan Department of Physical Therapy Human Health Sciences Graduate School of Medicine Kyoto University 53 Kawahara-cho Shogoin Sakyoku Kyoto Japan Department of System Design Engineering Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa Japan

ISBN: (纸本)9781450352130

Many women experience lumbopelvic pain (LPP) during pregnancy. It is thought that motion patterns, especially when accompanied by flexure and rotation of the trunk, are associated with LPP. This study investigates methods to evaluate the characteristics of the motion patterns that affect LPP during pregnancy. An experiment was conducted to obtain the motion characteristics of standing up and sitting down of pregnant women by using an inertial measurement unit (IMU). Then motion evaluation indexes were proposed from measured data of lumbar angular velocity obtained from the IMU. Next, the proposed indexes, maximum peak value, minimum peak value, peak-topeak (PP: range between maximum and minimum peaks) value, time of PP, PP divided by time of PP, root mean square of each parameter, and each index divided by body mass index (BMI), were calculated during standing up and sitting down for the roll, pitch, and yaw angles. Finally, we considered the presence of any relation between LPP and the motion characteristics by comparing the proposed indexes of an LPP group with those of a non-LPP group. Thus, it appears that maximum peak, PP/time of PP, maximum peak/BMI, PP/BMI, and (PP/Time of PP)/BMI of the pitch angle have some relevance to LPP. © 2016 ACM.

关键词： Obstetrics

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Corrigendum to "A mixed-effects model approach for the statistical analysis of vocal fold viscoelastic shear properties" [J. Mech. Behav. Biomed. Mater. 75 (2017) 477-485]

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Journal of the mechanical behavior of biomedical materials 2018年 79卷 114页

作者： Chet C Xu Roger W Chan Han Sun Xiaowei Zhan Department of Otolaryngology-Head and Neck Surgery University of Texas Southwestern Medical Center Dallas TX 75390 USA Graduate Program in Biomedical Engineering University of Texas Southwestern Medical Center Dallas TX 75390 USA. Electronic address: che.xu@utsouthwestern.edu. Department of Speech Language Pathology National Taipei University of Nursing and Health Sciences Taipei Taiwan. Department of Quantitative Health Sciences the Cleveland Clinic Foundation Cleveland OH 44195 USA Department of Population and Quantitative Health Sciences Case Western Reserve University Cleveland OH 44106 USA. Department of Clinical Science University of Texas Southwestern Medical Center Dallas TX 75390 USA.

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LifeTime and improving European healthcare through cell-based interceptive medicine (vol 587, pg 377, 2020)

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NATURE 2021年第7852期592卷 E8-E8页

作者： Rajewsky, Nikolaus Almouzni, Genevieve Gorski, Stanislaw A. Aerts, Stein Amit, Ido Bertero, Michela G. Bock, Christoph Bredenoord, Annelien L. Cavalli, Giacomo Chiocca, Susanna Clevers, Hans De Strooper, Bart Eggert, Angelika Ellenberg, Jan Fernandez, Xose M. Figlerowicz, Marek Gasser, Susan M. Hubner, Norbert Kjems, Jorgen Knoblich, Jurgen A. Krabbe, Grietje Lichter, Peter Linnarsson, Sten Marine, Jean-Christophe Marioni, John C. Marti-Renom, Marc A. Netea, Mihai G. Nickel, Dorthe Nollmann, Marcelo Novak, Halina R. Parkinson, Helen Piccolo, Stefano Pinheiro, Ines Pombo, Ana Popp, Christian Reik, Wolf Roman-Roman, Sergio Rosenstiel, Philip Schultze, Joachim L. Stegle, Oliver Tanay, Amos Testa, Giuseppe Thanos, Dimitris Theis, Fabian J. Torres-Padilla, Maria-Elena Valencia, Alfonso Vallot, Celine van Oudenaarden, Alexander Vidal, Marie Voet, Thierry Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine in the Helmholtz Association Berlin Germany Charité-Universitätsmedizin Berlin Germany Berlin Institute of Health (BIH) Berlin Germany German Center for Cardiovascular Research (DZHK) Partner Site Berlin Berlin Germany Institute for Biology Humboldt University of Berlin Berlin Germany Cardiovascular and Metabolic Sciences Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany Department of Pediatric Oncology/Hematology Charité-Universitätsmedizin Berlin Berlin Germany Institut Curie CNRS PSL Research University Sorbonne Université Nuclear Dynamics Unit Equipe Labellisée Ligue contre le cancer Paris France VIB Center for Brain and Disease Research Leuven Belgium Department of Human Genetics KU Leuven Leuven Belgium Department of Neurosciences KU Leuven Leuven Belgium UK Dementia Research Institute at UCL University College London London UK Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK Department of Immunology Weizmann Institute of Science Rehovot Israel Centre for Genomic Regulation (CRG) Barcelona Institute of Science and Technology Barcelona Spain CNAG-CRG Centre for Genomic Regulation Barcelona Institute of Science and Technology Barcelona Spain Universitat Pompeu Fabra Barcelona Spain ICREA Barcelona Spain CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria Department of Laboratory Medicine Medical University of Vienna Vienna Austria Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases Vienna Austria Department of Medical Humanities Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Institute of Human Genetics UMR 9002 CNRS and University of Montpellier Montpellier France Department of Experimental Oncology IEO European Institute of Oncology IRCCS Milan Italy Department of Oncology and Hemato

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Correction to:FungalTraits:a user friendly traits database of fungi and fungus-like stramenopiles

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Fungal Diversity 2021年第2期107卷 129-132页

作者： Sergei Põlme Kessy Abarenkov RHenrik Nilsson Björn D.Lindahl Karina Engelbrecht Clemmensen Havard Kauserud Nhu Nguyen Rasmus Kjøller Scott T.Bates Petr Baldrian Tobias Guldberg Frøslev Kristjan Adojaan Alfredo Vizzini Ave Suija Donald Pfister Hans-Otto Baral Helle Järv Hugo Madrid Jenni Nordén Jian-Kui Liu Julia Pawlowska Kadri Põldmaa Kadri Pärtel Kadri Runnel Karen Hansen Karl-Henrik Larsson Kevin David Hyde Marcelo Sandoval-Denis Matthew E.Smith Merje Toome-Heller Nalin N.Wijayawardene Nelson Menolli Jr Nicole K.Reynolds Rein Drenkhan Sajeewa S.N.Maharachchikumbura Tatiana B.Gibertoni Thomas Læssøe William Davis Yuri Tokarev Adriana Corrales Adriene Mayra Soares Ahto Agan Alexandre Reis Machado Andrés Argüelles-Moyao Andrew Detheridge Angelina de Meiras-Ottoni Annemieke Verbeken Arun Kumar Dutta Bao-Kai Cui C.K.Pradeep César Marín Daniel Stanton Daniyal Gohar Dhanushka N.Wanasinghe Eveli Otsing Farzad Aslani Gareth W.Griffith Thorsten H.Lumbsch Hans-Peter Grossart Hossein Masigol Ina Timling Inga Hiiesalu Jane Oja John Y.Kupagme József Geml Julieta Alvarez-Manjarrez Kai Ilves Kaire Loit Kalev Adamson Kazuhide Nara Kati Küngas Keilor Rojas-Jimenez Krišs Bitenieks LászlóIrinyi LászlóGNagy Liina Soonvald Li-Wei Zhou Lysett Wagner M.Catherine Aime MaarjaÖpik María Isabel Mujica Martin Metsoja Martin Ryberg Martti Vasar Masao Murata Matthew P.Nelsen Michelle Cleary Milan C.Samarakoon Mingkwan Doilom Mohammad Bahram Niloufar Hagh-Doust Olesya Dulya Peter Johnston Petr Kohout Qian Chen Qing Tian Rajasree Nandi Rasekh Amiri Rekhani Hansika Perera Renata dos Santos Chikowski Renato L.Mendes-Alvarenga Roberto Garibay-Orijel Robin Gielen Rungtiwa Phookamsak Ruvishika S.Jayawardena Saleh Rahimlou Samantha C.Karunarathna Saowaluck Tibpromma Shawn P.Brown Siim-Kaarel Sepp Sunil Mundra Zhu-Hua Luo Tanay Bose Tanel Vahter Tarquin Netherway Teng Yang Tom May Torda Varga Wei Li Victor Rafael Matos Coimbra Virton Rodrigo Targino de Oliveira Vitor Xavier de Lima Vladimir S.Mikryukov Yongzhong Lu Yosuke Matsuda Yumiko Miyamoto Urm Institute of Ecology and Earth Sciences University of Tartu14A Ravila50411 TartuEstonia Natural History Museum University of Tartu46 Vanemuise Str51003 TartuEstonia Gothenburg Global Biodiversity Centre Box 46140530 GothenburgSweden Department of Biological and Environmental Sciences University of GothenburgGothenburgSweden Department of Soil and Environment Swedish University of Agricultural SciencesBox 701475007 UppsalaSweden Department of Forest Mycology and Plant Pathology Swedish University of Agricultural SciencesBox 702675007 UppsalaSweden Section for Genetics and Evolutionary Biology(EvoGene) Department of BiosciencesUniversity of OsloP.O.Box 1066BlindernNO-0316 OsloNorway University of Hawaiʻi at Mānoa 3190 Maile WaySt.John 102HonoluluHIUSA Department of Biology University of CopenhagenUniversitetsparken 152100 CopenhagenØDenmark Purdue University Northwest WestvilleIN 46391USA Institute of Microbiology Czech Academy of SciencesVidenska 108314220 Praha 4Czech Republic GLOBE Institute University of CopenhagenØster Farimagsgade 5KH7.2.321353 CopenhagenDenmark Dipartimento di Scienze della Vita e Biologia dei Sistemi Universitàdi TorinoViale Mattioli 2510125 TorinoItaly Department of Organismic and Evolutionary Biology and Farlow Library and Herbarium Harvard University22 Divinity AveCambridgeMA 02138USA Blaihofstr.42 72074 TübingenGermany SYNLAB Estonia Veerenni 53aTallinn 11313Estonia Escuela de Tecnología Médica Universidad Santo TomásLos Carreras 753OsornoChile Centro de Genómica y Bioinformática Universidad MayorCamino La Pirámide 5750HuechurabaSantiagoChile Norwegian Institute for Nature Research(NINA) Sognsveien 680855 OsloNorway School of Life Science and Technology University of Electronic Science and Technology of ChinaChengdu 611731People’s Republic of China Evolutionary Biology Faculty of BiologyBiological and Chemical Research CentreUniversity of Warsawul.Zwirki i Wigury 10102-089 WarsawPoland Department of Botany Swedish Museum of

Correction to:Fungal Diversity(2020)105:116 https://***/10.1007/s13225-020-00466-2 There were errors in the name of author László*** and in affiliation no.31 in the original *** original article has been cor... 详细信息

关键词： database ram friendly

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Design of Decision Support system Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Muhammad Iqbal Dahlan Abdullah H Hartono Cut Ita Erliana S Sriadhi Nurmawati M Adhi Prasnowo Abdurrozzaq Hasibuan Akbar Iskandar Kundharu Saddhono Abdussakir Hastuti Musa Muhammad Ikhsan Setiawan Youmeni Sagala Rumiris Siahaan Eka Mayastika Sinaga Anggraini Syahputri Feby Milanie Henry Aspan Muammar Khaddafi Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan-Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making system of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods.

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