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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Efficient parallel tree reductions on distributed memory environments

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Scalable Computing 2017年第1期18卷 1-15页

作者： Kakehi, Kazuhiko Matsuzakl, Kiminori Emoto, Kento Academic Co-Innovation Division UTokyo Innovation Platform Co. Ltd. 3-40-10 Hongo Bunkyo-ku Tokyo113-0033 Japan School of Information Kochi University of Technology 185 Tosayamadacho-Miyanokuchi Kami Kochi782-8502 Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820-8502 Japan

A new approach for fast parallel reductions on trees over distributed memory environments is presented. The start point of our approach is to employ the serialized representation of trees. Along this data representation with high memory locality and ease of initial data representation, we developed an parallelized algorithm which shares the essence with the parallel algorithm for parentheses matching problems. Our algorithm not only is proven to be theoretically efficient, but also has a fast implementation in a BSP style. © 2017. SCPE.

关键词： Trees (mathematics)

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Flexural and Compressive Properties of Hybrid Kenaf/Silica Nanoparticles in Epoxy Composite

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Procedia Chemistry 2016年 19卷 955-960页

作者： Farid Bajuri Norkhairunnisa Mazlan Mohamad Ridzwan Ishak Junichiro Imatomi Department of Aerospace Engineering Faculty of Engineering Universiti Putra Malaysia Selangor Malaysia School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan

Kenaf fiber like other natural fibers is used as a sustainable form of material to fabricate composite. But natural fibers are generally weaker than synthetic fibers due to the porosity of the fibers making them grow weaker mechanically and physically as time passes. To improve the quality of kenaf reinforced composite, silica nanoparticles was introduced as a filler material. Silica nanoparticle is a material with high surface area contributing to its high interfacial interaction with the matrix resulting in the improvement of the matrix. In this work, the composites were fabricated via vacuum infusion process by creating a system in which the compressed randomly orientated kenaf mat are laid in. The silica nanoparticles are dispersed into the epoxy using a homogenizer at 3000 rpm for 10 minutes before being infused into the fibers. The results shows that generally the inclusion of hydrophobic silica nanoparticles had a detrimental effect on the mechanical properties. However, composites with 2 vol% silica had the best mechanical properties of specimens with silica nanoparticles included at 43.8 MPa and 3.05 GPa for flexural strength and flexural modulus, and 40.0 MPa and 1.15 GPa for compressive strength and compressive modulus, respectively.

关键词： Silica Nanoparticles Kenaf Natural Fiber Mechanical Properties

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Plenary speaker

Plenary speaker

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International Conference on Power systems (ICPS)

作者： Anurag Srivastava Mohan Kolhe Alberto Borghetti Rajiv K. Varma Prasad Enjeti S. S. Mani Venkata Sushil K. Soonee Deepakraj M. Divan School of Electrical Engineering & Computer Science Washington State University USA Faculty of Engineering and Science University of Agder Norway Department of Electrical Electronic and Information Engineering “Guglielmo Marconi” University of Bologna Italy Electrical and Computer Engineering Department The University of Western Ontario London ON Canada Electrical and Computer Engineering Department Texas A & M University Texas USA Departmnet of Electrical Engineering University of Washington Seattle WA USA Power System Operation Corp. Ltd. New Delhi India John E Pippin Chair Director of the Center for Distributed Energy Georgia Institute of Technology Atlanta GA

Provides an abstract of the plenary presentation and may include a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.

关键词： Renewable energy sources Smart grids Electrical engineering Power system stability Patents Education

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PB-10Highly Sensitive Fluorescence Imaging of the Cytoplasmic pH Related to the Cellular Functions

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Microscopy 2017年第SUPPL_1期66卷 i37-i37页

作者： Morimoto, Yusuke V Department of Bioscience and Bioinformatics Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka Japan.

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Aware Environment for Workshop with Game Storming

Aware Environment for Workshop with Game Storming

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Noriyuki Kushiro Tatsuya Ehira Rei Kaihara Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iiduka Fukuoka Japan Department of Creative Informatics Kyushu Institute of Technology Iiduka Fukuoka Japan

ISBN: (纸本)9781509059119

A context aware environment for workshop with game storming was developed with vision sensors and was evaluated its capability for supporting facilitator of workshop through feasibility test. In this paper, overview of the aware environment for workshop, basic capability of the environment, and results of feasibility test are described.

关键词： Conferences Sensors Frequency estimation Thumb Indexes Cameras

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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

引用

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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Occurrence rate per bit for any control parameter on the logistic map over integers

Occurrence rate per bit for any control parameter on the log...

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International Symposium on Information Theory and Its Applications, ISITA

作者： Hideyuki Muraoka Shunsuke Araki Takeru Miyazaki Satoshi Uehara Ken'ichi Kakizaki Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka Japan Faculty of Environmental Engineering the University of Kitakyushu Kitakyushu Fukuoka Japan Kyushu Kogyo Daigaku Kitakyushu Fukuoka JP

We have been investigating behaviors of the logistic map over integers for constructing a pseudorandom number generator with the map. In the presented paper, we will give a 0/1-occurrence rate per bit for values by the logistic map over integers, and discuss suitable bit positions of a bit extraction for getting a pseudorandom bit sequence. First, we will show characteristic behaviors of occurrence rates of values by the map. Second, we will indicate any control parameter are classified into four types which have the distinguished 0/1-occurrence rate patterns. Third, we will show the 0/1-occurrence rate per bit for elements of a sequence generated by the map experimentally. Fourthly, we will introduce a part of the proof for the 0/1-occurrence rate per bit in the low-order bits. Finally, we will suggest suitable bit positions to be extracted for generating a pseudorandom bit sequence.

关键词： Logistics Generators Computational modeling Mathematical model computer science computers

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Implementation of augmented reality to train focus on children with s pecial needs

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Journal of Physics: Conference Series 2018年第1期978卷

作者： M F Syahputra P P Sari D Arisandi D Abdullah D Napitupulu M I Setiawan W Albra Asnawi U Andayani Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Research Center for Quality System and Testing Technology - Indonesian Institute of Sciences Department of Civil Engineering Narotama University Surabaya Indonesia Department of Management Universitas Malikussaleh Aceh Indonesia Department of Elementary Teacher Education Universitas Samudra Aceh Indonesia

Differences possessed by children with special needs such as differences in mental traits, sensory abilities, social and emotional behavior etc. of normal children causing learning and developmental barriers on children, so that requiring more specific services. Autism is one category of children with special needs who experience delays in responding to the things around him that caused by chaos in the brain work system. The tendency of autistic children who only focus on themselves makes it difficult to concentrate on one thing and easily switch when being talked. Training focus of the child can be done by giving them basic commands presented with visually appealing from the utilization of augmented reality and leap motion controller.

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Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization:a case study in Central Vietnam

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International Journal of Digital Earth 2016年第11期9卷 1077-1097页

作者： Dieu Tien Bui Binh Thai Pham Quoc Phi Nguyen Nhat-Duc Hoang Geographic Information System Group Department of Business Administration and Computer ScienceUniversity College of Southeast NorwayBøi TelemarkNorway Faculty of Geomatics and Land Administration Hanoi University of Mining and GeologyHanoiVietnam Department of Civil Engineering Gujarat Technological UniversityAhmedabadGujaratIndia Department of Geotechnical Engineering University of Transport TechnologyHa NoiVietNam Department of Environmental Sciences Hanoi University of Mining and GeologyHanoiVietnam Faculty of Civil Engineering Institute of Research and DevelopmentDuy Tan UniversityDanangVietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction,named as *** LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM *** this research,a GIS database with 129 historical landslide records in the Quy Hop area(Central Vietnam)has been collected to establish the hybrid *** receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to assess the performance of the newly constructed *** results show that the proposed model has high performances with approximately 82%of AUCs on both training and validating *** model’s results were compared with those obtained from other methods,Support Vector Machines,Multilayer Perceptron Neural Networks,and J48 Decision *** result comparison demonstrates that the DE-LSSVMSLP deems best suited for the dataset at hand;therefore,the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.

关键词： Shallow landslide Least-Squares Support Vector Machines differential evolution GIS Vietnam

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