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Limited angle acousto-electrical tomography

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arXiv 2017年

作者： Hubmer, Simon Knudsen, Kim Li, Changyou Sherina, Ekaterina Johannes Kepler University Linz Doctoral Program Computational Mathematics Altenbergerstraße 69 LinzA-4040 Austria Technical University of Denmark Department of Applied Mathematics and Computer Science Asmussens Allé Kongens Lyngby2800 Denmark Technical University of Denmark Department of Applied Mathematics and Computer Science Asmussens Allé Kongens Lyngby2800 Denmark School of Electronics and Information Northwestern Polytechnical University Xian China Technical University of Denmark Department of Applied Mathematics and Computer Science Asmussens Allé Kongens Lyngby2800 Denmark

This paper considers the reconstruction problem in Acousto-Electrical Tomography, i.e., the problem of estimating a spatially varying conductivity in a bounded domain from measurements of the internal power densities resulting from different prescribed boundary conditions. Particular emphasis is placed on the limited angle scenario, in which the boundary conditions are supported only on a part of the boundary. The reconstruction problem is formulated as an optimization problem in a Hilbert space setting and solved using Landweber iteration. The resulting algorithm is implemented numerically in two spatial dimensions and tested on simulated data. The results quantify the intuition that features close to the measurement boundary are stably reconstructed and features further away are less well reconstructed. Finally, the ill-posedness of the limited angle problem is quantified numerically using the singular value decomposition of the corresponding linearized problem.65J22, 35R30, 65M32 Copyright © 2017, The Authors. All rights reserved.

关键词： Boundary conditions

Quantum computing at the frontiers of biological sciences

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arXiv 2019年

作者： Emani, Prashant S. Warrell, Jonathan Anticevic, Alan Bekiranov, Stefan Gandal, Michael McConnell, Michael J. Sapiro, Guillermo Aspuru-Guzik, Alán Baker, Justin Bastiani, Matteo McClure, Patrick Murray, John Sotiropoulos, Stamatios N. Taylor, Jacob Senthil, Geetha Lehner, Thomas Gerstein, Mark B. Harrow, Aram W. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Yale School of Medicine Department of Psychiatry New HavenCT06511 United States University of Virginia School of Medicine Department of Biochemistry and Molecular Genetics CharlottesvilleVA22903 United States Department of Psychiatry Semel Institute David Geffen School of Medicine University of California–Los Angeles 695 Charles E. Young Drive South Los AngelesCA90095 United States Univ. of Virginia School of Medicine Department of Neuroscience CharlottesvilleVA22903 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Chemistry University of Toronto 80 St. George Street TorontoONM5S 3H6 Canada TorontoONM5S 1M1 Canada CIFAR Artificial Intelligence Research Chair Vector Institute TorontoONM5S 1M1 Canada Department of Computer Science University of Toronto 40 St. George Street TorontoONM5S 2E4 Canada Schizophrenia and Bipolar Disorder Program McLean Hospital BelmontMA02478 United States Department of Psychiatry Harvard Medical School BostonMA02114 United States Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham NottinghamNG7 2RD United Kingdom Machine Learning Team National Institute of Mental Health BethesdaMD20892 United States Section on Functional Imaging Methods National Institute of Mental Health BethesdaMD20892 United States Department of Psychiatry Yale University School of Medicine New HavenCT06511 United States Department of Physics Yale University New HavenCT06511 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States National Institute of Standards and Technology GaithersburgMD20899 United States Office of Genomics Research Coordination N

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Efficient and scalable calculation of complex band structure using sakurai-sugiura method

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arXiv 2017年

作者： Iwase, Shigeru Futamura, Yasunori Imakura, Akira Sakurai, Tetsuya Ono, Tomoya Department of Physics University of Tsukuba Tsukuba Ibaraki305-8571 Master’s/Doctoral Program in Life Science Innovation University of Tsukuba Department of Computer Science University of Tsukuba Tsukuba Ibaraki305-8573 Department of Computer Science University of Tsukuba Tsukuba Ibaraki305-8573 Department of Computer Science University of Tsukuba Tsukuba Ibaraki 305-8573 CREST Japan Science and Technology Agency Kawaguchi Saitama332-0012 Department of Physics University of Tsukuba Tsukuba Ibaraki 305-8571 Center for Computational Sciences University of Tsukuba Tsukuba Ibaraki305-8577

Complex band structures (CBSs) are useful to characterize the static and dynamical electronic properties of materials. Despite the intensive developments, the first-principles calculation of CBS for over several hundred atoms is still computationally demanding. We here propose an efficient and scalable computational method to calculate CBSs. The basic idea is to express the Kohn-Sham equation of the real-space grid scheme as a quadratic eigenvalue problem and compute only the solutions which are necessary to construct the CBS by Sakurai-Sugiura method. The serial performance of the proposed method shows a significant advantage in both runtime and memory usage compared to the conventional method. Furthermore, owing to the hierarchical parallelism in Sakurai-Sugiura method and the domain-decomposition technique for real-space grids, we can achieve an excellent scalability in the CBS calculation of a boron and nitrogen doped carbon nanotube consisting of more than 10,000 atoms using 2,048 nodes (139,264 cores) of Oakforest-PACS. Copyright © 2017, The Authors. All rights reserved.

关键词： Carbon nanotubes

Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

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Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

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arXiv 2018年

作者： Li, Richard Di Felice, Rosa Rohs, Remo Lidar, Daniel Department of Chemistry University of Southern California Los AngelesCA90089 United States Computational Biology and Bioinformatics Program Department of Biological Sciences University of Southern California Los AngelesCA90089 United States Center for Quantum Information Science & Technology University of Southern California Los AngelesCA90089 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States Center S3 CNR Institute of Nanoscience Via Campi 213/A Modena41125 Italy Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Electrical Engineering University of Southern California Los AngelesCA90089 United States

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. Copyright © 2018, The Authors. All rights reserved.

关键词： Simulated annealing

Body appreciation around the world: Measurement invariance of the Body Appreciation Scale-2 (BAS-2) across 65 nations, 40 languages, gender identities, and age

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Body image 2023年 46卷 449-466页

作者： Viren Swami Ulrich S Tran Stefan Stieger Toivo Aavik Hamed Abdollahpour Ranjbar Sulaiman Olanrewaju Adebayo Reza Afhami Oli Ahmed Annie Aimé Marwan Akel Hussam Al Halbusi George Alexias Khawla F Ali Nursel Alp-Dal Anas B Alsalhani Sara Álvares-Solas Ana Carolina Soares Amaral Sonny Andrianto Trefor Aspden Marios Argyrides John Jamir Benzon R Aruta Stephen Atkin Olusola Ayandele Migle Baceviciene Radvan Bahbouh Andrea Ballesio David Barron Ashleigh Bellard Sóley Sesselja Bender Kerime Derya Beydağ Gorana Birovljević Marie-Ève Blackburn Teresita Borja-Alvarez Joanna Borowiec Miroslava Bozogáňová Solfrid Bratland-Sanda Matthew H E M Browning Anna Brytek-Matera Marina Burakova Yeliz Çakır-Koçak Pablo Camacho Vittorio Emanuele Camilleri Valentina Cazzato Silvia Cerea Apitchaya Chaiwutikornwanich Trawin Chaleeraktrakoon Tim Chambers Qing-Wei Chen Xin Chen Chin-Lung Chien Phatthanakit Chobthamkit Bovornpot Choompunuch Emilio J Compte Jennifer Corrigan Getrude Cosmas Richard G Cowden Kamila Czepczor-Bernat Marcin Czub Wanderson Roberto da Silva Mahboubeh Dadfar Simon E Dalley Lionel Dany Jesus Alfonso D Datu Pedro Henrique Berbert de Carvalho Gabriel Lins de Holanda Coelho Avila Odia S De Jesus Sonia Harzallah Debbabi Sandesh Dhakal Francesca Di Bernardo Donka D Dimitrova Jacinthe Dion Barnaby Dixson Stacey M Donofrio Marius Drysch Hongfei Du Angel M Dzhambov Claire El-Jor Violeta Enea Mehmet Eskin Farinaz Farbod Lorleen Farrugia Leonie Fian Maryanne L Fisher Michał Folwarczny David A Frederick Matthew Fuller-Tyszkiewicz Adrian Furnham Antonio Alías García Shulamit Geller Marta Ghisi Alireza Ghorbani Maria Angeles Gomez Martinez Sarah Gradidge Sylvie Graf Caterina Grano Gyöngyvér Gyene Souheil Hallit Motasem Hamdan Jonathan E Handelzalts Paul H P Hanel Steven R Hawks Issa Hekmati Mai Helmy Tetiana Hill Farah Hina Geraldine Holenweger Martina Hřebíčková Olasupo Augustine Ijabadeniyi Asma Imam Başak İnce Natalia Irrazabal Rasa Jankauskiene Ding-Yu Jiang Micaela Jiménez-Borja Verónica Jiménez-Borja Evan M Johnson Veljko Jov School of Psychology and Sport Science Anglia Ruskin University Cambridge United Kingdom Centre for Psychological Medicine Perdana University Kuala Lumpur Malaysia. Electronic address: viren.swami@aru.ac.uk. Department of Cognition Emotion and Methods in Psychology Faculty of Psychology University of Vienna Vienna Austria. Department of Psychology and Psychodynamics Karl Landsteiner University of Health Sciences Krems an der Donau Austria. Institute of Psychology University of Tartu Tartu Estonia. Department of Psychology Koç University Istanbul Turkiye. Department of Psychology and Behavioural Studies Ekiti State University Ado-Ekiti Nigeria. Department of Art Studies Tarbiat Modares University Tehran Iran. Department of Psychology University of Chittagong Chattogram Bangladesh. Department of Psychoeducation and Psychology Université du Québec en Outaouais Saint-Jérôme Canada. INSPECT-LB: National Institute of Public Health Clinical Epidemiology and Toxicology Beirut Lebanon School of Pharmacy Lebanese International University Beirut Lebanon. Department of Management Ahmed Bin Mohammad Military College Doha Qatar. Faculty of Psychology Panteion University of Social and Political Sciences Athens Greece. Royal College of Surgeons Ireland-Bahrain Adliya Bahrain. Department of Midwifery Faculty of Health Sciences Munzur University Tunceli Turkiya. Department of Oral Medicine and Diagnostic Sciences Vision College of Dentistry and Nursing Vision Colleges Riyadh Saudi Arabia. Facultad de Ciencias de la Vida Universidad Regional Amazónica Ikiam Muyuna Ecuador. Federal Institute of Education Science and Technology of Southeast Minas Gerais Barbacena Brazil. Department of Psychology Universitas Islam Indonesia Yogyakarta Indonesia. Department of Psychology Aberystwyth University Ceredigion United Kingdom. Department of Psychology Neapolis University Pafos Paphos Cyprus. Department of Psychology De La Salle University Phillippines. Department of Gen

The Body Appreciation Scale-2 (BAS-2) is a widely used measure of a core facet of the positive body image construct. However, extant research concerning measurement invariance of the BAS-2 across a large number of nations remains limited. Here, we utilised the Body Image in Nature (BINS) dataset - with data collected between 2020 and 2022 - to assess measurement invariance of the BAS-2 across 65 nations, 40 languages, gender identities, and age groups. Multi-group confirmatory factor analysis indicated that full scalar invariance was upheld across all nations, languages, gender identities, and age groups, suggesting that the unidimensional BAS-2 model has widespread applicability. There were large differences across nations and languages in latent body appreciation, while differences across gender identities and age groups were negligible-to-small. Additionally, greater body appreciation was significantly associated with higher life satisfaction, being single (versus being married or in a committed relationship), and greater rurality (versus urbanicity). Across a subset of nations where nation-level data were available, greater body appreciation was also significantly associated with greater cultural distance from the United States and greater relative income inequality. These findings suggest that the BAS-2 likely captures a near-universal conceptualisation of the body appreciation construct, which should facilitate further cross-cultural research.

关键词： Body appreciation Body appreciation Scale-2 (BAS-2) Cross-cultural Measurement invariance Multi-group confirmatory factor analysis (MG-CFA) Psychometrics Structural analysis

Systematic literature review on corruption prevention efforts towards sustainable economy in Indonesia: ICT perspective

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IOP Conference Series: Earth and Environmental science 2018年第1期195卷

作者： Noerlina D M Kristin R Dewanti Sasmoko T N Mursitama A M Muqsith S P Fajrianti N S Krishti B A Makalew Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480 Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia 11480 Research Interest Group in Educational Technology Bina Nusantara University Jakarta Indonesia 11480 International Relations Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Psychology Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia 11480 Mobile Application & Technology Program School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Corruption is an extraordinary crime and must be eradicated not only as fast as possible, but also as efficient and as effective as possible as it hinders the process of achieving sustainable economy. In current modern society, information technology exists as a multidisciplinary tool to solve lingering problems that could not be solved by traditional efforts. This paper aims to provide knowledge regarding identified efforts to fight corruption specifically in Indonesia region. Systematic Literature Review (SLR) methodology is used as the methodology, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow is used as framework to identify relevant records. Scopus database is used as data source. A total of 10 records are labelled as relevant to this research, and the findings are synthesized. It was found from the records that the main areas of interest for ICT research for corruption prevention in Indonesia are (1) information transparency, (2) operational enhancement, (3) success evaluation, (4) security and fraud, and (4) decision support. The findings are expected to assist future research in term of providing valuable insights on corruption prevention using ICT in Indonesia.

关键词：

ThinkLog: Interactive learning for supply chain management

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ThinkLog: Interactive learning for supply chain management

IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Lindawati Eko Nugroho Rio Fredericco Za'Aba Bin Abdul Rahim Robert de Souza The Logistics Institute - Asia Pacific National University of Singapore Singapore Kummara Studio Bandung Indonesia Center for Research on Information & Communication Technology Institute Technology Bandung Indonesia GameLab Computer Science Program Bina Nusantara University Jakarta Indonesia Kummara Studio Bandung Indonesia The Logistics Institute - Asia Pacific National University of Singapore Singapore

Serious games have been used to facilitate learning and training processes with examples of implementation in healthcare and military training. The learning objectives of these games are to help the players understand specific and complex concepts. This paper focuses on developing a board game, named ThinkLog, to facilitate learning on Supply Chain Management (SCM). It serves as a face-to-face interactive learning tool that can be expended to cover variations of scenarios. Using two interactive sessions with government officials, we are able to validate that ThinkLog was effective in deepening the players' understanding of SCM concepts.

关键词： Games Supply chains Conferences Education Supply chain management Tools

Challenges for Free Access to Law in a Multi-Jurisdictional Developing Country: Building the Legal information Institute of India

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Journal of National Law University Delhi 2018年第1期1卷 63–93页

作者： Graham Greenleaf VC Vivekanandan Philip Chung Ranbir Singh Andrew Mowbray A Graham Greenleaf Professor of Law D Information Systems University of New South Wales. B Dr.V.C.Vivekanandan Ministry of HRD IP Chair Professor NALSAR University of Law Hyderabad. C Philip Chung Lecturer in Law University of Technology Sydney and Conjoint Lecturer in Law UNSW. D Prof. (Dr.) Ranbir Singh Vice-Chancellor National Law University Delhi. E Andrew Mowbray Professor of Law D Computer Science at the University of Technology Sydney. This article first appeared in 8(3) SCRIPTed 292 (2011). The assistance of Rajan Sharma system developer for LII of India at AustLII Jill Matthews Indexer prior AustLII staff and SCRIPTed editors and referees is gratefully acknowledged. An earlier version of this article was presented at the Law via the Internet Conference University of Hong Kong 2011. The article was completed while Graham Greenleaf was a Visiting Fellow at the SCRIPT/AHRC Law and Technology Centre University of Edinburgh. The LII of India has been assisted by an AusAID PSLP (Public Sector Linkages Program) grant concerning access to South Asian legal information and from an ARC (Australian Research Council) LIEF grant concerning CommonLII