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arXiv 2022年

作者： Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge-Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application. © 2022, CC BY-NC-ND.

关键词： Color

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Corrigendum to "Monastrol suppresses invasion and metastasis in human colorectal cancer cells by targeting fascin independent of kinesin-Eg5 pathway" [Biomed. Pharmacother. 175 (2024) 116785]

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Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2024年 179卷 117411页

作者： Begoña Alburquerque-González Silvia Montoro-García Ángel Bernabé-García Manuel Bernabé-García Priscila Campioni-Rodrigues Alejandro Rodríguez-Martínez Irene Luque Tuula Salo Alfonso Pérez-Garrido Horacio Pérez-Sánchez María Luisa Cayuela Ginés Luengo-Gil Enrico Luchinat Fatima Postigo-Corrales Tommaso Staderini Francisco José Nicolás Pablo Conesa-Zamora Health Sciences Faculty Universidad Católica de Murcia (UCAM) Guadalupe Spain. Regeneración Oncología Molecular y TGF-ß. IMIB-Arrixaca Carretera Madrid-Cartagena El Palmar 30120 Spain. Research group "Telomerasa Envejecimiento y Cáncer" CIBERER Hospital Clínico Universitario Virgen de la Arrixaca IMIB-Arrixaca Murcia Spain. ECM and Hypoxia research unit Faculty of Biochemistry and Molecular Medicine University of Oulu Aapistie 7C Oulu FI-90014 Finland Microelectronic Research Unit Faculty of Information Technology and Electrical Engineering University of Oulu Oulu FI-90570 Finland. Department of Physical Chemistry Institute of Biotechnology and Excellence Unit in Chemistry Applied to Biomedicine and Environment School of Sciences University of Granada Granada 18071 Spain Structural Bioinformatics and High-Performance Computing (BIO-HPC) Research Group Universidad Católica de Murcia (UCAM) Guadalupe Spain. Department of Physical Chemistry Institute of Biotechnology and Excellence Unit in Chemistry Applied to Biomedicine and Environment School of Sciences University of Granada Granada 18071 Spain. Oral Medicine and Pathology Research Unit of Population Health University of Oulu Finland Medical Research Center and Oulu University Hospital Aapistie 3 Oulu FI-90220 Finland Department of Oral and Maxillofacial Diseases University of Helsinki Haartmaninkatu 8 Helsinki FI-0014 Finland Translational Immunology Research Program (TRIMM) and iCAN Digital Precision Cancer Medicine Flagship University of Helsinki Finland Department of Pathology Helsinki University Hospital Helsinki Finland. Health Sciences Faculty Universidad Católica de Murcia (UCAM) Guadalupe Spain Pathology and Clinical Analysis Department Group of Molecular Pathology and Pharmacogenetics Instituto Murciano de Investigación Biosanitaria (IMIB) Hospital Universitario Santa Lucía Cartagena Spain. CERM - Magnetic Resonance Center and Dipartimento di Chimica Università degli Studi di Firenze Via Luigi

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Artificial intelligence technologies and related urban planning and development concepts: How are they perceived and utilized in Australia?

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Journal of Open Innovation: Technology, Market, and Complexity 2020年第4期6卷 1-21页

作者： Yigitcanlar, Tan Kankanamge, Nayomi Regona, Massimo Maldonado, Andres Ruiz Rowan, Bridget Ryu, Alex Desouza, Kevin C. Corchado, Juan M. Mehmood, Rashid Li, Rita Yi Man School of Built Environment Queensland University of Technology 2 George Street Brisbane 4000 QLD Australia School of Management Queensland University of Technology 2 George Street Brisbane 4000 QLD Australia Bisite Research Group University of Salamanca Salamanca 37007 Spain Air Institute IoT Digital Innovation Hub Salamanca 37188 Spain Department of Electronics Information and Communication Faculty of Engineering Osaka Institute of Technology Osaka 535-8585 Japan High Performance Computing Center King Abdulaziz University Al Ehtifalat St Jeddah 21589 Saudi Arabia Sustainable Real Estate Research Center Hong Kong Shue Yan University 10 Wai Tsui Cres North Point Hong Kong

Artificial intelligence (AI) is a powerful technology with an increasing popularity and applications in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing. Although many of these areas closely relate to the urban context, there is limited understanding of the trending AI technologies and their application areas—or concepts—in the urban planning and development fields. Similarly, there is a knowledge gap in how the public perceives AI technologies, their application areas, and the AI-related policies and practices of our cities. This study aims to advance our understanding of the relationship between the key AI technologies (n = 15) and their key application areas (n = 16) in urban planning and development. To this end, this study examines public perceptions of how AI technologies and their application areas in urban planning and development are perceived and utilized in the testbed case study of Australian states and territories. The methodological approach of this study employs the social media analytics method, and conducts sentiment and content analyses of location-based Twitter messages (n = 11,236) from Australia. The results disclose that: (a) digital transformation, innovation, and sustainability are the most popular AI application areas in urban planning and development;(b) drones, automation, robotics, and big data are the most popular AI technologies utilized in urban planning and development, and;(c) achieving the digital transformation and sustainability of cities through the use of AI technologies—such as big data, automation and robotics—is the central community discussion topic. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

关键词： Artificial intelligence (AI) Australia Automation Big data Digital transformation Innovation Public perception Robotics Sustainability Urban planning and development

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Preface

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Journal of Reliable Intelligent Environments 2019年第2期5卷 65-65页

作者： Coronato, Antonio Augusto, Juan Carlos Institute for High Performance Computing and Networking National Research Council Naples Italy Research Group on Development of Intelligent Environments Department of Computer Science Middlesex University London United Kingdom

This second issue of our fifth volume of the Journal of Reliable Intelligent Environments consists of four papers. One of them is a Survey Paper in and three other report on core technical advances in health security and automation engineering. Literature Review and Metadata Analysis of Ransomware Attacks and Detection Mechanisms, by A. Maigida, S. Abdul-hamid, M. Olalere, J. Alhassan, H. Chiroma, and D. Gbenga, offers a survey on a well-known security area, one which still requires more work, because despite media coverage the problem still persists, partly due to evolving platforms which may help confuse non-technology savvy users, and authors advocate for a shift in strategy.

关键词： automotive engineering paper SECURITY AREAS Shift ransomware Metadata Literature Review

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Music, computing, and Health: A Roadmap for the Current and Future Roles of Music Technology for Health Care and Well-Being

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Music and Science 2021年 4卷

作者： Agres, Kat R. Schaefer, Rebecca S. Volk, Anja van Hooren, Susan Holzapfel, Andre Dalla Bella, Simone Müller, Meinard de Witte, Martina Herremans, Dorien Ramirez Melendez, Rafael Neerincx, Mark Ruiz, Sebastian Meredith, David Dimitriadis, Theo Magee, Wendy L. Yong Siew Toh Conservatory of Music National University of Singapore Singapore Social and Cognitive Computing Department Institute of High Performance Computing A*STAR Singapore Institute for Psychology Health Medical Neuropsychology Unit Leiden University Leiden Netherlands Leiden Institute for Brain and Cognition Leiden University Leiden Netherlands Academy of Creative and Performing Arts Leiden University Leiden Netherlands Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Faculty of Health care Department of Arts Therapies Zuyd University of Applied Sciences Heerlen Netherlands KenVaK Research Centre for the Arts Therapies and Psychomotricity Heerlen Netherlands Faculty of Psychology Open University of The Netherlands Heerlen Netherlands Division of Media Technology and Interaction Design KTH Royal Institute of Technology Stockholm Sweden International Laboratory for Brain Music and Sound Research (BRAMS) Outremont QC Canada Department of Psychology University of Montreal Montreal QC Canada Centre for Research on Brain Language and Music (CRBLM) Montreal QC Canada University of Economics and Human Sciences in Warsaw Warsaw Poland International Audio Laboratories Erlangen Friedrich-Alexander Universität Erlangen-Nürnberg Erlangen Germany HAN University of Applied Sciences Department of Arts Therapies and Psychological Studies Nijmegen Netherlands University of Amsterdam Research Institute of Child Development and Education Amsterdam Netherlands Treatment Centre for People with Mild Intellectual Disabilities and Psychiatric and Behavioral Disorders Gennep Netherlands Information Systems Technology and Design Singapore University of Technology and Design Singapore Music and Machine Learning Lab Music Technology Group Universitat Pompeu Fabra Barcelona Spain Faculty of EEMCS Interactive Intelligence Group Delft University of Technology Delft Netherlands Centre for Digital Music School of Electronic Engineerin

The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, computing, and Health” was held to discuss best practices and state-of-the-art at the intersection of these areas with researchers from music psychology and neuroscience, music therapy, music information retrieval, music technology, medical technology (medtech), and robotics. Following the discussions at the workshop, this article provides an overview of the different methods of the involved disciplines and their potential contributions to developing music technology for health and well-being. Furthermore, the article summarizes the state of the art in music technology that can be applied in various health scenarios and provides a perspective on challenges and opportunities for developing music technology that (1) supports person-centered care and evidence-based treatments, and (2) contributes to developing standardized, large-scale research on music-based interventions in an interdisciplinary manner. The article provides a resource for those seeking to engage in interdisciplinary research using music-based computational methods to develop technology for health care, and aims to inspire future research directions by evaluating the state of the art with respect to the challenges facing each field. © The Author(s) 2021.

关键词： health care interdisciplinarity MedTech music information retrieval (MIR) music neuroscience Music psychology music technology music therapy well-being

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An FPGA-based approach for packet deduplication in 100 gigabit-per-second networks

An FPGA-based approach for packet deduplication in 100 gigab...

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2017 International Conference on Reconfigurable computing and FPGAs, ReConFig 2017

作者： Ruiz, Mario Sutter, Gustavo López-Buedo, Sergio Zazo, Jose Fernando De Vergara, Jorge E. López High Performance Computing and Networking Research Group Escuela Politécnica Superior Universidad Autónoma de Madrid Spain NAUDIT HPCN Spain

ISBN: (纸本)9781538637975

Network traffic monitoring usually faces the problem of packet duplication, which arises when port mirroring is being used. That is, when traffic is copied from the ports of a switch or a router that are being monitored, to a mirror port where a monitoring probe is attached. Thus, a packet can be copied twice, both at the ingress and egress ports, therefore generating duplicates. Information redundancy caused by packet duplication not only leads to increased workloads at the monitoring probes, but also calls for more disk space to store the network traces. Actually, packet duplication may increase 100% the monitoring load. There are different sorts of packet duplication;in this paper we focus on switching duplication, because it is the most common in a network monitoring scenario, where the network probe is attached to a core switch. We present a high performance FPGA architecture that is able to detect and remove duplicated packets in 100 Gbit/s networks. It is based on a 64-bit key and a BRAM-based shift register that allows us to build an element-based sliding window of size up to 79,872 elements. The design targets the Xilinx Virtex UltraScale family, using the integrated 100G Ethernet Subsystem available in such devices, and it has been tested on a VCU108 evaluation kit. © 2017 IEEE.

关键词： Shift registers

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Gene expression of methylation cycle and related genes in lymphocytes and brain of patients with schizophrenia and non-psychotic controls

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Biomarkers in Neuropsychiatry 2021年 5卷 100038-100038页

作者： Sershen, Henry Guidotti, Alessandro Auta, James Drnevich, Jenny Grayson, Dennis R. Veldic, Marin Meyers, Jordan Youseff, Mary Zhubi, Adrian Faurot, Keturah Wu, Renrong Zhao, Jingping Jin, Hua Lajtha, Abel Davis, John M. Smith, Robert C. Nathan Kline Institute for Psychiatric Research Orangeburg NY United States NYU Langone Medical Center Department of Psychiatry New York NY United States Psychiatric Institute University of Illinois Department of Psychiatry Chicago IL United States High Performance Biological Computing Group and the Roy J. Carver Biotechnology Center University of Illinois Urbana United States Department of Psychiatry and Psychology Mayo Clinic Rochester MN United States Department of Psychiatry Vanderbilt University Nashville TN United States Harlem Hospital Department of Psychiatry New York NY United States Department of Physical Medicine & Rehabilitation University of North Carolina at Chapel Hill NC United States Department of Psychiatry The Second Xiangya Hospital Central South University Changsha Hunan China Mental Health Institute of the Second Xiangya Hospital Central South University Changsha Hunan China University of California San Diego Department of Psychiatry San Diego and VA San Diego Healthcare System San Diego CA United States

Some of the biochemical abnormalities underlying schizophrenia, involve differences in methylation and methylating enzymes, as well as other related target genes. We present results of a study of differences in mRNA expression in peripheral blood lymphocytes (PBLs) and post-mortem brains of chronic schizophrenics (CSZ) and non-psychotic controls (NPC), emphasizing the differential effects of sex and antipsychotic drug treatment on mRNA findings. We studied mRNA expression in lymphocytes of 61 CSZ and 49 NPC subjects using qPCR assays with TaqMan probes to assess levels of DNMT, TET, GABAergic, NR3C1, BDNF mRNAs, and several additional targets identified in a recent RNA sequence analysis. In parallel we studied DNMT1 and GAD67 in samples of brain tissues from 19 CSZ, 26 NPC. In PBLs DNMT1 and DNMT3A mRNA levels were significantly higher in male CSZ vs NPC No significant differences were detected in females. The GAD1, NR3C1 and CNTNAP2 mRNA levels were significantly higher in CSZ than NPC. In CSZ patients treated with clozapine, GAD-1 related, CNTNAP2, and IMPA2 mRNAs were significantly higher than in CSZ subjects not treated with clozapine. Differences between CSZ vs NPC in these mRNAs was primarily attributable to the clozapine treatment. In the brain samples, DNMT1 was significantly higher and GAD67 was significantly lower in CSZ than in NPC, but there were no significant sex differences in diagnostic effects. These findings highlight the importance of considering sex and drug treatment effects in assessing the substantive significance of differences in mRNAs between CSZ and NPC. © 2021 The Author(s)

关键词： DNMTs Epigenetics GABAergic Lymphocyte vs brain mRNA biomarkers Schizophrenia

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Implementation of an Efficient Blind Docking Technique on HPC Architectures for the Discovery of Allosteric Inhibitors

Implementation of an Efficient Blind Docking Technique on HP...

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International Conference on Parallel Processing Workshops (ICPPW)

作者： Horacio Pérez-Sánchez José P. Cerón-Carrasco José M. Cecilia Structural Bioinformatics and High Performance Computing Research Group (BIO-HPC) Universidad Católica de Murcia (UCAM)

ISBN: (纸本)9781538610459

The problem of the discovery and marketing of new drugs can be vastly accelerated through high performance computing (HPC), molecular modeling techniques, and more specifically by means of the techniques commonly named as computational drug discovery (CDD) and in silico high throughput screening. These techniques usually assume a unique interaction site (active site) between potential drugs and a chosen protein target. This can lead to drastic limitations regarding the number and types of novel drugs that can be discovered since allosteric sites and other interaction spots different from active site are not explored. In order to solve this problem in this paper we introduce a technique based on advanced CDD technologies that exploit HPC architectures and called Blind Docking (BD). We also report our business prototyping efforts following Lean Startup principles in order to bring BD technology into the market.

关键词： Proteins Drugs Servers Computer architecture Computational modeling Software Companies

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Bragg soliton compression and fission on a CMOS-compatible platform

arXiv

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arXiv 2019年

作者： Sahin, Ezgi Blanco-Redondo, Andrea Xing, Peng Ng, Doris K.T. Png, Ching E. Tan, Dawn T.H. Eggleton, Benjamin J. Photonics Devices and Systems Group Singapore University of Technology and Design 8 Somapah Rd. Singapore487372 Singapore Electronics and Photonics Department Institute of High Performance Computing Agency for Science Technology and Research 1 Fusionopolis Way Singapore138632 Singapore School of Physics University of Sydney NSW2006 Australia University of Sydney NSW2006 Australia Institute of Microelectronics A*STAR 2 Fusionopolis Way #08-02 Innovis Tower Singapore138634 Singapore

higher-order soliton dynamics, specifically soliton compression and fission, underpin crucial applications in ultrafast optics, sensing, communications and signal processing. Bragg solitons exploit the strong dispersive properties of periodic media near the photonic band edge, enabling soliton dynamics to occur on chip-scale propagation distances and opening avenues to harness soliton compression and fission in integrated photonic platforms. However, implementation in CMOS-compatible platforms has been hindered by the strong nonlinear loss that dominates the propagation of high-intensity pulses in silicon and the low-optical nonlinearity of traditional silicon nitride. Here, we present CMOS-compatible, on-chip Bragg solitons, with the largest soliton-effect pulse compression to date with a factor of ×5.7, along with the first time-resolved measurements of soliton fission on a CMOS-compatible platform. These observations were enabled by the combination of unique cladding-modulated Bragg grating design, the high nonlinearity and negligible nonlinear loss of compositionally engineered ultra-silicon-rich nitride (USRN: Si7N3). Copyright © 2019, The Authors. All rights reserved.

关键词： Solitons

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On the impact of TCP segmentation: Experience in VoIP monitoring 15

On the impact of TCP segmentation: Experience in VoIP monito...

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15th IFIP/IEEE International Symposium on Integrated Network and Service Management, IM 2017

作者： Muelas, David De Vergara, Jorge E. López Ramos, Javier García-Dorado, José Luis Aracil, Javier High Performance Computing and Networking Research Group Escuela Politécnica Superior Universidad Autónoma de Madrid Spain Naudit HPCN S.L. Spain

ISBN: (纸本)9783901882890

Quality of Service (QoS) and Experience (QoE) monitoring is a must during the management of services deployed over the Internet. This is particularly critical for Voice over IP (VoIP), as its degradation is immediately perceived by end users. From our experience, we highlight the impact that TCP segmentation exerts on online VoIP monitoring systems. On the one hand, it makes difficult to interpret the segmented signaling messages for application monitoring. On the other hand, complete messages do not provide information about packet level behavior, which is necessary for internetworking layer monitoring. Paradoxically, the Network Management community has not paid much attention to this fact, although it compromises several VoIP management tasks. To fill in this gap, we provide an empirical evaluation of its impact for the most popular VoIP signaling protocols using traces from enterprise networks, and present the architecture and heuristic that we are currently developing to partially solve the effect of the segmentation. Our proposal avoids the overhead of reconstructing the entire data stream and, at the same time, it enables the analysis of the packets that are actually sent. To do so, it maps TCP flags with segmented application messages, and exploits data structures that reduce latency. In this way, our solution paves the way for online monitoring tools that take into account both internetworking and application layers performance. © 2017 IFIP.

关键词： Voice/data communication systems

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