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IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

作者： Dewan Mahnaaz Mahmud Sayeed Hasan S.M. Masum Ahmed Mohammad Zeyad Energy and Technology Research Division Advanced Bioinformatics Computational Biology and Data Science Laboratory Bangladesh Chattogram Bangladesh Erasmus+ Joint MSC in Smart Cities and Communities Faculty of Engineering University of Mons (UMONS) Mons Belgium Erasmus+ Joint MSC in Smart Cities and Communities University of the Basque Country (UPV/EHU) Bilbao Spain

Renewable energy systems (RES) are becoming more prominent because of the depletion of natural resources. Optimum sizing of the hybrid RES is necessary to ensure that renewable energy sources penetrate. Improper sizing may result in higher initiating costs or an inability to meet load demand under various weather conditions. By analyzing with Hybrid Optimization Multiple Energy Resources (HOMER pro), this study shows the ideal hybrid energy system that provides the lowest cost of energy production, emissions, and so on. This study provides a grid-connected hybrid power system model based on metrological data collected from a residential building in Mohammadpur, Dhaka, Bangladesh. Solar energy is used as a sustainable energy source thus the cost of the system was decreased, which is also environmentally friendly. This renewable energy also helped to minimize the levelized cost of energy (COE). The conclusion estimates operational costs, production costs, net present cost, and energy cost for the two combinations evaluated for the proposed microgrid system. According to the simulation results, delivering power to the load via a microgrid would be a viable and cost-effective solution.

关键词： Renewable energy sources Costs Simulation Buildings Microgrids Production Solar energy

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Embedding Model Design for Producing Book Recommendation 4

Embedding Model Design for Producing Book Recommendation

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4th International Conference on Information Management and Technology, ICIMTech 2019

作者： Rahutomo, Reza Perbangsa, Anzaludin Samsinga Soeparno, Haryono Pardamean, Bens Bioinformatics Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Internet services often recommend contents to users in order to maintain the interaction. Recommendation system plays a major role to formulate and produce a series of recommendation based on users' behavior. Surprisingly, user-generated scoring or known as ratings are the main raw materials to learn the pattern of favorable contents of each user. As a part of collaborative filtering strategy, rating is considerable to be included in formulating recommended contents. In this research, the basic formulation to recommend books is discovered. The recommendation system has been tested on one random-picked user behavior and successfully has generated five recommended books by analyzing prior activities. The embedding model produced the recommended books with 59% of accuracy. This research is done to provide an insightful experience for developing content recommendation system in Binus University's corporate learning system. © 2019 IEEE.

关键词： Recommender systems

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Transbronchial cryobiopsy followed by as-needed surgical lung biopsy versus immediate surgical lung biopsy for diagnosing interstitial lung disease (the COLD study): a randomised controlled trial

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The Lancet Respiratory Medicine 2024年第7期12卷 513-522页

作者： Kalverda, Kirsten A Ninaber, Maarten K Wijmans, Lizzy von der Thüsen, Jan Jonkers, René E Daniels, Johannes M Miedema, Jelle R Dickhoff, Chris Hölters, Jürgen Heineman, David Kant, Merijn Radonic, Teodora Shahin, Ghada Cohen, Danielle Boerrigter, Bart Nijman, Suzan Nossent, Esther Braun, Jerry Mathot, Bas Poletti, Venerino Hetzel, Jürgen Dijkgraaf, Marcel Korevaar, Daniel A Bonta, Peter I Annema, Jouke T Department of Respiratory Diseases Amsterdam University Medical Centers University of Amsterdam Amsterdam Netherlands Department of Respiratory Diseases Leiden University Medical Center Leiden Netherlands Department of Pathology and Clinical Bioinformatics Erasmus Medical Center Rotterdam Netherlands Department of Respiratory Diseases Amsterdam University Medical Centers Vrij Universiteit Amsterdam Amsterdam Netherlands Department of Respiratory Diseases Erasmus Medical Center Rotterdam Netherlands Department of Cardiothoracic Surgery Amsterdam University Medical Centers Vrij Universiteit Amsterdam Amsterdam Netherlands Department of Respiratory Diseases Canisius Wilhelmina Ziekenhuis Nijmegen Netherlands Department of Respiratory Diseases Amphia Hospital Breda Netherlands Department of Pathology Amsterdam University Medical Centers Vrij Universiteit Amsterdam Amsterdam Netherlands Department of Surgery Leiden University Medical Center Leiden Netherlands Department of Pathology Leiden University Medical Center Leiden Netherlands Department of Medical Specialties Giovan Battista Morgagni Hospital University of Forlì Forlì Italy Department of Respiratory Diseases and Allergy Aarhus University Hospital Aarhus Denmark Department of Medical Oncology and Pneumology Eberhard Karls University Tübingen Germany Department of Pneumology Cantonal Hospital of Winterthur Winterthur Switzerland Department of Epidemiology and Data Science Amsterdam University Medical Centers University of Amsterdam Amsterdam Netherlands

Background: An adequate diagnosis for interstitial lung disease (ILD) is important for clinical decision making and prognosis. In most patients with ILD, an accurate diagnosis can be made by clinical and radiological data assessment, but in a considerable proportion of patients, a lung biopsy is required. Surgical lung biopsy (SLB) is the most common method to obtain tissue, but it is associated with high morbidity and even mortality. More recently, transbronchial cryobiopsy has been introduced, with fewer adverse events but a lower diagnostic yield than SLB. The aim of this study is to compare two diagnostic strategies: a step-up strategy (transbronchial cryobiopsy, followed by SLB if the cryobiopsy is insufficiently informative) versus immediate SLB. Methods: The COLD study was a multicentre, randomised controlled trial in six hospitals across the Netherlands. We included patients with ILD with an indication for lung biopsy as assessed by a multidisciplinary team discussion. Patients were randomly assigned in a 1:1 ratio to the step-up or immediate SLB strategy, with follow-up for 12 weeks from the initial procedure. Patients, clinicians, and pathologists were not masked to the study treatment. The primary endpoint was unexpected chest tube drainage, defined as requiring any chest tube after transbronchial cryobiopsy, or prolonged (>24 h) chest tube drainage after SLB. Secondary endpoints were diagnostic yield, in-hospital stay, pain, and serious adverse events. A modified intention-to-treat analysis was performed. This trial is registered with the Dutch Trial Register, NL7634, and is now closed. Findings: Between April 8, 2019, and Oct 24, 2021, 122 patients with ILD were assessed for study participation;and 55 patients were randomly assigned to the step-up strategy (n=28) or immediate SLB (n=27);three patients from the immediate SLB group were excluded. Unexpected chest tube drainage occurred in three of 28 patients (11%;95% CI 4–27%) in the step-up group, and t

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Association between echocardiographic features, troponin levels, and survival time in hospitalized COVID-19 patients with cardiovascular events

Journal of Anesthesia and Translational Medicine

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Journal of Anesthesia and Translational Medicine 2024年第2期3卷 36-44页

作者： Furmanek, Stephen Salunkhe, Vidyulata Pahwa, Siddharth Samanapally, Harideep Nathala, Pavani Xu, Qian Han, Yuchen Huang, Emma C. Ali, T'shura Deepti, Fnu Glynn, Alex McGuffin, Trevor Huang, Justin J. Farah, Ian Jones, Christopher M. Ramirez, Julio A. Clifford, Sean P. Arnold, Forest W. Kong, Maiying Roser, Lynn Huang, Jiapeng Division of Infectious Diseases Center of Excellence for Research in Infectious Diseases (CERID) Department of Medicine University of Louisville 501 E Broadway Louisville 40202 KY United States Department of Bioinformatics and Biostatistics School of Public Health and Information Sciences University of Louisville 485 E Gray St Louisville 40202 KY United States School of Nursing University of Louisville 555 S Floyd St Louisville 40202 KY United States Department of Anesthesiology & Perioperative Medicine University of Louisville 530 S Jackson St Louisville 40202 KY United States Department of Pharmacology & Toxicology University of Louisville 505 S Hancock St Louisville 40202 KY United States Department of Cardiovascular & Thoracic Surgery University of Louisville 201 Abraham Flexner Way Louisville 40202 KY United States Center for Integrative Environmental Health Sciences University of Louisville 500 S Preston St Louisville 40202 KY United States Division of Transplantation Department of Surgery University of Louisville 323 E Chestnut St Louisville 40202 KY United States Norton Infectious Diseases Institute Norton Healthcare 234 E Gray St Louisville 40202 KY United States Department of Anesthesiology Duke University Durham 27710 NC United States Biometrics and Data Science Fosun Pharma Beijing 100026 China

Introduction: This study aims to explore the predictive roles of echocardiographic parameters and biomarkers in determining outcomes among hospitalized COVID-19 patients experiencing cardiovascular events. Methods: A retrospective cohort study was conducted involving 49 COVID-19 patients who encountered cardiovascular events during hospitalization and underwent echocardiography. Our findings revealed notable associations between echocardiographic parameters and survival time. Results: A decrease in left ventricular ejection fraction (LVEF) of 10% was linked to a 20% reduction in survival time (TR: 0.80, 95% CI: 0.67 – 0.96, p = 0.017). Similarly, an increase in left ventricular (LV) volume by 10 mL was associated with a 9% decrease in survival time (TR: 0.91, 95% CI: 0.84 – 0.98, p = 0.011). Moreover, an increase in left atrial (LA) volume by 10 mL corresponded to an 8% decrease in survival time (TR: 0.92, 95% CI: 0.86 – 0.99, p = 0.026). Additionally, each 1 cm increase in right ventricular (RV) diameter was linked to a 22% reduction in survival time (TR: 0.78, 95% CI: 0.61 – 0.99, p = 0.043). Furthermore, a 10 mL increase in right atrial (RA) volume was associated with a 12% decrease in survival time (TR: 0.88, 95% CI: 0.78 – 0.98, p = 0.017). Notably, a tenfold rise in troponin levels was linked to a 33% decrease in survival time (TR: 0.67, 95% CI: 0.48 – 0.93, p = 0.014). Conclusions: Our study emphasizes the significant associations between various echocardiographic parameters and troponin levels with reduced survival time among COVID-19 patients experiencing cardiovascular events. These findings highlight the potential utility of echocardiography and troponin assessment in predicting outcomes and guiding management strategies in this patient population. © 2024 Wuhan Institute of Intelligent Perioperative Medicine (WIIPM)

关键词： Brain natriuretic peptide Cardiovascular COVID-19 Echocardiography SARS-CoV-2 Troponin

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169P High-dimensional analysis of tumor infiltrating immune cells reveals major differences in the tumor immune microenvironments of pleural mesothelioma and lung cancer

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Immuno-Oncology and Technology 2023年 20卷 100628-100628页

作者： Rigutto, A. Nunez, N. Kienzler, J. Kirschner, M. Opitz, I. Hiltbrunner, S. Fournier, N. Lourenço, J. Gottardo, R. Becher, B. Curioni-Fontecedro, A. Faculty of Science and Medicine University of Fribourg Fribourg Switzerland Institute of Experimental Immunology University of Zurich Zurich Switzerland Department of Thoracic Surgery University Hospital Zurich Zurich Switzerland Translational Data Science Facility-Agora Cancer Research Center SIB - Swiss Institute of Bioinformatics Lausanne Switzerland Faculty of Science and Medicine University of Fribourg and Cantonal Hospital Fribourg Fribourg Switzerland

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Publisher Correction: scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data

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Nature communications 2024年第1期15卷 2212页

作者： Songming Tang Xuejian Cui Rongxiang Wang Sijie Li Siyu Li Xin Huang Shengquan Chen School of Mathematical Sciences and LPMC Nankai University Tianjin 300071 China. MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST Department of Automation Tsinghua University 100084 Beijing China. Department of Computer Science University of Virginia Charlottesville VA 22903 USA. School of Statistics and Data Science Nankai University Tianjin 300071 China. Beijing Key Laboratory for Radiobiology Department of Radiation Biology Beijing Institute of Radiation Medicine 100850 Beijing China. School of Mathematical Sciences and LPMC Nankai University Tianjin 300071 China. chenshengquan@***.

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Information system model for maize research to anticipate the impact of climate change on Indonesian food security

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AIP Conference Proceedings 2023年第1期2594卷

作者： A. S. Perbangsa F. A. Munawwar M. B. Pabendon B. Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Indonesia Cereals Research Institute Maros South Sulawesi 90514 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

As a rich country in genetic resources, Indonesia has the potential for strengthening food security. Maize is one of the commodities that greatly affect food security in Indonesia. Maize is also widely used as animal feed. The high demand for maize requires efforts to increase the productivity of sustainable cultivation. Various research efforts that have been carried out require the support of a comprehensive information system. This study aimed to build a research model for maize genetic resource information systems that can help search for superior varieties. The data collection method used was collecting genotype, phenotype, climate data and interviewing the maize breeders or researchers. As for the design of the model, this study used the Object-Oriented Analysis & Design (OOAD) method with notation from Unified Modelling Language (UML). The result of this research was a web-based model of information systems for maize research.

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Optimization of Microgrid System for Community Electrification by using HOMER Pro

Optimization of Microgrid System for Community Electrificati...

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IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

作者： Md.Kamrul Islam Jannatul Mawa Akanto Mohammad Zeyad S.M. Masum Ahmed Energy and Technology Research Division Advanced Bioinformatics Computational Biology and Data Science Laboratory Bangladesh Chattogram Bangladesh Erasmus+ Joint MSC in Smart Cities and Communities University of the Basque Country (UPV/EHU) Bilbao Spain Erasmus+ Joint MSC in Smart Cities and Communities Faculty of Engineering University of Mons (UMONS) Mons Belgium

A microgrid included multiple energy sources such as a diesel generator, photovoltaic system (PV), wind turbines (WTs), and so on. The key reason for the growth of hybrid energy technology or microgrid is the reliability, abundance of renewable energy (RE) and it can use the resources in an efficient manner. This research aims to incorporate a stand-alone community microgrid in Cumilla, Bangladesh to deliver electricity to a residential community and determine the optimum solution to satisfy total demand. The load profile is considered in this study for a residential community situated in Cumilla. Moreover, three case studies are taken into account to analyze the optimum result. The simulation analysis is executed in the optimization software that is the Hybrid Optimization Model for Multiple Energy Resources (HOMER pro). Several types of analysis are conducted such as NPV, COE, emission, energy production, and operating cost. The simulation results reveal that case 3 (solar, wind and diesel generator) is the optimum solution as it has the lowest NPV, COE, and operating cost.

关键词： Analytical models Costs Simulation Wind speed Microgrids Generators Software

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Multimodal learning with graphs

arXiv

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arXiv 2022年

作者： Ektefaie, Yasha Dasoulas, George Noori, Ayush Farhat, Maha Zitnik, Marinka Bioinformatics and Integrative Genomics Program Harvard Medical School BostonMA02115 United States Department of Biomedical Informatics Harvard University BostonMA02115 United States Harvard College CambridgeMA02138 United States Broad Institute of MIT and Harvard CambridgeMA02142 United States Harvard Data Science Initiative CambridgeMA02138 United States Division of Pulmonary and Critical Care Department of Medicine Massachusetts General Hospital BostonMA United States

Artificial intelligence for graphs has achieved remarkable success in modeling complex systems, ranging from dynamic networks in biology to interacting particle systems in physics. However, the increasingly heterogeneous graph datasets call for multimodal methods that can combine different inductive biases—the set of assumptions that algorithms use to make predictions for inputs they have not encountered during training. Learning on multimodal datasets presents fundamental challenges because the inductive biases can vary by data modality and graphs might not be explicitly given in the input. To address these challenges, multimodal graph AI methods combine different modalities while leveraging cross-modal dependencies using graphs. Diverse datasets are combined using graphs and fed into sophisticated multimodal architectures, specified as image-intensive, knowledge-grounded and language-intensive models. Using this categorization, we introduce a blueprint for multimodal graph learning, use it to study existing methods and provide guidelines to design new models. © 2022, CC BY.

关键词： Blueprints

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The use of human mobility data on infectious disease control: Covid-19 as an example

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Taiwan Journal of Public Health 2023年第2期42卷 148-152页

作者： Fu, Han Chan, Ta-Chien Wu, Chieh-Yin Wen, Tzai-Hung Lan, Chih-Chan Chou, Mei-Fang Lim, Chen-Fatt Lee, Wei-Sen Chen, Wei-Jen Liu, Yu-Lun Cheng, Hao-Yuan Lin, Bo-Cheng Kuo, Fei-Ying Lin, Yu-Xuan Tsai, Yi-Chen Chang, Ning Lin, Hsien-Ho Chang, Hsiao-Han Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine Taiwan Center for Humanities and Social Sciences Academia Sinica Taiwan College of Public Health National Taiwan University Taiwan Department of Geography Environment and Resources National Taiwan University Taiwan Far EasTone Telecommunications Government and Enterprise Big Data Application Department Taiwan National Disaster Prevention and Relief Science and Technology Center Taiwan National Institutes of Health Taiwan Centers for Disease Control Ministry of Health and Welfare Taiwan Department of Real Estate and Urban and Rural Environment National Taipei University Taiwan National Tsing Hua University School of Science Technology and Management Taiwan Institute of Systems Neuroscience National Tsing Hua University Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Taiwan

Human mobility data are used to evaluate the effectiveness of crowd control measures and delineate geographical zones and other epidemic prevention decisions for the COVID-19 epidemic. This application experience also revealed the challenges faced by the application of human mobility data in infectious disease research and practice. For example, there is no available public data and its usage regulations and empirical data to support the research results of the relationship between human movement and epidemic. Moreover, the three parties - data provider, researcher, and practical worker - have no approach to communicating with each other. It is suggested that in the future, a tripartite collaboration mode can be developed in which major domestic telecommunications companies provide, the National Disaster Prevention Center handles and maintains, and the government and research institutions apply to the National Disaster Prevention Center for use;establish a complete data platform and strengthen instant communication and cooperation channels. © 2023, Taiwan Public Health Association. All rights reserved.

关键词： Big data COVID-19 Human mobility data Infectious disease control

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