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Evaluation of a differential evolution/constructal design algorithm for geometrical optimization of double t-shaped cavity intruded into a heat generating wall

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Defect and Diffusion Forum 2019年第1期396卷 145-154页

作者： Gonzales, Gill Velleda Isoldi, Liércio André Rocha, Luiz Alberto Oliveira Da Silva Neto, Antônio José Dos Santos, Elizaldo Domingues Instituto Federal Sul-rio-grandense Campus Santana Do Livramento Paul Harris Street 410 Sant'Ana do Livramento RS Brazil Universidade Federal Do Rio Grande Graduate Program of Computational Modeling Itália Avenue km 8 Rio Grande RS Brazil Universidade Do Vale Do Rio Dos Sinos Graduate Program of Mechanical Engineering São Leopoldo RS Brazil Politechnical Institute Universidade Estadual Do Rio de Janeiro Bonfim Street 25 Vila Amélia Nova Friburgo RJ Brazil

In the present work it is investigated the performance of an algorithm that associates Differential Evolution and Constructal Design for geometrical optimization of a heat transfer problem. It is considered the intrusion of a cooled Double T-shaped cavity into a rectangular conducting solid wall with internal heat generation. The main purpose here is to evaluate the algorithm capability to reproduce the effect of geometric ratios over the dimensionless maximum excess of temperature (performance indicator of the heat transfer problem), as well as, the influence of Differential Evolution (DE) parameters over the optimization analysis. The definition of search space for each degree of freedom and problem constraints is performed with Constructal Design, while the Differential Evolution algorithm is used in the optimization process. Here parameters as mutation operator (M), crossover constant (CR), differential amplification factor (F), Population Size (PS) and Generations number (G) are evaluated. A theoretical recommendation about the suitable parameters set for the optimization algorithm for this kind of heat transfer problem is proposed. Results indicated that the crossover constant (CR) and amplification factor (F) are important parameters for suitable prediction of the effect of degrees of freedom over thermal performance. Moreover, when CR = 0.7 and F = 1.5 results obtained with the algorithm are more robust for the achievement of the best shapes and requires lower number of iterations (IT = PS ×G) for reproduction of effect of geometric variables over performance. © 2019 Trans Tech Publications Ltd, Switzerland.

关键词： Population statistics

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To Sharpen or not to Sharpen? On the Effect of Sharpening Filters Applied to Magnified Images 14

To Sharpen or not to Sharpen? On the Effect of Sharpening Fi...

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14th International Conference on Digital Image Processing, ICDIP 2022

作者： Emmendorfer, Leonardo R. de Olviveira, Vinicius Menezes Schein, Tatiana T. de Jesus, Junior C. Rodriguez, Bárbara D.A. Electrical Energy Processing Department Federal University of Santa Maria 97105-340 Brazil Center for Computational Science Federal University of Rio Grande 96201-900 Brazil Computational Modeling PhD Program Federal University of Rio Grande 96201-900 Brazil Computer Engineering Graduate Program Federal University of Rio Grande 96201-900 Brazil Institute of Mathematics Statistics and Physics Federal University of Rio Grande 96201-900 Brazil

ISBN: (纸本)9781510657564

Super-resolution algorithms aim to produce magnified high-resolution versions from low-resolution images. Some methods, however, are prone to generate blur during the process. Simple sharpening filters are adopted to alleviate this type of artifact. However, the actual effectiveness of this approach is not clear-cut in the literature. This work evaluates the effect of three simple sharpening filters on the quality of images obtained from super-resolution methods. Two metrics were considered in the evaluation: the Peak signal-to-noise ratio (PSNR) metric, and the Learned Perceptual Image Patch Similarity (LPIPS). One of the filters could consistently improve the LPIPS metric of magnified images from diverse benchmark sets on top of seven super-resolution methods. The increments obtained for the perceptual metric seem to occur due to the sharpening effect. Improvements on PSNR values were not as consistent. © 2022 SPIE.

关键词： Quality control

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Stochastic Petri Net Models for the Study of Macrophage Reprogramming

Stochastic Petri Net Models for the Study of Macrophage Repr...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Elvis H. Ribeiro Alexandre B. Pigozzo Carolina R. Xavier Rodrigo W. dos Santos Marcelo Lobosco Department of Computer Science Federal University of Sao Joao Del Rei Graduate Program in Computational Modeling Federal University of Juiz de Fora

ISBN: (纸本)9781728118680

In recent years, Petri nets are being used for modeling complex biological systems. Examples include the modeling of biochemical reactions, protein interaction networks, gene regulation networks and the immune system. In this work, Petri nets are used to model the innate immune response to a bacterial infection. The objective of this work is to study how changes in macrophage phenotype impact the regulation and resolution of the immune response. From simulations performed, we have observed that the conversion between a M1 proinflammatory phenotype to a M2 regulatory phenotype during an inflammatory response is an important process to avoid a state of persistent inflammation.

关键词： stochastic Petri net innate immune response macrophage reprogramming chronic inflammation Petri nets Innate Immune Response Chronic inflammation Macrophages reprogramming Inflammatory Response modeling Immune System

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Networks in Systems Biology 1

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丛书名： computational Biology

1000年

作者： Fabricio Alves Barbosa da Silva Nicolas Carels Marcelo Trindade dos Santos Francisco José Pereira Lopes

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A Strategy for Parametrization Refinement in the Solution of a Geometric Inverse Problem

A Strategy for Parametrization Refinement in the Solution of...

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Southern Conference on computational modeling (MCSUL)

作者： Franciane Conceicao Peters Luis Paulo da Silva Barra Graduate Program on Computational Modeling Federal University of Juiz de Fora Juiz de Fora Brazil Grad. Program on Comput. Modeling Fed. Univ. of Juiz de Fora Juiz de Fora Brazil

This paper treats the problem of identifying a single inclusion in a conductor domain based on the knowledge of measured electrical potentials on the external boundary of the conductor body due to known injected electrical currents. The inclusion boundary is approximated by an Extended X-Spline, that allows identify inclusions with smooth or sharp boundary. In this work, the forward problem is solved by an implementation of the direct formulation of the Boundary Element Method (BEM) and the inverse one is solved by Levenberg-Marquardt method, which requires the evaluation of the objective function derivatives, here approximated by finite differences. This work presents a methodology to increase the number of optimization variables during the solution of the inverse problem in order to improve the quality of the results.

关键词： Electric potential Geometry Optimization Minimization Current measurement Electrodes Shape

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Patient-Centric Healthcare Service Systems: Evidence-Based Medicine as Architecturally Significant Requirement

Patient-Centric Healthcare Service Systems: Evidence-Based M...

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IEEE/ACM International Workshop on Software Engineering in Healthcare Systems (SEHS)

作者： Patrick Letouze Valeria Martins da Silva Jose I.M. de Souza Jùnior Graduate Program of Computational Modeling of Systems Universidade Federal do Tocantins - UFT Palmas Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781509022076

Healthcare Service Systems may use and support evidence-based medicine, and to accomplish that, their design has to be patient-centered focusing on quality of evidence and strength of recommendation. Hence, this paper intends to promote the debate on the design of Healthcare Service Systems. We propose a framework that attempts to systematize the design and development of Healthcare Service Systems, especially in terms of software engineering. The framework is intended to support the design of Healthcare Service Systems by understanding a complex health treatment as a project, which would provide naturally patient-centeredness, and by considering Evidence-Based Medicine guidelines and recommendations as architecturally significant requirements in the design of Healthcare Service Systems, which would provide focus on quality of evidence and strength of recommendation. Therefore, we would have a SOA user-centric approach and a systematic service design.

关键词： Guidelines Medical services Medical diagnostic imaging Protocols Systematics Standards Electrocardiography

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Biomedical data and AI

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Science China Life Sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Early surveillance of rice bakanae disease using deep learning and hyperspectral imaging

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aBIOTECH 2024年第3期5卷 281-297页

作者： Sishi Chen Xuqi Lu Hongda Fang Anand Babu Perumal Ruyue Li Lei Feng Mengcen Wang Yufei Liu College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China State Key Laboratory of Rice Biology and Breeding Zhejiang UniversityHangzhou 310058China Computational Modeling and Nanoscale Processing Unit National Institute of Food TechnologyEntrepreneurship and Management-ThanjavurMinistry of Food Processing IndustriesThanjavur 613005India College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China Global Education Program for AgriScience Frontiers Graduate School of AgricultureHokkaido UniversitySapporo 060-8589Japan

Bakanae disease,caused by Fusarium fujikuroi,poses a significant threat to rice production and has been observed in most rice-growing *** disease symptoms caused by different pathogens may vary,including elongated and weak stems,slender and yellow leaves,and dwarfism,as *** disease is likely to cause necrosis of diseased seedlings,and it may cause a large area of infection in the field through the transmission of ***,early disease surveillance plays a crucial role in securing rice *** monitoring methods are both time-consuming and labor-intensive and cannot be broadly *** this study,a combination of hyperspectral imaging technology and deep learning algorithms were used to achieve in situ detection of rice seedlings infected with bakanae *** data were obtained on the 9th,15th,and 21st day after rice infection to explore the physiological and biochemical performance,which helps to deepen the research on the disease *** data were obtained over these same periods of infection,and a deep learning model,named Rice Bakanae Disease-Visual Geometry Group(RBD-VGG),was established by leveraging hyperspectral imaging technology and deep learning *** on this model,an average accuracy of 92.2%was achieved on the 21st day of *** also achieved an accuracy of 79.4%as early as the 9th *** characteristic wavelengths were extracted to increase the feasibility of using portable spectral equipment for field ***,the model offers an efficient and non-destructive surveillance methodology for monitoring bakanae disease,thereby providing an efficient avenue for disease prevention and control.

关键词： Bakanae disease Hyperspectral imaging Deep learning Early surveillance Disease monitoring

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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A mathematical model of the innate immunological response to Brucella infection

A mathematical model of the innate immunological response to...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： João Víctor Costa De Oliveira Carlos Cristiano Hasenclever Borges Leonardo Augusto De Almeida Marcelo Lobosco Graduate Program on Computational Modeling Federal University of Juiz de Fora Juiz de Fora Brazil Laboratory of Molecular Biology of Microorganisms Federal University of Alfenas Alfenas Brazil

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Brucellosis is a highly contagious zoonotic disease caused by bacteria from the genus Brucella. It affects various animal species, with significant economic consequences for live-stock producers. The disease causes reproductive losses, such as abortions and reduced fertility, leading to decreased live-stock production. Additionally, infected animals may experience reduced milk production and weight gain, further impacting the economic viability of livestock operations. Furthermore, the potential for zoonotic transmission to humans poses risks to public health. In this study, we propose a new mathematical model that describes the innate immune response to brucellosis, focusing on the interactions between antigens and the innate immune system. The model is formulated as a system of five partial differential equations that represent healthy tissue, bacteria, cytokines, resting and mature antigen-presenting cells, and is solved using the finite difference method. To validate our model, we compare the initial numerical results with experimental data from the literature, achieving an absolute error of 0.0017.

关键词： Economics computational modeling Biological system modeling Partial differential equations Production Bacteria Mathematical models Numerical models Public healthcare Diseases

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