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How different spatial resolutions of digital models affects the geospatial distribution evaluation of the Index of Connectivity

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Journal of South American Earth Sciences 2025年 163卷

作者： Eberval Marchioro Geraldo André Rosseto Barreto Ialy Gomes Ferreira Adelsom Soares Filho Diogo Costa Buarque Department of Geography (DGEO) Graduate Program in Geography (PPGG) Federal University of Espírito Santo/Brazil (UFES) Coordinator of the Laboratory for Monitoring and Modeling Environmental Systems (Lamosa) Brazil Graduate Program in Management and Regulation of Water Resources (ProfÁgua/UFES) Brazil Graduate Program in Geography at UFES Brazil Graduate Program in Civil Engineering at UFV Brazil Department of Geography Graduate Program in Geography Federal University of Grande Dourados (UFGD) Brazil Department of Environmental Engineering Graduate Program in Environmental Engineering (PPGEA) Professional Master's in Water Resources Management and Regulation (ProfÁgua/UFES) Federal University of Espírito Santo/Brazil (UFES) Brazil

Digital Terrain Models (DTM) and Digital Elevation Models (DEM) are important for obtaining the Index of Connectivity, as they provide valuable information to assess the possibility of sediments reaching the riverbed in watershed basins. This is crucial for proactive management, as it allows the adoption of preventive and mitigating measures. Therefore, this study aims to analyze the effect of the spatial resolution of DEMs with resolutions of 5 m and 2 m, and between the DTM and DEM at 2 m, in determining the Index of Connectivity (IC). Additionally, it was investigated whether it is possible to use only one spatial resolution of digital models to assess the geospatial distribution of IC for all hydrogeomorphological landscapes of the Duas Bocas River watershed, located in the Metropolitan Region of Greater Vitória, in the state of Espírito Santo, Southeast Brazil. For this study, the Borselli Index of Connectivity model (et al., 2008) was used, originally developed for rural areas of Italy and widely applied in different regions worldwide. The data used, including Digital Elevation and Terrain Models and land use and cover information, were obtained from the Integrated Geospatial Base System of the State of Espírito Santo (Brazil), which is publicly *** results indicate that a better geospatial representation of IC occurs when changing the spatial resolution of DEMs from a 5 m pixel to a 2 m pixel and when using the 2 m DTM instead of the 2 m DEM. When analyzing the relationship between IC and the hydrogeomorphological landscapes in the basin, it was observed that, in the absence of models with an even finer pixel resolution, the 2 m DTM is the most suitable option, as it presented IC values consistent within and between landscapes in the Escalated Terraces of Southern Espírito Santo, Coastal Hills and Massifs, and Coastal Plateaus sectors. The exception was the fluvio-lagoon plain, which requires an even finer pixel resolution, necessitating further st

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Cascaded evolutionary multiobjective identification based on correlation function statistical tests for improving velocity analyzes in swimming

Cascaded evolutionary multiobjective identification based on...

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2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM 2014

作者： Ayala, Helon Vicente Hultmann Da Cruz, Luciano Ferreira Freire, Roberto Zanetti Coelho, Leandro Dos Santos Industrial and Systems Engineering Graduate Program PUCPR Curitiba Brazil Industrial and Systems Engineering Graduate Program Department of Electrical Engineering UFPR Curitiba Brazil

ISBN: (纸本)9781479944682

By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively. © 2014 IEEE.

关键词： Multiobjective optimization

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Role of the Ionomer in Supporting Electrolyte-Fed Anion Exchange Membrane Water Electrolyzers

ACS electrochemistry

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ACS electrochemistry 2025年第2期1卷 239-248页

作者： Emily K Volk Arielle L Clauser Melissa E Kreider Diego D Soetrisno Sunilkumar Khandavalli Joshua D Sugar Stephanie Kwon Shaun M Alia Advanced Energy Systems Graduate Program Colorado School of Mines Golden Colorado 80401 United States. Sandia National Laboratories Livermore California 94550 United States. Chemistry and Nanoscience Center National Renewable Energy Laboratory Golden Colorado 80401 United States. Materials Science Center National Renewable Energy Laboratory Golden Colorado 80401 United States. Department of Chemical and Biological Engineering Colorado School of Mines Golden Colorado 80401 United States.

While anion exchange membrane water electrolyzers (AEMWEs) have achieved significant performance advances in recent decades, overpotentials remain high relative to their proton exchange membrane water electrolyzer (PEMWE) counterparts, requiring AEMWE-specific catalyst layer design strategies to further advance this technology. In this work, the role of the ionomer in catalyst layer structure and quality, catalyst layer stability, and ion conduction for supporting electrolyte-fed AEMWEs is assessed for catalyst layers composed of NiFeO and PiperION TP85 from Versogen at variable ionomer contents (0-30 wt %) for tests up to 200 h. The results reveal that, for supporting electrolyte-fed AEM devices, the ionomer is not required for ion conduction through the catalyst layer. Instead, the ionomer is found to play a critical role in catalyst layer structure and stability, where intermediate ionomer contents lead to the lowest overpotentials, highest effective surface areas, and lowest catalyst layer resistances. Catalyst layer stability is found to be a function of both catalyst adhesion and ionomer loss. These results show that an ionomer may be selected which is not of the same chemistry as the anion exchange membrane, mitigating ionomer stability concerns throughout the catalyst layer and offering a pathway towards highly active and stable AEMWEs.

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OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems

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Advanced Intelligent systems 2025年第3期7卷

作者： Chen, Po-Yuan Ko, Tai-Ming Institute of Bioinformatics and Systems Biology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei115 Taiwan Institute of Statistical Science Academia Sinica Taipei115 Taiwan Department of Biological Science and Technology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan National Yang Ming Chiao Tung University Hsinchu300 Taiwan School of Pharmacy College of Pharmacy Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung807 Taiwan

Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) and antioxidants, plays a pivotal role in inflammatory responses associated with both chronic diseases and acute injuries. In this study, OXidative Stress PREDictor (OxSpred), a supervised learning model tailored to accurately annotate the oxidative stress state of innate immune cells at the single-cell level, is introduced. Compared to the traditional gene-set-variation-analysis-based enrichment method, OxSpred demonstrates superior accuracy with an area under the receiver operating characteristic curve of 0.89 and offers interpretable embeddings with significant biological relevance. Using the predicted ROS states, precise elucidation and interpretation of the roles of novel innate immune cell subtypes can be achieved. Overall, OxSpred enhances the utility of single-cell transcriptomic datasets by providing a robust in silico method for determining intracellular oxidative stress states, thereby enriching the understanding of innate immune cell functions during inflammation. © 2024 The Author(s). Advanced Intelligent systems published by Wiley-VCH GmbH.

关键词： Cells

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Electromagnetic textile absorber applied to 4G and 5G bands

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Scientific Reports 2025年第1期15卷 1-11页

作者： Paulo H. B. Carvalho Ewaldo E. C. Santana Allan K. D. Barros Filho Paulo F. Silva Júnior Keyll C. R. Martins Talita C. Azevedo Waldemir P. Martins Mauro A. Medeiros Rubens S. Gonçalves Lourival M. Sousa Filho Gricirene S. Correia Gabrielle M. Fernandes Talita C. Pinheiro Carlos A. M. Cruz Brenda A. S. Rodrigues Graduate Program in Electrical Engineering Federal University of Maranhão (UFMA) São Luís MA Brazil Graduate Program in Computer and Systems Engineering Maranhão State University (UEMA) São Luís MA Brazil Graduate Program in Mechanical Engineering Federal Institute of Maranhão (IFMA) São Luís MA Brazil Department of Electrical Engineering Federal Institute of Paraíba (IFPB) João Pessoa PB Brazil Graduate Program in Electrical Engineering Federal University of Amazonas (UFAM) Manaus AM Brazil Department of Electronics and Computation Federal University of Amazonas (UFAM) Manaus AM Brazil

Absorber materials are developed to reduce electromagnetic radiation and ensure the compatibility of the operation of electronic equipment in environments subject to interference. This work presents the development of a low-cost textile electromagnetic absorber for 4G and 5G technologies, operating at frequencies of 2.5 GHz and 3.5 GHz. The proposed electromagnetic absorber utilizes a 1 mm-thick Denim substrate, with a graphite composite used in the agricultural and commercial polyvinyl acetate glue industry, with the relationship of 25 wt%. The measurements were carried out in a Vector Network Analyzer, model E5071C Agilent Technologies, with the characterization of the Denim substrate, the glue, and the identification of the best parameters for the construction of the absorber. In the project, three low-cost textile absorbers prototypes were fabricated, with G1 = 0.25 mm, G2 = 0.35 mm, and G3 = 0.5 mm of thickness layers of the composite deposited on a Denim fabric. The results indicate that the absorber prototypes G2 presents great results in the frequency range of 4G and 5G band, with a maximum absorption of 26.6 dB in 3.94 GHz, with a structure 98.83% thinner than the commercial absorber LF-75. The variation in absorption performance may be attributed to the different mechanisms by which the absorbers operate: the commercial absorber LF-75 primarily interacts with the magnetic field, whereas the textile prototype predominantly affects the electric field.

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Modeling supports the implementation of urban greening as a response to the challenges of sustainable spatial planning

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Journal of Environmental Management 2025年 386卷 125648页

作者： Kim, Eun Sub Hyun, Jung Hee Kim, Na Yeon Heo, Su Jeong Kim, Da Seul Lee, Dong Kun Low-Carbon and Climate Impact Research Centre School of Energy and Environment City University of Hong Kong Tat Chee Ave Hong Kong Kowloon Tong China Systemic Risk and Resilience Research Group Advancing Systems Analysis International Institute for Applied Systems Analysis Austria Department of Landscape Architecture and Rural System Engineering Seoul National University Seoul08826 Korea Republic of Integrated Major in Smart City Global Convergence Program Seoul National University Seoul08826 Korea Republic of Forest Disaster & Environment Department National Institute of Forest Science Seoul Korea Republic of Interdisciplinary Program in Landscape Architecture Seoul National University Seoul08826 Korea Republic of Specialized Graduate School of Intelligent Eco-Science 4 Dept. of Landscape Architecture Seoul National University Seoul08826 Korea Republic of

Urban greening is critical for sustainable urban development, climate change mitigation, and biodiversity conservation. However, the effectiveness of urban greening varies depending on the specific goals (e.g., enhancing biodiversity, reducing urban heat, or both) and their spatial implementation. To address the spatial variability in the effectiveness of greening, we propose a spatial decision support model based on the non-dominated sorting genetic algorithm-II (NSGA-II). This model aims to optimize urban greening locations to maximize biomass density, mitigate urban heat stress, and improve landscape connectivity. Applied to Suwon City, South Korea, the model's effectiveness was evaluated against a business-as-usual (BAU) scenario across four scenarios: connectivity-based, biomass density-based, heat stress-based, and an integrated-based scenario. The integrated approach, balancing trade-offs between ecological benefits and implementation costs, outperformed the BAU scenario by 8.84 %. Despite highlighting a weaker correlation with heat stress mitigation, this outcome indicates significant improvements in biomass density and landscape connectivity. Our findings underscore the necessity of an integrated planning approach to urban greening, as it can contribute toward attaining urban development goals. Additionally, by proposing an app-based model for policymakers, our outputs should enable the reconciliation of multiple environmental objectives in urban landscapes. © 2025 Elsevier Ltd

关键词： Biotic

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Cooperative Mainstream Traffic Flow Control on Freeways

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IFAC-PapersOnLine 2016年第32期49卷 89-94页

作者： Müller, Eduardo R. Carlson, Rodrigo C. Kraus, Werner Post-graduate Program in Automation and Systems Engineering Federal University of Santa Catarina FlorianópolisSC88040-900 Brazil

Mainstream Traffic Flow Control (MTFC) is a freeway traffic control method which aims to maximize throughput by regulating the mainstream flow upstream from a bottleneck. Using Variable Speed Limits (VSL) as actuators for MTFC, we study the effects of different penetration rates of automated vehicles on MTFC-VSL. Automated vehicles can be designed to be much more strict in complying with VSL, which leads to a better MTFC performance than with ordinary VSL. Simulation results show that higher penetration rates translate into better performance with a significant effect up to 30% penetration rate, and very little gains beyond that; and that mixing forms of applying VSL may be detrimental to traffic. © 2016

关键词： Highway traffic control Feedback control Flow control Speed control Automated vehicles Co operative systems Freeway traffic controls Mainstream flow Maximize throughput Penetration rates Traffic flow control Variable speed limits

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Towards a Predictive Approach for Omni-channel Retailing Supply Chains

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IFAC-PapersOnLine 2019年第13期52卷 844-850页

作者： Pereira, Marina Meireles Frazzon, Enzo Morosini Graduate Program in Production Engineering Industrial and Systems Engineering Department Technology Center Federal University of Santa Catarina Florianópolis Santa Catarina Brazil

The adoption of omni-channel strategy has changed the relation between retailers and customers and brought more complexity to the retailing supply chains. To address the increasing complexity, it is necessary to adopt innovative approaches based on information technologies and intelligent decision methods. The challenges to retailers are improving the accuracy of offline and online channels demand forecasting, better managing offline and online customer's needs, thus reducing the uncertainties of the omni-channel retailing supply chain. In this context, this research paper aims to propose a predictive approach for omni-channel retailing supply chain combining clustering with artificial neural network to handle demand uncertainty. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Neural networks Complex networks Learning systems Sales Supply chain management Channel strategies Clustering Demand forecasting Demand uncertainty Innovative approaches Intelligent decisions Omni channel Retail supply chain

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Applying machine learning to AHP multicriteria decision making method to assets prioritization in the context of industrial maintenance 4.0

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IFAC-PapersOnLine 2019年第13期52卷 2152-2157页

作者： Lima, Erick Gorski, Ewerton Loures, Eduardo F.R. Portela Santos, Eduardo A. Deschamps, Fernando Industrial and Systems Engineering Graduate Program Pontifícia Universidade Católica do Paraná Curitiba Brazil

The increasing competition among industries has led to the emergence of numerous tools and methods to support decision making focused on assets maintenance in a company, since ensuring good maintenance is directly linked with greater reliability and uptime for equipment, reducing losses in production processes and consequently increasing profitability. This work aims to use Machine Learning (ML) algorithms - Bayesian Networks (BN) and attribute relevance analysis (ARA), implemented in the Weka® platform, to process a dataset of event logs failure of industrial machine components. The approach aims to use the conditional probability relations generated by the BN and the ranking of criteria relevance for the design of an AHP decision-making model within the scope of industrial maintenance to prioritize which components of a specific machine are more susceptible to failures. The proposed integration mechanism aims to bring greater reliability to the weights assigned to the criteria of the AHP model, and consequently, a more accurate decision support. The results showed that the AHP model generated from a Bayesian Network is consistent with the conditional probabilities estimated by the BN, giving robustness to the decision sphere in the context of industrial maintenance. This AHP model can serve as a basis to be complemented by qualitative analysis criteria according to the need of the individual specialist, allowing the construction of strategic maintenance action plans. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Machine learning Analytic hierarchy process Bayesian networks Competition Decision making Decision support systems Hierarchical systems Maintenance Conditional probabilities Decision making models Industrial maintenance Integration mechanisms Multi criteria decision making methods Qualitative analysis Relevance analysis Strategic maintenance

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Discovery of rare association rules in the distribution of lawsuits in the federal justice system of Southern Brazil

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International Journal of Business Intelligence and Data Mining 2021年第2期18卷 127-154页

作者： dos Santos Gruginskie, Lúcia Adriana Roehe Vaccaro, Guilherme Luís Chiwiacowsky, Leonardo Dagnino Blesz, Attila Elod Graduate Program in Production Engineering and Systems Unisinos Sao Leopoldo RS Brazil Program in Industrial Engineering UCS-Universidade de Caxias do Sul Bento Gonçalves City RS Brazil

In the context of data mining, infrequent association rules may be beneficial for analysing rare or extreme cases with very low support values and high confidence. In researching risky situations or allocating specific resources, such rules may have a much greater impact than rules with high support value. The objective of this study is to obtain association rules from the database of lawsuits filed in the Federal Court of Southern Brazil in 2016, including both frequent and rare rules. By finding these rules, especially rare ones, the information collected can assist in the decision-making process, in this case, such as training clerks or establishing specialised courts. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Association rules

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