Visual indicator for the detection of methylmercury in blood: A critical biomarker for dietary exposure assessment by Yan Guo, Bing-chan Ma, Wen-qi Zhang, Bo-xin Li, Jia-ming Ou, Fen Liu, Chang-ye Hui

“…Methylmercury (MeHg), a significant dietary exposure biomarker, poses a substantial threat to public health, primarily due to the consumption of aquatic foods. Current detection methods are complex and unsuitable for on-site testing, necessitating the development of a simple and sensitive biosensor for rapid screening. …”
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An Empirical Comparison of Urban Road Travel Time Prediction Methods—Deep Learning, Ensemble Strategies and Performance Evaluation by Yizhe Wang, Yangdong Liu, Xiaoguang Yang

“…This study compares the predictive performance of deep learning methods with traditional shallow learning methods for urban road travel time prediction, and explores the potential for improving prediction effectiveness through multi-run training strategies for hyperparameter optimization and ensemble learning. …”
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Strategy of the effective structure of farmers funding by Denis Y. Samygin, Nikolay G. Baryshnikov

“…Therefore, a research objective is justification and development of strategic models of structure optimization of the budgetary support of peasant farms, taking into account efficiency of measures, which relevance is confirmed by scientific research of the leading scientists in this subject area.Materials and methods. …”
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TMS: Ensemble Deep Learning Model for Accurate Classification of Monkeypox Lesions Based on Transformer Models with SVM by Elsaid Md. Abdelrahim, Hasan Hashim, El-Sayed Atlam, Radwa Ahmed Osman, Ibrahim Gad

“…The Monkeypox Skin Lesion Dataset (MSLD) used in this study comprises monkeypox skin lesions, which were collected primarily from publicly accessible sources. The dataset contains 770 original images captured from 162 unique patients. …”
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The evolution of sprinting performance: Technological and regulatory influences from 1976 to 2024 by Dariusz Tadeusz SKALSKI, Magdalena PROŃCZUK, Kinga ŁOSIŃSKA, Ewelina LULIŃSKA, Joanna MOTOWIDŁO, Petr STASTNY, Adam MASZCZYK, Grzegorz TRYBEK

“…Data sources include official race results, biomechanical studies, and historical records of rule changes. …”
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Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system by Zhe Yin, Zhifan Zhang, Ruijin Zhu, Yifan Zhang, Jiyuan Wang, Wenxing Tang

“…The model integrates carbon capture and storage with power-to-gas (CCS-P2G), concentrated solar power plant (CSPP), combined heat and power (CHP) unit, and ground-source heat pump (GSHP). By optimizing the coordinated operation of multiple energy sources, the model enhances their complementarity and interaction. …”
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AdvFaceGAN: a face dual-identity impersonation attack method based on generative adversarial networks by Hong Huang, Yang Yang, Yunfei Wang

“…Innovatively, we incorporate source identity loss into the identity loss calculation, discovering that minor reductions in target identity similarity can be traded for significant improvements in source identity similarity, thus making the adversarial faces generated by our method highly similar to both the source identity and the target identity, addressing limitations in existing impersonation attack methods. …”
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Robust Pareto Transistor Sizing of GaN HEMTs for Millimeter-Wave Applications by Rafael Perez Martinez, Stephen Boyd, Srabanti Chowdhury

“…We utilize a derivative-free optimization method to effectively identify robust Pareto optimal device designs. …”
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Pit Collapse Risk Fusion Early-Warning Method Based on Machine Learning and Improved Cloud Dempster–Shafer by Jiajia Zeng, Bo Wu, Cong Liu

“…A high-accuracy metro pit collapse risk fusion early-warning method is proposed in present study. The main contributions include (1) presenting a new input to the fusion model by optimizing the machine learning model through a multi-step rolling method, and then using the basic probability assignment values obtained from the cloud model as input to the fusion model and (2) developing an improved methodology to address the paradoxical results of the fusion of traditional Dempster–Shafer evidence theory when there is a high level of conflict in multi-source risk prediction data. …”
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Finding the Root of the Pathos in the Planning System of Iran: 5-why Technique by Elham Vafaei, Gholamreza Geraeinejad

“…To answer this important question, the pathology of the planning system is examined from two dimensions: Its stages (preparation and compiling (prerequisite, structure, process and product), approval, pre-implementation, implementation and Supervision and evaluation) and its source (inside and outside the organization). Causal relationships between identified disadvantages based on the effectiveness matrix obtained and root disadvantages has been extracted using the 5-Why technique.The results show that the root disadvantages of the planning system are: "Lack of common understanding of concepts by planners, policy makers and implementers", "The rule of centralized and non-participatory methods in planning", "Lack of mechanism for resolving conflicts of interest between program elites", "Rigidity in considering the situation and not paying attention to possible scenarios in the future", "Failure to prepare an action plan and link it to the approved plan", "Existence of sectorial-regional and local orientations in the approval of programs", "Relying on government resources and not paying attention to internal and external capacities and resources", "Lack of attention of the planning system to the system of reform and adjustment in policies, goals and executive plans after monitoring and evaluation" and "severe weakness of regulatory mechanisms". …”
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A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV by HUANG Lei, QI Yin, CHEN Weihua, DU Xianfei, MA Bing, TANG Jizhou

“…This study is a rapid and efficient geomechanical modeling method to optimize the data required for fracturing site operations.…”
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A Method for Fault Localization in Distribution Networks with High Proportions of Distributed Generation Based on Graph Convolutional Networks by Xiping Ma, Wenxi Zhen, Haodong Ren, Guangru Zhang, Kai Zhang, Haiying Dong

“…To address the issues arising from the integration of a high proportion of distributed generation (DG) into the distribution network, which has led to the transition from traditional single-source to multi-source distribution systems, resulting in increased complexity of the distribution network topology and difficulties in fault localization, this paper proposes a fault localization method based on graph convolutional networks (GCNs) for distribution networks with a high proportion of distributed generation. …”
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Physicochemical and Functional Properties of Yanbian Cattle Bone Gelatin Extracted Using Acid, Alkaline, and Enzymatic Hydrolysis Methods by Song Zhang, Duanduan Zhao, Lu Yin, Ruixuan Wang, Zhiyan Jin, Hongyan Xu, Guangjun Xia

“…Yanbian cattle bone gelatin shows promise as an alternative source for halal gelatin production. This study also provides insights into optimizing gelatin production to enhance its functionality and sustainability.…”
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Optimized Polyhydroxybutyrate Production by <i>Neobacillus niacini</i> GS1 Utilizing Corn Flour, Wheat Bran, and Peptone: A Sustainable Approach by Gaurav Shrimali, Ajit Gangawane, Esha Rami, Hardik Shah, Kashyap Thummar, Dipak Kumar Sahoo, Ashish Patel, Jens Ejbye Schmidt

“…The bacterium was identified using morphological, biochemical, and molecular techniques. The optimization process involved adjusting variables such as inoculum age, inoculum size, incubation time, agitation rate, incubation temperature, pH of the medium, carbon sources, and nitrogen sources. …”
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A Deep Learning Inversion Method for 3D Temperature Structures in the South China Sea with Physical Constraints by Dongcan Xu, Yahao Liu, Yuan Kong

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Optimal tuning of PI based LF for three-phase SRF PLL synchronization system using pity beetle algorithm under grid abnormalities by P. Riyas, S. A. Lakshmanan

“…Abstract The importance of grid synchronization in recent years is primarily driven by the widespread integration of renewable energy sources (RES). As nations transition toward carbon–neutral power systems, the variable nature of renewables and the increasing prevalence of non-linear loads introduce significant challenges for maintaining effective grid synchronization. …”
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Wind Power Short-Term Prediction Method Based on Time-Domain Dual-Channel Adaptive Learning Model by Haotian Guo, Keng-Weng Lao, Junkun Hao, Xiaorui Hu

“…To address three key challenges in extracting temporal characteristics of strong volatility, adaptive fusion of multi-source features, and enhancing model interpretability, this paper proposes a Time-Domain Dual-Channel Adaptive Learning Model (TDDCALM). …”
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Efficiency of Bacteriophage-Based Detection Methods for Non-Typhoidal <i>Salmonella</i> in Foods: A Systematic Review by Preeda Phothaworn, Chatruthai Meethai, Wanchat Sirisarn, Janet Yakubu Nale

“…Further research and development will be pivotal to overcoming challenges and maximizing the efficiency of NTS phage-based detection to ensure optimal food safety.…”
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Comparing Acid and Enzymatic Hydrolysis Methods for Cellulose Nanocrystals (CNCs) Obtention from Agroindustrial Rice Husk Waste by Ricardo Hernández Pérez, René Salgado Delgado, Alfredo Olarte Paredes, Areli Salgado Delgado, Edgar García Hernández, Atenas Medrano Valis, Fryda Martínez Candia

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Automation of conceptual design and modification of aircraft-type unmanned aerial vehicles using multidisciplinary optimization and evolutionary algorithms. Part 2: results and ana... by V. A. Komarov, O. E. Lukyanov, V. H. Hoang, E. I. Kurkin, J. G. Quijada Pioquinto

“…An example of practical application of the methodology of multidisciplinary optimization of the concept parameters of aircraft-type flight vehicles is considered in the form of solving the problem of modifying two existing aircraft with characteristics presented in open sources. …”
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