VERIFICATION OF A TRAIN ON RAILWAY TRACK SIMULATION AND OPTIMIZATION SYSTEM by Adam MAŃKA, Piotr KISIELEWSKI, Jarosław KONIECZNY, Krzysztof LABISZ, Janusz ĆWIEK

“…The main achievement is the development of an algorithm that simulates the passage of a train over 500 km, the duration of which did not exceed two minutes. …”
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Study on multi-parameter optimization of seismic isolation bearings for continuous girder bridges considering interactions among key parameters by Zhaolan Wei, Bowen Yang, Qixuan You, Konstantinos Daniel Tsavdaridis, Shaomin Jia

“…First, using a conventional particle swarm optimization (PSO) algorithm, the individual and combined effects of each parameter on key response indicators are identified. …”
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Modeling circadian variability of core-clock and clock-controlled genes in four tissues of the rat. by Panteleimon D Mavroudis, Debra C DuBois, Richard R Almon, William J Jusko

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Mapping global risk levels of Bemisia tabaci in areas of suitability for open field tomato cultivation under current and future climates. by Rodrigo Soares Ramos, Lalit Kumar, Farzin Shabani, Marcelo Coutinho Picanço

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Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh by M. Azizur Rahman, Al-Amin Hossain, Binoy Debnath, Zinnat Mahmud Zefat, Mohammad Sarwar Morshed, Ziaul Haq Adnan

“…An android application, Intelligent Route Optimizer, is developed using the shortest path first algorithm based on the Dijkstra algorithm. The vehicle navigation scheme is programmed to change the direction according to the shortest possible path in the google map generated by the intelligent routing optimizer. …”
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CAFiKS: Communication-Aware Federated IDS With Knowledge Sharing for Secure IoT Connectivity by Ogobuchi Daniel Okey, Demostenes Zegarra Rodriguez, Frederico Gadelha Guimaraes, Joao Henrique Kleinschmidt

“…The experimental results demonstrate that the CAFiKS achieves high detection accuracy (up to 99%) on the selected datasets in identifying network traffic anomalies while using a compact network architecture for predictions. By incorporating knowledge distillation, FL clients effectively reduce communication bottlenecks and mitigate communication threats.…”
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Prognostic role of hemostasis-regulating genetic factors and their interaction with conventional risk factors at the early stages of coronary heart disease development by E. Yu. Andreenko, L. M. Samokhodskaya, A. V. Balatskyi, P. I. Makarevich, S. A. Boytsov

“…In participants with HCH, the PLA2/PLA2 genotype of GPIIIa was linked to increased MI risk for CHD patients (p=0,01; OR=6,0). Conclusion. The algorithm for predicting the genetic CHD risk may incorporate the assessment of the genetic polymorphism of GPIa (C807T), GPIIIa (PLA1/PLA2), factor XIII (V34L), and factor VII (R353Q). …”
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Analysis of the Strength Development, CO₂ Emissions, and Optimized Low-Carbon Design of Fly-Ash-Enhanced Composite Concrete by Bo Yang, Yu Dong, Xiao-Yong Wang

“…The correlation coefficient between the predicted and actual strength values was 0.98208. The parameter analysis indicates that, for a given FA/(C + FA) ratio or curing duration, the relative strength of the concrete increases more rapidly with a lower W/(C + FA) ratio. …”
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COMPREHENSIVE THERAPY OF ENDO-PERIODONTAL LESIONS: MOVING STEP BY STEP TOWARDS COMPLETE FUNCTIONAL REHABILITATION OF PATIENTS WITH COMBINED PATHOLOGY by Yu.O. Kinash, L.V. Kinash

“…The coefficient of concordance demonstrates the importance of the therapy we conducted with the possibility of predicting its outcomes, mathematically confirming and equating the data with index analysis. …”
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Integrating GIS and remote sensing for soil attributes mapping in degraded pastures of the Brazilian Cerrado by Rômullo Oliveira Louzada, Ivan Bergier, Édson Luis Bolfe, Jayme Garcia Arnal Barbedo

“…This study integrates active and passive remote sensing data with Machine Learning (ML) methods to predict the physicochemical properties of degraded sandy soils in the Brazilian Cerrado. …”
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The impact of SRRM2-AS1 in ovarian cancer: a comprehensive analysis based on pan-cancer and in vitro validation by Jiaojiao Lu, Xia Zheng, Xu Li

“…Immune cell infiltrations were assessed with the single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm, while subcellular localization was predicted using the lncATLAS database. …”
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Machine learning-driven identification of critical gene programs and key transcription factors in migraine by Lei Zhang, Yujie Li, Yunhao Xu, Wei Wang, Guangyu Guo

“…Random forest analysis predicted ARID3A as the top transcription factor regulating gene program 1, suggesting its potential role in modulating calcium-related genes involved in migraine. …”
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Phenotypic Trait Acquisition Method for Tomato Plants Based on RGB-D SLAM by Penggang Wang, Yuejun He, Jiguang Zhang, Jiandong Liu, Ran Chen, Xiang Zhuang

“…The relative errors when predicting the plant height, canopy width, and volume are 3.86%, 14.34%, and 27.14%, respectively, while the errors concerning the fruit count and fruit volume are 14.36% and 14.25%. …”
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Immunogenomic-Based Analysis of Hierarchical Clustering of Diffuse Large Cell Lymphoma by Longhao Wang, Wei Yuan, Lifeng Li, Zhibo Shen, Qishun Geng, Yuanyuan Zheng, Jie Zhao

“…Immunocharacteristics-related DLBCL subtypes’ construction predicts expected patient results and supplies conceivable immunotherapy candida.…”
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Improved Cd Detection in Rice Grain Using LIBS with Husk-Based XGBoost Transfer Learning by Weiping Xie, Jiang Xu, Lin Huang, Yuan Xu, Qi Wan, Yangfan Chen, Mingyin Yao

“…These samples were processed into rice husk, brown rice, and polished rice groups, and the reference Cd content was measured by ICP-MS. The XGBoost algorithm, known for its excellent performance in handling high-dimensional data and nonlinear relationships, was applied to construct both the XGBoost base model and the XGBoost-based transfer learning model to predict Cd content in brown rice and polished rice. …”
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A simple pedotransfer function to estimate fine fraction organic carbon contents of surface horizons in French soils by Eva Rabot, Pierre Barré, Claire Chenu, Amicie A. Delahaie, Manuel P. Martin, José-Luis Munera-Echeverri, Nicolas P.A. Saby

“…., fine fraction organic carbon (OCfine) and coarse fraction organic carbon, to improve our ability to understand controlling factors and predict SOC contents and SOC stability. In this study, we aimed at building a simple pedotransfer function to estimate OCfine content measured using a size fractionation protocol in French soils. …”
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Adaptation of strategic management accounting to the ac tivities of medical equipment distributors by N. A. Kamordzhanova, E. V. Satalkina, N. D. Fedorova

“…The strategic management tools developed in the study will provide medical equipment distributors with the opportunity to more effectively analyze the market, predict macroeconomic changes and develop strategies aimed at sustainable business development. …”
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Evaluating Ecological Vulnerability and Its Driving Mechanisms in the Dongting Lake Region from a Multi-Method Integrated Perspective: Based on Geodetector and Explainable Machine... by Fuchao Li, Tian Nan, Huang Zhang, Kun Luo, Kui Xiang, Yi Peng

“…Furthermore, the LightGBM algorithm was used for feature optimization, followed by the construction of six machine learning models—Multilayer Perceptron (MLP), Extremely Randomized Trees (ET), Decision Tree (DT), Random Forest (RF), LightGBM, and K-Nearest Neighbors (KNN)—to conduct multi-class classification of ecological vulnerability. …”
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MAS-PD: Transferable Adversarial Attack Against Vision-Transformers-Based SAR Image Classification Task by Boshi Zheng, Jiabin Liu, Yunjie Li, Yan Li, Zhen Qin

“…Adversarial attacks offer a potential solution, as they can significantly mislead models and cause incorrect predictions. However, recent research on adversarial examples focus on the vulnerability of convolutional neural network (CNN) models, while the attack on transformer models has not been extensively studied. …”
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Machine learning analysis of thermo-bioconvection in a micropolar hybrid nanofluid-filled square cavity with oxytactic microorganisms by Ahlawat Anil, Chaudhary Shilpa, Karuppusamy Loganathan, Mohammed Salman Arafath, Kandasamy Thirumalaisamy, Thameem Basha Hayath

“…In addition, a machine learning approach was employed to accurately predict fluid transport properties using a multilayer artificial neural network structured with a feed-forward backpropagation model and optimized using the Levenberg–Marquardt algorithm. …”
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