SCM-DL: Split-Combine-Merge Deep Learning Model Integrated With Feature Selection in Sports for Talent Identification by Didem Abidin, Muhammed G. Erdem

“…The SCM-DL integrated with the RFE_DTC feature selection method achieved the highest performance for six features, yielding an accuracy rate of 97.40% and a Matthews Correlation Coefficient performance rate of 96.6%. …”
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Multifaceted Biological Activity of Rutin, Quercetin, and Quercetin’s Glucosides by Danuta Zielińska, Małgorzata Starowicz, Małgorzata Wronkowska, Henryk Zieliński

“…The antioxidant potency was determined by electrochemical methods, whereas the ability of these compounds to inhibit angiotensin-converting enzyme (ACE) activity, acetylcholinesterase (AChE) activity, and advanced glycation endproduct (AGE) formation was examined in bovine serum albumin (BSA)/glucose and BSA/methylglyoxal (MGO) model systems to show their importance against hypertension, Alzheimer-type dementia, and diabetic complication, respectively. …”
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Risk Assessment Model for Metro Station Stair and Escalator Operation Systems Based on Bayesian Network by HOU Xiangyu, HU Hua, FANG Yong, MENG Yanli, HAO Yanxi, LIU Zhigang

“…Therefore, it is necessary to establish a risk assessment model for these systems and evaluate their associated risks. [Method] The SEO system is divided into two subsystems—stairs and escalators—and three functional units: buffering, walking, and dispersing. …”
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Study on Optimization of Process Parameters and Microstructure Properties of Laser-Cladded AlCoCrFeNi_2.1 Eutectic High Entropy Alloy by LI Zansong, WANG Dongsheng

“…In order to investigate the effects of processing parameters on the microstructure and mechanical properties of the AlCoCrFeNi2.1 eutectic high entropy alloy(EHEA)， an orthogonal experimental design coupled with a comprehensive-scoring method was used to preliminarily identified the optimal laser cladding conditions.Among the tested combinations， Sample 4 (laser power 1 800 W， scanning speed 360 mm/min， powder-feed rate 2.1 r/min) and Sample 5 (laser power 1 800 W， scanning speed 420 mm/min， powder-feed rate 2.4 r/min)received the highest scores.These two specimens were then subjected to multi-pass， single-layer laser cladding， and their microstructures and mechanical properties were systematically characterized.Results showed that the laser-cladded AlCoCrFeNi2.1 EHEA coating was composed predominantly of dual FCC and BCC phases.In the multi-pass coating， Sample 5 displayed a surface dominated by uniform equiaxed grains，whereas Sample 4 exhibited a mixture of columnar and equiaxed grains with larger， irregular sizes.Further investigations showed that Sample 5 possessed superior microhardness and wear resistance:an average hardness of 323.7 HV1.0，an average friction coefficient of 0.64，and markedly lower wear rate (1.16×10－6 mm3∙N－1∙mm－1) and wear volume (14.4 mm3) than Sample 4.Accordingly， the optimal laser-cladding parameters for AlCoCrFeNi2.1 EHEA were determined to be a laser power of 1 800 W， a scanning speed of 420 mm/min， and a powder-feed rate of 2.4 r/min.…”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…More importantly, it requires only a single discretization of the problem domain, eliminating the need for dynamic adjustment of meshes or sampling points during iterations—a necessity in methods like moving mesh techniques. This substantially enhances computational efficiency.…”
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Development of a multi-neoepitope vaccine targeting non-small cell lung cancer through reverse vaccinology and bioinformatics approaches by Elahe Asadollahi, Alireza Zomorodipour, Zahra-Soheila Soheili, Babak Jahangiri, Majid Sadeghizadeh

“…Among immunotherapeutic strategies, the personalized multi-neoepitope vaccine (MNEV) offers a promising approach for managing advanced-stage NSCLC.MethodsWe used reverse vaccinology, immunoinformatics, and bioinformatics to design an MNEV targeting lung cancer in murine (LL/2) cells. …”
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Obstacles and ways of forming effective protection of rice crops from weeds by L. Tsilinko

“…Assessment of the current level of soil contamination in rice checks with weed seeds and determination of the reasons for insufficient efficiency of herbicide application to ensure high yields of rice sown in the south of our country. …”
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Antigenic properties of sARs-CoV-2/human/RUs/nsk-FRCFtM-1/2020 coronavirus isolate from a patient in novosibirsk by A. A. Chepurnov, K. A. Sharshov, E. I. Kazachinskaya, Yu. V. Kononova, E. A. Kazachkova, O. P. Khripko, K. S. Yurchenko, A. Yu. Alekseev, M. I. Voevoda, A. M. Shestopalov

“…Purification, concentration and inactivation of the viral preparation were carried out according to standard methods. The purity of the purified preparation and the profile of viral proteins were determined by electrophoresis in 10% polyacrylamide gel (PAG) with the addition of sodium dodecyl sulfate (SDS). …”
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FEATURES OF FORMATION AND EXECUTION OF THE FEDERAL BUDGET IN THE MILITARY-INDUSTRIAL COMPLEX OF RUSSIA by Anzhela Z. Namitulina, Olga V. Kalashnikova

“…Objectives of the article: identify design characteristics of the defense component of the federal budget during the crisis of Economic Development. Methods: Methodological basis of this article are of economic and statistical methods of analysis.Results: Given that the management of the defense industry will be converted, you must use the positive experience of the international economic order to ensure the sustainability of their financial security. …”
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Spiking Neural Networks Optimized by Improved Cuckoo Search Algorithm: A Model for Financial Time Series Forecasting by Panke Qin, Yongjie Ding, Ya Li, Bo Ye, Zhenlun Gao, Yaxing Liu, Zhongqi Cai, Haoran Qi

“…Applied to futures market price difference prediction, experimental results demonstrate that ICS-SNN achieves reductions of 13.82% in MAE, 21.27% in MSE, and 15.21% in MAPE, while improving the coefficient of determination (R²) from 0.9790 to 0.9822, compared to the baseline SNN. …”
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Development of a Prediction Model for Specific Fuel Consumption in Rotary Tillage Based on Actual Operation by Seung-Jun Kim, Moon-Kyeong Jang, Seok-Joon Hwang, Won Suk Lee, Ju-Seok Nam

“…The model’s accuracy was analyzed using the coefficient of determination (R²) and root mean square error (RMSE), and it was compared with the ASABE’s fuel consumption prediction model. …”
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In-Season Potato Nitrogen Prediction Using Multispectral Drone Data and Machine Learning by Ehsan Chatraei Azizabadi, Mohamed El-Shetehy, Xiaodong Cheng, Ali Youssef, Nasem Badreldin

“…The results indicate that RF outperformed SVM and GBR, achieving the highest coefficient of determination (R² = 0.571) and the lowest mean absolute error (MAE = 0.365%) using the RFE feature selection method. …”
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Evaluation and ranking of solutions to overcome the barriers of Industry 4.0 enabled sustainable food supply chain adoption by Swapnil Lahane, Vishal Paliwal, Ravi Kant

“…The relative weights of each barrier are determined using the PF-AHP technique, and the solution to these barriers is prioritized using the PF-EDAS method. …”
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Validation of the Russian-language version of Ankylosing Spondylitis Quality of Life (ASQoL) questionnaire by L. D. Vorobyova, T. V. Dubinina, A. O. Sablina, A. B. Demina, E. V. Ilinykh, K. V. Sakharova, I. A. Andrianova, T. V. Korotaeva, L. V. Ivanova

“…Assessment of patient reported outcomes included an assessment of spinal pain, night spinal pain, spinal pain during the day using a numerical rating scale, patient’s global assessment of health, assessment of functional status using BASFI index and health related quality of life (HRQoL) using EQ-5D, SF-36 and ASQoL questionnaires. To determine reliability of ASQoL questionnaire, a test-retest analysis and determination of internal consistency by calculating the Cronbach's α coefficient were used. …”
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Statistical model for assessing the reliability of non-destructive testing systems by solving inverse problems by A. E. Alexandrov, S. P. Borisov, L. V. Bunina, S. S. Bikovsky, I. V. Stepanova, A. P. Titov

“…Under constraints on the data sample size, the proposed methodology allows the metal monitoring results to be applied with greater confidence than currently used methods at the same time as evaluating the efficiency of monitoring carried out by individual test teams or laboratories. …”
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Rapid Quantitative Detection of Dye Concentration in Pt/TiO₂ Photocatalytic System Based on RGB Sensing by Cuiyan Han, Ziao Wang, Jiahong Cui, Shuqi Liu, Liu Yang, Yang Fu, Baolin Zhu, Cheng Guo

“…The RGB-based PLS model achieved a coefficient of determination (R²) of 0.961 for the prediction set. …”
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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

“…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. …”
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Variogram modelling optimisation using genetic algorithm and machine learning linear regression: application for Sequential Gaussian Simulations mapping by André William Boroh, Alpha Baster Kenfack Fokem, Martin Luther Mfenjou, Firmin Dimitry Hamat, Fritz Mbounja Besseme

“…The study combines GA and machine learning to optimise variogram parameters, including range, sill, and nugget, by minimising the root mean square error (RMSE) and maximising the coefficient of determination (R2). The experimental variograms were computed and modelled using theoretical models, followed by optimisation via evolutionary algorithms. …”
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IMPLEMENTATION OF TRAUMA-PROTECTING TECHNOLOGICAL LINES FOR TRANSPORTATION OF GRAIN CROPS by R. Mirskykh

“…The study is based on the analysis of recent research in the field of mechanical damage to grain and methods for its minimization. Methods of theoretical mechanics, continuum mechanics, and the Federman–Buckingham theorem are used. …”
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FORECASTING VALUES OF CHROMATICITY OF DRINKING AND SOURCE WATERS USING ARIMA MODEL AND NEURAL NETWORK by D. V. Makarov, E. A. Kantor, N. A. Krasulina, A. V. Greb, Z. Z. Berezhnova

“…Optimal configurations of ARIMA-models were determined from the results of comparing the averaged values of the root mean squared errors (RMSE); optimal configurations of ANN were determined from the results of comparing the averaged values of RMSE and correlation coefficients (CC) on the test periods.Results. …”
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