A reduced simulation applied to viscoelastic fatigue of polymers using a time multi-scale approach based on partition of Unity method by Sebastian Rodriguez, Angelo Pasquale, Jad Mounayer, Diego Canales, Marianne Beringhier, Chady Ghnatios, Amine Ammar, Francisco Chinesta

“…In this context, the use of a space-time PGD approximation is proposed here to boost their resolution, where the temporal functions are constructed following a multi-scale strategy along with the partition of unity method, in order to catch each dynamic efficiently. …”
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Effects of two types of repetitive transcranial magnetic stimulation on brain network in Parkinson’s disease by Shuo Liu, Shuo Yang, Chen Wang, Jiarui Li, Lei Wang

“…The iTBS group showed post-treatment changes involving more brain regions in spatiotemporal variability. This study demonstrates that compared to 10Hz-rTMS, iTBS can reduce treatment time while providing superior improvement in functional brain connectivity for PD patients.…”
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SCIENTIFIC APPROACH TO A COMPLEX ASSESSMENT OF DETERMINANTS OF THE INSURANCE MARKET DEVELOPMENT OF UKRAINE by L. V. Popova, N. O. Kovalchuk, D. D. Polagnyn

“…The developed model contains a clear list and sequence of stages of the insurance market analysis and a specific methodology for assessing the impact of key factors, characteristic for changing conditions of management, on the efficiency of its functioning. Practical application allows to take into consideration the influence of individual determinants of the insurance market development on its condition, to increase the efficiency of managerial decisions in this area. …”
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Novel pyrochlores in the Bi2O3–MgO–Ta2O5 (BMT) system: Synthesis optimisation, phase equilibria and dielectric properties by K.B. Tan, P.Y. Tan, Y. Feng, C.C. Khaw, V. Raman, H.C. Ananda Murthy, R. Balachandran, S.K. Chen, O.J. Lee, K.Y. Chan, D. Zhou, M. Lu

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Coordination of technology of railway operation of the Republic of Tajikistan and organization of railways in international traffic by P. N. Pulatov

“…Proposed classification of technological restrictions and controlled variables in the performance of transport takes into account methods for changing external conditions for the functioning of the railway landfill and methods for increasing internal efficiency of its operation. …”
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Development of a High-Cell-Density Production Process for a Biotherapeutic Yeast, <i>Saccharomyces cerevisiae</i> var. <i>boulardii</i>, for Use as a Human Probiotic by Ghaneshree Moonsamy, Sarisha Singh, Yrielle Roets-Dlamini, Koketso Kenneth Baikgaki, Santosh Omrajah Ramchuran

“…Once the optimised batch was validated in the replicate batches, the statistical analysis indicated a high level of reproducibility, with low variability across key performance indicators such as biomass concentration (unit), CFU production (CFU.mL⁻¹), and substrate utilization efficiency (g.g⁻¹). …”
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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. Design variables included PVT inclination, azimuth, area, heat pump capacity, and tank volume, while operational variables were PVT backplate temperature and tank temperature. …”
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Optimization of K-Shaped Metal Sealing Ring for Subsea Tubing Hanger Based on Response Surface Method by Huan Xie, Hongxia Zhang, Yiwei Fan, Liyuan Liu, Wei Zeng

“…To address the issue of low optimization efficiency due to the need for repeated finite element calculations during the optimization process, quadratic response surface models are established for the sealing performance indicators of the K-shaped seal ring, which were then used as the optimization objective functions to enhance the optimization efficiency. …”
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Modeling the contribution of micronekton diel vertical migrations to carbon export in the mesopelagic zone by H. Thibault, F. Ménard, J. Abitbol-Spangaro, J.-C. Poggiale, S. Martini

“…Several metabolic parameters accounted for most of the variability in micronekton biomass, organic carbon production, and transport efficiency, mostly linked to respiration rates and capture efficiency. …”
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Developing a machine learning model for fast economic optimization of solar power plants using the hybrid method of firefly and genetic algorithms, case study: optimizing solar the... by Ali Omidkar, Razieh Es'haghian, Hua Song

“…The objective functions were to optimize the exergy efficiency and the heat cost. …”
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Learning compositional sequences with multiple time scales through a hierarchical network of spiking neurons. by Amadeus Maes, Mauricio Barahona, Claudia Clopath

“…The hierarchical model redistributes the variability: it achieves high motif fidelity at the cost of higher variability in the between-motif timings.…”
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RNAtango: Analysing and comparing RNA 3D structures via torsional angles. by Marta Mackowiak, Bartosz Adamczyk, Marta Szachniuk, Tomasz Zok

“…RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. …”
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Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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Smart Fermentation Technologies: Microbial Process Control in Traditional Fermented Foods by Chong Shin Yee, Nur Asyiqin Zahia-Azizan, Muhamad Hafiz Abd Rahim, Nurul Aqilah Mohd Zaini, Raja Balqis Raja-Razali, Muhammad Ameer Ushidee-Radzi, Zul Ilham, Wan Abd Al Qadr Imad Wan-Mohtar

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Combined analysis of 16S rRNA gene sequencing data reveals core vaginal bacteria across livestock species by Lucille C. Jonas, Lucille C. Jonas, Curtis R. Youngs, Stephan Schmitz-Esser, Stephan Schmitz-Esser

“…Recent publications have uncovered a high degree of variability of the livestock vaginal microbiota, making it difficult to focus functional research on individual microorganisms. …”
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Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage by Per Pettersson, Eirik Keilegavlen, Tor Harald Sandve, Sarah E. Gasda, Sebastian Krumscheid

“…The uncertainty in upscaled flow functions and other uncertain parameters are efficiently propagated to leakage estimates using numerical reservoir simulation of a two‐phase system of CO2 and brine. …”
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Assessment of RBFs Based Meshfree Method for the Vibration Response of FGM Rectangular Plate Using HSDT Model by Manish Srivastava, Jeeoot Singh

“…Radial basis functions (RBFs) with modified radial distance are proposed for vibration analysis of functionally graded materials (FGM) rectangular plates. …”
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Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

“…Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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Neural Network-Based Design of a Buck Zero-Voltage-Switching Quasi-Resonant DC–DC Converter by Nikolay Hinov, Bogdan Gilev

“…The converter is a piecewise linear system mathematically described by Kirchhoff’s laws and represented through switching functions. In this way, a mathematical model is used to generate data on the behavior of the state variables obtained under various design parameters. …”
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Multiobjective Optimization of Stress-Release Boot of Solid Rocket Motor under Vertical Storage Based on RBF Model by Qiuwen Miao, Huihui Zhang, Zhibin Shen, Weiyong Zhou

“…Stress-release boot can effectively improve the structural integrity of SRM (solid rocket motor), but it will also influence the loading fraction and interior ballistic performance, so the purpose of this paper is to propose a multiobjective optimization method for stress-release boot. The design variables are the front and rear depth of the stress-release boot, and four optimization variables were determined according to the analysis of SRM performance. …”
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