Comparative Pacing Profile and Chronometric Performance in Elite Swimmers with Intellectual Impairments and Able-Bodied Athletes by Luca Puce, Piotr Zmijewsk, Nicola Luigi Bragazzi, Carlo Trompetto

“…Performance metrics were assessed using 50 m split times, and within-group variability was evaluated through coefficients of variation. …”
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Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique. by Tuan Anh Nguyen

“…The proposed method is formed based on the combination of an Active Disturbance Rejection Control (ADRC) technique with control coefficients tuned by a dynamic fuzzy technique formed based on special membership functions called Active Disturbance Rejection Control Based on Fuzzy (ADRCBF). …”
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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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A Protocol for Advanced Psychometric Assessment of Surveys by Janet E. Squires, Leslie Hayduk, Alison M. Hutchinson, Lisa A. Cranley, Mark Gierl, Greta G. Cummings, Peter G. Norton, Carole A. Estabrooks

“…Reliability is assessed with internal consistency coefficients and information functions. A unitary approach to validity consisting of accumulating evidence based on instrument content, response processes, internal structure, and relations to other variables is taken. …”
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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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Cardiometabolic risk factors in predicting obstructive coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, E. D. Emtseva, A. A. Vishnevskiy

“…The predictors of this model were 7 categorical (total cholesterol (CS) ≥5,9 mmol/L, low-density lipoprotein cholesterol >3,5 mmol/L, waist-to-hip ratio ≥0,9, waist-to-height ratio ≥0,69, atherogenic index ≥3,4, lipid accumulation product index ≥38,5 cm*mmol/L, uric acid ≥356 pmol/L) and 2 continuous (high density lipoprotein cholesterol and insulin resistance index) variables.Conclusion. The developed algorithm for selecting predictors made it possible to determine their significant predictive threshold values and weighting coefficients characterizing the degree of influence on endpoints. …”
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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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Genetic characterisation of Germanata Veneta and Mignon local duck breeds (Anas platyrhynchos) using whole-genome sequencing by Francesco Perini, Enrico Bortoletto, Filippo Cendron, Umberto Rosani, Emiliano Lasagna, Maristella Baruchello, Martino Cassandro, Mauro Penasa

“…Both breeds showed low genetic variability and high inbreeding (GER: FHOM = 0.305 ± 0.184; MIG: FHOM = 0.369 ± 0.163). …”
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Absorbing Aerosol Effects on Hyperspectral Surface and Underwater UV Irradiances from OMI Measurements and Radiative Transfer Computations by Alexander Vasilkov, Nickolay Krotkov, Matthew Bandel, Hiren Jethva, David Haffner, Zachary Fasnacht, Omar Torres, Changwoo Ahn, Joanna Joiner

“…The output underwater products include the hyperspectral diffuse attenuation coefficients of the planar and scalar irradiances. Effects of the seasonal variability of AAOD on the UV index and the deoxyribonucleic acid (DNA) damage dose rates are considered. …”
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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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Influences of Gait Training with Knee–Ankle–Foot Orthosis on Gait Ability and Independence in Severe Hemiplegia and Pusher Behavior with Unilateral Spatial Neglect Following Stroke... by Kota Sawa, Miko Tamura, Saori Arai

“…Onset days and SPV variability errors influenced severe hemiplegia cases, whereas SPV‐EO variability errors impacted USN cases, with moderate regression coefficients (p < 0.05). …”
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Fate-tox: fragment attention transformer for E(3)-equivariant multi-organ toxicity prediction by Sumin Ha, Dongmin Bang, Sun Kim

“…To address these challenges with multiple strategies, we developed FATE-Tox, a novel multi-view deep learning framework for multi-organ toxicity prediction. For variability of substructures, we used three fragmentation methods such as BRICS, Bemis-Murcko scaffolds, and RDKit Functional Groups to formulate fragment-level graphs so that diverse substructures can be used to identify toxicity for different organs. …”
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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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Feasibility, reliability and validity of smartphone administered cognitive ecological momentary assessments in breast cancer survivors by Ashley M. Henneghan, Ashley M. Henneghan, Emily W. Paolillo, Kathleen M. Van Dyk, Kathleen M. Van Dyk, Oscar Y. Franco-Rocha, Mansi Patel, So Hyeon Bang, Raeanne C. Moore

“…Test–retest reliability was examined using intraclass correlation coefficients for each cognitive EMA (tests and self-report questions), and Pearson's correlation was used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive variables.Results105 breast cancer survivors completed the EMA protocol with high adherence (87.3%) and high satisfaction (mean 87%). …”
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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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