Faktor-Faktor yang Mempengaruhi Auditor Switching dengan Financial Distress sebagai Pemoderasi by Herninda Pitaloka, Agung Guritno

“…The analysis included descriptive statistical tests, model feasibility tests, classification matrix tests, the formation of logistic regression functions, partial parameter significance tests, simultaneous parameter significance tests, coefficients of determination tests and MRA tests. …”
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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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Monte Carlo-Based Strategy for Assessing the Impact of EEG Data Uncertainty on Confidence in Convolutional Neural Network Classification by Pierre Sedi Nzakuna, Vincenzo Gallo, Vincenzo Paciello, Aime Lay-Ekuakille, Angelo Kuti Lusala

“…We introduce robust evaluation metrics, including the proportion of area under the curve (AUC) of probability density functions (PDFs) <inline-formula> <tex-math notation="LaTeX">$\geq 70$ </tex-math></inline-formula>% accuracy, overlap coefficients, and percentile-based thresholding, which provide a more comprehensive assessment of model performance, capturing not only accuracy but also confidence and ambiguity in predictions. …”
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Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption by Minjian Li, Chongqiao Tang, Junhan Gu, Nianchu Li, Ahemaide Zhou, Kunlin Wu, Zhibo Zhang, Hui Huang, Hongqiang Ren

“…To overcome the complexity of wastewater compositions, an unsupervised machine learning algorithm, spectral clustering, is introduced to analyze 2,576 WWTPs across China, effectively characterizing influent quality as a single variable and contributing to robust benchmarks with 75 % of the fittings achieving coefficients of determination (R2) >0.85. …”
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Structural Integrity and Life Assessment of Ti-6Al-4V Orthopaedic Implants by Katarina Čolić, Svetlana M. Kostić, Simon Sedmak, Nenad Gubeljak, Aleksandar Grbović

“…In X-FEM, the finite element space is enriched with discontinuity functions and asymptotic functions at the crack tip, which are integrated into the standard finite element approximation using the unity division property. …”
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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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Test–retest reliability and validity in lower limb proprioception tests using image capture technique in healthy adults by Aisuke Takahashi, Hikaru Kawana, Katsuhiro Furukawa

“…In statistical analysis, the test–retest reliability and construct validity were evaluated using intraclass correlation coefficients (ICC) and Spearman’s rank correlation coefficients. …”
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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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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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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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