Developing a novel layer network structure for a LSTM model to predict mean monthly river streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Shahaboddin Daneshvar, Farshad Ahmadi

“…For doing so, to select the most effective parameters on MRSF m , the Pearson’s correlation coefficient (PCC) and Cosine amplitude sensitivity (CAS) as features selection process are carried out for potential meteorological variables in the study area (i.e., average monthly temperature (T m ), evaporation (ET m ), and precipitation (P m )) and target (MRSF m ). …”
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Forecasting Electricity Production in a Small Hydropower Plant (SHP) Using Artificial Intelligence (AI) by Dawid Maciejewski, Krzysztof Mudryk, Maciej Sporysz

“…Renewable Energy Sources (RESs) are difficult to predict due to weather variability. Electricity production by a run-of-river SHP is marked by the variability related to the access to instantaneous flow in the river and weather conditions. …”
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High expression of SOX9 is a diagnostic and prognostic indicator of glioma by Libo Xu, Zhenhao Wang, Mao Li, Qingsong Li

“…Screening was performed by LASSO coefficients to select non-zero variables that satisfied the coefficients of lambda. min, and four genes were screened out. …”
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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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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty by Sojkin Bogdan, Bartkowiak Paweł, Michalak Szymon

“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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Evolution and transformation of vineyard landscapes and promotion of sustainable viticulture. The case of Boukornine protected area in Tunisia by Abdelkarim Hamrita, Faouzi Haouala, Khouloud Annabi, Rania Kouki, Rania Kouki, Mokhtar Rejili, Bouthaina Al Mohandes Dridi

“…This shift has contributed to landscape homogenization and a decline in ecological functionality. Nonetheless, the vicinity of Boukornine National Park provides critical ecosystem services—such as microclimate regulation and biodiversity support—that buffer vineyards against environmental stressors.DiscussionThe study emphasizes the need for sustainable transitions in vineyard management through the adoption of organic farming practices, efficient irrigation systems, and the valorization of local terroirs. …”
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Nonlinear Creep Constitutive Model of Rock Considering Hardening Effect by Dipeng Zhu, Zhiyong Hu, Shuguang Zhang, Wei Qiu, Yijie Wang, Donglan Chen, Fan Mingzhuo, Shutian Zhao, Ye Sun, Wenbo Liu

“…To precisely capture the nonlinearity of rock creep and the law of accelerated deformation, a hardening function and a damage variable are introduced. Based on traditional rheological models, creep mechanisms, and damage laws, an accelerated creep constitutive model integrating hardening and damage effects is established. …”
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Exploring individual and organizational contributors to workplace deviant behavior by D. Daryono, R. Gunawan, U. Udin

“…The novelty and originality of this research lie in its integration of these three variables to understand their combined impact on workplace deviant behavior. …”
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Three-dimensional dynamics of mesothelin-targeted CAR.CIK lymphocytes against ovarian cancer peritoneal carcinomatosis by Federica Galvagno, Valeria Leuci, Annamaria Massa, Chiara Donini, Ramona Rotolo, Sonia Capellero, Alessia Proment, Letizia Vitali, Andrea Maria Lombardi, Valentina Tuninetti, Lorenzo D’Ambrosio, Alessandra Merlini, Elisa Vigna, Giorgio Valabrega, Luca Primo, Alberto Puliafito, Dario Sangiolo

“…MSLN-CAR.CIK effectively killed and were functionally efficient against OC targets. In a “floating-like” 3D context with floating OC spheroids, both tumor localization and killing by MSLN-CAR.CIK were significantly boosted by fluid flow. …”
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Techno-economic assessment of low-carbon ammonia as fuel for the maritime sector by Wouter Schreuder, J. Chris Slootweg, Bob van der Zwaan

“…We incorporate three different cost levels for ammonia and a variable engine efficiency ranging from 35 % to 55 %. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Based on the spectral principal components, three classifiers were built to classify the maturity level: support vector machine, backpropagation neural network, and radial basis function neural network. Excellent results with a classification accuracy of 100% were obtained. …”
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Approximation by interpolation spectral subspaces of operators with discrete spectrum by M.I. Dmytryshyn

“…Applications to spectral approximations of the regular elliptic operators with variable smooth coefficients in the space $L_q(\Omega)$ over an open bounded set $\Omega\subset\mathbb{R}^n$ and some self-adjoint ordinary elliptic differential operators in a bounded interval $\Omega=(a,b)$ are shown.…”
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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
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Investigation into the monitoring and control of mechanical dynamics in inclined mining equipment utilizing digital twin technology by Panshi XIE, Hang YANG, Yongping WU, Baofa HUANG, Weidian LIN, Leilei YI

“…Ultimately, the feasibility and efficacy of this system are corroborated through a multi-functional, variable-angle large-scale "support-surrounding rock" system physical simulation platform. …”
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An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0 by S. Masson, S. Jullien, E. Maisonnave, D. Gill, G. Samson, M. Le Corre, L. Renault

“…The present paper details the development and the functionalities of the coupling interface we implemented in WRF. …”
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CdiA Effectors from Uropathogenic Escherichia coli Use Heterotrimeric Osmoporins as Receptors to Recognize Target Bacteria. by Christina M Beck, Julia L E Willett, David A Cunningham, Jeff J Kim, David A Low, Christopher S Hayes

“…These findings suggest that self-recognition and kin selection are important functions of CDI.…”
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In vitro differentiation of common lymphoid progenitor cells into B cell using stromal cell free culture system by Pan Yang, Xiaoling Chen, Hao Wen, Meiling Yu, Haili Yu, Li Wang, Liang Gong, Lintao Zhao

“…However, the complex nature of operations and the intrinsic variability of stromal cell functionality, which can be influenced by factors such as radiation exposure or contamination, pose considerable challenges to their wider application. …”
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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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Family Resilience and Its Influencing Factors Among Patients With Lung Cancer Based on Double ABC‐X Theoretical Framework by Ziyi Shen, Yan Fang, Chengcheng Li, Xin Luo, Junling Cui, Yanchang Liu, Jingfang Hong

“…Relationships between variables and pathways were also explored based on the Double ABC‐X as the theoretical framework. …”
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