Low-frequency rTMS modulates small-world network properties in an AVH-related brain network in schizophrenia by Lin Zhang, Li Guo, Xiaohui Liu, Jing Han, Yuanqiang Zhu, Chaozong Ma, Ye Li, Weiliang Ye

“…Resting-state fMRI data were collected before and after treatment to assess functional connectivity within the predefined 35-region AVH-related network. small-worldness (σ), normalized clustering coefficient (γ), and normalized characteristic path length (λ), as well as functional segregation (clustering coefficient [Cp], local efficiency [El]) and functional integration (global efficiency [Eg], characteristic path length [Lp])—were analyzed before and after rTMS. …”
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Numerical solutions for fractional optimal control problems using Mü‎‎‎‎‎‎‎ntz-Legendre polynomials by Mohammad Sahabi, Allahbakhsh Yazdani Cherati

“…To achieve this, stable and efficient methods for calculating the fractional integral and derivative operators of Müntz-Legendre functions based on three-term recurrence formulas and Jacobi-Gauss quadrature rules are presented. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Under the BIA, an alpha coefficient (α) of 15% is applied, whereas in the SA, each business line has a specific beta coefficient (β) ranging between 12% and 18%. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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Classification of petroleum origin and integrity by FTIR by FJ. Guzmán-Osorio, VI. Domínguez-Rodríguez, RH. Adams, CE. Lobato-García, A. Guerrero-Peña, JR. Barajas-Hernández

“…The canonic functions derived from the discriminate analysis had correlation coefficients of 0.994, 0.900, and 0.867, among the variables studied and the classification factor. …”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

“…This study investigates the operational efficiency of the lab-scale oxidation ditch (OD) functioning in simultaneous nitrification and denitrification modes, focusing on forecasting biochemical oxygen demand (BOD₅) concentrations over a five-day horizon. …”
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Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

“…This study addresses these challenges by introducing a new optimal bankruptcy rule (OpPro rule) through a simulation-optimization model (MODSIM-NSGAII), where MODSIM simulates the spatial and temporal variability of water resources, and the NSGA-II optimization algorithm includes two objective functions of maximizing basin-wide ecological sustainability and maximizing economic efficiency reflecting ''equitable and reasonable utilization'' of water. …”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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Adsorption of Cd (II) Using Chemically Modified Rice Husk: Characterization, Equilibrium, and Kinetic Studies by Javier Montalvo-Andía, Warren Reátegui-Romero, Alexis D. Peña-Contreras, Walter F. Zaldivar Alvarez, María E. King-Santos, Víctor Fernández-Guzmán, José Luis Guerrero-Guevara, Jhon E. Puris-Naupay

“…In optimal experimental conditions, the maximum adsorption efficiency was 92.65%. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) were used allowing the identification of the main functional groups and morphology of rice husk and treated rice husk, and the results showed an improvement of adsorption characteristics after rice husk treatment with NaOH. …”
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IrrigApp: An Online Tool for Determining Crop Water Use and Evaluating Irrigation Scheduling Options by José O. Payero

“…., county, crop, soil type, start date, end date, irrigation applications, and irrigation efficiency). IrrigApp calculates daily crop evapotranspiration (ETc) and conducts a daily soil water balance to estimate several daily and seasonal variables, such as ETc under dryland and irrigated conditions, soil water content in the crop root zone, and water losses by runoff and deep percolation. …”
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Optimizing Load Frequency Control of Multi-Area Power Renewable and Thermal Systems Using Advanced Proportional–Integral–Derivative Controllers and Catch Fish Algorithm by Saleh A. Alnefaie, Abdulaziz Alkuhayli, Abdullah M. Al-Shaalan

“…Additionally, by contrasting the performance of the PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers, the efficiency of the CFA is confirmed. Additionally, a sensitivity analysis that considers simultaneous modifications of the frequency bias coefficient (B) and speed regulation (R) within a range of ±25% validates the efficacy and dependability of the suggested CFA-tuned PI(1+DD). …”
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Optimum System Design Using Rough Interval Multi-Objective De Novo Programming by Iftikhar Hussein, Hegazy Zaher, Naglaa Ragaa Saeid, Hebaa Sayed Roshdy

“…This paper suggested a new approach for solving uncertainty of De novo programming problems (DNP) using a combination model consisting of a rough interval multi-objective programming (RIMOP) and DNP, where coefficients of decision variables of objective functions and constraints are rough intervals (RIC). …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…The DL model exhibited high accuracy in tissue quantification and TP53 status prediction, outperforming traditional methods in terms of precision and efficiency. DL-based approaches offer significant promise for enhancing biomarker testing and precision oncology by reducing intra- and inter-observer variability, but further validation is required to optimize their integration into real-world clinical workflows. …”
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Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart by Amanda Dos Santos Mendes, Tulio S. Almeida, Marcela A. G. Machado, Paloma Maria Silva Rocha Rizol

“…This work showed that intuitionistic fuzzy control charts are efficient at detecting special causes, and that the computer interface developed is capable of performing the proposed functions.…”
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On a Solution of a Third Kind Mixed Integro-Differential Equation with Singular Kernel Using Orthogonal Polynomial Method by Ahmad Alalyani, M. A. Abdou, M. Basseem

“…While when using the separation method, we are able to obtain FIE with time coefficients, and these functions are described as an integral operator in time. …”
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Vibration Analysis of Rotating Tapered Timoshenko Beams by a New Finite Element Model by Bulent Yardimoglu

“…A new finite element model is developed and subsequently used for transverse vibrations of tapered Timoshenko beams with rectangular cross-section. The displacement functions of the finite element are derived from the coupled displacement field (the polynomial coefficients of transverse displacement and cross-sectional rotation are coupled through consideration of the differential equations of equilibrium) approach by considering the tapering functions of breadth and depth of the beam. …”
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Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model. by Rui Meng, Kristofer E Bouchard

“…The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. …”
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Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

“…A multilevel model of fuzzy logical inference is constructed, representing the dependency between quality factors. Membership functions for linguistic variables are formed and their weight coefficients are determined using pairwise comparison matrices. …”
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Removal of chromium from synthetic wastewater by electrocoagulation and using natural coagulant (blend of hen eggshell powder with lime): optimization of response surface methodolo... by Werkne Sorsa Muleta, Firomsa Bidira Abdi, Endrias Adane Bekele

“…The central composite design of the response surface methodology was employed to estimate and optimize process variables, such as initial Cr concentration (225–475 mg/L), solution pH (5–9), and current density (0.35–045 A/m2), and treatment time (30–40 min) with an electrode distance (ED) of 0.5 and 1 cm, respectively. 99.90% and 99.74% of removal efficiencies were observed at initial Cr concentration of 456.11 mg/L, a solution pH of 5.45, with current density of 0.47 A/m2, and treatment time of 36.84 min. …”
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Vanadium remediation from polluted wastewater using a novel non-conventional adsorbent by Manar Banwan Hasan, Suha Anwer Ibrahim, Nisreen Mizher Rahmah, Thekra Atta Ibrahim, Alaa Hani Alminshid, Mohammed Nsaif Abbas

“…The obtained results indicated that the vanadium recovery efficiency reached 81 % and was in direct proportion to the pH, agitation speed, and contact time, and inversely with other variables, while adsorption capacity reaching 0.1 mg/g. …”
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