Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Spatial dependencies between large-scale brain networks. by Robert Leech, Gregory Scott, Robin Carhart-Harris, Federico Turkheimer, Simon D Taylor-Robinson, David J Sharp

“…Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. …”
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Stress Estimation Based on Stochastic Method for Strength Evaluation of Floating Wind Turbines by Byungmo Kim, Beomil Kim

“…Next, each time series was stochastically fitted to Weibull distribution function. The most probable maximum (MPM) von-Mises stresses were estimated according to the probability level corresponding to the design life of the platform on the fitted curves. …”
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Process engineering by Ahmed Mohamed Farid Shaaban, Azza Ibrahim Hafez, Mona Amin Abdel-Fatah, Nabil Mahmoud Abdel-Monem, Mohamed Hanafy Mahmoud

“…The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number. …”
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A Quasi-Convex RKPM for 3D Steady-State Thermomechanical Coupling Problems by Lin Zhang, D. M. Li, Cen-Ying Liao, Li-Rui Tian

“…A meshfree, second-order, quasi-convex reproducing kernel scheme is employed to approximate field variables for solving the linear Poisson equation and the elastic thermal stress equation in sequence. …”
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Psychophysiological and Performance Effects of Biofeedback and Neurofeedback Interventions in a Top 100 Female Chess Player by Juan Pedro Fuentes-García, Santos Villafaina

“…Specifically, the sensorimotor rhythm stimulation (12–15 Hz) can enhance cognitive functions such as selective attention and working memory. …”
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Unveiling Theranostics: Nanocomplex-Assisted Photodynamic Eradication of Aggressive Cancer Cells and Modulation of Tumor-Associated Macrophages by Butkute A, Kazlauske E, Mlynska A, Peciukaityte E, Karabanovas V, Rotomskis R, Steponkiene S

“…The nanocomplex accumulated efficiently and uniformly across all CRC cell lines, regardless of their aggressiveness or drug sensitivity. …”
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Reconstructing Equatorial Electron Flux Measurements From Low‐Earth‐Orbit: A Conjunction Based Framework by D. L. Stumbaugh, J. Bortnik, S. G. Claudepierre

“…For each conjunction, we fit the equatorial pitch angle distribution (PAD) parameterized by the function JD=C⋅sinNα. The resulting conjunction data set contains the POES electron flux measurements, L and magnetic local time coordinates, geomagnetic activity Auroral Electrojet index, and C and N coefficients from the PAD fit for each conjunction. …”
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RP-18 HPLC Analysis of Drugs’ Ability to Cross the Blood-Brain Barrier by Anna W. Sobańska, Adam Hekner, Elżbieta Brzezińska

“…On the other hand, discriminant function analyses involving log k and (log k)/PSA as discriminating variables separated the CNS+ and CNS− compounds with the success rate ca. 90%. …”
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Global dynamics and time-optimal control studies for additional food provided holling type-III mutually interfering prey-predator systems with applications to pest management by D. Bhanu Prakash, D. K. K. Vamsi

“…Abstract In this study, we derive and analyze an additional food provided prey-predator model with Holling type-III functional response, incorporating mutual interference among predators. …”
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Exploring Purpose-Driven Methods and a Multifaceted Approach in Dam Health Monitoring Data Utilization by Zhanchao Li, Ebrahim Yahya Khailah, Xingyang Liu, Jiaming Liang

“…Dam monitoring tracks environmental variables (water level, temperature) and structural responses (deformation, seepage, and stress) to assess safety and performance. …”
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Comparison of Numerical Results With Experiment Using Digital Image Correlation System of Multiobjective Structural Optimised Wind Turbine Blade by Ramazan Özkan, Mustafa Serdar Genç

“…ABSTRACT This paper presents a novel approach to the structural design of small‐scale turbine blades using the Artificial Bee Colony (ABC) Algorithm to optimise both mass and cost (objective functions), with a comparison to experimental results obtained using a Digital Image Correlation (DIC) system. …”
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Barriers in Proliferating Digital Technologies at Russian Companies: Causes and Effects by A. S. Melnikov, E. G. Kalabina

“…As a result a systematized picture of enterprise functioning was developed in the context of overcoming barriers in introducing digital technologies and identification of situational and contextual variables influencing the effect of their introduction. …”
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Parallel Primal-Dual Method with Linearization for Structured Convex Optimization by Xiayang Zhang, Weiye Tang, Jiayue Wang, Shiyu Zhang, Kangqun Zhang

“…This paper presents the Parallel Primal-Dual (PPD3) algorithm, an innovative approach to solving optimization problems characterized by the minimization of the sum of three convex functions, including a Lipschitz continuous term. The proposed algorithm operates in a parallel framework, simultaneously updating primal and dual variables, and offers potential computational advantages. …”
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The Brain Behind the Grid: A Comprehensive Review on Advanced Control Strategies for Smart Energy Management Systems by Gowthamraj Rajendran, Reiko Raute, Cedric Caruana

“…This paper presents a systematic review of key digital technologies—such as artificial intelligence, the Internet of Things, blockchain, and digital twins—employed in AES, providing a critical assessment of their individual functionalities, interdependencies, and collective contributions to the energy sector. …”
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VARX Granger analysis: Models for neuroscience, physiology, sociology and econometrics. by Lucas C Parra, Aimar Silvan, Maximilian Nentwich, Jens Madsen, Vera E Parra, Behtash Babadi

“…We also provide methods for enhancing model efficiency, such as L2 regularization for limited data and basis functions to cope with extended delays. …”
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Frequency Stability Analysis Based on Full State Model in Autonomous-Synchronization Voltage Source Interfaced Power System by Zhenyao LI, Deqiang GAN, Moude LUAN, Guoqing HE

“…Then, the parameters of the autonomous-synchronization voltage source model are compared with those of the synchronous machine model, and it is proved that the function of the governor is equivalent to increasing the system damping, which can reduce the steady-state error of the system frequency after being disturbed. …”
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Optimized Blade Design of Counter-Rotating-Type Pump-Turbine Unit Operating in Pump and Turbine Modes by Jin-Woo Kim, Jun-Won Suh, Young-Seok Choi, Kyoung-Yong Lee, Toshiaki Kanemoto, Jin-Hyuk Kim

“…The pump and turbine mode efficiencies of the unit were selected as the objective functions and they combined into a single specific objective function with the weighting factors. …”
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MAGNETOHYDRODYNAMICS NANOFERRO FLUID FLOWS PASSING THROUGH A MAGNETIC POROUS SPHERE UNDER THERMAL RADIATION EFFECT by Basuki Widodo, Eirene Juwita Ningtyas Pamela, Dieky Adzkiya, Chairul Imron, Tri Rahayuningsih

“…The dimensional mathematical model is further transformed into non-dimensional mathematical model by using non-dimensional variables. The non-dimensional mathematical model is simplified using the similarity equation by utilizing the stream function. …”
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Artificial Neural Network (ANN) Modeling of Plasma and Ultrasound-assisted Air Drying of Cumin Seeds by M. Namjoo, M. Moradi, M. A. Nematollahi, H. Golbakhshi

“…Therefore, the wavelet-based neural network (WNN), the multilayer perceptron neural network (MLPNN), and the radial-basis function neural network (RBFNN), as three well-known artificial neural networks models, were used to map the inputs and output data and the results were compared with the Multiple Quadratic Regression (MQR) analysis. …”
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