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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Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

“…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
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Research on optimization strategies of university ideological and political parenting models under the empowerment of digital intelligence by Fan Lv

“…It constructs the no-incentive, cost-sharing, and collaborative cooperation models, respectively, and obtains the optimal trajectories for the degree of effort, the subsidy coefficient, the optimal benefit function, and the digital and intelligent technology stock. …”
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Assessment of Intrarenal Artery Doppler Resistive Index in Normotensive Patients and Patients with Essential Hypertension by Obinna E. Abonyi, Uloma B. Nwogu, Vitus K. Ika, Julius A. Agbo, Beatrice U. Maduka, Sharonrose O. Nwadike

“…The renal resistive index (RRI) is a useful tool for assessing kidney function in hypertensive patients, but population-specific data are scarce. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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