THE STRUCTURE OF HAPPINESS REPRESENTATION FOR RUSSIAN AND AMERICAN REPRESENTATIVES by S. Yu. Zhdanova, A. V. Pecherkina, A. A. Strokanov

“…Statistical analysis of the data was based on the use of the coefficient of φ-angular Fisher transform, correlation coefficient φ, and cluster analysis.Results and scientific novelty. …”
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EM Algorithm in the Modified Slash Power Maxwell Distribution with an Application by Francisco A. Segovia, Yolanda M. Gómez, Héctor J. Gómez, Inmaculada Barranco-Chamorro, Héctor W. Gómez

“…We study its probability density function and some properties, such as moments, asymmetry and kurtosis coefficient. …”
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Adaptive Fractional-Order Nonsingular Fast Terminal Sliding Mode Control for Manipulators by Xin Zhang, Ran Shi

“…Secondly, in view of the problems of large chattering and slow convergence speed in the reaching stage, this paper designs a variable exponential power-reaching law (VEPRL), which has the ability to change the exponential coefficients according to the system state adaptively. …”
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Global path planning algorithm for mining vehicles integrating simplified visibility graph and A* algorithm by ZHANG Chuanwei, LU Siyan, QIN Peilin, ZHOU Rui, ZHAO Ruiqi, YANG Jiajia, ZHANG Tianle, ZHAO Cong

“…To address the low path planning efficiency of mining vehicles in narrow, winding underground tunnels with unknown obstacles, a global path planning algorithm, DVGA*, was proposed, integrating simplified visibility graphs (SVG) and the A* algorithm. …”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…The mean squared error is assumed as the loss function which stipulates several restrictions: deviatoric character of internal variables, compliance with the flow rule, the differentiation of elastic and plastic steps and the associativity of the flow rule. …”
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Generating Electricity with Hydraulically Amplified Self-Healing Electrostatic (HASEL) Transducers by Isabel Hess, Stephen Chamot, Blake Boren, Patrick Musgrave

“…This study identifies hydraulically amplified self-healing electrostatic (HASEL) transducers as electricity generators, contrary to their conventional role as actuators. HASELs are soft, variable-capacitance transducers inspired by biological muscles which were developed to mimic the flexibility and functionality of natural muscle tissues. …”
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Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

“…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
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The Fuzzy Response Surface Reliability Analysis Method of Turbine Blades by PAN Cheng-yi, WEI Wen-long, ZHANG Chun-yi

“…The analysis result shows that the blade reliability indexes decrease with the increase of fuzzy coefficient. Compared with the traditional method based on random variables, this method is more reasonable for the description of uncertainty, and the evaluation of reliability is more accurate theoretically.…”
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Which Metrics Can I Monitor? Test-Retest Reliability of Countermovement Jump and Countermovement Rebound Jump Force-Time Metrics in Youth Soccer Players In-Season by Andrew Badby, Paul Comfort, Nicholas Ripley, Matthew Cuthbert, Francisco Robles-Palazón, Peter Mundy, John McMahon

“…Objective measures provide the most effective means of monitoring the magnitude and time course of changes in neuromuscular function (NMF) resulting from physical activity if measurements are repeatable (reliability). …”
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A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study. by Patrizio Barca, Fabio Paolicchi, Giacomo Aringhieri, Federica Palmas, Daniela Marfisi, Maria Evelina Fantacci, Davide Caramella, Marco Giannelli

“…CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. …”
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Sensitivity analysis of melting heat transfer in Williamson fluid by Aliya Batool, Zakir Hussain, Dilawar Hussain

“…The model is simplified to ordinary differential equations by introducing similarity variables and tackled by bvp4c Matlab function. The significant variables on flow model are identified by Response Surface Method (RSM). …”
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A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

“…The study employed the batch collection of training samples utilizing experience replay and a double-network mechanism, along with the preprocessing of neural network state inputs, and the investigation into feasible regions within the action space using a variable ε-greedy strategy. A loss function based on the value function was then constructed, and network parameters were updated iteratively by a batch gradient descent method. …”
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Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller by Monika Gupta, P. M. Tiwari, R. K. Viral, Ashish Shrivastava, Basem Abu Zneid, Iryna Hunko

“…Conventional controllers such as P and PI are widely used in PV applications due to their simplicity, but they exhibit notable limitations in dynamic environments, including increased Total Harmonic Distortion (THD), slower transient response, and poor voltage regulation—particularly under variable irradiance conditions. The proposed GWO-PID method overcomes these limitations by leveraging the GWO algorithm’s global search capability to dynamically optimize the PID gains (Kp, Ki, Kd) based on a composite fitness function that minimizes Mean Squared Error (MSE) and THD. …”
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Mitigating Load Imbalance and Enhancing Distribution Transformer Performance via Fuzzy Inference System by Althoff Hibban, Azriyenni Azhari Zakri, Dirman Hanafi, Boy Ihsan, Umair Ali

“…To address this issue, this study proposes a fuzzy logic-based approach using a Mamdani-type Fuzzy Inference System (FIS). The input variables, current magnitudes in phases R, S, and T, are represented by trapezoidal membership functions classified into several categories. …”
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A Brief Political Economy of Energy Subsidies in the Middle East and North Africa by Laura El-Katiri, Bassam Fattouh

“…While it is clear that energy subsidy reform will not be the only variable at play, its potential socio-economic dividends are important factors for enabling some common regional objectives—sustainable fiscal policies, fiscal space to invest in key areas, and a more efficient and equitable distribution of scarce resources—to be achieved, helping to promote a more stable political status quo in the long term. …”
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Optimizing switching sequences in AC-AC converters for enhanced safety and performance in conveyor systems by Velmurugan Dhandapani, Gopinath Balasubramanian

“…Industrial systems require optimized control to maintain efficiency under variable loads. Fault conditions influence power stability and overall system functionality. …”
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Classification of Biological Data using Deep Learning Technique by Azha Javed, Muhammad Javed Iqbal

“…Previous work failed to properly address issues related to the classification of biological sequences i.e. protein including efficient encoding of variable length biological sequence data and implementation of deep learning based neural network models to enhance the performance of classification/ recognition systems. …”
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Haemodynamics-driven developmental pruning of brain vasculature in zebrafish. by Qi Chen, Luan Jiang, Chun Li, Dan Hu, Ji-wen Bu, David Cai, Jiu-lin Du

“…The brain blood vasculature consists of a highly ramified vessel network that is tailored to meet its physiological functions. How the brain vasculature is formed has long been fascinating biologists. …”
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Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics by Gabriel Katul, Andrew Bragg, Ivan Mammarella, Heping Liu, Qi Li, Elie Bou‐Zeid

“…As the coefficient of variation CVe in ϵ increases, αo must be adjusted by a multiplier 1+CVe2−3/32 that was derived from a log‐normal model for the probability density function of ϵ. …”
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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…However, naive implementation of the Volterra polynomial model usually introduces significant complexity due to the large number of model coefficients. Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. …”
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