Passive Heat Stimuli as a Systemic Training in Elite Endurance Athletes: A New Strategy to Promote Greater Metabolic Flexibility by Sergi Cinca-Morros, Martin Burtscher, Fernando Benito-Lopez, Jesús Álvarez-Herms

“…<b>Objectives:</b> The ability to efficiently regulate body temperature is crucial during endurance activities such as trail running, especially during competitive events in hot conditions. …”
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Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm by S. Sharifi, N. Hafezi, M. H. Aghkhani

“…In the first step, energy consumption and production were calculated by multiplying the variables by their corresponding coefficients. In the second step, all the variables that maximize paddy yield were entered into MATLAB software. …”
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Lattice Boltzmann Method for the Generalized Black-Scholes Equation by Fangfang Wu, Duoduo Xu, Ming Tian, Yingying Wang

“…The proposed lattice Boltzmann model can also be applied to a class of partial differential equations with variable coefficients and source terms.…”
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Multi-objective design optimization of a transonic axial fan stage using sparse active subspaces by Richard Amankwa Adjei, Chengwei Fan

“…Active subspace was used to compute the active variables via singular value decomposition and a hybrid polynomial correlated function expansion was used to construct a surrogate model on the active subspace. …”
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Zoning and Identification of Factors Affecting Illegal Livestock Grazing in Golestan National Park Using Logistic Regression by Meysam Madadi, HamidReza Rezaei, Alireza Mohammadi, Bagher Nezami Balochi, Maryam Shahbazi

“…The Aspect factor with a coefficient of 0.0015 was determined to be the least influential independent variable. …”
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Predictive model of small choroidal melanoma progression after eye-saving treatment based on clinical, morphometric and immunological parameters by E. B. Myakoshina, I. G. Kulikova, N. V. Balatskaya, L. A. Katargina, S. V. Saakyan

“…A formula was calculated where P (z) is the value of the logistic function; Z, linear combination of symptoms; bo , intercept (free term), bi – regression coefficients for parameters Zi.P (z) = 1 : 1 + e – b0– b1z1– b2z2– b3z3– b4z4The logistic function increases monotonically and takes the values from 0 to 1 for any b and Z values [P∈ (0;1)]. …”
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Numerical and Experimental Study of a Hydrodynamic Analysis of the Periodical Fluctuation of Bio-Inspired Banded Fins by Chonglei Wang, Qihang Liu, Junhao Yang, Chunyu Guo

“…By using a method of controlling variables, such as wave number, swing angle, and frequency, where only one independent variable is changed at a time while the others remain constant, the impact on thrust coefficient function and the obtained periodic variation laws governing hydrodynamic performance are studied. …”
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Relación entre comunidad íctica y cobertura vegetal riparia en dos períodos hidrológicos (Eje Cafetero, Colombia) by María Angélica Pérez-Mayorga, Saúl Prada-Pedreros

“…Therewere no significant differences (P>0.05) among the structural variables, the HYPE and the RVC. According to r and r2 the diet of most fish species did not vary as a function of RVC and HYPE; however, according to the CCA diet varies as a function of HYPE but not of RVC. …”
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INVESTIGATION OF UV/TiO2-ZnO-Co PHOTOCATALITIC DEGRADATION OF AZO DYE (REACTIVE RED 120) BY RESPONSE SURFACE METHODOLOGY by MOHSEN MANSOURI, MARJAN TANZIFI, HOSSEIN LOTFI, MOHSEN NADEMI

“…Results were in agreement with empirical values and the sensitivity analysis showed above parameters as the most efficient variables in decolorization efficiency. Analysis of variance (ANOVA) revealed highly determination coefficient value (R2 = 0.9996 and adjusted-R2 = 0.999) and satisfactory prediction second-order regression model. …”
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Online identification of stability region for large-scale wind farms, Part I: Clustering based piecewise affine impedance modeling by Jia Luo, Peng Wang, Haoran Zhao, Chenxinwei Yuan, Tiancheng Liu, Vladimir Terzija

“…In each partition, the impedance is expressed as a first-order explicit function of the complex variable and the operating state variables. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Attributes of Internal Audit and Prevention, Detection and Assessment of Fraud in Pakistan by Naveed Khan, Abdul Rafay, Amer Shakeel

“… With it being considered as a value-added activity, the Internal Audit function (IAF) of a firm is one of the most important functions in an organization. …”
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APPLICATION OF HYBRID RANDOM SEARCH METHOD TO OPTIMISATION OF ENGINEERING SYSTEMS’ PARAMETERS by A. V. Panteleev, D. A. Rodionova

“…These problems belong to the class of constrained global optimization problems, where the level surface of the objective function has uneven relief and there is a large number of variables. …”
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Transfer Robustness Optimization for Urban Rail Transit Timetables by Liqiao Ning, Peng Zhao, Wenkai Xu, Ke Qiao

“…Next, to improve the computational efficiency, we propose an approximate linearization approach for the EETC function and introduce two types of binary variables and auxiliary substitution variables to convert the nonlinear model to a mixed-integer linear model. …”
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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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Respiratory Muscle Strength as a Predictor of VO2max and Aerobic Endurance in Competitive Athletes by Gökhan Deliceoğlu, Banu Kabak, Veli O. Çakır, Halil İbrahim Ceylan, Muntean Raul-Ioan, Dan Iulian Alexe, Valentina Stefanica

“…A total of 41 athletes, drawn from the disciplines of biathlon, judo, and cross-country, participated in this study. Respiratory function tests (RFTs) were administered to assess various respiratory parameters, including changes in chest circumference. …”
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Stability and Optimal Control Analysis for a Fractional-Order Industrial Virus-Propagation Model Based on SCADA System by Luping Huang, Dapeng Gao, Shiqiang Feng, Jindong Li

“…As is known to all, there is no unified method to establish a Lyapunov function. In this paper, by constructing an appropriate Lyapunov function and applying the method of undetermined coefficients, we prove the global asymptotic stability for all possible equilibrium points. …”
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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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A design-based framework for optimal stratification using super-population models with application on real data set of breast cancer. by Faizan Danish

“…This study investigates the determination of stratification points for two study variables within the framework of simple random sampling, with a focus on estimating the population mean using a closely related auxiliary variable. …”
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