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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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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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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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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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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Trajectory Planning Based on Screw Theory with Consideration of the Optimal Berth Position for a Space Robot by Yong Wang, Ying Liao, Kejie Gong

“…First, the berth position is transformed into the desired position of the end-effector, and its constraints are described. Joint variables are parameterized using a sinusoidal function combined with a five-order polynomial function. …”
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Analysis the Impact of Covid-19 on Green Accounting and Its Implications on Profitability by Reschiwati Reschiwati, Fran Sayekti, Tasia Veronica

“…The next difference is that the Performance and Environmental Disclosure variables function as both Y variables and X variables (intervening). …”
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Sensory profiles in older adults with orthopedic conditions during quiet stance: a cross-sectional study by Marine Brika, France Mourey, Alexandre Kubicki

“…Methods Fifty-one older adults (76.9 ± 7.6 years) were divided into 2 Functional Groups (FG-/FG+) according to a composite score that included 3 variables (gait speed, grip strength and fear of falling). …”
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Underactuated Spatial Mechanism of Vehicle Door Latch with Force Constraint by Sulong Li, Lubin Hang, Mingyuan Wang, Xiaojie Huang

“…Aiming at less space occupation，efficient driving and high-end multi-function of the door latch release branch chain，the type synthesis of single loop spatial mechanism is carried out，and the RRRSR mechanism which could realize power release is obtained. …”
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Kernel Density Estimation for Joint Scrambling in Sensitive Surveys by Alvan Caleb Arulandu, Sat Gupta

“…Randomized response models aim to protect respondent privacy when sampling sensitive variables but consequently compromise estimator efficiency. …”
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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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Sparse Learning of the Disease Severity Score for High-Dimensional Data by Ivan Stojkovic, Zoran Obradovic

“…This problem is solved by addressing a dual formulation which is smooth and allows an efficient optimization. The proposed approach might be used as an effective and reliable tool for both scoring function learning and biomarker discovery, as demonstrated by identifying a stable set of genes related to influenza symptoms’ severity, which are enriched in immune-related processes.…”
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Tomato quality based on colorimetric characteristics of digital images by Thaísa B. Bello, Anderson G. Costa, Thainara R. da Silva, Juliana L. Paes, Marcus V. M. de Oliveira

“…The correlation between colorimetric and physico-chemical variables was analyzed using the Pearson’s coefficient. …”
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Fast Möbius transform: An algebraic approach to information decomposition by Abel Jansma, Pedro A. M. Mediano, Fernando E. Rosas

“…Our approach is based on a formula for estimating the Möbius function that circumvents important computational bottlenecks and can in some cases offer a double-exponential speedup. …”
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Estimation of Stochastic Frontier Models with Fixed Effects through Monte Carlo Maximum Likelihood by Grigorios Emvalomatis, Spiro E. Stefanou, Alfons Oude Lansink

“…This paper proposes a procedure for choosing appropriate densities for integrating the incidental parameters from the likelihood function in a general context. The densities are based on priors that are updated using information from the data and are robust to possible correlation of the group-specific constant terms with the explanatory variables. …”
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Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data. by Neda Aminnejad, Michelle Greiver, Huaxiong Huang

“…This research focuses on developing a predictive model to classify diabetic patients showing signs of kidney function impairment based on their CKD development risk. …”
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Jacobian-Free Newton Krylov Methods for Steady and Transient Neutron Transport Models by ZHANG Yangyi, ZHANG Tiancheng, ZHOU Xiafeng

“…To further improve computational efficiency of comeSn_JFNK, in the JFNK solution, neutron scalar fluxes instead of neutron angular fluxes were chosen as the global solution variables. …”

Jointed rock slope stability evaluation based on PEM-JFEM method by XIAO Shu, WU Shun-chuan, GAO Yong-tao, HAN Guang, ZHOU Yu, CHENG Ai-ping

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