Variáveis climáticas e o desempenho de um pivô central, em Cristalina Goiás Climatic variables and performance of center pivot at Cristalina, Goiás, Brazil by William Evangelista, Carlos A. S. Oliveira, Cícero L. Silva

“…<br>This research aimed to evaluate center pivot performance as a function of wind speed (VV), relative humidity of air (UR) and mean air temperature (T) and establish a stochastic model to estimate application efficiency as a function of these independent variables. …”
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Full linearization of nonlinear flow control valves via variable gear ratio design by Thitipun Thongnueakhaeng, Tawat De Haas, Thananchai Leephakpreeda

“…Abstract The paper proposes the full linearization of nonlinear characteristics of flow control valves via variable gear ratio design. The inherent nonlinear function of the normalized valve capacity coefficients to the percentages of valve opening is derived from flow experiments. …”
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Variable convergence train noise active control algorithm based on feedforward reference by LI Tao, HE Yuyao, WANG Ning, LI Zhuang, SHEN Zhaoyuan, XIAO Gang

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Long-Term Teleconnections Between Global Circulation Patterns and Interannual Variability of Surface Air Temperature over Kingdom of Saudi Arabia by Abdullkarim K. Almaashi, Hosny M. Hasanean, Abdulhaleem H. Labban

“…The empirical orthogonal function (EOF) method is employed for analyzing SAT due to its effectiveness in extracting dominant patterns of variability during the winter (DJF) and summer (JJA) seasons. …”
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Variable power functional dilution adjustment of spot urine by Thomas Clemens Carmine

“…This study introduces a novel variable power functional creatinine correction method (V-PFCRC) to normalize analytes to 1 g/L CRN by utilizing uncorrected analyte levels and two analyte-specific coefficients, c and d. …”
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On empirical Bayes estimation of multivariate regression coefficient by R. J. Karunamuni, L. Wei

“…We investigate the empirical Bayes estimation problem of multivariate regression coefficients under squared error loss function. In particular, we consider the regression model Y=Xβ+ε, where Y is an m-vector of observations, X is a known m×k matrix, β is an unknown k-vector, and ε is an m-vector of unobservable random variables. …”
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Arbitrary Random Variables and Wiman’s Inequality by Andriy Kuryliak, Oleh Skaskiv, Andriy Bandura

“…We study the class of random entire functions given by power series, in which the coefficients are formed as the product of an arbitrary sequence of complex numbers and two sequences of random variables. …”
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Interpolation of the Function of Two Variables with Large Gradients in the Boundary Layers by A.I. Zadorin

“…The problem of interpolation for the function of two variables with large gradients in the boundary layers is investigated. …”
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Analysis and assessment of the validity dough "theory of functions of the complex variable" by Lidiya A. Muratova

“…In article the analysis of quality of the "Theory of Functions of a Complex Variable" test is carried out. …”
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A radial variable for de Sitter two-point functions by Manuel Loparco, Jiaxin Qiao, Zimo Sun

“…We show that the two-point function of a free massive scalar in the Bunch-Davies vacuum has an exponentially convergent series expansion in this variable with positive coefficients only. …”
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Reliability Analysis in Presence of Random Variables and Fuzzy Variables by Cui Lijie, Lü Zhenzhou, Li Guijie

“…Furthermore, a technique based on the probability density function evolution method is employed to improve the computational efficiency of the proposed indices. …”
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Magnetic Deflection Coefficient Investigation for Low Energy Particles by Baghdad Science Journal

“…The results showed had been tabulated and graphically represented as functions of their variables. These results a satisfactory agreement between experimental values and theoretical data given in the literature showed.…”
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Investigating fluctuation varieties in the propagation of the perturbed KdV equation with time-dependent perturbation coefficient by Marwan Alquran

“…By assigning various functional forms such as periodic, polynomial, and decaying exponential, to the proposed time-dependent coefficient, novel solitary wave patterns of types like-breather, regular(singular)-bell shaped, and periodic solutions are emerged with fluctuations. …”
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Research on Energy-Efficient Building Design Using Target Function Optimization and Genetic Neural Networks by Youxiang Huan

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Thrust-efficiency limits of a swimming tail with variable chordwise flexural rigidity by Hossam Alqaleiby, Muhammad R. Hajj

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An Ultrafast Image Simulation Technique with Spatially Variable Point-spread Functions by Zeyu Bai, Peng Jia, Jiameng Lv, Xiang Zhang, Wennan Xiang, Lin Nie

“…During real observations, images obtained by optical telescopes are affected by spatially variable point-spread functions (PSFs), a crucial effect requiring accurate simulation. …”
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Impact of CYP3A4 functional variability on ziprasidone metabolism by Qi Zhou, Qi Zhou, Yameng Wu, Zhize Ye, Zheyan Zhang, Kai Zheng, Jianchang Qian, Zhongxiang Xiao, Yang Lu

“…This study explored the functional variability of CYP3A4 in ziprasidone metabolism, focusing on drug interactions and genetic polymorphisms.MethodsThe metabolic inhibition and kinetic properties of ziprasidone were evaluated through in vitro experiments utilizing rat liver microsomes (RLM), human liver microsomes (HLM), and CYP3A4 baculosomes. …”
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Kriging-Based Variable Screening Method for Aircraft Optimization Problems with Expensive Functions by Yadong Wang, Xinyao Duan, Jiang Wang, Jin Guo, Minglei Han

“…Applying the variables screening technique can enhance the efficiency of the airfoil optimization process under acceptable accuracy.…”
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Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson’s Disease Mobility Assessments by Rana M. Khalil, Lisa M. Shulman, Ann L. Gruber-Baldini, Sunita Shakya, Jeffrey M. Hausdorff, Rainer von Coelln, Michael P. Cummings

“…Although the total duration remains relatively consistent between trials (intraclass correlation coefficient (ICC) = 0.62 to 0.95), greater variability is seen in subtask duration and sensor-derived measures, reflected in machine learning performance and statistical differences. …”
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EVALUATION OF SUBSOIL MASSIF STABILITY TAKING INTO ACCOUNT THE IRREGULARITY OF CONSTITUENT ROCKS ON THE BASIS OF A RANDOM SIZE AND FUNCTION MODEL by M. O. Allaev

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