A POD-Based Reduced-Dimension Method for Solution Coefficient Vectors in the Crank–Nicolson Mixed Finite Element Method for the Fourth-Order Parabolic Equation by Xiaohui Chang, Hong Li

“…This research proposes a method for reducing the dimension of the coefficient vector for Crank–Nicolson mixed finite element (CNMFE) solutions to solve the fourth-order variable coefficient parabolic equation. …”
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Patterns of intra-cluster correlation coefficients in school-based cluster randomised controlled trials of interventions for improving social-emotional functioning outcomes in pupi... by Kitty Parker, Michael Nunns, ZhiMin Xiao, Tamsin Ford, Paul Stallard, Willem Kuyken, Nick Axford, Obioha C. Ukoumunne

“…Abstract Background The cluster randomised trial (CRT) design is increasingly used to evaluate the impact of school-based interventions for improving social-emotional functioning outcomes in pupils. Good knowledge is required on plausible values of the intra-cluster correlation coefficient (ICC) of the outcome to calculate the required sample size in such studies. …”
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Variability of Interpolation Errors and Mutual Enhancement of Different Interpolation Methods by Yunxia He, Mingliang Luo, Hui Yang, Leichao Bai, Zhongsheng Chen

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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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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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ON TECHNIQUE OF FUZZY EXPERT KNOWLEDGE REPRESENTATION by Lyudmila Victorovna Borisova, Valery Petrovich Dimitrov, Inna Nikolayevna Nurutdinova

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Modeling creep for a closed cylindrical shell under hydrostatic pressure by M. A. Magomedov, V. V. Kuznetsov, B. M. Yazyev, S. V. Litvinov

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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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DBEM solutions to modified Helmholtz problems for FGMs of space–time-dependent properties by Mohammad Ivan Azis

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On an Optimal Quadrature Formula for Classes of Functions Given by Modulus of Continuity by M. Sh. Shabozov

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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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On the Generalized $ \overline{\theta({\tt{t}})} $-Fibonacci sequences and its bifurcation analysis by Rajiniganth Pandurangan, Sabri T. M. Thabet, Imed Kedim, Miguel Vivas-Cortez

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An Analysis of Cotton Production Technology on the Harran Plain by Abdulbaki Bılgıc, Seyda Ipekcıoglu, Tamer Isgın

“…In this research, it was aimed to determine effects of three production factors; labor, capital, and land, on the current level of cotton output produced by a sample of local cotton farmers operating on the Harran Plain in Turkey and whether this relation may be used to assess the returns-to-scale parameter, also known as the function coefficient in the production economics literature. …”
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An Improvement of Least Squares Theory: Theory of Least p-Variances Approximation and p-Uncorrelated Functions by Mohammad Masjed-Jamei

“…In this direction, some new concepts, such as p-covariances with respect to a fixed variable, p-correlation coefficients with respect to a fixed variable, and p-uncorrelatedness with respect to a fixed variable, are defined in order to establish least p-variance approximations. …”
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Geographic gradients in a functional trait: variation of body size and size diversity in ground beetle Poecilus cupreus (Linnaeus, 1758) (Coleoptera, Carabidae) by Raisa A. Sukhodolskaya, Sergey L. Luzyanin, Teodora M. Teofilova, Vladimir Landgraf, Nadezhda L. Ukhova, Tamara A. Avtaeva, Kirill Yu. Maksimovich, Andrey D. Belosludcev, Roman P. Gorbunov

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Correlation and path analysis of interaction between snap beans yield and its components with crop management by N. Shaban

“…Results showed that fresh weight of pod/studied variant (+++0.99), fresh weight of one pod (+++0.77), fresh weight of pods/ plant (+++0.67), calcium content in bean pods (++0.57), pods number /plant (++0.51), pollen fertility (++0.44) had positive impact on yield. The partial function of the studied parameters on variability of bean yield is 98.9%. …”
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On a geometric approach to the estimation of interpolation projectors by Mikhail V. Nevskii, Alexey Y. Ukhalov

“…Here $\sigma S$ is the result of homothety of $S$ with respect to the center of gravity with coefficient $\sigma$. Let $d\geqslant n+1,$ $\varphi_1(x),\ldots,\varphi_d(x)$ be linearly independent monomials in $n$ variables, and $\varphi_1(x)\equiv 1,$ $\varphi_2(x)=x_1,\ \ldots, \varphi_{n+1}(x)=x_n.$ Put $\Pi:=$lin$(\varphi_1,\ldots,\varphi_d).$ The interpolation projector $P: C(\Omega)\to \Pi$ with a set of nodes $x^{(1)},\ldots, x^{(d)} \in \Omega$ is defined by equalities $Pf\left(x^{(j)}\right)=f\left(x^{(j)}\right).$ Denote by $\|P\|_{\Omega}$ the norm of $P$ as an operator from $C(\Omega)$ to $C(\Omega)$ . …”
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Evaluation of remote sensing soil moisture data products with a new approach to analyse footprint mismatch with in-situ measurements by Qiuxia Xie, Li Jia, Massimo Menenti, Qiting Chen, Jingxue Bi, Yonghui Chen, Chunmei Wang, Xinju Yu

“…SMAP L3.0, ASCAT V3.0, ESA/CCI V7.1 and GLDAS V2.2) are vital for applications in hydrology, climate variability, and agriculture. This study uses a new SSM evaluation approach by combining temporal evolution, Coefficient of Variation (CV), Cumulative Distribution Function (CDF), evaluation metrics, and Triple Collocation Analysis (TCA) to assess SSM accuracy and spatial–temporal variability, particularly the impact of footprint mismatch when comparing retrieved SSM with in-situ measurements. …”
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Experimental Characteristics of Mechanical Continuously Variable Transmission with Internal Force Functions by A. V. Yurkevich, A. V. Tereshin, V. A. Soldatkin

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Influence of Mismatch of Parameters of Quadrature Channels on the Work of the Adaptive Selection System for Moving Targets by S. I. Ziatdinov

“…An expression is obtained for the frequency transfer function of an adaptive passive noise suppression system with a variable cut-off zone relative to the average frequency of the spectrum of interference signals. …”
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