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  1. 81

    Multivariate Spatial Autoregressive Model with Latent Variables: Application to Economic Growth Modeling by Anik Anekawati, Purhadi, Mohammad Rofik

    Published 2025-10-01
    “…Research involving causal relationships among latent variables that generally use structural equation modeling (SEM) analysis and spatial data simultaneously has an unavoidable impact on using spatial SEM analysis. …”
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    Article
  2. 82
  3. 83

    Stochastic Characteristics and Optimal Control for a Stochastic Chemostat Model with Variable Yield by Rong Yan, Shulin Sun

    Published 2020-01-01
    “…In this paper, a stochastic chemostat model with variable yield and Contois growth function is investigated. …”
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    Article
  4. 84

    Blood pressure variability combined with coagulation function in early prediction and outcome assessment of germinal matrix-intraventricular hemorrhage in preterm infants with gest... by Lijun Jiang, Qian Yu, Hui Li, Fudong Wang, Feng Liu, Zhenxing Xu

    Published 2025-01-01
    “…<h4>Objective</h4>To determine the association between blood pressure variability (BPV), coagulation indexes, and germinal matrix-intraventricular hemorrhage (GMH-IVH) in preterm infants with gestational age ≤ 32 weeks. …”
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  5. 85

    Interannual variability in thermal state of the upper mixed layer in the Bering Sea in winter by V. A. Luchin

    Published 2023-10-01
    “…Series of annual mean fields of the mixed layer temperature in December-March were decomposed by applying the empirical orthogonal function (EOF); dynamics of the first two components of decomposition (described in sum 50.4 % of the initial fields variability) are analyzed. …”
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  6. 86

    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

    Published 2010-03-01
    “…<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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    Article
  7. 87

    Sparsity‐optimised farrow structure variable fractional delay filter for wideband array by Wenjing Zhou, Mingwei Shen, Min Xu, Guodong Han, Yudong Zhang

    Published 2023-06-01
    “…The established cost function is formulated as a parametric minimisation problem with multiple regularisation constraints, and solved by the modified three‐block alternating direction multiplier method (MTB‐ADMM), which is improved by introducing core variable correction items to ensure stable and fast convergence. …”
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  8. 88
  9. 89

    Blood Pressure Variability and Severity of Early Prognosis in Patients with Acute Pontine Infarction by Xinsheng Han, Gaocai Zhang, Ning Liu, Hongyang Zhang, Jianke Xu, Miao Han, Yun Zhang, Yan Zhang, Li Chen

    Published 2020-01-01
    “…Increased blood pressure (BP) variability may worsen the prognosis of stroke. This study aimed at investigating the association between BP variability and early functional prognosis in patients with pontine infarction. …”
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  10. 90

    Seismic Response of Variable Section Column with a Change in Its Boundary Conditions by Alexandre de Macêdo Wahrhaftig, Moshe Eisenberger, Castro Baptista Elias, Luiz Antônio Malheiros Filho

    Published 2025-04-01
    “…As research recommendations, analysis of columns with variable cross-sections and different shapes, different distributed loadings, applying the rotational spring for both ends and over the shape functions, and analysis of buildings by an equivalent system are suggested. …”
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    Article
  11. 91

    The nursing process and total health cost variability: an analysis using machine learning by Maria Consuelo Company-Sancho, Victor M. González-Chordá, Maria Isabel Orts-Cortés

    Published 2025-07-01
    “…Methods Analytical and retrospective observational study of a population of 1,691,075 people over the age of 15. The explanatory variables were age, sex and nursing process data, with total healthcare cost as the outcome variable. …”
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  12. 92

    Evaluation of Spatio-Temporal Gait Variability during Obstacle Crossing in Parkinson\'s Disease by Elaheh Azadian, Mahdi Majlesi, Ali Fatahi, Rezvan Bakhtiyarian

    Published 2023-12-01
    “…The difference between the two groups was significant in the variability coefficient of variables such as double support time, single support time, stride time, step length, and percentage of opposite foot contact with the ground. …”
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  13. 93

    Geospatial analysis of soil property variability in cyclone-affected areas of southern Malawi by Jabulani Nyengere, Innocent Gomani, Isaac Tchuwa, Wilfred Kadewa, Agnes Mercy Hamisi, Chikondi Chisenga, Emmanuel Chinkaka, Weston Mwase, Precious Masuku, Harineck Tholo

    Published 2025-06-01
    “…The soil properties exhibited significant variability, as demonstrated by the coefficients of variation, with available phosphorus (P) showing the highest variability at 156.9%, followed by exchangeable potassium (K +) at 139.6% and electrical conductivity (EC) at 95.3%. …”
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  14. 94

    Correlation between intradialytic blood pressure variability and cognitive impairment in patients on maintenance hemodialysis by Jingfang Wan, Jun Liu, Jing Pan, Lili Fu, Dandan He, Yaru Yao, Yani He, Kehong Chen

    Published 2025-02-01
    “…The intradialytic SBP was converted to the following 4 candidate short-term BPV indices: standard deviation (SD), coefficient of variation (CV), average real variability (ARV), RANGE. …”
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  15. 95

    Characteristics stochastic analysis of long and narrow deep excavations under soil spatial variability by Shouhua Liu, Zhaoliang Wang, Yadong Chen, Guohua Fang, Yiding Zhao, Junsheng Yang, Huasheng Sun

    Published 2025-03-01
    “…As the coefficient of soil spatial variability increases, the diversity and chaotic characteristics of ground surface settlements become more prominent. …”
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  16. 96

    RESEARCH CONCAVE CIRCULAR HOLE TEMPLATE LINEAR VARIABLE THICKNESS STIFFNESS AND STRENGTH THEORIES by LI ShaoJie

    Published 2015-01-01
    “…This paper studies linear variable thickness circular aperture concave template theory of stiffness and strength calculation.First,set up mechanical model:Template for circular concave,outside the perimeter fixed; center has a round hole,inside the perimeter free,outside under uniformly distributed vertical load.Secondly,the establishment of mathematical model:Derivation of concave template in the axisymmetric condition,ordinary differential equation with variable coefficients of elastic curved surface,and gives the mathematical expressions of boundary conditions.Again,in view of the differential equation boundary value problem,the displacement method and the Matlab algorithm,it is concluded that the deflection of concave template function,and establish the stiffness calculation condition of concave template.Then,determine the concave template on the bending moment and the maximum bending moment and stress,so as to establish a concave template strength calculation conditions.Finally,numerical examples.This paper presents the function solutions,to change law of control concave template section variable parameters.In this way,not only highlight the interdependent relationship between the quantity of each,and optimization,and discussion and application.The result is suitable for uniform,continuous,isotropic material artifacts.Because in the process of calculation and data processing with error,so the formula is similar.…”
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  17. 97

    MODELING OF SHIP MOVEMENT IN SHALLOW WATER ACCORDING TO A SPECIFIC TRAJECTORY AT VARIABLE DEPTH by Z. M. Abdullaeva

    Published 2017-12-01
    “…Mathematical models of ship movement in shallow water at variable navigation depths, which differ from the existing ones, are developed: the coefficients of variable hydrodynamic equations are not constant values, but variables obtained by approximating the shallow water impact curves onto hydrodynamic coefficients in the form of third-order polynomials.Conclusions. …”
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