INVARIANTS OF GENERALIZED RAPOPORT-LEAS EQUATIONS by E. N. Kushner

“…For the generalized Rapoport-Leas equations, algebra of differential invariants is constructed with respect to point transformations, that is, transformations of independent and dependent variables. The finding of a general transformation of this type reduces to solving an extremely complicated functional equation. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…However, most of them take no consideration of natural physical laws that may cause issues of physical inconsistency among different variables. In this paper, we proposed PGTransNet, a novel physics-guided transformer network for 3D Ocean temperature and salinity forecasting. …”
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Spatial Analysis of the Relationship between Ecological Factors and Housing Prices in Tehran by Atefeh Kolyaei, Tahir Prizadi, Habibollah Fasihi

“…Among the independent variables, the average annual temperature, distance from river valleys, distance from fault lines, and green coverage showed the highest correlation coefficients; however, these relationships were negative, indicating an inverse correlation. …”
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Presenting a model of political behavior based on the theory of shadow management in the public sector with a hybrid method by Ghorbanali Khazaei Pool, davood kiakojouri, Mohammad Javad Tghipourian

“…Components related to power and political behavior based on shadow management theory were identified and validated with the kappa coefficient. Based on the research findings, political behavior in the public sector has 72 components in three different dimensions: the white political behavior dimension with 28 components that has a practical function and is based on political behavior knowledge and helps achieve organizational goals; the black political behavior dimension with 26 components that are harmful and act in favor of groups under the supervision of shadow managers and prevent the achievement of the organization's goals; and the gray political behavior with 18 components that may be both beneficial and detrimental to the organization's goals. …”
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Evaluating the Effectiveness of Quality Control Measures in Project Management: A Study of Construction Companies in Lusaka by Mwanza Jacob, Chimbomba Kelvin

“…A solid positive relationship appeared between how well technology supports quality control and general quality control practices (Pearson coefficient = 0.893). Quality control measures improve the efficiency of construction projects, but they should be further improved as many projects still get delayed as a result of quality issues. …”
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Model Evaluasi Usability Menggunakan Confirmatory Factor Analysis pada KRS Online by Endah Ratna Arumi, Pristi Sukmasetya, Agus Setiawan

“…Results of usability measurement found that the highest value on the variable "Memory" with an average value of 4.19, and the lowest value on "Error" with an average value of 2.9 within 5 scale. …”
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Algorithm for Dynamic Reactive Power Optimization of Regional Power Grid Based on Interior Point Method and Neighborhood Search Decoupling Dynamic Programming Method by Jie ZHANG, Hengfeng WANG, Shengchun LIU, Huabiao WANG, Canghai WANG, Yao RAN, Xianmin WANG, Yongfei MA, Wei YAN

“…The two-stage method could not only ensure the quality of the optimal solution, but also avoid solving the state combination explosion problem with discrete variables, which greatly improves the computational efficiency. …”
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Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

“…Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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Cross-sectional associations between physical activity and sedentary time with cardiovascular health in children from the ALSPAC study using compositional data analysis by K. M. Sansum, B. Bond, R. M. Pulsford, A. McManus, A. O. Agbaje, A. M. Skinner, A. R. Barker

“…Multiple linear regression analyses were adjusted for key covariates with LPA, MVPA and ST entered as compositional exposure variables. Neither LPA, MVPA or ST were significantly associated with the vascular outcomes. …”
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Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…In recent years, the use of machine learning techniques (ML) has become widespread for analysing the effects of operational factors on anaerobic digestion efficiency. Among these, Support Vector Regression (SVR) with a Radial Basis Function (RBF) kernel has been used to predict biogas yield based on diverse operating parameters. …”
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Mild Cognitive Impairment and Cardiometabolic Risk Factors in Bosnian and Herzegovinian Patients with Heart Failure by Jasna Ibrahimović-Pašić, Orhan Lepara, Amela Dervišević, Nermina Babić, Nesina Avdagić, Amina Valjevac, Asija Začiragić

“…Associations between categorical variables and correlation coefficients were assessed by the Chi-square and Spearman test, respectively. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…Dehui City in Jilin Province, China, was selected as the case study area, where multidimensional data including vegetation indices, ecological function parameters, and environmental variables were collected, covering seven key growth stages of rice. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…To overcome these challenges, this study employs the deep learning model TabNet, incorporating Digital Elevation Model (DEM) data and ERA5 meteorological variables, to fuse MERRA-2 AOD with MODIS MAIAC AOD observations. …”
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Decoding the role of serum cholinesterase among type 2 diabetes mellitus patients at RIMS, Ranchi – A hospital-based study by Avijit Saha, Abha Kumari, Santosh Kumar, Abhay Kumar, Chandrakanta Munni

“…This condition is characterized by variable levels of insulin resistance, impaired insulin secretion, and elevated glucose production. …”
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Serum Interleukin-6, Interleukin-17A, and transforming growth factor beta are raised in systemic sclerosis with interstitial lung disease by Anupam Wakhlu, Rasmi Ranjan Sahoo, Jyoti Ranjan Parida, Mohit K Rai, Durga P Misra, Vinita Agrawal, Vikas Agarwal

“…Serum IL-6, IL-17A and TGF β1 levels were assayed using ELISA kit and compared among disease subtypes and clinical parameters. Spearman coefficient was used to test correlation between continuous variables. …”
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The Relationship between Calcium-phosphorus Metabolism Disorder and Cognitive Impairment in Maintenance Hemodialysis Patients by Geng Ming-hui, Li Yu-yan, Tao Mi, Liao Wen-wen, He Yi-qing, Gao Ping

“…Correlations between MoCA scores and calcium and phosphorus metabolic variables were analyzed by Spearman's method. Logistic regression was utilized for examining the influencing factors of the occurrence of MHD-MCI. …”
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Safety Assessment of Loop Closing in Active Distribution Networks Based on Probabilistic Power Flow by Wenchao Cai, Yuan Gao, Xiping Zhang, Qin Si, Jiaoxin Jia, Bingzhen Li

“…By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. …”
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Study on a Quantitative Evaluation Method of Goaf Instability Risk of Phosphate Deposits in Layered Rock Mass by Dongfang CHEN, Mengke WANG, Dingping XU, Haiwang YE, Qizhou WANG, Jian LIU, Bin XIANG

“…The Hermite random polynomial coefficients between the input field of c and <italic>ϕ</italic>_j and the output field of the FAI are solved by the probability collocation method, establishing an explicit function expression between the probability collocation point and the FAI. …”
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Multiple mechanisms contribute to leakiness of a frameshift mutation in canine cone-rod dystrophy. by Keiko Miyadera, Ian Brierley, Jesús Aguirre-Hernández, Cathryn S Mellersh, David R Sargan

“…This is rapid and blinding in a colony of dogs in which the mutation was characterised but in dogs with the same mutation in the pet population there is very variable disease severity and rate of progression.<h4>Objective</h4>We hypothesized that this variability must be associated with leakiness of the RPGRIP1 mutation, allowing continued RPGRIP1 production. …”
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Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka by Amila T. Peiris, Jeevani Jayasinghe, Upaka Rathnayake

“…This paper develops artificial neural network (ANN) models to forecast wind power generation in “Pawan Danawi”, a functioning wind farm in Sri Lanka. Wind speed, wind direction, and ambient temperature of the area were used as the independent variable matrices of the developed ANN models, while the generated wind power was used as the dependent variable. …”
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