Analysis of Mechanical and Thermal Material Characteristics of GPL-Reinforced Double-FG Composite Nanoplates under Temperature Load by Kerim Gökhan Aktaş

“…The analysis is conducted to evaluate the influence of variables like temperature rise, GPLs weight ratio and GPLs distribution patterns on the thermal and mechanical properties of the nanoplate such as effective modulus of elasticity, Poisson's ratio, coefficient of thermal expansion and coefficient of thermal conductivity. …”
Get full text

An Investigation on Health Literacy and Its Impact on Health-Promoting Behaviors among the Residents of Mashhad by Mohammad Hasan Sharbatiyan

“…The beta regression findings indicate that the functional, relational, critical, and fundamental components significantly influence the dependent variable, with a percentage correlation value of 69% respectively. …”
Get full text

Mechanical Impedance Control in the Human Arm While Manually Transporting an Open-Top Fluid Filled Dish by Navit Roth, Rami Seliktar, Joseph Mizrahi

“…The function used for damping included first-order dependence on angular velocity. …”
Get full text

Modeling Overall Survival in Patients With Pancreatic Cancer From a Pooled Analysis of Phase II Trials by Eva Rahman Kabir, Faruque Azam, Tanisha Tabassum Sayka Khan, Hasina Yasmin, Namara Mariam Chowdhury, Syeda Maliha Ahmed, Baejid Hossain Sagar, Nasrin Ahmed Tahrim

“…The relationship between predictors and OS was explored by a gamma generalized linear model (GLM) with a log‐link function and compared with linear models. Results The Spearman rank correlation coefficient between PFS/TTP and OS was 0.88 (95% confidence interval [CI] 0.85–0.89; p < 0.0001; n = 610) and between ORR and OS was 0.58 (0.52–0.64; p < 0.0001; n = 514). …”
Get full text

Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

“…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
Get full text

Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
Get full text

Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases by Adel M. Hemeida, Mohammed S. Al-Blehed, Saad El-Din Desouky

“…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. …”
Get full text

Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor by Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, Gustavo Scaglia

“…The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. …”
Get full text

Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
Get full text

Flow-based cytometric analysis of cell cycle via simulated cell populations. by M Rowan Brown, Huw D Summers, Paul Rees, Paul J Smith, Sally C Chappell, Rachel J Errington

“…We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. …”
Get full text

Parametric Survival Models of Hemodialysis Patients in Relation with Patient-Related Factors by Reem Yousif MEKKI, Mohamed Hassan MUDAWI, Manahil Saidahmed MUSTAFA, Altaiyb Omer Ahmed MOHMMED, Ahmed Bakheet Abd ALLA, Abdel Rahman AHMED

“…Based on the Cox-Snell Residuals and AIC, BIC, and Gompertz (PH) model is an efficient model than other when the values of (AIC=662.21), (BIC=703.83) and (R2=0.211) where maintained Study assessed that the variables dealing with univariate models were signifi cant but had a signifi cant effect on hemodialysis survival. …”
Get full text

A theory and data-driven method for rapid bottom hole pressure calculation in UGS by Yang Li, Haiwei Guo, Xianfeng Gong, Naixin Lu, Kairui Zhang

“…To enhance the operational and maintenance efficiency of UGS, this paper innovatively proposes a new method for calculating bottom hole pressure. …”
Get full text

A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
Get full text

A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM by Sorin IONITESCU

“…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
Get full text

Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Confusion matrix analysis further confirmed RF as the optimal model, achieving 0.875 accuracy and robust inter-rater agreement (Cohen's kappa coefficient = 0.696) in the testing cohort. SHAP analysis identified the adenoid-to-nasopharyngeal ratio as the predominant diagnostic indicator, followed by tympanometric type and history of recurrent respiratory infections.ConclusionAn RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.…”
Get full text

Study on the Photosynthetic Physiological Responses of Greenhouse Young Chinese Cabbage (<i>Brassica rapa</i> L. <i>Chinensis Group</i>) Affected by Particulate Matter Based on Hyp... by Lijuan Kong, Siyao Gao, Jianlei Qiao, Lina Zhou, Shuang Liu, Yue Yu, Haiye Yu

“…Particulate matter affects both the light environment and air quality in greenhouses, obstructing normal gas exchange and hindering efficient physiological activities such as photosynthesis. …”
Get full text

Extreme combination of wind effects and analysis of wind load characteristics for low-rise buildings by Haiwei Guan, Yuji Tian, Yuliang Qi, Weihu Chen

“…Based on transcendental probability theory, the probability density functions of two non-Gaussian scalar sums of wind effects are derived from the relationship between the probability density of the sum of random variables and the joint probability density function of sub-random variables by Hermite polynomial transformation. …”
Get full text

Mathematical solutions for coupled nonlinear equations based on bioconvection in MHD Casson nanofluid flow by Khalil Ur Rehman, Nosheen Fatima, Wasfi Shatanawi, Nabeela Kousar

“…We established an artificial neural network (ANN) model, incorporating Tan-Sig and Purelin transfer functions, to enhance the accuracy of predicting skin friction coefficient (SFC) values along the surface. …”
Get full text

Improved basal drag of the West Antarctic Ice Sheet from L-curve analysis of inverse models utilizing subglacial hydrology simulations by L.-S. Höyns, L.-S. Höyns, L.-S. Höyns, T. Kleiner, A. Rademacher, M. Rückamp, M. Wolovick, M. Wolovick, A. Humbert, A. Humbert

“…Since we cannot directly measure basal properties on a large scale, inverse models can be used to infer the basal drag coefficient by minimizing a cost function that depends on a velocity misfit and a regularization term.…”
Get full text

FUNGSI GREEN UNTUK PERSAMAAN DIFUSI-ADVEKSI DENGAN SYARAT BATAS DIRICHLET by Josua Josua, Evi Noviani, Fransiskus Fran

“…Mathematically, diffusion-advection equation can be written as  where  is concentration of material in the fluid, stands for the advection velocity, and  for diffusion coefficient. In this paper, a solution  is sought by using the Green’s function concept. …”
Get full text