Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China by Xuepeng Zhang, Taixia Wu, Qiqi Du, Ninglei Ouyang, Wei Nie, Yang Liu, Peng Gou, Guangchao Li

“…Based on this idea, a new framework for assessing EH is proposed. The efficient machine learning model (light gradient boosting machine model) and the variable explanation model (SHapley Additive exPlanation model) are combined to quantify the functional relationships between various driving factors and EH, thereby exploring the impacts of climatic factors, socioeconomic development (SED), and ecological restoration projects (ERP) on EH. …”
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CGF with Bio-Oss collagen as grafting materials for simultaneous implant placement after osteotome sinus floor elevation: a prospective study by Bashar Shahood, Seba Harphoush, Belal O. M. Muhaisen, Jing Qiu

“…The Implants Survival Rate (ISR) was the primary outcome variable. Secondary outcome variables included radiographic measurements assessed at four follow-up time points, the Implant Stability Quotient (ISQ), and bone density (B). …”
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Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination by Ashagrie Sharew Iyassu, Ashagrie Sharew Iyassu, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Zelalem G. Dessie, Zelalem G. Dessie, Temesgen T. Zewotir

“…BackgroundImmunization is an efficient and cost-effective public health program. …”
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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. …”
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Impact of adopting improved Arabica varieties on the livelihood of organic coffee producers’ of Ethiopia: Continuous treatment approach by Negussie Zeray Gebru, Tasew Tadesse, Wajana Wae

“…The technique proved efficient in elucidating non-linear causal links between adoption intensities, dosages, and outcome variables. …”
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Elastostatic analysis of tapered FGM beams with spatially varying material properties by Justín Murín, Stephan Kugler, Juraj Paulech, Juraj Hrabovský, Vladimír Kutiš, Herbert Mang, Mehdi Aminbaghai

“…In this article an effective method for elastostatic analysis of tapered beams made of functionally-graded material (FGM) is presented. The spatially variable stiffness of the beam is the consequence of the continuous longitudinal variability of the cross-sectional dimension, accompanied by the variability of the material properties in three orthogonal directions. …”
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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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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. …”
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Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences by Alessandra Traini, Massimo Iorizzo, Harpartap Mann, James M. Bradeen, Domenico Carputo, Luigi Frusciante, Maria Luisa Chiusano

“…However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. …”
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Association between metabolic parameters and erection in erectile dysfunction patients with hyperuricemia by Guo-Wei Du, Pei-Ning Niu, Zhao-Xu Yang, Xing-Hao Zhang, Jin-Chen He, Tao Liu, Yan Xu, Jian-Huai Chen, Yun Chen

“…Fasting plasma glucose (β = −0.628, P < 0.001), uric acid (β = −0.552, P < 0.001), triglycerides (β = −0.088, P = 0.047), low-density lipoprotein cholesterol (β = −0.164, P = 0.027), glycated hemoglobin (HbA1c; β = −0.562, P = 0.012), and smoking history (β = −0.074, P = 0.037) exhibited significant negative impacts on erectile function. The coefficient of determination (R²) for the model was 0.239, and the adjusted R² was 0.230, indicating overall statistical significance (F-statistic = 26.52, P < 0.001). …”
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Modelagem da produtividade e gestão da qualidade acadêmica by Annibal Parracho Sant'Anna

“…It is a hierarchical model because technical coefficients of the academic production function are modeled as function of second level explanatory variables in such a way that such production function is allowed to change coherently from one department to another. …”
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Bivariate Epanechnikov-exponential distribution: statistical properties, reliability measures, and applications to computer science data by H. M. Barakat, M. A. Alawady, I. A. Husseiny, M. Nagy, A. H. Mansi, M. O. Mohamed

“…The statistical properties of the EP-EX-FGM model are examined, including product moments, coefficient of correlation between the internal variables, moment generating function, conditional distribution, concomitants of order statistics (OSs), mean residual life function, and vitality function. …”
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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…SDKU-Net integrates dynamic kernel adjustment, a combined loss function incorporating Focal and Tversky Loss, and optimizer switching to effectively tackle class imbalance and improve segmentation quality. …”
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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. …”
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Variations in Creatinine Generation Among Patients With Glomerular Disease: Evidence From the NEPTUNE and CureGN Studies by Shalini S. Ramachandra, Melody Chiang, Michael Arbit, Dorey A. Glenn, Laura H. Mariani, Jarcy Zee

“…Analytical Approach: The intraclass correlation coefficient illustrated crG variability within individuals. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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