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

“…The fused dataset demonstrates significant improvements over the original MERRA-2 AOD, with an increase in the coefficient of determination (R²) by 0.1065 and a reduction in root mean square error (RMSE) by 0.0369. …”
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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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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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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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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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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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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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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. …”
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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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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. …”
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Optimal design for eigen-frequencies of a longitudinal bar using Pontryagin's maximum principle considering the influence of concentrated mass by Bui Hai Le, Tran Minh Thuy

“…By considering eigen frequencies as state variables, the analogy coefficient k in the necessary optimality condition is explicitly determined. …”
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Moral Development and Wisdom: The Mediating Role of Moral Intelligence and Emotional Intelligence by Heng Zheng, Jing Dong, Yang Lihua

“…Results: The results showed that the conceptual model of the study had an appropriate fit. Examining the coefficients of the effects of the research variables on each other, it seemed that moral development had a direct standardized effect coefficient of 0.53 on intelligence. …”
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The impact of energy poverty on the health capital of middle-aged and older adult residents in rural China by Cuiting Yu, Tianrun Li, Qin Wan

“…Endogeneity was addressed using instrumental variables and propensity score matching.ResultsThe findings indicate that energy poverty has a significant negative impact on health capital, with a regression coefficient of −0.221(p<0.01), lowering self-rated health levels. …”
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PENGARUH MUTASI TERHADAP SEMANGAT KERJA PEGAWAI NEGERI SIPIL PADA KANTOR PELAYANAN PAJAK PRATAMA KOTA PEMATANG SIANTAR by Arnimisari Juliana Ambarita, Hatta Ridho

“…The data processed by the correlation coefficient and the determinant Moment Product to see the great influence of the variable X against Y variable. …”
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A Novel Technique for Transmission of M-Ary Signal through Wireless Fading Channel Using Wavelet Denoising by Md. Zahangir Alam, Charles Chittaranjan Patra, Colin Patra, M. Abdus Sobhan

“…The result of the simulation study reveals that the BER performance can be increased using an appropriate control variable to force the mean of each detail coefficient to zero.…”
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Skin Lesion Image Segmentation Algorithm Based on MC-UNet by Guihua Yang, Bingxing Pan

“…On the ISIC2017 dataset, it achieves a Dice coefficient of 89.43%, an accuracy of 94.81%, and a sensitivity of 90.41%. …”
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Path integral for multiplicative noise: Generalized Fokker-Planck equation  and entropy production rate in stochastic processes with threshold by F. S. Abril-Bermúdez, C. J. Quimbay, J. E. Trinidad-Segovia, M. A. Sánchez-Granero

“…Then, using the Parisi-Sourlas method, we estimate the transition probability between states of a stochastic variable [X(t)] based on the cumulant-generating function (K_{η}) of the noise. …”
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