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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Fokker-Planck Central Moment Lattice Boltzmann Method for Effective Simulations of Fluid Dynamics by William Schupbach, Kannan Premnath

“…This can be interpreted as a new path for the collision process in terms of the relaxation of the various central moments to “equilibria”, which we term as the Markovian central moment attractors that depend on the products of the adjacent lower order moments and a diffusion coefficient tensor, thereby involving of a chain of attractors; effectively, the latter are nonlinear functions of not only the hydrodynamic variables, but also the non-conserved moments; the relaxation rates are based on scaling the drift coefficient by the order of the moment involved. …”
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Effect of Pre-Trip Information in a Traffic Network with Stochastic Travel Conditions: Role of Risk Attitude by Yun Yu, Shiteng Zheng, Yuankai Li, Huaqing Liu, Jianan Cao

“…User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi></mrow></semantics></math></inline-formula>. …”
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Technical Efficiency of Sweet Potato Production: A Stochastic Frontier Analysis by Godfrey C. Onuwa, Solomon T. Folorunsho, Ganiyu Binuyo, Mercy Emefiene, Onyekwere P. Ifenkwe

“…Data collected was analyzed using descriptive statistics and stochastic frontier production function. The socioeconomic variables of the respondents affected their farm efficiency and level of farm output. …”
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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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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

“…Firstly, we design a loss function that deliveries the physical relationship among temperature, salinity and density by fusing the Thermodynamic Equation. …”
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Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study by Fatih Dolu, Oğuzhan Fatih Ay, Aydın Hakan Kupeli, Enes Karademir, Muhammed Huseyin Büyükavcı

“…However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. …”
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Distinctive Gait Variations and Neuroimaging Correlates in Alzheimer's Disease and Cerebral Small Vessel Disease by Xia Zhou, Wen‐Wen Yin, Chao‐Juan Huang, Si‐Lu Sun, Zhi‐Wei Li, Ming‐Xu Li, Meng‐Meng Ren, Ya‐Ting Tang, Jia‐Bin Yin, Wen‐Hui Zheng, Chao Zhang, Yu Song, Ke Wan, Yue Sun, Xiao‐Qun Zhu, Zhong‐Wu Sun

“…Gait metrics included the timed up and go (TUG) test, dual‐task TUG (DTUG) test, Berg balance scale (BBS), dual‐task cost (DTC), step length, gait speed, cadence and coefficient of variation of gait. The relationships among structural and perfusion variations, gait metrics and cognitive function were examined. …”
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Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor by Jun Yang, Xian-yu Wu, Zhen-guo Wang

“…The fuel equivalence ratio for each injection port was taken as the design variables. And the combustion efficiency, the total pressure recovery coefficient, and the drag coefficient were chosen as the objective functions. …”
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From Nasion to Sellion: repositioning landmarks for radioprotection-tailored 3D cephalometric analysis by Marco Serafin, Benedetta Baldini, Elisa Boccalari, Salvatore Bocchieri, Sergio Sambataro, Chiarella Sforza, Giuseppe Baselli, Gianluca Martino Tartaglia, Alberto Caprioglio

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Developing CGMap: Characterizing Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes by Shuzhen Bai, Chu Lin, Xiaoling Cai, Suiyuan Hu, Jing Wu, Ling Chen, Wenjia Yang, Linong Ji

“…However, glucose variability decreased with increased BMI. Meanwhile, greater glycemic variability was associated with worse islet function, higher baseline glucose level, and higher hemoglobin.…”
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Approximate analytical solution of a class of highly nonlinear time–fractional-order partial differential equations by Richard Olu Awonusika

“…The method assumes a fractional power series in the time variable whose expansion coefficients are functions of the space variable. …”
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Long-term conservation tillage breaks the plough pan and promotes the development of preferential flow by Jinze Han, Jianye Li, Qiang Chen, Xingyi Zhang

“…Macropores and preferential flow critically regulate soil hydrological functions and ecosystem services in agricultural systems. …”
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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. …”
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Strong Amplitude Modulation of Hard-band X-Ray Quasiperiodic Oscillation with Soft-band Flux in RE J1034+396 by Ruisong Xia, Hao Liu, Yongquan Xue

“…They are highly correlated, with an average cross-correlation function (CCF) peak coefficient of 0.61 and a lag of approximately 3 ks. …”
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Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder by Muzher Saleem, Ghada A. Khouqeer, Fazal Haq, Naglaa AbdelAll, Arshad Hussain, Mohammed Sallah

“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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Machine learning-based prediction of pervaporation permeation using physicochemical properties of permeant-membrane and process conditions by Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, Ali Elkamel

“…Two types of inputs were evaluated: regular variables (Type I) and dimensionless groups derived from these regular variables (Type II). …”
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Faktor-Faktor yang Mempengaruhi Auditor Switching dengan Financial Distress sebagai Pemoderasi by Herninda Pitaloka, Agung Guritno

“…The analysis included descriptive statistical tests, model feasibility tests, classification matrix tests, the formation of logistic regression functions, partial parameter significance tests, simultaneous parameter significance tests, coefficients of determination tests and MRA tests. …”
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Non-Iterative Estimation of Multiscale Geographically and Temporally Weighted Regression Model by Ya-Di Dai, Hui-Guo Zhang

“…The Multiscale Geographically and Temporally Weighted Regression model overcomes the limitation of estimating spatiotemporal variation characteristics of regression coefficients for different variables under a single scale, making it a powerful tool for exploring the spatiotemporal scale characteristics of regression relationships. …”
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