Simulating Land Use and Evaluating Spatial Patterns in Wuhan Under Multiple Climate Scenarios: An Integrated SD-PLUS-FD Modeling Approach by Hao Yuan, Xinyu Li, Meichen Ding, Guoqiang Shen, Mengyuan Xu

“…Wuhan is selected as the case study area, with simulations conducted under three IPCC-aligned climate scenarios—SSP1-2.6, SSP2-4.5, and SSP5-8.5—to project land use changes by 2030. The SD model demonstrates robust predictive performance, with an overall error of less than ±5%, while the PLUS model achieves high spatial accuracy (average Kappa >0.7996; average overall accuracy >0.8856). …”
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Impact of wildfires on spatial and temporal evolution of groundwater recharge in an Atlantic pine forest: An integrated approach using field, remote sensing and modeling. by Mariana La Pasta Cordeiro, João Pedro Nunes, Maria Teresa Condesso de Melo

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GEOGRAPHICALLY WEIGHTED MACHINE LEARNING MODEL FOR ADDRESSING SPATIAL HETEROGENEITY OF PUBLIC HEALTH DEVELOPMENT INDEX IN JAVA ISLAND by Muhammad Azis Suprayogi, Bagus Sartono, Khairil Anwar Notodiputro

“…Our results show that the non-parametric GW-RF model shows high potential for explaining spatial heterogeneity and predicting PHDI versus a global model when including six major risk factors. …”
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Spatial analysis of G.f.fuscipes abundance in Uganda using Poisson and Zero-Inflated Poisson regression models. by Albert Mugenyi, Dennis Muhanguzi, Guy Hendrickx, Gaëlle Nicolas, Charles Waiswa, Steve Torr, Susan Christina Welburn, Peter M Atkinson

“…We finally used the Zero-Inflated Poisson (ZIP) regression model to predict tsetse abundance due to its superiority over the standard Poisson after model fitting and testing using the Vuong Non-Nested statistic.…”
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Investigating the impacts of telecommuting on the spatial, temporal, and modal distribution of travel using an agent-based transport simulation model by Bijoy Saha, Mahmudur Rahman Fatmi, Nazmul Arefin Khan

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Highly Sensitive Photoacoustic Imaging: A New Strategy for Ultrahigh Spatial Resolution Seismic Physical Model Imaging by Xin Liu, Wen Wang, Qiangzhou Rong, Baozhi Yu

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Phase field modeling for fracture prediction in goat tibia using an open-source quantitative computer tomography based finite element framework by Debangshu Paul, Zachariah Arwood, Pierre-Yves Mulon, Dayakar Penumadu, Timothy Truster

“…While predicting mechanical responses under various stress scenarios is of significant interest in the field of orthopedic research, finite element (FE) modeling studies specifically focusing on the tibia remain notably limited. …”
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Statistical damage constitutive model of cemented sand and gravelbased on a modified spatially mobilized plane yield criterion by Jiangui Yang, Honglei Ren, Qiang Li, Shuling Cai

“…The physical significance of the WeibullWeibull distribution parameters m and F0 was examined, and the variation of these parameters with respect to gel content and confining pressure was analyzed and modified. Finally, the predicted results of the proposed model were compared with experimental values and those from other constitutive models. …”
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Optimizing Clinical Management of COVID-19: A Predictive Model for Unvaccinated Patients Admitted to ICU by Ahmed Farhan, Khouloud Ayed, Sara Zayati, Rym Akrout, Akram Dlala, Amal Abouda, Nesrine Zoghlami, Halima Mahjoubi, Iheb Labbane, Asma Gati

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Multiscale Spatio-Temporal Attention Network for Sea Surface Temperature Prediction by Zhenxiang Bai, Zhengya Sun, Bojie Fan, An-An Liu, Zhiqiang Wei, Bo Yin

“…Deep learning has shown preliminary success in modeling the dynamic spatial-temporal dependencies within SST signals, yet it remains challenging to obtain precise SSTs due to the inherent variabilities across multiple temporal and spatial scales, driven by distinct physical processes. …”
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Quantifying Root Cohesion Spatial Heterogeneity Using Remote Sensing for Improved Landslide Susceptibility Modeling: A Case Study of Caijiachuan Landslides by Zelang Miao, Yaopeng Xiong, Zhiwei Cheng, Bin Wu, Wei Wang, Zuwu Peng

“…This approach, integrated with land use-specific hydrological parameters and an infinite slope stability model, significantly improves landslide susceptibility predictions compared to models ignoring root cohesion or using uniform assignments. …”
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Monitoring and forecasting of land use/land cover (LULC) in Al-Hassa Oasis, Saudi Arabia based on the integration of the Cellular Automata (CA) and the Cellular Automata-Markov Mod... by Ashraf Abdelkarim

“…This study sought to integrate the Cellular Automata-Markov Model (CA-Markov) and the Cellular Automata (CA) using sensing data for land cover maps for the years: 1988, 2000, 2013 and 2020 to monitor, detect, and predict the spatial and temporal of Land Use/Land Cover (LULC) change in Al-Hassa Oasis, Saudi Arabia. …”
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Exploring efficiency and spatial equity trade-offs in docked bike-sharing by Yusfita Chrisnawati, Yusak O. Susilo

“…This study addresses limitations in bike-sharing planning by integrating a disaggregated demand model based on individual user behavior, generated through agent-based simulations, with a supply model derived from spatial analysis. …”
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Effect of Spatial Variations in Floodplain Vegetation on Bed Shear Stress Distribution by REN Chun-ping, YANG Fan, ZHANG Yuan-yuan, WANG Hong-fei

“…To account for the effects of vegetation, a vegetation module was incorporated into the hydrodynamic model. The model considered plant height, width, and density, with vegetation resistance simplified as bed roughness. …”
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COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

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Spectral Energy Density in an Axisymmetric Galaxy as Predicted by an Analytical Model for the Maxwell Field by Mayeul Arminjon

“…Finally, the first predictions of the model for the spatial variation of the SED in the Galaxy are compared with those of a radiation transfer model. …”
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Identifying leptospirosis hotspots in Selangor: uncovering climatic connections using remote sensing and developing a predictive model by Muhammad Akram Ab Kadir, Rosliza Abdul Manaf, Siti Aisah Mokhtar, Luthffi Idzhar Ismail

“…The feature importance score indicated river water level and rainfall contributes most to the model. Conclusions This GIS-based study identified a primarily sporadic occurrence of leptospirosis in Selangor with minimal spatial clustering. …”
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Electric Vehicle Charging Demand Prediction Model Based on Spatiotemporal Attention Mechanism by Yang Chen, Zeyang Tang, Yibo Cui, Wei Rao, Yiwen Li

“…The experimental results indicate that the proposed model has a more powerful comprehensive ability to capture spatiotemporal relationships and improve accuracy and stability in different prediction steps.…”
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Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity by Jiashan Li, Xinqi Gong

“…Methods This study leverages a pre-trained model with spatial awareness to enhance the prediction of protein-ligand binding affinity. …”
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ST-GAT Resident OD Prediction Model Based on Mobile Signaling Data by Xianguang Jia, Weijie Fang, Yingying Lyu, Jinke Zhang, Mengyi Guo, Dong Li, Jie Qu, Fengxiang Guo

“…In this paper, this model is compared with the existing ST-GCN, DMS, GMM, PSAM-CNN, ST-Transformer, and COMD models, and the experimental results show that the predicted values of the ST-GAT model have a significant improvement in the prediction accuracy compared to other models. …”
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