Ecological Zoning Based on Suitability Evaluation of Ecological Product Development from the Value-Risk-Cost-Demand Perspective by Ming Gao, Pei Du, Xinxin Zhou, Zhenxia Liu, Wen Luo, Zhaoyuan Yu, Linwang Yuan

“…The findings suggest that the integrated assessment model proposed in this study has produced more reasonable outcomes in terms of spatial layout, land use area, reduction of fragmentation and ecological risk. …”
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Geospatial digital mapping of soil organic carbon using machine learning and geostatistical methods in different land uses by Yahya Parvizi, Shahrokh Fatehi

“…This study was conducted to evaluate potential of different simulation models to map the spatial variability of SOC as affected by land use in a study area in Qarasu watershed in Kermanshah province, west of Iran. …”
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A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems. by Bogdan Petre, Philip Kragel, Lauren Y Atlas, Stephan Geuter, Marieke Jepma, Leonie Koban, Anjali Krishnan, Marina Lopez-Sola, Elizabeth A Reynolds Losin, Mathieu Roy, Choong-Wan Woo, Tor D Wager

“…In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. …”
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Scale-dependent effects of tree species diversity on soil erosion resistance by Huaqing Liu, Xiaodong Gao, Xining Zhao

“…However, the understanding of the effects of tree species diversity on soil erodibility across spatial scales remains incomplete. This study employed the Universal Soil Loss Equation model to quantify soil erodibility and aligned it with tree species diversity data obtained from the Global Forest Biodiversity Initiative database. …”
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Influence of geometry heterogeneity on Liesegang patterns in rocks by Chong Liu, Klaus Regenauer-Lieb, Manman Hu

“…We demonstrate that the spatial distribution of reactive fluids and the shape of nucleation zones play critical roles in determining the final pattern morphology. …”
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Construction and Analysis of Slope Plane Deformation of High CFRD Based on Statistical Analysis of Multi‐Points Monitoring Data by Xiongxiong Zhou, Wenjun Cai, Qiujiang He, Jing Zhou, Bingqian Zhou

“…Based on the actual monitoring data of the Hongjiadu CFRD, this paper comprehensively analyzes the influence of the filling process, water level change, and time effect on the settlement of the CFRD during the construction and impoundment periods, and establishes the settlement statistical model of all monitoring points. By studying the relationship between the parameters of the settlement statistical model of each monitoring point and its own position coordinates, a spatial–temporal distribution model of the dam slope plane is established by using the thin plate spline interpolation method, and it is used to predict the settlement of the dam slope plane. …”
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CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA by Atiek Iriany, Wigbertus Ngabu, Danang Arianto, Arditama Putra

“…Geographically Weighted Regression Kriging (GWRK) is a special case of Geographically Weighted Regression (GWR) model, which is modeling with the effect of spatial autocorrelation on the GWR model error. …”
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MySTOCKS: Multi-Modal Yield eSTimation System of in-prOmotion Commercial Key-ProductS by Cettina Giaconia, Aziz Chamas

“…Unlike traditional approaches, MySTOCKS leverages an advanced deep learning framework that incorporates transformer models with self-attention mechanisms and domain adaptation capabilities, enabling accurate temporal and spatial modeling tailored to the dynamic requirements of the agrifood supply chain. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

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Spatiotemporal evolution and multi-scenario simulation of the land-use cover change and habitat quality in arid and semi-arid areas: a case study of the urban agglomeration along t... by Tianle Ma, Wenhao Cheng, Wenxuan Yao

“…Habitat quality (HQ) is recognized as a significant factor in biodiversity maintenance and ecological conservation advancement, and the land-use cover change (LUCC) can directly affect the spatial pattern and evolution of HQ. Land-use datasets spanning 2010, 2015, and 2020 were analyzed through the integrated application of the future land-use simulation (FLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model, supplemented by multiple analytical indicators, resulting in LUCC patterns and HQ variations being investigated within the urban agglomeration along the Yellow River in Ningxia, China. …”
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Urban pertussis epidemiological patterns in a highly vaccinated megacity: Policy impacts and control strategies in Chongqing, China, 2005-2024 by Rui Shen, Jiawei Xu, Yugang Li, Jianxing Yu, Na Sun, Zilu Xu, Xueying Xu, Xiao Liu, Yang Liu, Bosong Li, Li Qi, Luzhao Feng

“…Methods: Using population-based surveillance data (2005-2024) from Chongqing (population 32.1 million; DTP3 coverage >97%), we conducted hierarchical Bayesian spatial modeling and age-structured Susceptible-Infected-Recovered-Vaccinated transmission analysis. …”
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Remote sensing techniques to assess badlands dynamics: insights from a systematic review by Rosa Colacicco, Marco La Salandra, Isabella Lapietra, Alberto Refice, Domenico Capolongo

“…Satellite imagery is a leading tool due to its extensive spatial and temporal coverage, enhancing land-use change monitoring and erosion modeling capabilities. …”
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A Coordinated Allocation Method for Right-Turn Strategy at Signalized Intersections with Optimal Pedestrian and Vehicle Delays by Yu Bai, Wanyan Luo

“…With strict enforcement of pedestrian right of way at all intersections, the inappropriate right-turn resource allocation from a spatial and temporal perspective will lead to a reduction in the operational efficiency of the intersection. …”
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Artificial intelligence-powered precision: Unveiling the tumor microenvironment for a new frontier in personalized cancer therapy by Songwei Feng, Xia Yin, Yang Shen

“…Artificial intelligence (AI) provides unparalleled capabilities to analyze and decipher the complexities of the TME through multi-omics integration, spatial modeling, and predictive analytics. By combining computational innovations with clinical insights, AI is driving a new paradigm in precision medicine. …”
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Computational hybrid analysis of drug diffusion in three-dimensional domain with the aid of mass transfer and machine learning techniques by Mohammed Alqarni, Ali Alqarni

“…In this work, we developed a novel hybrid model based on mass transfer and machine learning for predicting drug diffusion in a 3D space. …”
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Asthma prevalence and risk factors in Poonch and Rajouri districts, India: an epidemiological and geospatial analysis by Arshad Ahmed, Kheraj, Jorge Rocha, Alireza Mohammadi

“…The model exhibited strong fit (Nagelkerke R2 = 0.82) and high predictive accuracy (ROC-AUC = 0.98). …”
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Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements by Liansheng Deng, Yugang Xiao, Qusen Chen, Wei Peng, Zhao Li, Hua Chen, Zhiwen Wu

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Specific island biogeographic and landscape features shape plant diversity and habitat specialism on edaphic quartz islands in an arid ocean by Pia Maria Eibes, Ute Schmiedel, Jens Oldeland, Severin David Howard Irl

“…Including measures of landscape features, (e.g. matrix contrast) improved the predictive power of several models. However, distance-based isolation measures had little explanatory value in relation to the observed variance. …”
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Distribution and Habitat Suitability of the Malabar Slender Loris (<i>Loris lydekkerianus malabaricus</i>) in the Aralam Wildlife Sanctuary, India by Smitha D. Gnanaolivu, Joseph J. Erinjery, Marco Campera, Mewa Singh

“…Projections for 2070 under RCP 2.6, 4.5, and 8.5 scenarios predict habitat reductions of 52%, 13%, and 8%, respectively, signaling significant vulnerability under changing climatic conditions. …”
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Advancing smart communities with a deep learning framework for sustainable resource management. by Yongyan Zhao

“…The models outperformed baseline methods, with LSTMs achieving an MAE of 1.8 for water demand prediction and autoencoders detecting anomalies with an F1-score of 95.5%.…”
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