Modeling consequences of spatial closures for offshore energy: Loss of fishing grounds and fishery‐independent data by M. Campbell, J. F. Samhouri, J. W. White

“…This produced two effects in the model: initial loss of fishery yield due to the closure and reductions in fishing effort when the loss of data triggered precautionary measures in the harvest control rule. …”
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Underutilized crops for diversified agri-food systems: spatial modeling and farmer adoption of buckwheat in Italy by Marta Verza, Luca Camanzi, Luca Mulazzani, Antonio Giampaolo, Santiago Rodriguez, Giulio Malorgio, Konstadinos Mattas

“…It evaluates how factors such as financial incentives, peer influence, and farmers’ willingness to adopt affect the diffusion of this underutilized crop. To this end, a spatial agent-based model (ABM) is employed to simulate farmers’ decision-making processes based on profit maximization and peer influence. …”
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The educational system of Yakutia: overcoming the challenges by V. M. Savvinov

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STVMamba: precipitation nowcasting with spatiotemporal prediction model by Maoyang Zou, Longrui Wen, Yuanyuan Huang, Yuan He, Jingzhong Xiao

“…The Spatial-Temporal Vision Mamba (STVMamba) is proposed, a novel spatiotemporal prediction model specifically designed for precipitation nowcasting. …”
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Integrating Higher Education Strategies into Urban Cluster Development: Spatial Agglomeration Analysis of China’s Key Regions by Yangguang Hu, Chuang Yang, Junfeng Ma

“…Using dynamic panel regression and spatial econometric models, the results show that HEA yields significant local and spatial spillover benefits, particularly in core cities that facilitate knowledge diffusion and resource sharing. …”
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A multimodal model for protein function prediction by Yu Mao, WenHui Xu, Yue Shun, LongXin Chai, Lei Xue, Yong Yang, Mei Li

“…Protein structure provides richer spatial and functional insights, which can significantly improve prediction accuracy. …”
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Six-Dimensional Spatial Dimension Chain Modeling via Transfer Matrix Method with Coupled Form Error Distributions by Lu Liu, Xin Jin, Huan Guo, Chaojiang Li

“…The experimental validation on an aero-engine casing assembly shows that the SDC model captures multidimensional closed-loop spatial errors, with absolute errors of max–min closed-loop distances below 9.3 μm and coaxiality prediction errors under 8.3%. …”
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Synergistic Evolution and Spatial-Temporal Differences in Green Technological Innovation and Carbon Emission Reduction in the Construction Industry from the Perspective of New Prod... by Zihao Niu, Qingjie Xie

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Gradual Variation-Based Dual-Stream Deep Learning for Spatial Feature Enhancement With Dimensionality Reduction in Early Alzheimer’s Disease Detection by Najmul Hassan, Abu Saleh Musa Miah, Taro Suzuki, Jungpil Shin

“…These features are processed through a dual-stream DL model, where each stream captures complementary spatial features. …”
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Building the optimal hybrid spatial Data-Driven Model: Balancing accuracy and complexity by Emanuele Barca, Maria Clementina Caputo, Rita Masciale

“…Based on these findings, we have developed a methodology that employs a series of statistical tests and data analytics to identify essential features hidden in spatial data in order to assess the predictive model (of white/grey kind) that best approximates underlying spatial processes. …”
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Drivers of Future Indian Ocean Warming and Its Spatial Pattern in CMIP Models by S. Gopika, K. Sadhvi, J. Vialard, V. Danielli, S. Neetu, M. Lengaigne

“…Abstract Coupled Model Intercomparison Project phases 5 and 6 (CMIP5/6) projections display substantial inter‐model diversity in the future tropical Indian Ocean warming magnitude and spatial pattern. …”
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Optimal Harvesting for an Age-Spatial-Structured Population Dynamic Model with External Mortality by Yong Han Kang, Mi Jin Lee, Il Hyo Jung

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Spatial Modeling of Trace Element Concentrations in PM₁₀ Using Generalized Additive Models (GAMs) by Mariacarmela Cusano, Alessandra Gaeta, Raffaele Morelli, Giorgio Cattani, Silvia Canepari, Lorenzo Massimi, Gianluca Leone

“…A stepwise procedure was followed to determine the model with the optimal set of covariates. A leave-one-out cross-validation method was used to estimate the prediction error. …”
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Spatial distribution model of anoa, Bubalus spp., in Tanjung Peropa Wildlife Reserve by Ola Aso, Abdul Mustari, Lilik Prasetyo

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Temporal and spatial pattern analysis and forecasting of methane: Satellite image processing by Fatima Elshukri, Noor Hussam Abusirriya, Nathan Joseph Braganza, Abdulkarem Amhamed, Odi Fawwaz Alrebei

“…Atmospheric dispersion modeling is a critical tool in environmental research, offering insights into spatial and temporal patterns of pollutants. …”
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Reduced temporal and spatial stability of neural activity patterns predict cognitive control deficits in children with ADHD by Zhiyao Gao, Katherine Duberg, Stacie L. Warren, Li Zheng, Stephen P. Hinshaw, Vinod Menon, Weidong Cai

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Spatial characterization of tertiary lymphoid structures as predictive biomarkers for immune checkpoint blockade in head and neck squamous cell carcinoma by Daniel A. Ruiz-Torres, Michael E. Bryan, Shun Hirayama, Ross D. Merkin, Evelyn Luciani, Thomas J. Roberts, Manisha Patel, Jong C. Park, Lori J. Wirth, Peter M. Sadow, Moshe Sade-Feldman, Shannon L. Stott, Daniel L. Faden

“…Tertiary Lymphoid Structures (TLS) have shown promising potential for predicting response to ICB. However, their exact composition, size, and spatial biology in HNSCC remain understudied. …”
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Leveraging Spatial and Temporal Data to Predict Heavy Freight Vehicle Traffic Flow on Rural Road Network by Alireza Gholami, Seyedehsan Seyedabrishami

“…The extreme gradient boosting (XGBoost) model surpasses the time-series model in predictive accuracy, yielding average R-squared values of 84.7% and 85.8% on the test data for trucks and tractor-trailers, respectively. …”
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Digitally mapping soil health at regional scale: disentangling drivers and predicting spatial land use effects by Valentina Rubio, Joseph Amsili, David G. Rossiter, Andrew McDonald, Harold van Es

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Spatial Prediction of Soil Total Phosphorus in a Karst Area: Comparing GWR and Residual-Centered Kriging by Laimou Lu, Penghui Li, Liang Zhong, Mingbao Luo, Liyuan Xing, Chunlai Zhang

“…GWRK also achieved the highest R² (0.67), demonstrating robust predictive capability. MM_OK and MC_OK models performed well and showed smoother spatial transitions, while the OK model displayed the lowest predictive accuracy (62%). …”
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