End-to-End Vector Simplification for Building Contours via a Sequence Generation Model by Longfei Cui, Junkui Xu, Lin Jiang, Haizhong Qian

“…Traditional methods often rely on complex rule design, feature engineering, and iterative optimization. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…However, when using these models, the spatial heterogeneity of the relationship between soil and environmental variables is often not fully considered, which limits the predictive capability of the models, especially in large-scale regions with complex soil landscapes. …”
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Reconstruction of the Magnetic Particle Imaging System Matrix Using Symmetries and Compressed Sensing by A. Weber, T. Knopp

“…Magnetic particle imaging (MPI) is a tomographic imaging technique that allows the determination of the 3D spatial distribution of superparamagnetic iron oxide nanoparticles. …”
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Hybrid approaches enhance hydrological model usability for local streamflow prediction by Yiheng Du, Ilias G. Pechlivanidis

“…Abstract Hydrological models are essential for predicting water flux dynamics, including extremes, and managing water resources, yet traditional process-based large-scale models often struggle with accuracy and process understanding due to their inability to represent complex, non-linear hydrometeorological processes, limiting their effectiveness in local conditions. …”
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Patterns and Mechanisms of Niche Partitioning Between Related Parasitoids (Hymenoptera) Sharing the Same Host Species by Vladimir E. Gokhman

“…Nevertheless, many cases of coexistence of related wasp species on the same host defy simple explanations since they apparently result from complex interactions between the host and its parasitoids. …”
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Spatiotemporal Evolution of Precipitation Concentration in the Yangtze River Basin (1960–2019): Associations with Extreme Heavy Precipitation and Validation Using GPM IMERG by Tao Jin, Yuliang Zhou, Ping Zhou, Ziling Zheng, Rongxing Zhou, Yanqi Wei, Yuliang Zhang, Juliang Jin

“…Key methods include Mann–Kendall trend tests for detecting changes, Hurst exponents for persistence, Pettitt detection for abrupt shifts, random forest modeling to assess atmospheric teleconnections, and hot spot analysis for spatial clustering. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…The SuperSOM model achieved an R2 of 0.60 for training and 0.291 for testing, identifying spatial patterns across depth zones. Finally, a hybrid model combining an unsupervised SOM and followed by the supervised Random Forest model returned an accuracy of 83.47% for the training and 80.77% for the test, with Bathymetry, Chlorophyll, and Coarse Sand as key predictive variables. …”
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YOLOv9-LSBN: An Improved YOLOv9 Model for Cotton Pest and Disease by Ruohong He, Fengkui Zhang, Jikui Zhu, Yulong Wang, Daorina Yang, Ting Zhang, Ping Li

“…To achieve accurate identification of cotton aphids and diseases in natural complex environments, an enhanced YOLOv9 model named YOLOv9-LSBN (Large Selective Kernel Network with Bidirectional Feature Pyramid) is proposed. …”
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Spatiotemporal Mapping and Driving Mechanism of Crop Planting Patterns on the Jianghan Plain Based on Multisource Remote Sensing Fusion and Sample Migration by Pengnan Xiao, Yong Zhou, Jianping Qian, Yujie Liu, Xigui Li

“…The accurate mapping of crop planting patterns is vital for sustainable agriculture and food security, particularly in regions with complex cropping systems and limited cloud-free observations. …”
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A Spatiotemporal Sequence Prediction Framework Based on Mask Reconstruction: Application to Short-Duration Precipitation Radar Echoes by Zhi Yang, Changzheng Liu, Ping Mei, Lei Wang

“…However, existing spatiotemporal sequence prediction methods still struggle to disentangle complex spatiotemporal dependencies effectively and fail to capture the nonlinear chaotic characteristics of precipitation systems. …”
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Dynamic Reliability Evaluation of Road Vehicle Subjected to Turbulent Crosswinds Based on Monte Carlo Simulation by Bin Wang, Yongle Li, Helu Yu, Haili Liao

“…Actually, the natural wind is a random process in time domain due to turbulence, and the surface roughness of a road is also a random process but in spatial domain. …”
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Data-driven segmentation of cortical calcium dynamics. by Sydney C Weiser, Brian R Mullen, Desiderio Ascencio, James B Ackman

“…We show that a set of spatial and temporal metrics obtained from the components can be used to build a random forest classifier, which separates neural activity and artifact components automatically at human performance. …”
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Failure Risk Investigation of Transmission Tower-line System Under Sequential Earthquake Considering Input Directionality by LIU Juncai, DONG You

“…ObjectiveTransmission tower-line structures are representative spatial distribution systems. They typically span hundreds or even thousands of kilometers and inevitably traverse regions with high seismic intensities. …”
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Application of Jane Jacobs’ Theory in the Analysis of the Borders of Territory Monitoring in Urban Spaces from Citizens’ Points of View in Bandar Abbas by Amirhamzeh Shahbazi, Esmaeil zakerimnabi, Alireza Shahbazi

“…The research underscored the complexity of urban surveillance, indicating that effective monitoring extended beyond spatial design to encompass the diverse experiences and backgrounds of citizens. …”
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Patterns of nutrients and algal biomass in an intermittent Mediterranean river under intense human activity by Gabriela Córdoba-Ariza, Rafael Muñoz-Mas, Ramon J. Batalla, Josep Mas-Pla, Sergi Sabater

“…To achieve this, monthly measurements of water quality, physicochemical characteristics and algal biomass were collected at 23 different locations over 14 months, coinciding with the onset of drought conditions in the region. Random forest regression and the model-agnostic SHapley Additive exPlanations (SHAP) enabled us to identify the most influential hydrological and land use features for nutrient concentrations and map the spatial variation of their effects across the basin. …”
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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

“…Asthma prevalence among Gujjar and Bakarwal tribes in the high-altitude Himalayas is shaped by a complex interplay of altitude, socioeconomic status, and demographic factors. …”
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A Hybrid Regression–Kriging–Machine Learning Framework for Imputing Missing TROPOMI NO₂ Data over Taiwan by Alyssa Valerio, Yi-Chun Chen, Chian-Yi Liu, Yi-Ying Chen, Chuan-Yao Lin

“…This structure enables the framework to capture both spatial autocorrelation and complex relationships between NO₂ concentrations and environmental drivers. …”
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Pediatric BurnNet: Robust multi-class segmentation and severity recognition under real-world imaging conditions by Xiang Li, Zhen Liu, Lei Liu

“…Images were resized to 256 × 256 pixels and augmented by flipping and random rotation. A DeepLabv3 network with a ResNet101 backbone was enhanced with channel- and spatial attention modules, dropout-reinforced Atrous Spatial Pyramid Pooling, and a weighted cross-entropy loss to counter class imbalance. …”
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Association between landscape transformation and the Chagas disease vector dynamics in a rural area with continuous surveillance and control by Leonardo Sandon, Diego Weinberg, Manuel O. Espinosa, Marcelo C. Abril, Roberto Chuit, Ximena Porcasi, Maria V. Periago

“…While deforestation reduces sylvatic reservoirs, it also influences domestic triatomine populations, highlighting the complex interplay between environmental changes and vector ecology. …”
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Obtaining Mode Shapes through the Karhunen-Loève Expansion for Distributed-Parameter Linear Systems by Claudio Wolter, Marcelo A. Trindade, Rubens Sampaio

“…It consists in decomposing a spatial correlation matrix, which can be obtained through numerical or physical experiments. …”
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