Quantifying the Cumulative Effects of Large-Scale Reclamation on Coastal Wetland Degradation by Linlin Cui, Guosheng Li, Miao Zhao, Zhihui Zhang

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Quantifying the Synergy Between Industrial Structure Optimization, Ecological Environment Management, and Socio-Economic Development by Zexi Xue, Zhouyun Chen, Qun Lin, Ansheng Huang

“…Additionally, drawing on the framework of evolutionary economics, the study quantified the temporal evolution and spatial characteristics of the coupling coordination level among the three subsystems based on the results of the degree of coupling coordination model. …”
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Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging by Saurabh Bhattacharya, Sashikanta Prusty, Sanjay P. Pande, Monali Gulhane, Santosh H. Lavate, Nitin Rakesh, Saravanan Veerasamy

“…Current approaches are less helpful for forecasting, however, as they do not always blend spatial and temporal patterns from different sources properly. …”
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Episodic Gregariousness Leads to Level‐Dependent Core Habitats: A Case Study in Eastern Copperheads (Agkistrodon contortrix) by Tyler C. Christensen, Robert Kwait, Michael Van Clef, Brooke Maslo

“…Wildlife–habitat selection is influenced by multiple life‐history requirements, which act over varying spatial and temporal scales, and result in dispersion patterns that can differ across ecological levels. …”
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A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research by Md. Rajaul Karim, M. M. Mahbubul Syeed, Ashifur Rahman, Khondkar Ayaz Rabbani, Kaniz Fatema, Razib Hayat Khan, Md Shakhawat Hossain, Mohammad Faisal Uddin

“…This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.…”
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Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan by Liping Wang, Haonan Chen, Zhe Li

“…To recognize the error patterns of the mainstream SPPs over Taiwan, this study evaluates the temporal and spatial performance of NOAA Climate Prediction Center (CPC) morphing technique (CMORPH V1) and NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07 Final) during 2019–2021, with an emphasis on exploring the multi-scale performance of CMORPH and IMERG and their dependence on precipitation intensity and season. …”
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Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model by Shanshan Wang, Jingwu Liu

“…Two datasets, Geo-Life Log (with location data) and Time-Life Log (without location data), were constructed to evaluate the impact of spatial information on classification performance. …”
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On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…Plant functional types were useful at the site level for the improved representation of spatial patterns but had a significant leverage on upscaling results – i.e., having a disproportionate impact on the spatial patterns, especially for XGBoost, but less for the LSTM model.…”
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Integrating remote sensing, GIS, and machine learning for zoonotic cutaneous leishmaniasis modelling by Fatemeh Parto Dezfooli, Mohammad Javad Valadan Zoej, Fahimeh Youssefi, Ebrahim Ghaderpour

“…Utilizing data from 2014 to 2019, spatial and temporal patterns are investigated using Moran’s I, Getis-Ord Gi* statistics, and the Mann-Kendall (MK) test, while high-risk ZCL maps are generated through Extreme Gradient Boosting (XGBoost) and Random Forest (RF) models. …”
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Coastal Storm – Surge Combination Risk Identification and Resilience Planning Based on Supply and Demand Assessment of Flood Regulation Ecosystem Services: A Case Study of Fujian D... by Jian TIAN, Tianyu XIU, Suiping ZENG

“…Globally, urban stormwater management is transitioning toward ecological solutions, emphasizing the role of flood regulation ecosystem services (FRES) as a sustainable and adaptive strategy for mitigating storm-surge disasters. This research evaluates the spatial-temporal dynamics of FRES supply and demand in coastal urban agglomerations, identifies critical regions with storm – surge combination risk, prioritizes planning interventions, and proposes actionable strategies to enhance urban flood resilience.MethodsFocusing on the Fujian Delta urban agglomeration, an analytical framework is developed to assess FRES supply and demand. …”
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Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model by Amir Miraki, Pekka Parviainen, Reza Arghandeh

“…Our framework employs a parallel feature extraction module that simultaneously captures temporal dynamics and spatial correlations, enabling improved forecasting accuracy. …”
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Computational Analysis Method for Multi-subject Behavior in Public Spaces Based on Targeted Computer Vision Tracking by Chao YAN, Siyan LIU, Shanshu HE, Leiqing XU

“…Subsequently, computational analysis and visualization methods for revealing the interaction behaviors of different groups are explored, which involves a pedestrian identification threshold model based on human proportion characteristics that enables targeted identification and differentiation of children from adults, and a dedicated analysis module designed to visualize behavioral patterns of each identified crowd and thereby provide visual patterns for the spatial-temporal distributions of different crowds. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…In the spatial domain, the Temporal Convolutional Network (TCN) models long-range dependencies by expanding causal convolutions, thereby capturing local and global spatial relationships. …”
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Hand Tremor Characterization from a Spatiotemporal Convolutional Representation by Jessica Pedraza Cadena, John Edinson Archila Valderrama, Franklin Sierra-Jerez, Alejandra Moreno Tarazona, Fabio Martínez Carrillo

“…Conclusions: This approach showed efficacy regarding the localization of tremor patterns, recovering movement information while preserving the spatial and temporal representation. …”
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Comparison of BARRA and ERA5 in replicating mean and extreme precipitation over Australia by K. K. W. Cheung, F. Ji, F. Ji, N. Nishant, J. Teng, J. Bennett, D. L. Liu

“…Both datasets reproduce daily timescale probability density distributions and spatial patterns of mean precipitation well with minor biases. …”
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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

“…The author first makes a preliminary analysis of the wireless network data (mainly the data of cellular mobile networks) obtained by Internet service providers, reveals that the data of adjacent base stations have temporal and spatial correlations, then establishes a hybrid deep learning model for spatio-temporal prediction, and proposes a new spatial model training algorithm. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…The model synergizes CNNs for hierarchical spatial feature extraction and SNNs for biologically inspired temporal dynamics processing. …”
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An Exploration of the Use of Educational Robotics in Preschool Education by Veronica Mihaela Rus, Beatrice Almășan

“…The results show that the use of educational robots in different stages of teaching, learning and evaluation helps in the development process of children by understanding the cause-effect relationship, acquiring spatial and temporal orientation skills, developing communication skills and supporting socio-emotional interactions with children of the same age. …”
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Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer by Ruowu Wu, Yandan Liang, Lianlei Lin, Zongwei Zhang

“…However, the existing data-based weather prediction methods cannot adequately capture the spatial and temporal evolution characteristics of the target region, which makes it difficult for the existing methods to meet practical application requirements in terms of efficiency and accuracy. …”
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Improvement of SAM2 Algorithm Based on Kalman Filtering for Long-Term Video Object Segmentation by Jun Yin, Fei Wu, Hao Su, Peng Huang, Yuetong Qixuan

“…SAM 2’s fixed temporal window approach indiscriminately retains historical frames, failing to account for frame quality or dynamic motion patterns. …”
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