Surface temperature change amplifies social inequality in heat exposure? Evidence from Shanghai, China by Peng Zeng, Cheng Chen, Fengyun Sun, Yaoyi Liu, Xinyu Zhang, Yue Che

“…We employed a boosted regression tree model to quantify LST changes, offering better predictive performance than traditional linear regression, and used geographically weighted regression with data from China's sixth population census to assess the city-wide and local scale inequality differences in exposure to LST changes and summer LST. …”
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Lip-Reading Classification of Turkish Digits Using Ensemble Learning Architecture Based on 3DCNN by Ali Erbey, Necaattin Barışçı

“…While LSTM models are effective in processing temporal data, 3DCNN-based models, which can process both spatial and temporal information, achieved higher accuracy in this study. …”
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Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East by Younes Khosravi, Taha B.M.J. Ouarda, Saeid Homayouni

“…The results indicate that Stacking-EML not only significantly improves prediction accuracy compared to individual models and traditional CMIP6 outputs but also enhances climate projections by integrating multiple ML models, offering more reliable, regionally refined forecasts. …”
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Camouflage Target Detection Method with Mutual Compensation of Local-Global Features by HE Wenhao, GE Haibo

“…In the field of camouflage object detection (COD), the latest proposed methods mainly use the local features of the camouflaged target to complete the COD task. The output prediction map has problems such as rough target contours and incomplete objects. …”
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Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints by Ryong-Gyu Lee, Yong-Hoon Kim

“…The effectiveness of DeepSCF is demonstrated using a complex carbon nanotube-based DNA sequencer model. This work evidences that the nearsightedness in electronic structure can be optimally represented via the spatial locality in CNNs, offering insight into the success of various machine learning-based atomistic materials simulations.…”
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Contribution of relative humidity on aerosol optical depth role in influencing the regionalization pattern of precipitation over West Africa by Ayomide Victor Arowolo, Ayodeji Festus Ologun, Precious Ebiendele, Ayodeji Oluleye

“…Understanding the complex interactions between aerosol optical depth (AOD), relative humidity, and precipitation is essential for improving climate and weather prediction models, particularly in regions like West Africa, which are vulnerable to climate variability. …”
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Flood Hazard Assessment Using Weather Radar Data in Athens, Greece by Apollon Bournas, Evangelos Baltas

“…This study highlights the significance of incorporating radar precipitation and real-time soil moisture assessments to improve flood prediction accuracy and provide valuable flood risk assessments.…”
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On the division of things into immovable and movable by Nikolić Dušan Ž.

“…In this context, it should be noted that apart from the GPS, there are also precise digital programs and models that enable predictive land mapping (digital land surface models for predictive mapping). …”
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Spatiotemporal patterns and environmental determinants of wildlife-vehicle collisions in Banke National Park, Nepal by Narayan Prasad Koju, K. C. Anish, Keshav Dodhari, Pratikshya Giri, Miriam Lee, Sudip Pokhrel, Asmina Ghimire, Lila Nyaichyai, Kenneth Otieno Onditi, Xuelong Jiang, Randall C. Kyes

“…The methodological approach integrated field surveys, spatial analyses using kernel density estimation, and statistical modelling to pinpoint collision hotspots and elucidate contributing factors. …”
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A Novel Monitoring Method of Wind-Induced Vibration and Stability of Long-Span Bridges Based on Permanent Scatterer Interferometric Synthetic Aperture Radar Technology by Jiayue Ma, Xiaojun Xue, Guoliang Zhi, Haoyang Zheng, Hanqing Zhu

“…Experimental results demonstrate that this method offers precise, real-time monitoring of wind-resistant stability. By leveraging the spatial accuracy and long-term monitoring capability of PS-InSAR, along with the time-series forecasting strength of ARMA models, the method enables data-driven analysis of bridge vibrations. …”
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Seasonal Early Warning of Impacts of Harmful Algal Blooms on Farmed Shellfish in Coastal Waters of Scotland by O. Stoner, T. Economou, A. R. Brown

“…Through a comprehensive yearly prediction experiment, we demonstrate considerable skill in predicting the impact of unseen HAB seasons at a regional level.…”
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Spatiotemporal Impacts of Urban Structure and Socioeconomic Factors on Carbon Dioxide Emissions: A Case Study of the Yangtze River Delta Urban Agglomeration by Zhechen Zhou, Su Xu, Jun Wang, Haitao Shen

“…The results show the following: (a) The spatial differentiation of urban structures between cities was obvious, and 4 landscape indices showed significant spatial autocorrelation. …”
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Machine Learning and Spatio Temporal Analysis for Assessing Ecological Impacts of the Billion Tree Afforestation Project by Kaleem Mehmood, Shoaib Ahmad Anees, Sultan Muhammad, Fahad Shahzad, Qijing Liu, Waseem Razzaq Khan, Mansour Shrahili, Mohammad Javed Ansari, Timothy Dube

“…A predictive model for the Normalized Difference Vegetation Index (NDVI), supported by SHAP analysis, identified soil moisture and precipitation as primary drivers of vegetation growth, with the ANN model achieving an R2 of 0.8556 and an RMSE of 0.0607 on the testing dataset. …”
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SODU2-NET: a novel deep learning-based approach for salient object detection utilizing U-NET by Hyder Abbas, Shen Bing Ren, Muhammad Asim, Syeda Iqra Hassan, Ahmed A. Abd El-Latif

“…Finally, the architecture has been improved by adding a residual block at the encoder end, which is responsible for both saliency prediction and map refinement. The proposed network is designed to learn the transformation between input images and ground truth, enabling accurate segmentation of salient object regions with clear borders and accurate prediction of fine structures. …”
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Joint Intensity and Spatio-Temporal Representation Learning for Extreme Precipitation Nowcasting by Zefeng Pan, Renlong Hang, Qingshan Liu, Chunxiang Shi, Zhiqiang Xu, Xiao-Tong Yuan

“…However, the existing methods tend to inadequately weigh precipitation intensity features by only implicitly learning and modeling these features within the spatial distribution. …”
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Computational principles of neural adaptation for binaural signal integration. by Timo Oess, Marc O Ernst, Heiko Neumann

“…The circuit incorporates an adaptation mechanism operating at the synaptic level based on local inhibitory feedback signals. The model's predictive power is demonstrated in various simulations replicating physiological data. …”
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CapSurv: Capsule Network for Survival Analysis With Whole Slide Pathological Images by Bo Tang, Ao Li, Bin Li, Minghui Wang

“…The results illustrate the proposed CapSurv model has the ability to improve the performance of the prediction by comparing with state-of-the-art survival models.…”
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Data fusion-based improvements in empirical regression and machine learning for global daily ∼ 8 km resolution sea surface nitrate estimation and interpretation by Aifen Zhong, Difeng Wang, Fang Gong, Jingjing Huang, Zhuoqi Zheng, Xianqiang He, Qing Zhang, Qiankun Zhu

“…Here we aim to enhance the accuracy and spatial resolution of SSN retrievals by developing improved regression and machine learning models, enabling the generation of global daily ∼ 8 km SSN products from satellite and model data. …”
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Multi-Timescale Fault Interactions and Earthquakes: A Review by Mian Liu

“…Earthquake models are based on elastic rebound, which predicts cyclic stress accumulation and release on fault planes. …”
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The effects of seasonal human mobility and Aedes aegypti habitat suitability on Zika virus epidemic severity in Colombia. by Brandon Lieberthal, Brian Allan, Sandra De Urioste-Stone, Andrew Mackay, Aiman Soliman, Shaowen Wang, Allison M Gardner

“…Our research uses the novel approach of combining geographical modeling of mosquito presence with network modeling of human mobility to offer a comprehensive simulation environment for Zika virus epidemics that considers a substantial number of spatial and temporal factors compared to the literature. …”
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