Soil moisture retrieval and spatiotemporal variation analysis based on deep learning by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Liya Shi, Wen Ma

“…The soil moisture map produced by the optimal model reveals a spatial distribution pattern in the Weiku Oasis, characterized by higher moisture levels in the center and lower levels at the periphery. …”
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The roles of surface processes in porphyry copper deposit preservation by B. Hadler Boggiani, T. Salles, C. Mallard, N. Atwood

“…To highlight the influence of paleo-reconstructions on exhumation rate estimates, we analyze simulated erosion rates across the Andean region using two distinct paleo-climate models and find significant spatial and temporal differences across the Central Andes. …”
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Enhancing burned area monitoring with VIIRS dataset: A case study in Sub-Saharan Africa by Boris Ouattara, Michael Thiel, Barbara Sponholz, Heiko Paeth, Marta Yebra, Florent Mouillot, Patrick Kacic, Kwame Hackman

“…To address this, future versions of the algorithm will integrate the updated VIIRS reflectance data alongside VIIRS active fire from the National Oceanic and Atmospheric Administration to reduce CE and improve understanding spatial patterns.…”
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Spatiotemporal Determinants of Urban Leptospirosis Transmission: Four-Year Prospective Cohort Study of Slum Residents in Brazil. by José E Hagan, Paula Moraga, Federico Costa, Nicolas Capian, Guilherme S Ribeiro, Elsio A Wunder, Ridalva D M Felzemburgh, Renato B Reis, Nivison Nery, Francisco S Santana, Deborah Fraga, Balbino L Dos Santos, Andréia C Santos, Adriano Queiroz, Wagner Tassinari, Marilia S Carvalho, Mitermayer G Reis, Peter J Diggle, Albert I Ko

“…Although infection risk varied between years, the spatial distribution of risk associated with fixed and random effects did not vary temporally. …”
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Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…To enhance SEE, we introduce a hybrid deep-learning (DL) framework that integrates convolutional neural networks (CNN) and long short-term memory (LSTM) networks for joint EE and security optimization. The CNN extracts spatial features, while the LSTM captures temporal dependencies, enabling a more robust and adaptive modeling of dynamic IoT communication patterns. …”
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Global burden of gallbladder and biliary diseases (1990–2021) with healthcare workforce analysis and projections to 2035 by Fangyi Dai, Yuzhou Cai, Shangjin Yang, Jingyang Zhang, Yong Dai

“…This study aims to examine the temporal and spatial patterns of these diseases globally from 1990 to 2021, analyze healthcare workforce distribution relative to disease burden, and project the disease burden to 2035. …”
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Two-dimensional modeling of nitrate transport in canola field under Moistube irrigation using HYDRUS 2D/3D by Tinashe Lindel Dirwai, Tinashe Lindel Dirwai, Aidan Senzanje, Aidan Senzanje, Tafadzwanashe Mabhaudhi, Tafadzwanashe Mabhaudhi, Tafadzwanashe Mabhaudhi, Tafadzwanashe Mabhaudhi

“…While previous studies have explored wetting patterns under Moistube Irrigation (MTI) and discussed qualitative nitrate retention, few have quantitatively simulated nitrate transport through variably saturated zones with fine temporal-spatial resolution.MethodsA field experiment was conducted in a 20 m × 8 m naturally ventilated greenhouse using three irrigation regimes: (i) full irrigation (100% ETc), (ii) optimal deficit irrigation (75% ETc), and (iii) extreme deficit irrigation (55% ETc). …”
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Effects of the unity vacuum suspension system on transtibial gait for simulated non-level surfaces. by Gabrielle Thibault, Hossein Gholizadeh, Emily Sinitski, Natalie Baddour, Edward D Lemaire

“…Significant differences between active and inactive vacuum conditions (p<0.05) were found for some temporal-spatial and kinematic gait parameters, but the differences were small and not considered clinically significant. …”
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Establishment and characterization of liver‐specific Apoa4‐Cre and Cyp2c11‐Cre rat models in juvenile and adult stages by Wei Dong, Xiang Gao, Feifei Guan, Jirong Pan, Wei Chen, Li Zhang, Lianfeng Zhang

“…Rosa26‐imCherry rats were employed to hybridize with the Cre rats to obtain the Apoa4‐Cre/Rosa26‐imCherry and Cyp2c11‐Cre/Rosa26‐imCherry rats. The temporal and spatial patterns of Cre expression were determined by the observation of red fluorescence on tissue sections. …”
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Understanding flood and drought extremes under a changing climate in the Blue Nile Basin: A review by Demelash Ademe Malede, Vetrimurugan Elumalai, Tesfa Gebrie Andualem, Yilkal Gebeyehu Mekonnen, Mesenbet Yibeltal, Girum Getachew Demeke, Tena Alamirew, Shimelash Molla Kassaye, Yonas Gebreslasie Hagos, Anmut Enawgaw Kassie, Mulatu Kassa, Gizachew Sewagegn Berihun, Ram L. Ray

“…Extreme flood and drought events arise from temporal and spatial variations in the Earth's water cycle, significantly affecting water resources and the environment. …”
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Mapping Burned Area in the Caatinga Biome: Employing Deep Learning Techniques by Washington J. S. Franca Rocha, Rodrigo N. Vasconcelos, Soltan Galano Duverger, Diego P. Costa, Nerivaldo A. Santos, Rafael O. Franca Rocha, Mariana M. M. de Santana, Ane A. C. Alencar, Vera L. S. Arruda, Wallace Vieira da Silva, Jefferson Ferreira-Ferreira, Mariana Oliveira, Leonardo da Silva Barbosa, Carlos Leandro Cordeiro

“…This research aims to evaluate the effectiveness of a fire detection model and analyze the spatial and temporal patterns of burned areas, providing essential insights for fire management and prevention strategies. …”
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Genetic diversity of norovirus in Shenzhen Based on continuous surveillance from 2016 to 2022 by Xin Wang, Wanqiu Liu, Wanqiu Liu, Wanqiu Liu, Mingda Hu, Hui Ma, Yaqing He, Boqian Wang, Kexin Li, Kexin Li, Kexin Li, Rui Zhang, Rui Zhang, Rui Zhang, JingJing Fu, JingJing Fu, Hailong Zhang, Long Chen, Xinru Zhao, Xinru Zhao, Xinru Zhao, Buaijier Aimaiti, Buaijier Aimaiti, Buaijier Aimaiti, Hongbin Song, Hongguang Ren, Xiaofeng Hu

“…It involved analyzing the demographic, spatial, and temporal distribution of norovirus infections. …”
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Agricultural GDP exposure to drought and its machine learning-based prediction in the Jialing River Basin, China by Xinzhi Wang, Qingxia Lin, Zhiyong Wu, Yuliang Zhang, Changwen Li, Ji Liu, Shinan Zhang, Songyu Li

“…Subsequently, the standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSMI) were applied to analyze the spatial-temporal patterns of droughts. Additionally, cropland exposure to drought was evaluated using gridded agricultural GDP data derived from pixel interpolation. …”
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DECIPHeR-GW v1: a coupled hydrological model with improved representation of surface–groundwater interactions by Y. Zheng, Y. Zheng, G. Coxon, M. Rahman, R. Woods, S. Salwey, S. Salwey, S. Salwey, Y. Rong, D. E. Wendt

“…Furthermore, our model reproduces temporal patterns of the groundwater level time series, with more than half of the wells achieving a Spearman correlation coefficient of 0.6 or higher when comparing simulations to observations. …”
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Ecological and climatic transferability of airborne lidar-driven aboveground biomass models in Piñon-Juniper woodlands by Jessie F. Eastburn, Michael J. Campbell, Philip E. Dennison, William Rl Anderegg, Kevin J. Barrett, Patrick A. Fekety, Samuel W. Flake, David W. Huffman, Steven A. Kannenberg, Kelly L. Kerr, Andrew J. Sánchez Meador, Jody C. Vogeler

“…Piñon-juniper (PJ) woodlands are an expansive and dynamic dryland ecosystem in the US that encompass a wide range of spatial, temporal, and ecological diversity. The dynamism of PJ woodland extent and abundance over space and time is attributable to variability in species compositions, stand structures, climatic conditions, and disturbance patterns. …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…Embodying principles of openness and transcending temporal and spatial constraints, online courses afforded global learners opportunities for continued education during the pandemic. …”
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Integrating plot-based methods for monitoring biodiversity in island habitats under the scope of BIODIVERSA + project BioMonI: Tree monitoring in Terceira, Tenerife and Réunion Isl... by Paulo Borges, Leila Morgado, Rosalina Gabriel, Rui Elias, Mirana Gauche, Claudine Ah-Peng, Rüdiger Otto, Lea de Nascimento, Dominique Strasberg, Nathaly Guerrero-Ramírez, Holger Kreft, José María Fernández-Palacios

“…These standardised data collections within permanent plots allow for consistent, replicable observations across temporal and spatial scales. Initiatives like the Global Island Monitoring Scheme (GIMS) highlight the value of permanent plots in capturing ecological gradients and anthropogenic disturbance patterns. …”
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A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation by Jonathan Schmidt, Luca Schmidt, Felix M. Strnad, Nicole Ludwig, Philipp Hennig

“…Current statistical downscaling methods infer these phenomena as temporally decoupled spatial patches. However, to preserve physical properties, estimating spatio-temporally coherent high-resolution weather dynamics for multiple variables across long time horizons is crucial. …”
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Gobbling activity of eastern wild turkeys relative to male movements and female nesting phenology in South Carolina by Michael J. Chamberlain, Patrick H. Wightman, Bradley S. Cohen, Bret A. Collier

“…Gobbling activity varies significantly both temporally and spatially, and relationships between gobbling activity and reproductive phenology are unclear. …”
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Probabilistic Interference Prediction for Dynamic 6G In-X Sub-Networks by Pramesh Gautam, Carsten Bockelmann, Armin Dekorsy

“…The effectiveness of the proposed predictors is evaluated using a spatially consistent 3GPP channel model incorporating realistic mobility and two distinct extreme traffic models. …”
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