Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

“…The attention mechanism directs the model’s focus to the most informative features, improving predictive accuracy. …”
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Book reviews [International Journal of Emotional Education, 17(1)] by Helen Cowie

“…Because the book offers a complex new way of looking at concentric spatial psychology and how this model might apply to contexts of social and emotional education, we invited two reviewers, Dr Daniel Stolfi, an anthropologist and psychotherapist, and Prof Paul Bartolo, a psychologist and educator with a special interest in social and emotional education, to give their different perspectives on the book. …”
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The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China by Bowen Chen, Jinqiao Zhou, Hongfeng Zhang

“…Additionally, Moran’s I and Getis-Ord Gi* are introduced to detect the spatial autocorrelation of sentiment attitudes. Furthermore, by constructing a multivariable geographical detector model and MGWR, the study explores the impact of factors such as the development of the digital economy, the construction of smart cities, local government policy attention, the digital literacy of local residents, and the level of education infrastructure on the distribution of sentiment attitudes. …”
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Spatial Effects in the Context of Kazakhstan’s Regions by A. R. Kerimbayev, Y. B. Bukatov, A. Kudebayeva, L. S. Spankulova

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LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure by Zhi Liu, Xiaoli Zhang, Yong Wu, Yuansu Xu, Zhengying Cao, Zhibo Yu, Zihang Feng, Hongbin Luo, Chi Lu, Weibin Wang, Guanglong Ou

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Urban environmental and population factors as determinants of COVID-19 severity: A spatially-resolved probabilistic modeling approach. by Jacob Roxon, Marie-Sophie Dumont, Eric Vilain, Mircea T Sofonea, Roland J-M Pellenq

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Spatial Modeling of Airborne Particles (PM2.5 and PM10) in Tehran city Using Convolutional Neural Network. by Abed Bashar Doost, Mohammad Saadi Mesgari

“…Taken and spatial modeling of two pollutants using CNN has been done. …”
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ReScConv-xLSTM: An improved xLSTM model with spatiotemporal feature extraction capability for remaining useful life prediction of Aero-engine by Mingxing Huang, Lanying Yang, Gang Jiang, Xingan Hao, Hong Lu, Hang Luo, Peng Wang, Jinyang Li

“…Although deep learning models based on LSTM and Transformer have achieved significant results in this field, these models typically only extract temporal features, neglecting spatial features, and struggle with parallel computation, leading to a bottleneck in RUL prediction performance. …”
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Spatial‑temporal variability of water balance components in the North area of the Zailiisky Alatau Range by V. G. Konovalov, N. V. Pimankina

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Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting by Ang Guo, Yanghe Liu, Shiyu Shao, Xiaowei Shi, Zhenni Feng

“…Rapidly accumulating, large-scale and long-term meteorological data provide unprecedented opportunities for data-driven meteorological models and fine-grained numerical weather prediction. …”
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Modelling Salmo trutta Complex Spatial Distribution in Central Italy: A Random Forest Approach Revealing Underrepresented Lowland Populations Based on Spatially‐Explicit Predictors... by Lorenzo Talarico, Elena Catucci, Marco Martinoli, Michele Scardi, Lorenzo Tancioni

“…The model shows (i) high predictive ability (K = 0.76), (ii) predicts suitable, naturally‐infrequent lowland watercourses where brown trout occurs or may occur. …”
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A mixed modeling approach to predict the effect of environmental modification on species distributions. by Francesco Cozzoli, Menno Eelkema, Tjeerd J Bouma, Tom Ysebaert, Vincent Escaravage, Peter M J Herman

“…Human infrastructures can modify ecosystems, thereby affecting the occurrence and spatial distribution of organisms, as well as ecosystem functionality. …”
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A High‐Performance Coupled Human And Natural Systems (CHANS) Model for Flood Risk Assessment and Reduction by Haoyang Qin, Qiuhua Liang, Huili Chen, Varuna DeSilva

“…In this study, we propose a novel Coupled Human And Natural Systems (CHANS) modeling framework to capture the intricate interactive human behaviors and flooding process at a high spatial resolution. …”
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Modeling the impact of climate change on corvus species distribution in Somaliland: Bayesian spatial point process approach for conservation by Abdisalam Hassan Muse, Maysaa Elmahi Abd Elwahab

“…IntroductionThis study aimed to predict the spatial distribution of Corvus edithae (Somali crow) in Somaliland and explore its relationship with climatic covariates.MethodsWe applied a log-Gaussian Cox process model, utilizing the R-INLA package. …”
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Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

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Modeling suspected malaria cases in Papua province with second order Besag-York-Mollie 2 spatial regression by Kirana Azzahra, Ro'fah Nur Rachmawati, Muhamad Syazali

“…Based on these results, it is concluded that the INLA approach with second-order spatial modelling is effective for analysing and predicting suspected malaria cases in Papua. …”
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Assessing sensitivity of stream migration at Foothill Areas: Hydrological modeling and spatial analysis of the Red Sea coastal stream by Ahmed Foda, Ahmed Abdelhalim, Mustafa Elkhedr

“…An integrated methodology combining hydrological modeling using HEC-RAS 2D, GIS-based spatial analysis, and sediment transport simulation was implemented to quantify channel movement and assess potential scour locations. …”
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Spatial modeling of snow water equivalent in the high atlas mountains via a lumped process-based approach by Siham Acharki, Abdelghani Boudhar, Ayoub Bouihrouchane, Mostafa Bousbaa, Ismail Karaoui, Haytam Elyoussfi, Bouchra Bargam, El Mahdi El Khalki, Abdessamad Hadri, Abdelghani Chehbouni

“…Thus, accurate SWE assessment is essential for predicting the spatial distribution of snowpack and its temporal contributions to downstream outflow, particularly in semi-arid snow-fed basins like Morocco’s High Atlas regions. …”
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Reduction in the potential distribution of bee species in low latitudes under different climate change scenarios: conservation implications by Xinggang Tang, Xinggang Tang, Zheng He, Zheng He, Yue Deng, Yue Deng, Yingdan Yuan, Kaiming Zeng, Kaiming Zeng

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Dynamic spatiotemporal graph network for traffic accident risk prediction by Pengcheng Zhang, Wen Yi, Yongze Song, Penggao Yan, Peng Wu, Ammar Shemery, Keith Hampson, Albert P. C. Chan

“…The dynamic learning of spatial correlations, combined with the integration of road characteristics and contextual variables, significantly enhances the accuracy of traffic accident predictions. …”
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