Profile Aspects of Graphic Education at Polytechnic University by Irina D. Stolbova, Evgeniya P. Aleksandrova, Lyudmila V. Kochurova, Konstantin G. Nosov

“…To close the gap between the practice of polytechnic education and real engineering activities, it is necessary to introduce innovative educational technologies aimed at developing students’ ability to work in a team, competences in the field of modern information and communication technologies, as well as a willingness to carry out design based on spatial modeling.Within the framework of subject training, it is necessary to ensure the unity of fundamental (generalized, theoretical) knowledge and special knowledge corresponding to the profile of the training area. …”
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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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Integrative habitat analysis and multi-instance deep learning for predictive model of PD-1/PD-L1 immunotherapy efficacy in NSCLC patients: a dual-center retrospective study by Xiaoxiao Huang, Xiaoxin Huang, Yurun Xie, Kui Wang, Housheng Bai, Ruiling Ning, Xiqi Zhu, Deyou Huang, Guanqiao Jin

“…Finally, a separate PD-L1 expression dataset was used to compare the predictive performance of imaging models against PD-L1 status (positive/negative) and expression levels (high/low) to identify the optimal model for predicting immunotherapy clinical benefit. …”
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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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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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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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A New and Tested Ionospheric TEC Prediction Method Based on SegED-ConvLSTM by Yuanhang Liu, Yingkui Gong, Hao Zhang, Ziyue Hu, Guang Yang, Hong Yuan

“…In this paper, we propose a TEC prediction model, which simultaneously considers both spatial and temporal characteristics to extract spatiotemporal features of ionospheric distribution. …”
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Modelling of agricultural land dynamics using artificial neural networks and geospatial analysis in Melur Taluk, Tamil Nadu, India by Gowthaman M S, Murugasan R, Srinivasa Raju K, Makendran C

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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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Forecasting Day-Ahead Electricity Demand in Australia Using a CNN-LSTM Model with an Attention Mechanism by Laial Alsmadi, Gang Lei, Li Li

“…Despite advancements in various prediction models, existing approaches often struggle to capture the complex, nonlinear relationships between temperature variations and electricity consumption. …”
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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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Prediction of Airtightness Performance of Stratospheric Ships Based on Multivariate Environmental Time-Series Data by Yitong Bi, Wenkuan Xu, Lin Song, Molan Yang, Xiangqiang Zhang

“…Among the models evaluated, the NeuralProphet model demonstrated superior accuracy in long-term airtightness predictions, effectively capturing time-series dependencies and spatial interactions with environmental conditions. …”
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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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A Convolutional Neural Network–Long Short-Term Memory–Attention Solar Photovoltaic Power Prediction–Correction Model Based on the Division of Twenty-Four Solar Terms by Guodong Wu, Diangang Hu, Yongrui Zhang, Guangqing Bao, Ting He

“…The examination of the measured data from PV power stations and the comparison and analysis with other prediction models demonstrate that the model presented in this paper can effectively enhance the accuracy of PV power predictions.…”
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A deep learning model based on self-supervised learning for identifying subtypes of proliferative hepatocellular carcinoma from dynamic contrast-enhanced MRI by Hui Qu, Shuairan Zhang, Xuedan Li, Yuan Miao, Yuxi Han, Ronghui Ju, Xiaoyu Cui, Yiling Li

“…We developed a deep learning prediction model that employs a dynamic radiomics workflow and self-supervised learning (SSL). …”
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A Scalable Data-Driven Surrogate Model for 3D Dynamic Wind Farm Wake Prediction Using Physics-Inspired Neural Networks and Wind Box Decomposition by Qiuyu Lu, Yuqi Cao, Pingping Xie, Ying Chen, Yingming Lin

“…Results demonstrate that the proposed surrogate model accurately predicts the 3D dynamic wake evolution for single-turbine and multi-turbine configurations. …”
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Leveraging Deep Spatiotemporal Sequence Prediction Network with Self-Attention for Ground-Based Cloud Dynamics Forecasting by Sheng Li, Min Wang, Minghang Shi, Jiafeng Wang, Ran Cao

“…Compared with other spatiotemporal sequence prediction models, CloudPredRNN++ shows significant improvements in evaluation metrics, improving the accuracy of cloud dynamics forecasting and alleviating long-term dependency decay, thus confirming the effectiveness in ground-based cloud prediction tasks.…”
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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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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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