Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts by Yanhui Xie, Shuting Zhang, Xin Sun, Min Chen, Jiancheng Shi, Yu Xia, Ruixia Liu

“…The ever-increasing capacity of numerical weather prediction (NWP) models requires accurate flow information at higher spatial and temporal resolutions. …”
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Implications of Self-Potential Distribution for Groundwater Flow System in a Nonvolcanic Mountain Slope by Tada-nori Goto, Kazuya Kondo, Rina Ito, Keisuke Esaki, Yasuo Oouchi, Yutaka Abe, Maki Tsujimura

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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. …”
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Climate‐Associated Genetic Variation and Projected Genetic Offsets for Cryptomeria japonica D. Don Under Future Climate Scenarios by Kentaro Uchiyama, Tokuko Ujino‐Ihara, Katsuhiro Nakao, Jumpei Toriyama, Shoji Hashimoto, Yoshihiko Tsumura

“…ABSTRACT Revealing the spatial distribution of adaptive genetic variation is both a challenging and crucial task in evolutionary ecology, essential for understanding local adaptation within species, and in management, for predicting species responses to future climate change. …”
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Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

“…A machine learning (ML) model for predicting nitrate leaching was then developed, with the random forest (RF) model outperforming the support vector machine (SVM), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) models, achieving an R² of 0.75. …”
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Stochastic Portfolio Planning for Virtual Power Plants Using Stratified Sampling by Dosung Kim, Sung-Kwan Joo

“…Forecast errors are further modeled using a copula-based approach that captures spatial and temporal correlations. …”
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Georgia on Their Minds: Rethinking the Role of Geographic Scale in U.S. Elections by John Agnew, Michael Shin

“…Results from the 2022 Georgia senate runoff election between Raphael Warnock and Herschel Walker are examined with exploratory spatial data analysis (ESDA) and multi-level regression modeling (MLM) to illustrate how a more complete conception of geographic scale is implicated in electoral outcomes.…”
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Features of Conceptualization of Wine Drinking Situation in the Works of N. S. Leskov by O. A. Dimitrieva

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Trajectory- and Friendship-Aware Graph Neural Network with Transformer for Next POI Recommendation by Chenglin Yu, Lihong Shi, Yangyang Zhao

“…To address this, we propose a model that combines check-in trajectory information with user friendship relationships and uses a Transformer architecture for prediction (TraFriendFormer). …”
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Improving the estimation precision of the mapping of groundwater salinity by employing the Indicator Kriging Technique by Sandeep Ravish, Baldev Setia, Surinder Deswal, Vishal Puri, Bhupender Singh, Kuldeep Sharma, Ashok Kumar Yadav

“…By using nonlinear and nonparametric techniques with electrical conductivity thresholds, the IKT improved the salinity estimates’ spatial distribution accuracy. IKT was useful for public health, water management, and agricultural planning since it offered a more accurate and probabilistic prediction of high salinity levels. …”
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Early signs of strong El Niño–Southern Oscillation episodes by Wenxiu Zhong, Arnold Sullivan, Gian Luca Eusebi Borzelli, Ziguang Li

“…AI technology has highlighted the importance of sea surface salinity in obtaining accurate ENSO predictions, even beyond the spring predictability barrier (SPB), which is commonly understood as a prediction barrier that occurs during the boreal spring. …”
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Integrating Bayesian classification and ANN for lithofacies classification using well and seismic data: Bahregansar case study by Hessam Mansouri Siahgoli, Mohammad Ali Riahi, Majid Nabi-Bidhendi, Seyedmohsen Seyedali

“…Following well log corrections and shear wave velocity (Vs) prediction through rock physics modeling, an adaptive rock physics template (AI vs. …”
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Maritime Traffic Knowledge Discovery via Knowledge Graph Theory by Shibo Li, Jiajun Xu, Xinqiang Chen, Yajie Zhang, Yiwen Zheng, Octavian Postolache

“…Furthermore, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm is employed to identify suitable docking berths. …”
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Nonplanar 3D fault geometry controls the spatiotemporal distributions of slip and uplift: evidence from the Mw 7.5 2024 Noto Peninsula, Japan, Earthquake by Ryosuke Ando, Yo Fukushima, Keisuke Yoshida, Kazutoshi Imanishi

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Identification and Spatiotemporal Characteristic Analysis of Compound Weather and Climate Extremes for Maize in Different Climate Zones of the Songliao Plain by Ziyuan Zhou, Ying Guo, Dan Chen, Kaiwei Li, Rui Wang, Xiao Wei, Jiquan Zhang, Chunli Zhao, Zhijun Tong, Xingpeng Liu

“…Abstract Due to global climate anomalies, the intensity and spatial extent of weather and climate extremes have increased notably. …”
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Decision-Aid Framework for Face Authentication Detection Using ResNext50 and BiLSTM to Enhance Media Integrity by Ayat Abd-Muti Alrawahneh, Siti Norul Huda Sheikh Abdullah, Tarik Abuain, Sharifah Nurul Asyikin Syed Abdullah, Sarah Khadijah Taylor, Nur Hanis Sabrina Suhaimi

“…Unlike conventional approaches focusing solely on spatial features, the proposed hybrid model incorporates temporal analysis, enabling the detection of subtle manipulations distributed across sequential video frames. …”
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DTCMMA: Efficient Wind-Power Forecasting Based on Dimensional Transformation Combined with Multidimensional and Multiscale Convolutional Attention Mechanism by Wenhan Song, Enguang Zuo, Junyu Zhu, Chen Chen, Cheng Chen, Ziwei Yan, Xiaoyi Lv

“…Experiments on multiple wind-farm datasets and energy-related datasets demonstrate that DTCMMA outperforms mainstream methods such as Transformer, iTransformer, and TimeMixer in long-sequence forecasting tasks, achieving improvements in MSE performance by 34.22%, 2.57%, and 0.51%, respectively. The model’s training speed also surpasses that of the fastest baseline by 300%, significantly improving both prediction accuracy and computational efficiency. …”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…Results and DiscussionThe spatial prediction results demonstrated the effectiveness of the random forest model in classifying land suitability for wheat, barley, and alfalfa. …”
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Temperature field study of LSAM-50 flexible base asphalt pavement by Yufeng Bi, Minghao Mu, Mengyu Guo, Wanyu Wu, Tingting Ding, Chengduo Qian, Deshui Yu, Yingjun Jiang, Hongjian Su

“…Although numerous studies on pavement temperature distribution and prediction models have been conducted both domestically and internationally, significant differences still exist in the temperature distribution of pavements with varying structures and materials, as well as in different regions and terrains.…”
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An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics by Z. Tan, D. Xu, S. Taraphdar, J. Ma, G. Bisht, L. R. Leung

“…Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. …”
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