Comprehensive Probabilistic Analysis and Practical Implications of Rainfall Distribution in Pakistan by Fahad Haseeb, Shahid Ali, Naveed Ahmed, Nassir Alarifi, Youssef M. Youssef

“…Accurately selecting an appropriate probability distribution model is a critical challenge when predicting extreme rainfall in arid and semi-arid regions, especially in countries with diverse climatic conditions. …”
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Multi-Seasonal Risk Assessment of Hydrogen Leakage, Diffusion, and Explosion in Hydrogen Refueling Station by Yaling Liu, Yao Zeng, Guanxi Zhao, Huarong Hou, Yangfan Song, Bin Ding

“…Conversely, north/northwest winds in autumn/winter intensify hydrogen concentrations in compressor and station building areas. (3) An empirical formula integrating climatic parameters, leakage conditions, and spatial coordinates was proposed to predict hydrogen concentration (error < 20%). …”
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Effective management of urban water resources under various climate scenarios in semiarid mediterranean areas by Ioanna Nydrioti, Ioannis Sebos, Gianna Kitsara, Dionysios Assimacopoulos

“…The water resources management study of the region is carried out using the simulations of the RCA4 Regional Climate Model (RCM) driven by the HadGEM-ES global climate model of the Met Office Hadley Centre (MOHC) under 3 different climate emission scenarios, namely RCP 2.6, RCP 4.5 and RCP 8.5. …”
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Assessment of relationship between sea surface temperature (SST) changes and precipitation types in Nigeria from 2000 to 2022 by Tertsea Igbawua, Fanan Ujoh, Solomon Kwaghfan Mkighirga, Grace Adagba

“…The analysis of NIF values indicates a varied but generally stronger relationship between WAf SST anomalies and precipitation types compared to nino3.4 SST versus precipitation types. As a signal for prediction of seasonal and spatial distribution of precipitation across Nigeria’s different climatic zones, this outcome can support planning for food security, water and biodiversity conservation, and climate change adaptation and mitigation.…”
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Mesoscale Numerical Simulation and Cloud Microphysical Characteristics of the Warm Zone Blizzard in Northern Xinjiang by Anbei LI, Chenxiang JU, Yaman ZHOU, Man LI, Ruqi LI

“…The warm zone blizzard are both infrequent and highly destructive， making their accurate prediction a challenging and crucial focus.This study utilized four distinct cloud microphysics schemes （Lin， Thompson， WDM6， and WSM6） within the WRF mesoscale model to conduct a numerical simulation of a typical warm zone blizzard process in the northern Xinjiang in the middle of November 2016.The research objectives encompassed the evaluation of the model's capacity to simulate the warm zone blizzard， the selection of an optimal parameterization scheme， an analysis of the vertical distribution and evolution of hydrometeors during the snowstorm， and an exploration of the developmental patterns of related mesoscale systems contributing to the snowstorm.The analysis yielded the following key findings： （1） Among the diverse cloud microphysics parameterization schemes tested， the Lin scheme demonstrated the most favorable performance， effectively simulating snowfall magnitudes， spatial distributions， and trends.（2） In the cloud， all kinds of water condensate particles are active in the lower and middle troposphere， with graupel and snow being the most.Ice crystals， snow， cloud water and graupel particles are distributed from the upper layer to the lower layer.Near the windward slope of Altai Mountain is the center of the large concentration of each water condensate particle.The vertical alignment of the high value center of the four kinds of cloud water condensate particles in the strong snowfall area is conducive to the transformation of each particle.（3） High-humidity systems upstream moved westward， with the intensification of low-level southward jet streams resulting in pronounced moisture convergence.The western foothills of the Altai Mountains acted as a barrier， promoting moisture convergence by blocking the windward side； The low-level southerly jet also provides a continuous updraft and unstable condition for the generation of the blizzard.Strong snowfall is located in a wide updraft area between two groups of secondary circulations.The explosive growth of vertical movement is conducive to triggering the release of unstable energy， providing strong dynamic lifting conditions for the development and maintenance of the blizzard.…”
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Research trends and frontiers of groundwater-lake interaction by Zesen YANG, Jingjing LIN, Qixin CHANG, Aiguo ZHOU, Xiaolong HUANG

“…The primary research methods are stable isotopes, radioisotopes, temperature tracing, remote sensing, and numerical modelling. However, variations in data accuracy and spatial coverage continue to pose challenges for the practical application of these techniques. …”
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On the Universality of the Split Monopole Black Hole Magnetosphere by S. Selvi, O. Porth, B. Ripperda, L. Sironi

“…Our results enable a quantitative prediction of the timescales and spatial structure of these evolving magnetospheres, essential for understanding electromagnetic counterparts to gravitational wave events and reconnection-powered flares from accreting BHs.…”
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Application of deep learning for coherent pixel selection in time series InSAR for urban area and transport infrastructure monitoring by S. Azadnejad, A. Kandiri, A. Hrysiewicz, F. O’Loughlin, E.P. Holohan, S. Dev, S. Donohue

“…Predictions of temporal coherence from MLP and LSTM models are similar, but the MLP model training time is much faster. …”
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Skin-Inspired Magnetoresistive Tactile Sensor for Force Characterization in Distributed Areas by Francisco Mêda, Fabian Näf, Tiago P. Fernandes, Alexandre Bernardino, Lorenzo Jamone, Gonçalo Tavares, Susana Cardoso

“…The spatial sensitivity model was trained on 171,008 points and achieved a mean absolute error of 0.26 mm when predicting the location of applied force within a sensitive area of 25.5 mm × 25.5 mm using sensors spaced 4.5 mm apart. …”
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Laboratory study on temperature loss behavior of asphalt mixture during transportation by Tianyu Zhang, Xiang Liu, Xiao Li, Haoyuan Luo, Jingpeng Jia, Xiaolong Li

“…Furthermore, a backpropagation (BP) neural network model was employed to predict temperature variations during transportation. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…In this paper, we propose a novel framework for detecting anomalies in videos by uniquely analyzing spatial and temporal (spatio-temporal) features. We address challenges such as the processing of lengthy videos and the sparse occurrence of anomalies by segmenting and labeling anomalous parts within videos. …”
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Enhancing Aquifer Characterization With Position‐Encoded Hyperparameters: A Novel ES‐SIFG Approach by Meng Sun, Qiankun Luo, Yun Yang, Tongchao Nan, Jiangjiang Zhang, Lei Ma, Yu Li, Haichun Ma, Ming Lei, Yaping Deng, Jiazhong Qian

“…Abstract To accurately predict groundwater flow and solute transport, it is essential to precisely characterize the highly heterogeneous aquifer conditions. …”
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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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Enhanced YOLOv10 Framework Featuring DPAM and DALSM for Real-Time Underwater Object Detection by Suthir Sriram, Aburvan P., Arun Kaarthic T. P., Nivethitha Vijayaraj, Thangavel Murugan

“…The marine fusion loss (MFL) provides an object detection prediction that combines both binary cross-entropy loss and complete intersection over union (CIoU) loss to enhance bounding box localization while also including spatial context to incorporate important underwater features. …”
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Progressive Guided Fusion Network With Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection by Jiajia Wu, Guangliang Han, Haining Wang, Hang Yang, Qingqing Li, Dongxu Liu, Fangjian Ye, Peixun Liu

“…The depth map contains abundant spatial structure cues, which makes it extensively introduced into saliency detection tasks for improving the detection accuracy. …”
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Damage evolution and failure modes of coal-concrete composites with varying height ratios under cyclic loading by Renbo Gao, Fei Wu, Cunbao Li, Chunfeng Ye, Qingchuan He, Heping Xie

“…To elucidate these differences, interfacial effects were incorporated into a modified twin-shear unified strength theory. The refined model accurately predicts the internal strength distribution and failure characteristics of the composite structures. …”
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UAV-Based Multispectral Winter Wheat Growth Monitoring with Adaptive Weight Allocation by Lulu Zhang, Xiaowen Wang, Huanhuan Zhang, Bo Zhang, Jin Zhang, Xinkang Hu, Xintong Du, Jianrong Cai, Weidong Jia, Chundu Wu

“…Based on the optimal growth inversion model for winter wheat, spatial distribution of wheat growth in the study area is obtained. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…A comparative evaluation of six machine learning algorithms was conducted: XGBoost, LightGBM, Random Forests, k-Nearest Neighbors, Neural Networks and Decision Trees to assess prediction performance across each frequency band. Furthermore, SHAP (SHapley Additive exPlanations) was employed to elucidate the contribution of spatial and demographic characteristics to the intensity of the EMF. …”
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Three-Dimensional Spatio-Temporal Slim Weighted Generative Adversarial Imputation Network: Spatio-Temporal Silm Weighted Generative Adversarial Imputation Net to Repair Missing Oce... by Yiwan Yue, Juan Li, Yu Zhang, Meiqi Ji, Jingyao Zhang, Rui Ma

“…The generator captures the three-dimensional spatial distribution and vertical profile dynamic patterns through the spatio-temporal attention module, while the discriminator introduces gradient penalty constraints to prevent gradient vanishing. …”
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SODRS: Semisupervised Learning for One-Stage Small Object Detection in Remote Sensing Images by Mingquan Liu, Lei Kuang, Chengjun Li, Jing Tian, Zifang Chen, Xuewu Han

“…Finally, the conditional random fields-based label refinement is applied to postprocess the predicted labels, improving spatial relationships and dependencies among objects. …”
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