Aeromagnetic delineation of iron ore deposits in a complex geological terrain aided by fuzzy logic by Fahad Abubakar, Felix Bamidele Fatoye, Momohjimoh Abdulsalami, Abdullateef Aliyu

“…Validation using four known iron ore mining sites confirmed model accuracy, with all sites located within predicted high-potential zones. …”
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A global overview of marine heatwaves in a changing climate by Antonietta Capotondi, Regina R. Rodrigues, Alex Sen Gupta, Jessica A. Benthuysen, Clara Deser, Thomas L. Frölicher, Nicole S. Lovenduski, Dillon J. Amaya, Natacha Le Grix, Tongtong Xu, Juliet Hermes, Neil J. Holbrook, Cristian Martinez-Villalobos, Simona Masina, Mathew Koll Roxy, Amandine Schaeffer, Robert W. Schlegel, Kathryn E. Smith, Chunzai Wang

“…To make progress on predicting and projecting marine heatwaves and their impacts, a more complete mechanistic understanding of these extremes over the full ocean depth and at the relevant spatial and temporal scales is needed, together with models that can realistically capture the leading mechanisms at those scales. …”
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Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…<p>Incomplete spatiotemporal meteorological observations can result in misinterpretations of the current climate state, uncertainties in early warning systems, or inaccuracies in nowcasting models and can thereby pose significant challenges in hydrology research or similar applications. …”
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Artificial Intelligence and Objective‐Function Methods Can Identify Bankfull River Channel Extents by Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell

“…To address this limitation, we developed and tested two automated channel delineation methods that define bankfull according to different conceptualisations of bankfull extent: (a) a cross‐sectional method called HydXS that identifies the elevation which maximizes hydraulic depth (cross‐section area/wetted width); and (b) a neural network image segmentation model based on a pretrained model (ResNet‐18), retrained with images derived from a digital elevation model. …”
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Incorporating long-term numerical weather forecasts to quantify dynamic vulnerability of irrigation supply system: A case study of Shihmen Reservoir in Taiwan by Chia-Chuan Hsu, Yu-Pin Lin

“…Techniques including K-nearest neighbors (KNN) for spatial downscaling, Long Short-Term Memory (LSTM) networks for simulating rainfall runoff, and Monte Carlo simulations (MCS) for analyzing system vulnerability are employed. …”
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Boundary-Aware Transformer for Optic Cup and Disc Segmentation in Fundus Images by Soohyun Wang, Byoungkug Kim, Doo-Seop Eom

“…Furthermore, the proposed model more accurately captures the relative size and spatial alignment of the OD and OC and produces smooth and consistent boundary predictions in clinically significant regions such as the region of interest (ROI). …”
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A method to quantify jump dispersal of invasive species from occurrence data: the case of the spotted lanternfly, Lycorma delicatula by Nadège Belouard, Sebastiano De Bona, Matthew R. Helmus, Isabella G. Smith, Jocelyn E. Behm

“…The accuracy of predicting the spread of biological invasions is improved if models explicitly incorporate the two main dispersal mechanisms: diffusive spread and jump dispersal. …”
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Role of Cairns–Gurevich ion distribution on nonlinear wave propagation in negatively charged dusty plasma by N.S. Alharthi

“…The results demonstrated that soliton waves, explosive waves, and kink waves exhibit distinct behaviors depending on these parameters and the spatial context of Earth's magnetosphere. These findings provide new insights compared to previous studies into the conditions under which these waveforms emerge and evolve, especially in magnetized environments where earlier models were less effective at accurately characterizing or predicting wave behavior. …”
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SAL Method Applied in Grid Forecasting Product Verification with Three-Source Fusion Product by Debin Su, Jinhua Zhong, Yunong Xu, Linghui Lv, Honglan Liu, Xingang Fan, Lin Han, Fuzeng Wang

“…Therefore, forecasters can better understand the model prediction effect and what needs to be improved.…”
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Evaluating the performances of SVR and XGBoost for short-range forecasting of heatwaves across different temperature zones of India by Srikanth Bhoopathi, Nitish Kumar, Somesh, Manali Pal

“…In a nutshell, the study attempts to highlight the capability of advanced ML techniques combined with spatial climate data to enhance the prediction of extreme heatwave events. …”
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GD-Det: Low-Data Object Detection in Foggy Scenarios for Unmanned Aerial Vehicle Imagery Using Re-Parameterization and Cross-Scale Gather-and-Distribute Mechanisms by Rui Shi, Lili Zhang, Gaoxu Wang, Shutong Jia, Ning Zhang, Chensu Wang

“…The model is primarily composed of three components: (i) A lightweight re-parameterization feature extraction module which integrates RepVGG blocks into multi-concat blocks to enhance the model’s spatial perception and feature diversity during training. …”
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Micro, Small or Medium, New or Old—Are There Differences? Testing Business-Specific Difficulties by Mihaela Brîndușa Tudose, Savin Dorin Ionesi, Ionuț Dulgheriu, Liliana Buhu, Valentina Diana Rusu

“…To formulate general conclusions or predictions, in economic research, large databases are often used, related to more or less homogeneous samples, without taking into account the spatial or structural differences of the analysed processes or phenomena. …”
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Extended Kalman filter on sparse identification of nonlinear systems: application to the SoC estimation of a phase change material-based energy storage by Mustapha Habib, Youssef Elomari, Felix Hochwallner, Adam Buruzs, Tilman Barz, Qian Wang

“…Since SoC is not a direct measurement, there is a need for highly accurate prediction models. In this article, we propose solving this challenge by employing sparse identification of nonlinear dynamics (SINDy) to unlock the nonlinear dynamic complexity of PCM-TES. …”
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Individualizing glioma radiotherapy planning by optimization of a data and physics-informed discrete loss by Michal Balcerak, Jonas Weidner, Petr Karnakov, Ivan Ezhov, Sergey Litvinov, Petros Koumoutsakos, Tamaz Amiranashvili, Ray Zirui Zhang, John S. Lowengrub, Igor Yakushev, Benedikt Wiestler, Bjoern Menze

“…We present the Glioma Optimizing the Discrete Loss (GliODIL) framework, which infers the full spatial distribution of tumor cell concentration from available multi-modal imaging, leveraging a Fisher-Kolmogorov type physics model to describe tumor growth. …”
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Joint Inversion of InSAR and GNSS for surface subsidence and terrestrial water storage anomalies of small-area in west-central Yunnan Province, China by Ming Shangguan, Jingyi Guo, Shuguang Wu, Xu Zhou, Rong Zou, Xin Zhang

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Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles by Pengcheng Ma, Shuai Zhang, Bin Zhou, Wenqi Shao, Haowen Li, Tengfei Ma, Dong Guo

“…The article proposes a vehicle power exchange demand-oriented power exchange station siting planning scheme to meet the rapid replenishment demand of operating vehicles in urban areas. The spatial and temporal distribution of power exchange demand is predicted by considering the operation law, driving law, and charging decision of drivers; the candidate sites of power exchange stations are determined based on the data of power exchange demand; the optimization model of the site selection of power exchange stations with the lowest loss time of vehicle power exchange and the lowest cost of the planning and construction of power exchange stations is established and solved by using the joint algorithm of MLP-NSGA-II; and the optimization model is compared with the traditional genetic algorithm (GA) and the Density Peak. …”
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Rugged terrain and rigid hierarchy by Gen Tsudaka, Margaux N.A. Wienk, Jana B. Berkessel, Cynthia Boo

“…In Study 1 (78 countries; N = 156,658), we combined cross-national survey data from the European Values Study/World Values Survey with digital elevation models. Results demonstrated that national preferences for military rule and for a strong leader (who bypasses democratic processes) were higher in countries with more rugged terrain, even after controlling for economic factors, demographic indices, and spatial autocorrelation. …”
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Seismic Facies Classification of Salt Structures and Sediments in the Northern Gulf of Mexico Using Self-Organizing Maps by Silas Adeoluwa Samuel, Camelia C. Knapp, James H. Knapp

“…While conventional techniques like core analysis and well logs provide limited spatial reservoir information, seismic data can offer valuable 3D insights into fluid and rock properties away from the well. …”
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Analysis of temperature field evolution in ground freezing construction of twin tunnels in a coastal urban area by Tingfen Ye, Jun Hu, Jie Zhou, Huajing Gan, Lei Huang, Xinmin Shang

“…However, in the case of twin-tunnel (or two-lane tunnel) projects, accurately predicting the temperature field during the freezing process remains a critical challenge. …”
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SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…However, due to the lack of smoke and fire image matting datasets for model training, existing image matting methods exhibit significant errors in predicting the alpha values of smoke and fire targets, leading to unrealistic composite images. …”
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