Monitoring the Impacts of Human Activities on Groundwater Storage Changes Using an Integrated Approach of Remote Sensing and Google Earth Engine by Sepide Aghaei Chaleshtori, Omid Ghaffari Aliabad, Ahmad Fallatah, Kamil Faisal, Masoud Shirali, Mousa Saei, Teodosio Lacava

“…Although storage is conceptually a volumetric quantity, expressing it as depth allows for spatial comparison and enables conversion to volume by multiplying by the corresponding surface area.…”
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Spatiotemporal Distribution and Dispersal Pattern of Early Life Stages of the Small Yellow Croaker (<i>Larimichthys Polyactis</i>) in the Southern Yellow Sea by Xiaojing Song, Fen Hu, Min Xu, Yi Zhang, Yan Jin, Xiaodi Gao, Zunlei Liu, Jianzhong Ling, Shengfa Li, Jiahua Cheng

“…/m³), and the distribution areas varied between different months. The prediction of the model reveals the ecological adaptability of <i>L. polyactis</i> to temperature variations. …”
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First performance evaluation of easyPET.3D, a high-resolution and cost-effective benchtop preclinical PET scanner by Fabiana M. Ribeiro, Pedro M. C. C. Encarnação, Ana L. M. Silva, Pedro M. M. Correia, Afonso X. Pinto, Regina G. Oliveira, José Sereno, Mariana Lapo Pais, Antero Abrunhosa, Ismael F. Castro, Ana C. Santos, João F. C. A. Veloso

“…The performance characterization includes spatial resolution, sensitivity, count rate, scatter fraction (SF), and image quality (IQ) measurements. …”
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Cross-border impact of agricultural fertilizer use: Environmental spillovers and healthcare costs in European countries by Aleksandra Kuzior, Stanislav Vasylishyn, Vladyslav Hrei, Maksym Huzenko, Olena Akymenko, Oleksii Solohub, Tetiana Vasylieva

“…In contrast, the spatial error model best explained unsafe drinking water outcomes, highlighting the role of unobserved, spatially correlated environmental pressures. …”
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Knee Osteoarthritis Diagnosis: Future and Perspectives by Henri Favreau, Kirsley Chennen, Sylvain Feruglio, Elise Perennes, Nicolas Anton, Thierry Vandamme, Nadia Jessel, Olivier Poch, Guillaume Conzatti

“…Also, the use of Artificial Intelligence (AI) in the diagnosis seems essential to effectively develop and validate predictive models for KOA evolution, provided that a large and robust database is available. …”
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Chaperonin containing TCP1 subunit 5 as a novel pan-cancer prognostic biomarker for tumor stemness and immunotherapy response: insights from multi-omics data, integrated machine le... by Jiajun Li, Nuo Xu, Leyin Hu, Jiayue Xu, Yifan Huang, Deqi Wang, Feng Chen, Yi Wang, Jiani Jiang, Yanggang Hong, Huajun Ye

“…Furthermore, CCT5-high tumors exhibited immune-cold phenotypes, with reduced TILs and CD8⁺ T cell activity. The CCT5.Sig model, based on genes co-expressed with CCT5, achieved superior predictive accuracy for ICB response (AUC = 0.82 in validation and 0.76 in independent testing), outperforming existing pan-cancer signatures. …”
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Adapting Ensemble‐Calibration Techniques to Probabilistic Solar‐Wind Forecasting by N. O. Edward‐Inatimi, M. J. Owens, L. Barnard, H. Turner, M. Marsh, S. Gonzi, M. Lang, P. Riley

“…Typically, forecasts combine coronal model outputs with heliospheric models to predict near‐Earth conditions. …”
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Aerodynamic energy consumption analysis of divided evacuated tube transportation system by Ziwei Zhang, Yingxue Wang, Guanqing Wang, Feilong Li, Dengke Wang, Jianjun Luo

“…Theoretical discussions into reasonable parameter range including tube design and HST operation manners were conducted and then formed system-designing strategy. The spatial and temporal distribution law of tube gas circumstances were examined through model testing and numerical simulation. …”
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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

“…[Results and Discussions]The research findings confirmed the strong performance of the SIF reconstruction model in predicting soybean SIF. After simultaneously incorporating EVI, FPAR, and LST as explanatory variables to model, achieved a goodness of fit with an R2 value of 0.84, this statistical metric validated the model's capability in predicting SIF data, it also reflected that the reconstructed 8 d time resolution of SIF data's reliability of applying to small-scale agricultural crop photosynthesis research with 500 m×500 m spatial scale. …”
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Neuropsychological and clinical variables associated with cognitive trajectories in patients with Alzheimer's disease by Marianna Riello, Monica Moroni, Stefano Bovo, Flavio Ragni, Manuela Buganza, Raffaella Di Giacopo, Marco Chierici, Lorenzo Gios, Matteo Pardini, Matteo Pardini, Federico Massa, Federico Massa, Monica Dallabona, Elisa Vanzetta, Cristina Campi, Cristina Campi, Michele Piana, Michele Piana, Sara Garbarino, Manuela Marenco, Venet Osmani, Giuseppe Jurman, Antonio Uccelli, Antonio Uccelli, Bruno Giometto, Bruno Giometto, NeuroArtP3 Network, Filippo Gerli, Guido Pasquini, Claudia Niccolai, Matteo Betti, Emilio Portaccio, Maria Pia Amato, Rossi Andrea, Parodi Costanza, Ramaglia Antonia, Tortora Domenico, Severino Mariasavina, Andrea Falini, Antonella Castellano, Nicolò Pecco, Paola Scifo, Sonia Calloni

“…Model interpretability analysis revealed that the global cognitive state progression in AD patients is associated with: low spatial memory (Corsi block-tapping), verbal episodic long-term memory (Babcock's story recall) and working memory (Stroop Color) performances, the presence of hypertension, the absence of hypercholesterolemia, and functional skills inabilities at the IADL scores at baseline.ConclusionThis is the first AI study to predict cognitive trajectories of AD patients using routinely collected clinical data, while at the same time providing explainability of factors contributing to these trajectories. …”
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Leveraging U-Net and ASPP for effective fault detection in photovoltaic modules by Khalfalla Awedat, Masoud Alajmi, Mustafa Elfituri

“…The U-Net-ASPP_Cent model is particularly effective for central anomaly detection, while the U-Net-ASPP_Diag model excels at identifying directional faults such as cracks. …”
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Low-Carbon-Economic Collaborative Optimal Dispatching of Microgrid Considering Electricity-Hydrogen Integration by Lingling TAN, Wei TANG, Dongqing CHU, Zihan YU, Xingquan JI, Yumin ZHANG

“…In the low-carbon demand response model, with the saved carbon emission costs by reduced carbon emissions of microgrid users as an incentive signal, a mapping relationship between energy flow and carbon emission flow of microgrid is established to realize the transfer and allocation of carbon emission responsibilities and fine evaluation of carbon emission characteristics of microgrid operations, so as to establish a low-carbon DR model which guides users to participate in carbon emission reduction strategies according to the spatial and temporal differences of load carbon emission intensity, and to deeply explore the synergy between low-carbon and economy of source-load of microgrid. …”
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Improved landslide susceptibility assessment: A new negative sample collection strategy and a comparative analysis of zoning methods by Jiani Wang, Yunqi Wang, Manyi Li, Zihan Qi, Cheng Li, Haimei Qi, Xiaoming Zhang

“…In order to assess the impact of various negative sample collection strategies on the prediction accuracy of the landslide susceptibility assessment (LSA) model, and to investigate the effectiveness of landslide susceptibility zoning methods. …”
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Mapping potential water repellency of Danish topsoil by Lucas Carvalho Gomes, Peter Lystbæk Weber, Cecilie Hermansen, Anne-Cathrine Storgaard Danielsen, Sebastian Gutierrez, Deividas Mikstas, Charles Pesch, Mogens Humlekrog Greve, Per Moldrup, David A. Robinson, Lis Wollesen de Jonge

“…This study presents a comprehensive survey of SWR in Denmark and its predicted spatial distribution, using approximately 7,500 samples. …”
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Characteristics and mechanisms of soil salinization in humid climate areas by Chunrui Wu, Xinqiang Du, Bo Meng, Hui Guo

“…Study region: The Sanjiang Plain, China Study focus: Using 509 field-collected soil samples and multi-source remote sensing data (Landsat and Sentinel-2) as model inputs, among several machine learning methods tested, the XGBoost model was identified as the most effective and was used to construct a soil salinization inversion model, revealing the spatiotemporal evolution of soil salinization from 1992 to 2022. …”
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Enhancing Sea Ice Concentration Resolution in a Northern Sea Route Strait Using a Generative Adversarial Network by M. L. Rocha, A. H. Lynch, K. J. Bergen

“…However, typical climate model spatial resolutions limit the capacity to represent Arctic straits accurately. …”
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A Ship’s Maritime Critical Target Identification Method Based on Lightweight and Triple Attention Mechanisms by Pu Wang, Shenhua Yang, Guoquan Chen, Weijun Wang, Zeyang Huang, Yuanliang Jiang

“…The experimental results show that the average accuracy of this method in identifying seven types of targets—including buoys, bridges, islands and reefs, container ships, bulk carriers, passenger ships, and other ships—reached 92.1%, with a 12% reduction in the number of parameters. This enhancement improves the model’s ability to recognize and distinguish different targets and buoy colors.…”
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Graph-based analysis of histopathological images for lung cancer classification using GLCM features and enhanced graph by Imam Dad, JianFeng He, Zulqarnain Baloch

“…Our methodology leverages Gray-Level Co-occurrence Matrix (GLCM) features to quantify tissue texture, constructs a Sparse Cosine Similarity Matrix (SCSM) to model spatial relationships, and employs DeepWalk embeddings to capture topological patterns. …”
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Gait-based Parkinson’s disease diagnosis and severity classification using force sensors and machine learning by Navita, Pooja Mittal, Yogesh Kumar Sharma, Anjani Kumar Rai, Sarita Simaiya, Umesh Kumar Lilhore, Vimal Kumar

“…The proposed dual-stage model utilized a hypertuned Random Forest Tree (RFT) to classify the subjects into PD and non-PD classes at Stage 1 and a hypertuned Ensemble Regressor (ER) to predict the severity of illness at Stage 2. …”
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Responsiveness to the Effect of Fluoxetine in Male and Female Rats Exposed to Single Prolonged Stress: A Behavioral, Biochemical, Molecular and Histological Study by Reza Eshaghi-Gorji, Sareh Rashidi, Sakineh Shafia, Fereshteh Talebpour Amiri, Mansoureh Mirzae, Moslem Mohammadi

“…Conclusion: We observed that male and female rats with PTSD, show a reduction of the levels of serum IGF-1, impaired spatial memory in a recognition location memory task and enhanced apoptotic-related factors expression in the hippocampus, and decreased hippocampal dendritic branches. …”
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