Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East by Younes Khosravi, Taha B.M.J. Ouarda, Saeid Homayouni

“…The results indicate that Stacking-EML not only significantly improves prediction accuracy compared to individual models and traditional CMIP6 outputs but also enhances climate projections by integrating multiple ML models, offering more reliable, regionally refined forecasts. …”
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Advancing resilient power systems through hierarchical restoration with renewable resources by Mohannad Alhazmi, Peijin Li

“…At the upper level, Graph Neural Networks (GNNs) are used to predict fault locations and optimize network topology by analyzing the spatial and topological features of the grid. …”
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Numerical Solution of Binary Liquid-Phase Adsorption onto Porocel Clay Using Linear, Freundlich and Langmuir Isotherms by Olaosebikan A. Olafadehan, Alfred A. Susu

“…A computational scheme for the solution of the model equations is presented. The scheme is based on orthogonal collocation for spatial discretization of the resulting set of coupled hyperbolic and parabolic partial differential equations for the macro-and micro-system, respectively. …”
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Improving imperfect data from health management information systems in Africa using space-time geostatistics. by Peter W Gething, Abdisalan M Noor, Priscilla W Gikandi, Esther A A Ogara, Simon I Hay, Mark S Nixon, Robert W Snow, Peter M Atkinson

“…The resulting complete set can then be used to define treatment burdens for presumed malaria at any level of spatial and temporal aggregation. Validation of the model has shown that these burdens are quantified to an acceptable level of accuracy at the district, provincial, and national scale.…”
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Research on an Ecological Sensitivity Evaluation of Mountain-Type National Parks Under Multi-Modal Optimization: A Case Study of Shennongjia, China by Xingyu Zhou, Huan Huang, Shi Dai, Duanya Zheng, Jie Zhao

“…The results demonstrate that the refined data structure enhances terrain coupling accuracy by transitioning from “Vegetation Type—Runoff Coefficient” to “Vegetation Density—Runoff Coefficient” conversions, with the optimized model exhibiting superior sensitivity in spatial element identification. …”
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Seasonal Early Warning of Impacts of Harmful Algal Blooms on Farmed Shellfish in Coastal Waters of Scotland by O. Stoner, T. Economou, A. R. Brown

“…Through a comprehensive yearly prediction experiment, we demonstrate considerable skill in predicting the impact of unseen HAB seasons at a regional level.…”
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PKA regulation of neuronal function requires the dissociation of catalytic subunits from regulatory subunits by Weihong Xiong, Maozhen Qin, Haining Zhong

“…However, the spatiotemporal dynamics of endogenous PKA upon activation remain debated. The classical model predicts that PKA catalytic subunits dissociate from regulatory subunits in the presence of cAMP, whereas a second model proposes that catalytic subunits remain associated with regulatory subunits following physiological activation. …”
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Colonization in North American Arid Lands: The Journey of Agarito (Berberis trifoliolata) Revealed by Multilocus Molecular Data and Packrat Midden Fossil Remains. by Diego F Angulo, Leonardo D Amarilla, Ana M Anton, Victoria Sosa

“…The most important prediction of packrat middens palaeomodelling lies in the Mexican Plateau, a finding congruent with current and past niche modelling predictions for agarito and genetic results. …”
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Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants by Jiayun JI, Xiao XIAO, Pinlu YANG, Yang LIU, Yahong ZHOU

“…To overcome this, two neural network models—GA-BP and standard BP—were applied to predict Mn2+ concentrations at unsampled locations. …”
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A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research by Md. Rajaul Karim, M. M. Mahbubul Syeed, Ashifur Rahman, Khondkar Ayaz Rabbani, Kaniz Fatema, Razib Hayat Khan, Md Shakhawat Hossain, Mohammad Faisal Uddin

“…This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.…”
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Network-based multi-omics integrative analysis methods in drug discovery: a systematic review by Wei Jiang, Weicai Ye, Xiaoming Tan, Yun-Juan Bao

“…Future developments should focus on incorporating temporal and spatial dynamics, improving model interpretability, and establishing standardized evaluation frameworks.…”
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MeDML: Med-Dynamic Meta Learning - A multi-layered representation to identify provider fraud in healthcare by Nitish Kumar, Deepak Chaurasiya, Alok Singh, Siddhartha Asthana, Kushagra Agarwal, Ankur Arora

“…We test the dynamically generated meta embedding using various downstream models and show that it outperforms all baseline algorithms for provider fraud prediction task.…”
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Cross-modal interactive and global awareness fusion network for RGB-D salient object detection. by Runqing Li, Ling Yu, Zijian Jiang, Fanglin Niu

“…It outperforms salient object detection methods that rely solely on RGB images by leveraging the geometric morphology and spatial layout information from depth images. However, the existing RGB-D detection model still encounters difficulties in accurately recognising and highlighting salient objects when facing complex scenes containing multiple or small objects. …”
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Beyond surveys: high-resolution mapping of rural wealth in China using satellite and street view imagery by Weipan Xu, Qiumeng Li, Yaofu Huang, Yu Gu, Xun Li

“…Centered on the intelligent interpretation of rural housing features, we extract wealth-related visual elements from imagery and regress them against benchmark survey-based household wealth indicators to develop a high-accuracy township-level wealth prediction model (R² = 71%). This model is used to generate a nationwide, township-scale rural household wealth map. …”
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Voronoi tessellation captures very early clustering of single primary cells as induced by interactions in nascent biofilms. by Iris Hödl, Josef Hödl, Anders Wörman, Gabriel Singer, Katharina Besemer, Tom J Battin

“…Model predictions match empirical observations reasonably well, highlighting the role of biotic interactions even already during very early biofilm formation despite few and distant cells. …”
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Optimization for Metro Operation Scheme of Suburban Lines: A New Method for Dealing with the Imbalanced Passenger Flow by Xiaobing Ding, Gan Shi, Jiangang Jin, Lixing Yang, Zhigang Liu

“…First, a time-stamped data cropping strategy based on fine-grained time zones as the grid index is developed, which is used to deeply explore the OD spatiotemporal representation of passenger flow correlation mapping mechanism based on multisource data; then, the calculation model of the proportion of trains matching with the OD temporal and spatial characteristics of suburban passenger flow are constructed, and an efficient solution algorithm is developed to solve the problem of interest. …”
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CapSurv: Capsule Network for Survival Analysis With Whole Slide Pathological Images by Bo Tang, Ao Li, Bin Li, Minghui Wang

“…The results illustrate the proposed CapSurv model has the ability to improve the performance of the prediction by comparing with state-of-the-art survival models.…”
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Inter-annual cascade effect on marine food web: A benthic pathway lagging nutrient supply to pelagic fish stock. by Lohengrin Dias de Almeida Fernandes, Eduardo Barros Fagundes Netto, Ricardo Coutinho, PELD-RECA

“…These sequential events can explain major changes in ecosystem food web that were not predicted in previous short-term models.…”
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Gene circuit analysis of the terminal gap gene huckebein. by Maksat Ashyraliyev, Ken Siggens, Hilde Janssens, Joke Blom, Michael Akam, Johannes Jaeger

“…We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. …”
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Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning by Shahed Rezaei, Kianoosh Taghikhani, Alexandre Viardin, Reza Najian Asl, Ali Harandi, Nikhil Vijay Jagtap, David Bailly, Hannah Naber, Alexander Gramlich, Tim Brepols, Mustapha Abouridouane, Ulrich Krupp, Thomas Bergs, Markus Apel

“…Abstract Fast prediction of microstructural responses based on realistic material topology is vital for linking process, structure, and properties. …”
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