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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Spatiotemporal Differences in Dominants of Dryness/Wetness Changes in Southwest China by Shujia Zhou, Shanlei Sun, Wanrong Shi, Jiazhi Wang, Jinjian Li, Guojie Wang, Weiping Lou

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Multi-Scale Self-Attention-Based Convolutional-Neural-Network Post-Filtering for AV1 Codec: Towards Enhanced Visual Quality and Overall Coding Performance by Woowoen Gwun, Kiho Choi, Gwang Hoon Park

“…The objective is to address two persistent artifact issues observed in our previous MTSA model: visible seams at patch boundaries and grid-like distortions from upsampling. …”
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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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Coinfection of hepatitis B, tuberculosis, and HIV/AIDS in Beijing from 2016 to 2023: a surveillance data analysis by Chao Wang, Yunping Shi, Yang Liu, Ying Zhou, Jing Du, Xiao Hu, Wei Li, Jiaze Li, Yanlin Gao, Gang Li

“…The multivariate logistic model shown that males were more susceptible to be coinfected (ORs ranged from 1.50 to 27.81). …”
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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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Enhancing flood susceptibility mapping in Sana’a, Yemen with random forest and eXtreme gradient boosting algorithms by Yahia Alwathaf, Ahmed M. Al-Areeq, Yousef A. Al-Masnay, Ali R. Al-Aizari, Nabil M. Al-Areeq

“…Both models demonstrated high accuracy in predicting flood-prone areas, with RF achieving an accuracy of 92% and XGBoost slightly outperforming it with an accuracy of 94%. …”
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Pathways to Turbulent Dissipation in a Submarine Canyon by Charlotte Bellerjeau, Matthew H. Alford, Arnaud Le Boyer, Giovanni Dematteis, Alberto Naveira Garabato, Gunnar Voet, Nicole Couto, Bethan L. Wynne‐Cattanach

“…Fluxes from both methods agree within a factor of 3 with dissipation estimates from a finescale parameterization which is often used in climate‐scale ocean models. Coarse graining predicts 68% of energy fluxing to dissipation from frequencies lower than 8cpd, while the weakly nonlinear method predicts 34%. …”
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Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

“…The former can effectively balance the positive and negative samples to avoid over-learning of easy-to-classify samples during the training process; the latter successfully solves the problem of the failure of the detection method when there is no intersection between the prediction frame and the real detection frame, which significantly improves the robustness of the model. …”
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Vision transformer-based diagnosis of lumbar disc herniation with grad-CAM interpretability in CT imaging by Qingsong Chu, Xingyu Wang, Hao Lv, Yao Zhou, Ting Jiang

“…The performance of the model was further validated via gradient-weighted class activation mapping (Grad-CAM), providing interpretable insights into the regions of the CT scans that contributed to the model predictions. …”
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