The Impacts of Micro‐Porosity and Mineralogical Texture on Fractured Rock Alteration by Qian Zhang, Yanhui Dong, Sergi Molins, Hang Deng

“…Considerations of surface roughness with characteristic length on the same order of magnitude as mineral texture did not change the overall development of AL, which further highlights the importance of accounting for rock matrix properties in predicting long‐term evolution of fractured media. The resulting spatial variations of ALs and their impacts on bulk properties, however, are expected to be further complicated by the coupling of chemical and mechanical processes, and may trigger matrix disaggregation, erosion and other mechanisms of fractured media alteration.…”
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Study on Lightweight Bridge Crack Detection Algorithm Based on YOLO11 by Xuwei Dong, Jiashuo Yuan, Jinpeng Dai

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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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Pyramidal attention-based T network for brain tumor classification: a comprehensive analysis of transfer learning approaches for clinically reliable and reliable AI hybrid approach... by Tathagat Banerjee, Prachi Chhabra, Manoj Kumar, Abhay Kumar, Kumar Abhishek, Mohd. Asif Shah

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SIMULATION OF VINPOCETINE RELEASE PROCESS FROM MICROCAPSULES WITH HYDROPHOBIC SHELL by Yu. A. Polkovnikova, A. A. Glushko, I. Yu. Mikhailovskaya, Yo. S. Karieva

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Evolution Law of Longitudinal Deformation Curve and Release Coefficient of Viscoelastic Rock by WANG Jiachen, MENG Lingzan, ZHANG Dingli, LU Song, WEN Ming

“…Empirical formulas are fitted for the longitudinal deformation curve, including time, spatial, and spatiotemporal factors. The research conclusion can provide a more convenient method for predicting the deformation of soft rock tunnels.…”
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Decoupling Urban Street Attractiveness: An Ensemble Learning Analysis of Color and Visual Element Contributions by Tao Wu, Zeyin Chen, Siying Li, Peixue Xing, Ruhang Wei, Xi Meng, Jingkai Zhao, Zhiqiang Wu, Renlu Qiao

“…To address this gap, this study employs semantic segmentation and color computation on a massive street-view image dataset encompassing 56 cities worldwide, comparing eight machine learning models in predicting Visual Aesthetic Perception Scores (VAPSs). …”
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Metaverse and Digital Twins in the Age of AI and Extended Reality by Ming Tang, Mikhail Nikolaenko, Ahmad Alrefai, Aayush Kumar

“…As digital environments mature, architects are uniquely positioned to shape these dual-purpose ecosystems, leveraging AI, XR, and spatial computing to fuse data-driven models with immersive and user-centered experiences.…”
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SPL-YOLOv8: A Lightweight Method for Rape Flower Cluster Detection and Counting Based on YOLOv8n by Yue Fang, Chenbo Yang, Jie Li, Jingmin Tu

“…The proposed model effectively detects rape flower clusters with minimal computational overhead, offering technical support for yield prediction and elite cultivar selection in rapeseed breeding.…”
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Estimation of Soil Salinity by Combining Spectral and Texture Information from UAV Multispectral Images in the Tarim River Basin, China by Jiaxiang Zhai, Nan Wang, Bifeng Hu, Jianwen Han, Chunhui Feng, Jie Peng, Defang Luo, Zhou Shi

“…Spatial distribution maps of soil salinity were then generated for each model. …”
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AAMS-YOLO: enhanced farmland parcel detection for high-resolution remote sensing images by Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang

“…To improve detection accuracy in these contexts, this study proposes AAMS-YOLO, a YOLO-based farmland parcel detection model. In the feature extraction stage, the model incorporates an Adaptive Mix Attention (AMA) Block, balancing robust feature extraction with low computational overhead through spatial mixing and Efficient Multi-Scale Attention (EMA). …”
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Health classification of pumps using transformer-based deep learning by Arunachalam Shivaa T V, Jayaprasanth Devakumar, Arunshankar Jayabalan

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Boosting Cognitive Focus via Attention Types Detection using Brain-Computer Interfaces: A Pilot Study by Mihai-Robert BEU, Tudor DURDUMAN-BURTESCU, David GHEORGHICĂ ISTRATE

“…Results demonstrated a 57% concentration increase in AR versus VR (where participants performed identical tasks in a non-adaptive virtual environment) with personality-tailored models boosting classification accuracy by 10%. High-performing classifiers (e.g., Deep Neural Networks, XGBoost) achieved 87% accuracy, underscoring BCIs’ potential for personalized cognitive interventions in education and therapy. …”
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LoadSeer: Exploiting Tensor Graph Convolutional Network for Power Load Forecasting With Spatio-Temporal Characteristics by Jiahao Zhang, Bin Yu, Hanbin Lai, Lin Liu, Jinghui Zhou, Fengliang Lou, Yili Ni, Yan Peng, Ziheng Yu

“…Existing spatio-temporal prediction methods can only handle one factor in each dimension of time and space. …”
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Using electro-inductive sensor to trace moving and non-moving objects tracked by S. S. Kolmogorova, S. V. Biryukov

“…The research carries out a spatial model of path tracking using the dynamic parameters of the object's position, as well as the path of motion of electric field source. …”
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UAV-Based Remote Sensing Monitoring of Maize Growth Using Comprehensive Indices by Tingrui Yang, Jinghua Zhao, Ming Hong, Mingjie Ma, Shijiao Ma, Yingying Yuan

“…SHAP analysis revealed that GNDVI contributed most significantly to the predictive accuracy of the growth model. Spatial imaging distribution of maize inversion using the optimal CGMICT-RF model revealed discernible differences in overall crop growth. …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…This design reduces the computational complexity from quadratic to linear while preserving spatial context awareness. XFCOS enhances the original TSP-FCOS (Transformer-based Set Prediction with FCOS) model by integrating XFA into the transformer encoder, creating a CNN-ViT hybrid architecture, significantly reducing computational costs without sacrificing accuracy. …”
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Uncovering the importance of soil type, landscape connectivity, and pedodiversity for nature’s contributions to people in a typical agricultural region by Guangyi Deng, Haibo Jiang, Yang Wen, Chunguang He, Lianxi Sheng, Dehai Gu, Shuai Ma

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Mapping the invasive Spartina alterniflora in sub-meter level with improved phenological spectral features and deep learning method by Bingfeng Zhou, Meng Xu, Jinyan Tian, Yue Huang, Jie Song, Lin Zhu, Xiumin Zhu, Xinyuan Qu, Liyan Zhang, Xiaojuan Li, Huili Gong

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Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence. by Andrea L Araujo Navas, Nicholas A S Hamm, Ricardo J Soares Magalhães, Alfred Stein

“…<h4>Background</h4>Spatial modelling of STH and schistosomiasis epidemiology is now commonplace. …”
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