Experimental study on the influence of shale content in fault zone on fault friction coefficient based on circular shear test by Lingdong Meng, Dong Li, Xiaofei Fu, Yejun Jin, Zezhao Liu, Ziyang Li, Tong Zhang, Ruishan Du, Xiaoling Zhang

“…By integrating a 3D prediction model of clay content on fault surfaces, the spatial distribution of non-uniform friction coefficients across fault planes was determined. …”
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Detecting Changes in Soil Fertility Properties Using Multispectral UAV Images and Machine Learning in Central Peru by Lucia Enriquez, Kevin Ortega, Dennis Ccopi, Claudia Rios, Julio Urquizo, Solanch Patricio, Lidiana Alejandro, Manuel Oliva-Cruz, Elgar Barboza, Samuel Pizarro

“…A UAV-captured image was used to predict the spatial distribution of soil parameters, generating fourteen spectral indices and a digital surface model (DSM) from 103 soil plots across 49.83 hectares. …”
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Research Progress on Ambient Visual Information Analysis and Perception Measurement Methods for Motion Vision by Haipeng ZHU, Yuhang KONG, (JPN) OHNO Ryuzo

“…By integrating objective physical environment analysis with subjective perception evaluation, the research proposes a unified framework to explore the mechanisms linking built environments with spatial cognition, and predicts future research directions.MethodsThis research employs a comprehensive review methodology to examine the mechanisms of dynamic visual perception in urban public spaces. …”
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Bayesian integration of information in hippocampal place cells. by Tamas Madl, Stan Franklin, Ke Chen, Daniela Montaldi, Robert Trappl

“…Our results suggest that useful predictions regarding the firing fields of place cells can be made based on a single underlying principle, Bayesian cue integration, and that such predictions are possible using a remarkably small number of model parameters.…”
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Analysing factors underlying the reporting of established non-native species by Phillip J. Haubrock, Ismael Soto, Ross N. Cuthbert, Irmak Kurtul, Elizabeta Briski

“…We employ a series of broadscale national predictors classified into ‘research’, ‘economy’, ‘environment & culture’, and ‘land-use’ to predict successful establishment. Our null models, which assume the distribution of non-native species mirrors that of each predictor, accurately predicted non-native species numbers across European countries. …”
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Assemblies, synapse clustering, and network topology interact with plasticity to explain structure-function relationships of the cortical connectome by András Ecker, Daniela Egas Santander, Marwan Abdellah, Jorge Blanco Alonso, Sirio Bolaños-Puchet, Giuseppe Chindemi, Dhuruva Priyan Gowri Mariyappan, James B Isbister, James King, Pramod Kumbhar, Ioannis Magkanaris, Eilif B Muller, Michael W Reimann

“…We confirmed our testable predictions in the MICrONS datasets, an openly available electron microscopic reconstruction of a large volume of cortical tissue. …”
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Coordinate Attention Filtering Depth-Feature Guide Cross-Modal Fusion RGB-Depth Salient Object Detection by Lingbing Meng, Mengya Yuan, Xuehan Shi, Qingqing Liu, Le Zhange, Jinhua Wu, Ping Dai, Fei Cheng

“…Second, a dense decoder guidance module is proposed to recover the spatial details of salient objects. Furthermore, a context-aware content module is proposed to extract rich context information, which can predict multiple objects more completely. …”
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Climate change enhances soil fauna population and biomass in grasslands of the Loess Plateau by Xi Yang, Ming’an Shao, Tongchuan Li

“…Conservatively estimated, the number of soil fauna on the Loess Plateau exceeds 4 × 1015, with the estimated total biomass of 4 × 106 t, equivalent to 2 Mt carbon. In addition, model predictions indicate that soil fauna populations and biomass of grassland in the Loess Plateau increased 27% and 29%, from 2000 to 2022. …”
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Infection prevention and control measures during the COVID-19 pandemic and airborne tuberculosis transmission during primary care visits in South Africa by Nicolas Banholzer, Keren Middelkoop, Remo Schmutz, Juane Leukes, Kathrin Zürcher, Matthias Egger, Robin Wood, Lukas Fenner

“…These changes corresponded with a reduction in modeled Mtb transmission risk (0.04% vs 1.36%; P = 0.046). …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…InSAR techniques allow for high-precision measurements of surface deformation across large areas, making them invaluable in understanding and modeling subsidence patterns. When combined with machine learning approaches, these technologies offer even greater potential for developing predictive models and susceptibility maps, enabling proactive risk management. …”
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Scalable Clustering of Complex ECG Health Data: Big Data Clustering Analysis with UMAP and HDBSCAN by Vladislav Kaverinskiy, Illya Chaikovsky, Anton Mnevets, Tatiana Ryzhenko, Mykhailo Bocharov, Kyrylo Malakhov

“…We applied a combination of Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and Hierarchical Density-Based Spatial Clustering (HDBSCAN) for unsupervised clustering. …”
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Research on the application of magnetic separation technology for the removal of black powder in natural gas pipelines by Hongwei YANG, Tianyu ZHANG, Fang LIU, Zhen LIU, Junxian CHEN, Wengang YANG

“…MethodsA three-dimensional model was developed using the finite element simulation software COMSOL to replicate magnetic system matrices. …”
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Multi-Scenario Land Use and Carbon Storage Assessment in the Yellow River Delta Under Climate Change and Resource Development by Zekun Wang, Xiaolei Liu, Shaopeng Zhang, Xiangshuai Meng, Hongjun Zhang, Xingsen Guo

“…The results of the study show the following: (1) Over the past 30 years, the land use pattern of the YRD has generally extended toward the sea, with land use transitions mainly from grasslands (the largest reduction: 1096.20 km²), wetlands, reservoirs and ponds, and paddy fields to drylands, culture areas, construction lands, salt pans, and tidal flats. (2) Carbon storage in the YRD exhibits significant spatial heterogeneity. …”
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Assessment the Effects of Climate Change on the Degree of Heating and Cooling Days of Iran by Hasan Zolfaqari, Hamid Rahimi, Rohollah Oji

“…Downscaled output of three RCM models of CNRM، EC-Earth and GFDL, with the spatial resolutions of 0.44 degrees under two emissions trajectories (RCPs 4.5 and 8.5), are applied in this regard. …”
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FDI-VSR: Video Super-Resolution Through Frequency-Domain Integration and Dynamic Offset Estimation by Donghun Lim, Janghoon Choi

“…In this paper, we propose FDI-VSR, a novel framework that integrates spatiotemporal dynamics and frequency-domain analysis into conventional SISR models without extensive modifications. We introduce two key modules: the Spatiotemporal Feature Extraction Module (STFEM), which employs dynamic offset estimation, spatial alignment, and multi-stage temporal aggregation using residual channel attention blocks (RCABs); and the Frequency–Spatial Integration Module (FSIM), which transforms deep features into the frequency domain to effectively capture global context beyond the limited receptive field of standard convolutions. …”
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Wireless Authentication Method Based on Near-Field Feature Fusion Network by QIU Jiefan, ZHOU Kezhong, ZHU Dongfu, ZHANG Jinhong, CHI Kaikai

“…This fused feature vector was then processed by a linear classifier to perform probabilistic prediction, completing the identity recognition process. …”
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A 3 h, 1 km surface soil moisture dataset for the contiguous United States from 2015 to 2023 by H. Yang, J. Yang, T. E. Ochsner, E. S. Krueger, M. Xu, C. B. Zou

“…In this study, we developed a new 3 h, 1 km spatially seamless SSM dataset spanning 2015 to 2023, covering the entire contiguous United States (CONUS), using a spatio-temporal fusion model. …”
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Mapping Coastal Soil Salinity and Vegetation Dynamics Using Sentinel-1 and Sentinel-2 Data Fusion With Machine Learning Techniques by Wen Liu, Tiezhu Shi, Zhinian Zhao, Chao Yang

“…The analysis has been conducted for a coastal region in China, where derived features, such as normalized difference vegetation index (NDVI), salinity indices, and SAR-based soil moisture proxies, have been used as inputs to the CNN model. The model achieved an overall accuracy of 87% and a kappa coefficient of 0.82, outperforming traditional classification methods by leveraging spatial feature learning and data augmentation. …”
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Data-Driven Simulation of Pedestrian Movement with Artificial Neural Network by Weili Wang, Jiayu Rong, Qinqin Fan, Jingjing Zhang, Xin Han, Beihua Cong

“…This paper presents a pedestrian movement simulation model based on the artificial neural network, in which two submodels are, respectively, used to predict velocity displacement and velocity direction angle at each time step. …”
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Redox regulation and dynamic control of brain-selective kinases BRSK1/2 in the AMPK family through cysteine-based mechanisms by George N Bendzunas, Dominic P Byrne, Safal Shrestha, Leonard A Daly, Sally O Oswald, Samiksha Katiyar, Aarya Venkat, Wayland Yeung, Claire E Eyers, Patrick A Eyers, Natarajan Kannan

“…The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide-mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family.…”
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