Golden Chip-Free Hardware Trojan Detection Using Attention-Based Non-Local Convolution With Simple Recurrent Unit by Rama Devi Maddineni, Deepak Ch

“…The emergence of machine learning and deep learning models has enhanced the feasibility of hardware Trojan detection, as these models can learn complex patterns and representations from extensive datasets. …”
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Evolution of “Production–Living–Ecological” Spaces Conflicts and Their Impacts on Ecosystem Service Values in the Farming–Pastoral Ecotone in Inner Mongolia During Rapid Urbanizati... by Ziqi Yu, Xi Meng, Gongjue Yu

“…Notably, industrial production space activities experienced the most significant increase, amounting to 277.09%. (2) Regional spatial conflict intensity shows an upward trend from 2000 to 2020, with the average conflict level increasing from 0.53 to 0.56, and high conflict values being concentrated in the east. (3) The ESV pattern in the FPE in Inner Mongolia is characterized by “high ESV in the east and low ESV in the central and western regions”, with an overall trend of increasing and then decreasing. …”
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Assessment of the coordinated relationship between blue-green space and urbanization in coastal mountain cities based on spatiotemporal evolution analysis: A case study in Qingdao,... by Chao Li, Siyan Yue, Xin Liu, Huan Dai, Xingyu Li

“…Spatially, the coupling degree between the systems had a strong difference and agglomeration, showing the general characteristic of “High in the center, low in the north and south, and decreasing inward from the coast”, which was more spatially consistent with the level of urbanization. …”
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Spatiotemporal evolution and trend prediction of coupled coordination between digital technology and manufacturing green transformation from provinces in China by Xin Huang, Xin Huang, Hongbing Deng, Hongbing Deng

“…The key findings of the study are as follows: (1) Digital technology and MGT have been progressing steadily in China, with continuous improvements in the level of development; (2) The degree of coupling coordination has shown consistent growth over the years, yet the distribution remains relatively uneven, exhibiting a “trapezoidal” spatial pattern with higher values in the eastern regions and lower values in the western regions; (3) Regional differences play a crucial role in the overall differences of the D-G system; and (4) The traditional Markov chain results show that the probability of the D‐G system maintaining the original state stage in the future is greater than 88.67%. …”
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How to Coordinate Urban Ecological Networks and Street Green Space Construction? Insights from a Multi-Scale Perspective by Shujun Hou, Ying Yu, Taeyeol Jung, Xin Han

“…This study examines the area within Chengdu’s Third Ring Road, employing the following methodologies: (1) constructing the regional ecological network using Morphological Spatial Pattern Analysis (MSPA), the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and circuit theory; (2) analyzing the street green view index (GVI) through machine learning semantic segmentation techniques; and (3) identifying key areas for the coordinated development of urban ecological networks and street green spaces using bivariate spatial correlation analysis. …”
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Connectivity and community structure of online and register-based social networks by Márton Menyhért, Eszter Bokányi, Rense Corten, Eelke M. Heemskerk, Yuliia Kazmina, Frank W. Takes

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Land use policy and green utilization efficiency in border cities: evidence from northeastern China’s carbon reduction practice by Xuncheng Fan, Lili Zhao

“…This study develops an innovative ’border location‐functional differentiation‐efficiency coupling‘ theoretical framework.MethodsUsing this foundation, we employ regression‐based path analysis and spatial analytical methods to evaluate the relationship between land use policies and green utilization efficiency across fourteen northeastern China border cities from 2010 to 2020.ResultsOur research reveals significant spatial heterogeneity in land use patterns. …”
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Will Wind Turbines Affect the Distribution of Alashan Ground Squirrel? Insights from Large-Scale Wind Farms in China by Yuan Wang, Wenbin Yang, Qin Li, Min Zhao, Ying Yang, Xiangfeng Shi, Dazhi Zhang, Guijun Yang

“…The burrow density distribution exhibited a multinuclear clustering pattern in both May and September, with a northwest–southeast spatial orientation. …”
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Deep Temporal and Structural Embeddings for Robust Unsupervised Anomaly Detection in Dynamic Graphs by Samir Abdaljalil, Hasan Kurban, Rachad Atat, Erchin Serpedin, Khalid Qaraqe

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Reservoir Stochastic Simulation Based on Octave Convolution and Multistage Generative Adversarial Network by Xuechao Wu, Wenyao Fan, Shijie Peng, Bing Qin, Qing Wang, Mingjie Li, Yang Li

“…Therefore, based on Generative Adversarial Networks (GANs), spatial distribution patterns of regional variables can be reproduced through high-order statistical fitting. …”
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Magnetotelluric Sampling and Geoelectric Hazard Estimation: Are National‐Scale Surveys Sufficient? by Benjamin S. Murphy, Greg M. Lucas, Jeffrey J. Love, Anna Kelbert, Paul A. Bedrosian, E. Joshua Rigler

“…However, we also find that the use of higher density MT data can in some areas lead to order‐of‐magnitude differences in line‐averaged electric field estimates at the level of individual transmission lines and can also yield significant differences in subregional hazard patterns. As we demonstrate using variogram plots, these differences reflect short‐spatial‐scale variability in Earth conductivity, which in turn reflects regional lithotectonic structure and history. …”
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MSDCA: A Multi-Scale Dual-Branch Network with Enhanced Cross-Attention for Hyperspectral Image Classification by Ning Jiang, Shengling Geng, Yuhui Zheng, Le Sun

“…Second, a multi-branch directional feature module (MBDFM) enhances the network’s sensitivity to directional patterns and long-range spatial relationships. It achieves this by applying axis-aware depthwise separable convolutions along both horizontal and vertical axes, thereby significantly improving the representation of spatial features. …”
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Analysis of the epidemiological characteristics of pulmonary tuberculosis in Shijiazhuang, China 2010–2023 by Xin Wang, Jianhua Guo, Jianhua Guo, Xiaojing Shi, Lihua Cui

“…BackgroundSpatio-temporal analysis is a key epidemiological tool for monitoring disease transmission and identifying outbreak hotspots. However, the patterns of pulmonary tuberculosis (PTB) spread over time and space in Shijiazhuang remain poorly understood. …”
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Optimizing Ecological Management in China: Insights from Chongqing’s Service Projections by Yang Duan, Wenjun Wu, Rufeng Xiao, Hongqiang Jiang, Bo Wang

“…This study focuses on Chongqing as a representative case to investigate spatial patterns, driving mechanisms, and future trajectories of ES supply–demand dynamics. …”
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Delineating potential DRT operating areas: An origin–destination clustering approach by Hussein Mahfouz, Malcolm Morgan, Eva Heinen, Robin Lovelace

“…This paper presents a method for identifying potential DRT service areas using spatial clustering of origin–destination (OD) flows. …”
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Study of harmful gas migration law and influencing factors after tunnel blasting in high-altitude tunnels under push ventilation conditions by Shigui Fu, Zegong Liu, Jinwei Qiu, Shuai Yang, Guodong Qiao, Gangjian An

“…To investigate the migration patterns of CO during the ventilation process following blasting in high-altitude tunnels, this paper employs a three-dimensional model of tunnel blasting excavation under push ventilation. …”
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Landscape analysis of m6A modification regulators reveals LRPPRC as a key modulator in tubule cells for DKD: a multi-omics study by Li Jiang, Hongda Yu, Jie Jian, Xulin Sai, Yudian Wang, Yufei Zhang, Xiai Wu

“…The significance of N6-methyladenosine (m6A) modification in the pathogenesis of DKD has become increasingly prominent.AimThis study aimed to investigate the specific expression patterns of the m6A geneset in the pathogenesis of DKD.MethodBulk RNA, single-cell and spatial transcriptome were utilized to clarify the hub gene. 3 types of machine learning algorithms were applied. …”
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Mapping Urban Villages in Beijing–Tianjin–Hebei Core Cities Through a Dual-Stage Fusion of Individual Building Footprints and Glimmer Imagery by Jianqiang Hu, Yuheng Fu, Chaoqun Zhang, Manchun Li, Bingbo Gao, Qiancheng Lv, Jing Yang, Ziyue Chen

“…Current research on UV identification often relies solely on high-resolution satellite imagery, neglecting the unique spatial patterns and socioeconomic characteristics of UVs, thus limiting the effective distinction between UVs and other confusing land-use types. …”
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The Coupling Coordination Degree and Spatio-Temporal Divergence Between Land Urbanization and Energy Consumption Carbon Emissions of China’s Yangtze River Delta Urban Agglomeration... by Zhengru Li, Yang Yu, Bo Liu, Xiaoyu Zhang, Tianyin Li, Nuo Shi, Yichen Ren

“…The carbon emission subsystem showed sustained stable decline, with a gradual reduction in the number of cities maintaining low carbon emission levels. (2) Temporally, the overall coupling coordination degree of the urban agglomeration system demonstrated an upward trend, progressing from severe imbalance to the primary coordination stage. (3) Spatially, significant regional differences in coupling coordination degree were observed, showing higher values in the southeastern areas compared to the northwestern regions. (4) Most areas exhibited no significant clustering characteristics in the coupling coordination degree between land urbanization and energy consumption carbon emissions, while the local spatial clustering patterns demonstrated temporal variations. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…<b>This approach struggles with accurately modeling complex patterns in high-resolution images and often results in redundant samples.…”
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