Identification of Spatial Influencing Factors and Enhancement Strategies for Cultural Tourism Experience in Huizhou Historic Districts by Yue Yang, Shaoshan Du, Yang Xiao

“…By integrating multi-source data such as geographic information and Dianping reviews and applying the Partial Least Squares Regression (PLSR) statistical method, this study measures the correlation between the spatial morphology of Huizhou historic districts and cultural tourism experience indicators, identifying spatial influencing factors affecting cultural tourism experiences. …”
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Spatial distribution of emissions, temperatures, and particulate matter in a combustion zone of a pellet boiler by Alexander Backa, Radovan Nosek, Nikola Čajová Kantová, Sławomir Sładek

“…This study investigates the spatial distribution of PM and gaseous emissions within the combustion chamber of a small-scale pellet boiler. …”
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Spatial–Temporal Hotspot Management of Photovoltaic Modules Based on Fiber Bragg Grating Sensor Arrays by Haotian Ding, Rui Guo, Huan Xing, Yu Chen, Jiajun He, Junxian Luo, Maojie Chen, Ye Chen, Shaochun Tang, Fei Xu

“…Here, our research reports a spatial–temporal hot spot management system integrated with fiber Bragg grating (FBG) temperature sensor arrays and cooling hydrogels. …”
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Spatial-temporal patterns and attribution of evapotranspiration in the Middle Yellow River Basin under changing environments by Bo Liu, Shouzhang Peng, Yongxia Ding, Qinggong Han

“…Therefore, it is urgent to investigate the contributions of climate and underlying surface changes to ET and its components variations, along with the influencing factors on spatial distribution. This study investigated the spatial-temporal patterns of ET, transpiration (T), and transpiration fraction (TF) in the MYRB and conducted an attribution analysis of their spatial distribution and temporal dynamics, utilizing the parameter-calibrated SiB2 model. …”
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GNNWR: an open-source package of spatiotemporal intelligent regression methods for modeling spatial and temporal nonstationarity by Z. Yin, J. Ding, Y. Liu, R. Wang, Y. Wang, Y. Chen, J. Qi, S. Wu, Z. Du

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Acquisition of Crop Spatial Patterns Based on Remote Sensing Data from Sentinel-2 Satellite by Yinan Wang, Kai Guo, Xiangbing Kong, Jintao Zhao, Buhui Chang, Chunjing Zhao, Fengying Jin

“…Utilizing the characteristic representation of the Normalized difference vegetation index (NDVI) temporal data from Sentinel-2 satellite imagery, a multi-scale segmentation of patches is conducted based on spatiotemporal fusion images. Decision tree classification rules are constructed through the analysis of crop phenological differences, facilitating the extraction of the crop spatial patterns (CSPs) in the two provinces. …”
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Single-Shot, Monochrome, Spatial Pixel-Encoded, Structured Light System for Determining Surface Orientations by Ahsan Elahi, Qidan Zhu, Jun Lu, Umer Farooq, Ghulam Farid, Muhammad Bilal, Yong Li

“…This study introduces a technique for determining surface orientations by projecting a monochrome, spatial pixel-encoded pattern and calculating the surface normals from single-shot measurement. …”
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Spatial analysis of COVID-19 incidence and mortality rates in northwest iran for future epidemic preparedness by Mohsen Soleimani, Ahmad Jalilvand

“…Using data from 39,739 hospitalized COVID-19 cases recorded between February 2020 and September 2021, sourced from the Medical Care Monitoring Center, we conducted descriptive and geospatial analyses. Demographic, clinical, and spatial variables were analyzed using logistic regression and advanced spatial techniques, including Kernel Density Estimation and Local Moran’s I, to identify risk factors and disease hotspots. …”
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Marine object detection in forward-looking sonar images via semantic-spatial feature enhancement by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Nan Xu

“…Specifically, we introduce the competitive coordinate attention mechanism (CCAM) and the spatial group enhance attention mechanism (SGEAM), both integrated into the backbone network to effectively capture semantic and spatial features within sonar images, while feature fusion is employed to suppress complex marine background noise. …”
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Identifying urban spatial clusters via flow dynamics: a coupled tensor-based method by Zilong Zhao, Zihan Kan, Mei-Po Kwan, Luliang Tang

“…Revealing spatial clustering patterns among urban geographic units is crucial for synergistic regional development and integrated urban management. …”
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Modeling Spatial Distribution of Snow Water Equivalent Using Transfer Learning Across Mountainous Basins by Lama El Halabi, Utkarsh Mital, Dipankar Dwivedi

“…High operational costs of lidar observations limit the frequency and coverage of SWE estimates at high spatial resolutions, leading to significant data gaps. …”
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Improved YOLO-Based Pulmonary Nodule Detection with Spatial-SE Attention and an Aspect Ratio Penalty by Xinhang Song, Haoran Xie, Tianding Gao, Nuo Cheng, Jianping Gou

“…Yet, they frequently overlook spatial context and struggle to capture subtle variations in aspect ratios, which hinders their ability to detect small objects. …”
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Evaluation of the spatial distribution pattern of animal bites in Southern Iran: implications for public health interventions by Hossein Ghazanfarpour, Mohsen Pourkhosravani, Elaheh FallahLaleh-Zari, Ehsan Movahed

“…Accordingly, the present study was conducted to evaluate and analyze the spatial distribution of animal bites in Zahedan City. …”
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Population density, water supply, and the risk of dengue fever in Vietnam: cohort study and spatial analysis. by Wolf-Peter Schmidt, Motoi Suzuki, Vu Dinh Thiem, Richard G White, Ataru Tsuzuki, Lay-Myint Yoshida, Hideki Yanai, Ubydul Haque, Le Huu Tho, Dang Duc Anh, Koya Ariyoshi

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Spatial distribution and risk factors of Schistosoma haematobium and hookworm infections among schoolchildren in Kwale, Kenya. by Evans Asena Chadeka, Sachiyo Nagi, Toshihiko Sunahara, Ngetich Benard Cheruiyot, Felix Bahati, Yuriko Ozeki, Manabu Inoue, Mayuko Osada-Oka, Mayuko Okabe, Yukio Hirayama, Mwatasa Changoma, Keishi Adachi, Faith Mwende, Mihoko Kikuchi, Risa Nakamura, Yombo Dan Justin Kalenda, Satoshi Kaneko, Kenji Hirayama, Masaaki Shimada, Yoshio Ichinose, Sammy M Njenga, Sohkichi Matsumoto, Shinjiro Hamano

“…<h4>Methodology/principal findings</h4>We conducted a cross-sectional study of 368 schoolchildren from six primary schools. …”
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Spatial–Temporal Evolution of Ecological Network Structure During 1967–2021 in Yongding River Floodplain by Junyi Su, Minghao Wu, Zhicheng Liu

“…Using the Yongding River floodplain as a case study, this study applied morphological spatial pattern analysis, landscape connectivity metrics, and biodiversity assessments to identify core ecological source areas. …”
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Environmental factors affecting the BMI of older adults in the Philippines spatially assessed using machine learning by D.K. Mendoza, A.B. Araza, L.D. Groot, M. Mensink, R.C. Tan

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Exploring Road Traffic Accidents Hotspots Using Clustering Algorithms and GIS-Based Spatial Analysis by Hussien Kamh, Saleh H. Alyami, Afaq Khattak, Mana Alyami, Hamad Almujibah

“…This study conducts a comprehensive spatial analysis of road traffic accidents (RTAs) in Najran, a city emblematic of rapid urbanization in Saudi Arabia, which is facing significant public safety challenges due to an increase in vehicular traffic. …”
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Modeling the Ecological Network in Mountainous Resource-Based Cities: Morphological Spatial Pattern Analysis Approach by Liyun Zeng, Rita Yi Man Li, Hongzhou Du

“…It employs multiple data sets, including land use data, remote sensing images, Shuttle Radar Topography Mission (SRTM) digital elevation, vegetation coverage data, etc., to conduct the quantitative analysis. Five groups of spatial resolution datasets (i.e., 30 m, 60 m, 90 m, 150 m, and 300 m) are employed for comparison and selection through MSPA to identify and analyze core landscape types. …”
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A novel method of BiFormer with temporal-spatial characteristics for ECG-based PVC detection by Siyuan Chen, Zhen Wang, Hao Wang, Shuai Wang, Yang Li, Yang Li, Bing Wang

“…We then transformed the one-dimensional time-series signals into two-dimensional images using Markov Transition Fields (MTFs), considering state transition probabilities and spatial location information to comprehensively capture signal features. …”
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