GEOLOGICAL AND TOPOGRAPHICAL INFLUENCES ON HYDROGEOLOGY OF KENYAN MARBLE QUARRY AREAS, KAJIADO COUNTY, SW KENYA: POSSIBLE INDICATIONS FOR POLLUTION by Moses Ancho Isa, Charles Maina Gichaba, Aaron Kutukhulu Waswa

“…Patterns of spatial groundwater table elevation over the area show average correlation with surface elevation patterns. …”
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Graphical representation of landscape heterogeneity identification through unsupervised acoustic analysis by Maria J. Guerrero, Camilo Sánchez‐Giraldo, César A. Uribe, Víctor M. Martínez‐Arias, Claudia Isaza

“…While remote sensing images quantify landscape heterogeneity, they might fail to detect ecological patterns in moderately disturbed areas, particularly at minor spatial scales. …”
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Med-DGTN: Dynamic Graph Transformer with Adaptive Wavelet Fusion for multi-label medical image classification by Guanyu Zhang, Yan Li, Tingting Wang, Guokun Shi, Li Jin, Zongyun Gu, Zongyun Gu

“…To address these challenges, we propose Med-DGTN, a dynamically integrated framework designed to advance multi-label classification performance in clinical imaging analytics.MethodsThe proposed Med-DGTN (Dynamic Graph Transformer Network with Adaptive Wavelet Fusion) introduces three key innovations: (1) A cross-modal alignment mechanism integrating convolutional visual patterns with graph-based semantic dependencies through conditionally reweighted adjacency matrices; (2) Wavelet-transform-enhanced dense blocks (WTDense) employing multi-frequency decomposition to amplify low-frequency pathological biomarkers; (3) An adaptive fusion architecture optimizing multi-scale feature hierarchies across spatial and spectral domains.ResultsValidated on two public medical imaging benchmarks, Med-DGTN demonstrates superior performance across modalities: (1) Achieving a mean average precision (mAP) of 70.65% on the retinal imaging dataset (MuReD2022), surpassing previous state-of-the-art methods by 2.68 percentage points. (2) On the chest X-ray dataset (ChestXray14), Med-DGTN achieves an average Area Under the Curve (AUC) of 0.841. …”
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Quantitative assessment of factors that influence heat vulnerability in residential areas using machine learning and unmanned aerial vehicle by Jawoon Gu, Dongwoo Kim, Chulmin Jun, Seungwoo Son

“…High-resolution thermal imagery captured by unmanned aerial vehicles (UAVs) and interpretable machine learning (ML) techniques were used to model and analyze thermal patterns at the microscale. The study site, adjacent to a river and designated as an Urban Regeneration Area, is particularly vulnerable to summer heat.Exploratory data analysis (EDA) was conducted to examine statistical characteristics and spatial patterns, followed by confirmatory data analysis (CDA) using nonlinear regression models such as CatBoost, Random Forest, and XGBoost. …”
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An updated regional model skill assessment for seasonal and interannual variability of bottom temperature across the eastern Bering Sea shelf by Kelly A. Kearney, Phyllis J. Stabeno, Albert J. Hermann, Albert J. Hermann, Calvin W. Mordy, Calvin W. Mordy

“…We then use this combination of data to systematically assess the skill of the Bering10K ROMS model in capturing these features, focusing on spatial variability in skill metrics and the potential processes leading to these patterns. …”
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Climate‐associated variation in the within‐season dynamics of juvenile ticks in California by Samantha Sambado, Andrew J. MacDonald, Andrea Swei, Cheryl J. Briggs

“…We find that feeding patterns were variable and synchronous feeding of juvenile ticks on key blood meal hosts was associated with mean temperature. …”
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From Viewing to Structure: A Computational Framework for Modeling and Visualizing Visual Exploration by Kuan-Chen Chen, Chang-Franw Lee, Teng-Wen Chang, Cheng-Gang Wang, Jia-Rong Li

“…The framework’s applicability across different viewers was validated through consistent structural patterns observed across all three participants, while simultaneously revealing individual differences in their visual exploration strategies. …”
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Electric Power Consumption Forecasting Models and Spatio-Temporal Dynamic Analysis of China’s Mega-City Agglomerations Based on Low-Light Remote Sensing Imagery Incorporating Socia... by Cuiting Li, Dongmei Yan, Shuo Chen, Jun Yan, Wanrong Wu, Xiaowei Wang

“…This method provides a timely and accurate spatial update of EPC dynamics, offering fine-scale characterization of urban EPC patterns using night light images.…”
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Spatiotemporal Dynamics and Driving Mechanisms of Ecosystem Services in the Beijing–Tianjin–Hebei Urban Agglomeration: Implications for Sustainable Land Use Planning by Shuanqging Sheng, Jinchuan Huang

“…Furthermore, socioeconomic activities, particularly increasing population density, exhibited a growing negative impact on HQ and CS, highlighting the intensifying role of anthropogenic interventions in shaping ecosystem service patterns. This study unveils the spatial heterogeneity of ecosystem services and their driving mechanisms in the context of urbanization, offering valuable insights to inform regional ecological conservation and sustainable development policies.…”
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A spatiotemporal analysis of opioid prescriptions in Indiana from 2015 to 2019 by Paula A. Jaimes-Buitron, Nicole Adams, Nan Kong, Carolina Vivas-Valencia

“…While spatiotemporal analyses have explored aspects of the opioid crisis, spatiotemporal patterns of opioid prescribing have not been sufficiently studied. …”
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Shifting frontiers of nitrogen pollution: A multi-scale assessment of long-term anthropogenic nitrogen inputs across the Yellow River basin by Jincheng Li, Zhonghua Li, Qiang Wang, Yan Chen, Xinyue Zhang, Taher Kahil, Dor Fridman

“…The results show that the NANI increases by 108.9% over the study period, accompanied by a clear shift in spatial patterns. Nitrogen inputs grow most rapidly in historically low-input upstream areas, forming a “reverse growth” trend. …”
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A Geospatial Livestock-Carrying Capacity Model (GLCC) in the Akmola Oblast, Kazakhstan by Jiaguo Qi, Zihan Lin, Mark A. Weltz, Kenneth E. Spaeth, Gulnaz Iskakova, Jason Nesbit, David Toledo, Tlektes Yespolov, Maira Kussainova, Lyazzat K. Makhmudova, Xiaoping Xin

“…The modeling results showed distinct spatial patterns of LCC across the Oblast, reflecting variability in rangeland productivity with higher values concentrated in southern and southeastern regions (up to 0.5 animals/ha). …”
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On the Scales of Dynamic Topography in Whole‐Mantle Convection Models by M. Arnould, N. Coltice, N. Flament, V. Seigneur, R. D. Müller

“…The interplay between mantle convection and lithosphere dynamics generates a complex spatial and temporal pattern of dynamic topography consistent with constraints for Earth.…”
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Joint Classification of Hyperspectral and LiDAR Data via Multiprobability Decision Fusion Method by Tao Chen, Sizuo Chen, Luying Chen, Huayue Chen, Bochuan Zheng, Wu Deng

“…In the multifeature extraction module, the local texture features and spatial features of the image are extracted to consider the local texture and spatial structure of the image data. …”
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Harnessing Multi-Source Data and Deep Learning for High-Resolution Land Surface Temperature Gap-Filling Supporting Climate Change Adaptation Activities by Katja Kustura, David Conti, Matthias Sammer, Michael Riffler

“…Our approach addresses common challenges in satellite-derived LST data, such as gaps caused by cloud cover, image border limitations, grid-pattern sensor artifacts, and temporal discontinuities due to infrequent sensor overpasses. …”
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Comparison and Impact Factor Analysis of Ground PM2.5 Retrieved by Aqua and Himawari-8 Satellite Products in Guangdong, China by Tingyuan Li, Xuejiao Deng, Jingyang Chen, Jie Xu, Jin Shen

“…Abstract Fine particulate matter (particles sizes < 2.5 µm; PM2.5) concentrations can be obtained at high spatial resolutions using satellite remote sensing. …”
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Alterations in Suitable Cultivation Area for <i>Scutellaria baicalensis</i> under Future Climatic Scenarios in China: Geodetector-Based Prediction by Yuanyuan Yin, Jing’ai Wang, Wensheng Zhang, Benfeng Yin, Jixia Huang, Zijing Zhang

“…However, there is rare knowledge on the effect and interactive effect of different variables on the spatial heterogeneity of <i>S. baicalensis</i> and how the pattern of suitable cultivation area in China would shift in response to climate change. …”
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Assessing the potential for traffic carbon emission reductions through residential travel mode shifts: insights from massive vehicle trajectory data and scenario simulations by Shaoying Li, Shaoli Li, Shuyuan Xu, Hanwen Xu, Xuanting Chen, Quan Mu, Zhangzhi Tan

“…This highlights the importance of multimodal transport in reducing transportation-related carbon emissions. Regarding the spatial pattern, peripheral areas present substantial carbon reduction potential, accounting for nearly 50 % of the total. …”
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Mapping surface soil organic carbon in the coal–grain composite area: threshold and interaction effects of coal mining activities by Zhaoqi Wu, Xiangyang Feng, Yiyun Chen, Zihao Wu, Xinyu Bao, Xin Zou

“…Conclusions These results highlight the importance of introducing mining activities and considering threshold and interaction effects, which help to understand the spatial pattern of SOC in the coal–grain composite areas.…”
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The Role of a Smartphone Application in Monitoring the Risk of Hearing Loss Associated with Personal Listening Devices in Young Adults by Deniz Tuz, Selin Sariçamlik, Ceren Bodur, Gülce Kirazli, Pelin Piştav Akmeşe

“…All six participants who underwent audiological assessment exhibited normal hearing thresholds. However, a pattern of decline at high frequencies was noted. …”
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