Testing the sensitivity of Tract-Based Spatial Statistics to simulated treatment effects in preterm neonates. by Gareth Ball, James P Boardman, Tomoki Arichi, Nazakat Merchant, Daniel Rueckert, A David Edwards, Serena J Counsell

“…Early neuroimaging may provide a surrogate marker for brain development and outcome after preterm birth. Tract-Based Spatial Statistics (TBSS) is an advanced Diffusion Tensor Image (DTI) analysis technique that is sensitive to the effects of prematurity and may provide a quantitative marker for neuroprotection following perinatal brain injury or preterm birth. …”
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The Spatial Distribution Dynamics of Shark Bycatch by the Longline Fishery in the Western and Central Pacific Ocean by Shengyao Xia, Jiaqi Wang, Xiaodi Gao, Yiwei Yang, Heyang Huang

“…Utilizing data on shark bycatch from the longline fishery, as released by the Western and Central Pacific Fisheries Commission, this study applied the boosted regression tree model to examine the impact of environmental factors on the bycatch per unit effort (BPUE) of key bycatch species, as well as to predict the spatial distribution dynamics of both BPUE and bycatch risk (BR). …”
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A Spatially‐Distributed Machine Learning Approach for Fractional Snow Covered Area Estimation by Shalini Mahanthege, William Kleiber, Karl Rittger, Balaji Rajagopalan, Mary J. Brodzik, Edward Bair

“…Here, we propose a new machine learning approach conditioned on MODIS fSCA, as well as a set of physiographic features, and fit to Landsat fSCA over a portion of the Sierra Nevada USA. The predictions are daily 30m fSCA. The approach relies on two stages of spatially‐varying models. …”
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Aging and head and neck cancer insights from single cell and spatial transcriptomic analyses by Yi Pei, Zhuying Mou, Lai Jiang, Jinyan Yang, Yuheng Gu, Jie Min, Lingyi Sunzhang, Nan Xiong, Xiang Xu, Hao Chi, Ke Xu, Sinian Liu, Huiyan Luo

“…Additionally, a Cox regression model was developed based on GSTP1 and age to provide personalized prediction tools for clinical use in predicting patient survival. …”
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Spatial distribution and population structure of the invasive Anopheles stephensi in Kenya from 2022 to 2024 by Jeanne N. Samake, Duncan K. Athinya, Sylvia Milanoi, Edith Ramaita, Margaret Muchoki, Seline Omondi, Bernard Abong’o, Damaris Matoke-Muhia, Charles Mbogo, Kibor Keitany, Wolfgang Richard Mukabana, Florence Oyieke, Mildred Shieshia, Monica Mburu, Sheila Ogoma, Elizabeth Nyawira, Celestine Wekesa, Brian Bartilol, Martin Rono, Marta Maia, Wendy O’Meara, Samuel Kahindi, Cristina Rafferty, Jonathan S. Schultz, Julie R. Gutman, John E. Gimnig, Sarah Zohdy, Eric Ochomo

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Robust skeletal motion tracking using temporal and spatial synchronization of two video streams. by Vytautas Abromavičius, Ervinas Gisleris, Kristina Daunoravičienė, Jurgita Žižienė, Artūras Serackis, Rytis Maskeliūnas

“…This study proposes a three-dimensional human skeleton tracking system for upper limb activities that integrates temporal and spatial synchronization to improve depth estimation accuracy for rehabilitation exercises. …”
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Characterizing spatial immune architecture in metastatic melanoma using high-dimensional multiplex imaging by Joel Eliason, Santhoshi Krishnan, Yasunari Fukuda, Matias A. Bustos, Dan Winkowski, Sungnam Cho, Akshay Basi, Akshay Basi, Regan Baird, Elizabeth A. Grimm, Michael A. Davies, Dave S. B. Hoon, Arvind Rao, Arvind Rao, Arvind Rao, Arvind Rao, Jared K. Burks, Jared K. Burks, Suhendan Ekmekcioglu

“…In advanced disease, immunosuppressive neighborhoods emerge alongside changes in immune cell localization, with spatial patterns of immune coordination—particularly involving CTLs, NK cells, and B cells—strongly predicting survival. …”
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Assessing the potential for carbon storage enhancement in forests of Xinjiang Uygur autonomous region, China by Zhizhong Chen, Mei Zan, Jingjing Kong

“…This study integrates multi-source remote sensing and forest inventory data to model Xinjiang’s forest age and carbon density (2019 baseline: 186.76 Mg/hm2 biomass, 93.38 Mg/hm2 carbon density, 46-year average age), revealing a south-to-north “low-high-low” spatial pattern. …”
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Effective rain rate model for analysing overestimated rain fade in short millimetre-wave terrestrial links due to distance factor by Asma Ali Budalal, Ibraheem Shayea, Md. Rafiqul Islam, Jafri Din, Abdulsamad Ebrahim Yahya, Yousef Ibrahim Daradkeh, Marwan Hadri Azmi

“…Thus, an effective rain rate concept and model are proposed to represent rain intensity variations for short paths to eliminate the need for an effective path length that more accurately predicts rain attenuation at path lengths exceeding 1 km. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…Accurate real-time temperature prediction in electrochemical energy storage systems plays a critical role in enhancing battery performance, extending lifespan, and preventing thermal runaway, a major safety concern. …”
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The impact of the subventricular zone invasion types and MGMT methylation status on tumor recurrence and prognosis in glioblastoma by Zhiying Shao, Hao Yan, Min Zhu, Zhengyang Liu, Ziqin Chen, Weiqi Li, Chenyang Wang, Longzhen Zhang, Junnian Zheng

“…We aimed to conduct a retrospective study to mainly investigate the prognostic value of SVZ invasion and MGMT status, and developed a novel clinical prediction model based on our findings. Methods: 139 patients with IDH wild-type GBM were retrospectively studied. …”
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Prediction method of gas content in deep coal seams based on logging parameters: A case study of the Baijiahai region in the Junggar Basin by Yijie Wen, Shu Tao, Fan Yang, Yi Cui, Qinghe Jing, Jie Guo, Shida Chen, Bin Zhang, Jincheng Ye

“…Notably, the gas enrichment areas are predominantly distributed in well blocks adjacent to fault systems, such as wells C31 and BJ8, etc., which align with the favorable geological conditions for deep CBM accumulation in the Baijiahai region. These spatial distribution patterns not only corroborate existing geological insights but also further validate the reliability of the MAML model in predicting gas content within deep coal seams.…”
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Analysis and prediction of urban agglomeration ecological footprint based on improved three-dimensional ecological footprint and shared socioeconomic pathways by Ruirui Jiang, Liangjun Fei, Shouxuan Kang

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Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory. by Qi Dai, Xiao-Yan Liu, Fang-Yi Sun, Fang-Rong Ren

“…The study carries out regression analysis and a long-short-term memory model (LSTM) to respectively filter out the factors and predict TCEI. …”
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A deep learning model based on self-supervised learning for identifying subtypes of proliferative hepatocellular carcinoma from dynamic contrast-enhanced MRI by Hui Qu, Shuairan Zhang, Xuedan Li, Yuan Miao, Yuxi Han, Ronghui Ju, Xiaoyu Cui, Yiling Li

“…The model analyzes temporal and spatial patterns in DCE-MRI data to identify the proliferative subtype efficiently and accurately. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…RSSI data, temporal and spatial management with simple low-processing methods adopted, achieved a maximum prediction accuracy average of 81.53% across all datasets, while ML algorithms (Random Forest) achieved a maximum prediction accuracy average of 87.24%.…”
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Sensitivity Analysis of the WRF Model to Simulate Precipitation in the Metropolitan Area of the Valley of Mexico for the Period June-September 2019 by Indalecio Mendoza Uribe, Víctor Kevin Contreras Tereza, Pamela Iskra Mejía Estrada, Olivia Rodríguez López

“…The results of the model were compared with the observation records, considering five thresholds of rainfall. …”
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FEATURES OF THE MODEL OF A SPECIALIZED GEOSPATIAL DATABASE FOR VISUALIZING INDICATORS OF HUMAN SOCIO-ECONOMIC SECURITY IN WARTIME CONDITIONS by Zakharii S. Varnalii, Oleksii P. Fedchenko, Ihor V. Pampukha, Ihor V. Tolok

“…This includes the promptness, completeness, and quality of informational and spatial support for management and decision-making processes. …”
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A Multimodal Deep Learning Framework for Accurate Biomass and Carbon Sequestration Estimation from UAV Imagery by Furkat Safarov, Ugiloy Khojamuratova, Misirov Komoliddin, Xusinov Ibragim Ismailovich, Young Im Cho

“…A lightweight Transformer-based regression head then performs multitask prediction of AGB and CO₂e, capturing long-range spatial dependencies and enhancing generalization. …”
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An action decoding framework combined with deep neural network for predicting the semantics of human actions in videos from evoked brain activities by Yuanyuan Zhang, Manli Tian, Baolin Liu

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