Numerical Study of the Influence of the Spatial Distribution of Oversized Rock Blocks on the Stability of Soil-Rock Mixture Slopes by Wenwei Gao, Hairong Yang, JinBiao Teng, Yongshuai Sun

“…First, according to the stochastic approach, different numerical models of an S-RM slope were established with different oversized rock block spatial distributions. …”
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ASSESSMENT SPATIAL VARIABILITY OF SOIL ERODIBILITY BY USING OF GEOSTATISTIC AND GIS (Case study MEHR watershed of SABZEVAR) by Ayoubi, S.A, M. H. Alizadeh

“…Particle size distribution was determined by Hydrometer method and Organic matter was measured by wet oxidation approach. Then spatial analysis was done. Variography analysis on soil attributes according to soil erodibility, showed that Gaussian, exponential and spherical models were the most models to predict spatial variability of soil parameters. …”
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Ecological risk assessment of oilfield soil through the use of machine learning combining with spatial interaction effects by Shihan Wang, Mingxia Zheng, Yushan Tian, Hongyu Ding, Lina Yan, Beidou Xi, Yuanyuan Sun, Jing Su

“…The results indicated that the Gradient Boosting Machine (GBM) model exhibited strong performance in predicting concentrations of TPHs (R2=0.7730), As (R2=0.8614), Pb (R2=0.8678), Ni (R2=0.7539), Cd (R2=0.7447), and Hg (R2=0.6270) in soil. …”
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A small‐target traffic sign detection algorithm based on partial conv and atrous spatial pyramid by Yuqi Li, Zijian Wang, Han Zhang, Xinpeng Yao, Zhou Zhou, Xin Cheng

“…The detection head is decoupled to extract the location and class information of the predicted target separately, thereby enhancing the generalization ability of the proposed model. …”
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The spatial-temporal changes in water balance components under future climate change in the Gorganroud Watershed, Iran by Ghorbani Hossein, Akbari Azirani Tayebeh, Entezari Alireza, Baaghideh Mohammad

“…Our findings indicate that (1) minimum and maximum temperature will likely rise up to 3.3 °C and 4.3 °C, respectively, during 2071–2100 compared to the baseline of 1985–2014 under SSP585, (2) precipitation is predicted to increase up to 5.6% under SSP245, while it is expected to decrease up to 5% under the SSP585 in 2071-2100compared to the baseline, (3) in response to climate change, the study area will see a reduction in surface runoff, base flow, and lateral flow up to 7.7%, 13% and 10.2%, respectively, and an increase in evapotranspiration up to 11%) until the end of the century, (4) spatial analysis indicates that the eastern, southeastern, and northern regions of the watershed are projected to experience the most significant declines in hydrological components, with changes up to 50%. …”
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Colony Site Selection of Gray Heron (Ardea cinerea) During the Breeding Period at Multiple Spatial Scales by Ran Tian, Donghong Li, Shiyu Zhang, Yongbin Zhao, Guodong Yi

“…This study utilizes geographic information systems (GIS) and random forest (RM) models to examine the colony site selection during the breeding period of gray herons across various regions and spatial scales, providing insights into their adaptability and the environmental factors influencing their colony site selection. …”
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scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures by Qiaoni Yu, Yuan-Yuan Li, Yunqin Chen

“…The capability to predict malignancy probability empowers scMalignantFinder to capture dynamic characteristics during tumor progression. …”
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A dynamic, spatially periodic, micro‐pattern of HES5 underlies neurogenesis in the mouse spinal cord by Veronica Biga, Joshua Hawley, Ximena Soto, Emma Johns, Daniel Han, Hayley Bennett, Antony D Adamson, Jochen Kursawe, Paul Glendinning, Cerys S Manning, Nancy Papalopulu

“…Computational modelling predicts that different cell coupling strengths underlie the HES5 spatial patterns and rate of differentiation, which is consistent with comparison between the motoneuron and interneuron progenitor domains. …”
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Development of a UAV LiDAR-Based Framework for Consolidation Settlement Monitoring Through Spatial Analysis by Seok-Jun Ko, Seongho Hong, Tae-Young Kwak

“…We are the first to evaluate the spatial representativeness of consolidation settlement at multiple section sizes (10 m × 10 m, 50 m × 50 m, and 100 m × 100 m) using high-resolution LiDAR, revealing that larger section sizes produce greater spatial variability and prediction error. …”
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Deep MALDI-MS spatial omics guided by quantum cascade laser mid-infrared imaging microscopy by Lars Gruber, Stefan Schmidt, Thomas Enzlein, Huong Giang Vo, Tobias Bausbacher, James Lucas Cairns, Yasemin Ucal, Florian Keller, Martina Kerndl, Denis Abu Sammour, Omar Sharif, Gernot Schabbauer, Rüdiger Rudolf, Matthias Eckhardt, Stefania Alexandra Iakab, Laura Bindila, Carsten Hopf

“…QCL-MIR imaging-guided MSI allowed for unequivocal on-tissue elucidation of 157 sulfatides selectively accumulating in kidneys of arylsulfatase A-deficient mice used as ground truth concept and provided chemical rationales for improvements to ion mobility prediction algorithms. Using this workflow, we characterized sclerotic spinal cord lesions in mice with experimental autoimmune encephalomyelitis (EAE), a model of multiple sclerosis, and identified upregulation of inflammation-related ceramide-1-phosphate and ceramide phosphatidylethanolamine as markers of white matter lipid remodeling. …”
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A Simple Predictive Enhancer Syntax for Hindbrain Patterning Is Conserved in Vertebrate Genomes. by Joseph Grice, Boris Noyvert, Laura Doglio, Greg Elgar

“…These sequences tend to be located near developmental transcription factors and are enriched in known hindbrain activating elements, demonstrating the predictive power of this simple model.<h4>Conclusion</h4>Our findings support the theory that hundreds of CNEs, and perhaps thousands of regions across the human genome, function to coordinate gene expression in the developing hindbrain. …”
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Risk Assessment of Geological Hazards Based on Multi-Condition Development Scenarios: A Case Study of Huangshi Town, Guangdong Province by Gonghao Duan, Hui Xia, Anqi Du, Juan Ma

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Susceptibility modeling of hydro-morphological processes considered river topology by Nan Wang, Mingxiao Li, Hongyan Zhang, Weiming Cheng, Chao Du, Luigi Lombardo

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Spatial and temporal variation in the occurrence of bottlenose dolphins in the Chesapeake Bay, USA, using citizen science sighting data. by Lauren Kelly Rodriguez, Amber D Fandel, Benjamin R Colbert, Jamie C Testa, Helen Bailey

“…The goal of this study was to establish the spatial and temporal distribution of bottlenose dolphins throughout this large estuarine system and use statistical modeling techniques to determine how their distribution relates to environmental factors. …”
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TreeGrid: A Spatial Planning Tool Integrating Tree Species Traits for Biodiversity Enhancement in Urban Landscapes by Shrey Rakholia, Reuven Yosef, Neelesh Yadav, Laura Karimloo, Michaela Pleitner, Ritvik Kothari

“…Additionally, we trained a deep neural network (DNN) model using tool-generated data to predict bird habitat suitability across diverse urban contexts. …”
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Regional Brain Aging Disparity Index: Region-Specific Brain Aging State Index for Neurodegenerative Diseases and Chronic Disease Specificity by Yutong Wu, Shen Sun, Chen Zhang, Xiangge Ma, Xinyu Zhu, Yanxue Li, Lan Lin, Zhenrong Fu

“…This study proposes a novel brain-region-level aging assessment paradigm based on Shapley value interpretation, aiming to overcome the interpretability limitations of traditional brain age prediction models. Although deep-learning-based brain age prediction models using neuroimaging data have become crucial tools for evaluating abnormal brain aging, their unidimensional brain age–chronological age discrepancy metric fails to characterize the regional heterogeneity of brain aging. …”
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Modeling of Droplet Deposition in Air-Assisted Spraying by Jian Song, Zhichong Wang, Changyuan Zhai, Chenchen Gu, Kang Zheng, Xuecheng Li, Ronghua Jiang, Ke Xiao

“…To facilitate targeted pesticide application in the canopy of fruit trees, this study employed a newly developed wind-speed-adjustable orchard sprayer and established a prediction model for deposition based on data from orthogonal trials using a central composite design accounting for the coupling effect of three-dimensional spatial parameters. …”
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Echo state networks for modeling turbulent convection by Mohammad Sharifi Ghazijahani, Christian Cierpka

“…The ESN successfully models the flow qualitatively. Even for this highly turbulent flow, it is challenging to distinguish predictions from the ground truth. …”
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ANALYSIS OF SPATIAL EFFECTS ON FACTORS AFFECTING RICE PRODUCTION IN CENTRAL SULAWESI USING GEOGRAPHICALLY WEIGHTED PANEL REGRESSION by Nurul Fiskia Gamayanti, Junaidi Junaidi, Fadjryani Fadjryani, Nur'eni Nur'eni

“…This difference can of course be influenced by geographic location or spatial effects between regions. Central Sulawesi, which is one of the provinces with a large population compared to other provinces on the island of sulwesi, has a responsibility to meet the needs of its community, so it is necessary to take into account and increase the production of rice by relying on production in the province.Modeling of rice production that has spatial effects or heterogeneity between regions is needed as an analytical tool because if the modeling ignores spatial effects and generalizes the model, the modeling predictions will be biased. …”
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Optimizing snow property forecasts over the tibetan plateau through hybrid assimilation of satellite precipitation and water vapor radiances using WRF model configured with Noah-MP by Jing Ren, Chunlin Huang, Jinliang Hou, Ying Zhang, Ling Yang

“…Comparing with some reference datasets, the predictions exhibit good physical consistency between snow parameters and fine temporal-spatial resolution. …”
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