A Criterion of Reduction Quality of Femoral Neck Fractures Based on Spatial Residual Displacements of Femoral Head by Shuang‐Shuang Cui, Li‐Kun Zhao, Jing‐Bo Yu, Jian‐Xiong Ma, Xin‐Long Ma

“…The purpose of this study is to construct a reduction quality criterion based on spatial residual displacements of 3D reconstruction and to predict the occurrence of ONFH. …”
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Orthogonal intercellular signaling for programmed spatial behavior by Paul K Grant, Neil Dalchau, James R Brown, Fernan Federici, Timothy J Rudge, Boyan Yordanov, Om Patange, Andrew Phillips, Jim Haseloff

“…We used this model to predict optimal expression levels for receiver proteins, to create an effective two‐channel cell communication device. …”
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Spatial Compression Methods for Latent Diffusion Models by Vladimir Abramov, Mikhail Gromov

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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

“…In this research, we aimed to model and predict the spatial distribution of soil geophysical properties using parent material and terrain attributes with machine learning algorithms. …”
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SpatConv Enables the Accurate Prediction of Protein Binding Sites by a Pretrained Protein Language Model and an Interpretable Bio-spatial Convolution by Mingming Guan, Jiyun Han, Shizhuo Zhang, Hongyu Zheng, Juntao Liu

“…Traditional protein binding site prediction models usually extract residue features manually and then employ a graph or point-cloud-based architecture borrowed from other fields. …”
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Spatial variability and convergence of the coupled relationship between agricultural carbon emission reduction and rural revitalization in China by Hongli Yang, Kai Feng

“…IntroductionPromoting the coupled and coordinated development of agricultural carbon emission reduction and rural revitalization is a key link and an inevitable choice to achieve the goal of “double carbon” and sustainable rural development.MethodsThis study takes 31 provinces (cities) in China (excluding Hong Kong, Macao and Taiwan) from 2010 to 2022 as the research object, and adopts the entropy value method, the coupling coordination degree model, the Gini coefficient and its decomposition, and the convergence degree model, etc., to analyze the level of coupling coordination between agricultural carbon emission reduction and rural revitalization in terms of spatial and temporal development characteristics, regional differences and convergence.Results and discussionThe study found that: (1) the coupling and coordination level of agricultural carbon emission reduction and rural revitalization at the national level and in the four major regions continues to improve, and the type of coupled coordination in the provinces is dominated by “primary coordination” in 2022; (2) inter-regional differences are the main source of differences in the coupling and coordination level of agricultural carbon emission reduction and rural revitalization in China; (3) There is no σ-convergence in the coupled coordination level of agricultural carbon emission reduction and rural revitalization at the national level, but there are significant absolute β-convergence and conditional β-convergence, and there are some differences in the regional convergence characteristics, and there is obvious regional heterogeneity in the development of external factors on the coupled coordination level in different regions. …”
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Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China by Lingyao Wang, Taofeng Wu, Fangrong Ren

“…This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini coefficient, and decomposes carbon-emission factors using the LMDI method. …”
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Analysis and Prediction of Spatial and Temporal Land Use Changes in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains by Xiaoxu He, Zhaojin Yan, Yicong Shi, Zhe Wei, Zhijie Liu, Rong He

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Spatial and Temporal Characteristics of Land Use Changes in the Yellow River Basin from 1990 to 2021 and Future Predictions by Yali Cheng, Yangbo Chen

“…Additionally, the study predicts land use types in the study area for the year of 2030 by using the Future Land Use Simulation (FLUS) model. …”
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Modeling and mapping spatial distribution of baseline soil organic carbon stock, a case of West Hararghe, Oromia Regional State, Eastern Ethiopia by Martha Kidemu Negassa, Mitiku Haile, Gudina Legesse Feyisa, Lemma Wogi, Feyera Merga

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Revisiting the "satisfaction of spatial restraints" approach of MODELLER for protein homology modeling. by Giacomo Janson, Alessandro Grottesi, Marco Pietrosanto, Gabriele Ausiello, Giulia Guarguaglini, Alessandro Paiardini

“…The most frequently used approach for protein structure prediction is currently homology modeling. The 3D model building phase of this methodology is critical for obtaining an accurate and biologically useful prediction. …”
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Spatial Autoregressive Modeling on Linear Mixed Models for Dependency Between Regions by Timbang Sirait

“…In this study, we are concerned with the spatial lag or SAR models because dependency between variables of interest is easier to predict. …”
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Combining habitat selection, behavioural states, and individual variation to predict fish spatial usage near a barrier by Rachel Mawer, Jelger Elings, Stijn P. Bruneel, Ine S. Pauwels, Eliezer Pickholtz, Renanel Pickholtz, Johan Coeck, Peter L.M. Goethals

“…Model results were explored to assess the benefits of including behavioural state and understand state-specific habitat preferences, then cross-validated and used to develop an individual based model to predict fish spatial usage. …”
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Analysis of Temporal and Spatial Evolution Characteristics and Peak Prediction of Carbon Emissions in China Under the Dual-Carbon Target: A Case Study of Heilongjiang Province by Zhongxia Yu, Mingcong Zhang, Yingce Zhan, Yongxia Guo, Yuxian Zhang, Xiaoyan Liang, Chen Wang, Yuxin Fan, Mingfen Shan, Haiqing Guo, Wei Zhou

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Spatial Simulation and Optimization of Cropping Structure Under Climate and Land Use Change Conditions Considering Synergistic Economic Benefits and Carbon Reduction in Crop Growth... by Mo Li, Haiyan Li, Zhaoqiang Zhou, Yingshan Chen, Yijia Wang, Tianxiao Li, Qiang Fu

“…This approach is based on climate change conditions and it accurately simulates future land use changes and crop growth processes, establishes a carbon emission intensity optimization model, and generates a spatial planting structure optimization and regulation scheme based on intelligent optimization algorithms under changing scenarios. …”
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Optimizing the Portuguese wildfire fuel reduction program by Alan Ager, Bruno A. Aparício, José M.C. Pereira

“…In this study, we employed a scenario planning model to optimize the implementation of a national fuel management plan in Portugal and to understand tradeoffs among specific risk reduction objectives. …”
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I.S.G.E.: An Integrated Spatial Geotechnical and Geophysical Evaluation Methodology for Subsurface Investigations by Christos Orfanos, Konstantinos Leontarakis, George Apostolopoulos, Ioannis E. Zevgolis, Bojan Brodic

“…The automatically derived 3D models, depicting the spatial distribution of specific geotechnical parameters, provide engineers with an additional interpretation tool for better understanding the subsurface conditions of a survey area.…”
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Spatial model of international tourism and tourists' original motives by Oleksandr Korol, Tetiana Skutar

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Spatial analysis and prediction of psittacosis in Zhejiang Province, China, 2019–2024 by Zheyuan Ding, Haocheng Wu, Chen Wu, Kui Liu, Qinbao Lu, Xinyi Wang, Tianying Fu, Junjie Li, Ke Yang, Queping Song, Junfen Lin

“…This study aimed to characterize the epidemiological patterns and spatiotemporal distribution of psittacosis in Zhejiang Province, China, and to identify high-risk clusters through predictive modeling.MethodsWe conducted a comprehensive analysis of reported psittacosis cases in Zhejiang Province from January 2019 to June 2024. …”
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Prediction Modeling and Driving Factor Analysis of Spatial Distribution of CO₂ Emissions from Urban Land in the Yangtze River Economic Belt, China by Chao Wang, Jianing Wang, Le Ma, Mingming Jia, Jiaying Chen, Zhenfeng Shao, Nengcheng Chen

“…Based on socioeconomic grid data, such as nighttime lights and the population, this study proposes a spatial prediction method for CO₂ emissions from urban land using a Long Short-Term Memory (LSTM) model with added fully connected layers. …”
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