Publications by authors named "Hailing Xiong"

In the context of rapid urbanization, metropolitan areas are facing the risk of supply-demand mismatches among ecosystem services. Investigating the patterns, relationships, and driving factors of multiple supply-demand risks is of great significance to support the efficient management of regional ecological risks. We quantified the single/comprehensive supply-demand risk rates of six ecosystem services in Wuhan Metropolitan Area at the township scale in 2000, 2010, and 2020.

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Background: The Chinese population ranks among the highest globally in terms of stroke prevalence. In the clinical diagnostic process, radiologists utilize computed tomography angiography (CTA) images for diagnosis, enabling a precise assessment of collateral circulation in the brains of stroke patients. Recent studies frequently combine imaging and machine learning methods to develop computer-aided diagnostic algorithms.

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Article Synopsis
  • White matter lesions in relapsing-remitting multiple sclerosis (RRMS) can be categorized into three types: contrast enhancement lesions (CELs), iron rim lesions (IRLs), and non-iron rim lesions (NIRLs), but existing methods for classification, particularly using radiomics, are limited.
  • A study analyzed 875 WM lesions using machine learning techniques, with a focus on feature selection and model performance evaluation, comparing 2-class (IRLs and NIRLs) and 3-class (CELs, IRLs, and NIRLs) classification tasks.
  • Results showed that the LASSO with RF model excelled in 2-class classification, while LASSO with XGBoost performed best in
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Stroke is a highly lethal condition, with intracranial vessel occlusion being one of its primary causes. Intracranial vessel occlusion can typically be categorized into four types, each requiring different intervention measures. Therefore, the automatic and accurate classification of intracranial vessel occlusions holds significant clinical importance for assessing vessel occlusion conditions.

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To investigate the effects of biogas slurry return-to-field methods, the duration of biogas slurry return to field and the amount of heavy metals brought in from biogas slurry on the accumulation of heavy metals in soil-crop systems, and the importance of factors influencing heavy metal accumulation, 41 papers and 1972 pairs of data were integrated and analyzed. The results showed that the application of biogas slurry alone significantly increased the accumulation of As, Cd, Cr, Cu, and Zn in soil and As and Cr in crops by 20.5%, 15.

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The aggregation of variably charged nanoparticles is usually induced by the changes in internal and external conditions, such as solution temperature, pH, particle size, van der Waals force, and electrostatic repulsion among particles. In order to explore the effect of pH on the aggregation of variable charge nanoparticles, this paper proposed an extended model based on the 3D on-lattice Cluster-Cluster Aggregation (CCA) model. The extended model successfully established the relationship between pH and sticking probability, and used Smoluchowski theory to calculate the aggregation rate of nanoparticles.

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To determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an 'Input-Translate-Output' three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.

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Zeolites have been widely applied in soil improvement and environment protection. The study on ion specificity during ion exchange equilibrium is of important significance for better use of zeolites. The maximum adsorption capacities of alkali ions during ion exchange equilibrium in the clinoptilolite showed obvious specificity.

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Colloid aggregation is often induced by the change of internal or external conditions. In order to account for the dynamic features of the evolutional open system, a conceptual model for colloid aggregation in open systems was developed based on the classic Cluster-Cluster Aggregation (CCA) model. The extended model allows the important parameters of the classic CCA model, diffusion coefficient D(1) and sticking probability P(1) of primary particles, time-dependent.

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