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When assessing road network resilience, emergency management behavior should be considered, as this represents the road network's capacity to adapt to and recover from traffic accidents. Given the timeliness and variability of emergency management behavior, deterministic approaches seem inadequate to represent real road network performance. Thus, this paper innovatively designs an emergency management perspective-based dynamic evaluation method of road network resilience to traffic accidents. Firstly, based on four stages of emergency management, a road network resilience evaluation index system encompassing resilience capabilities, resilience attributes and traffic accident emergency management ability indicators is constructed. Afterwards, the gray relational technique for order preference by similarity to the ideal solution (GRA-TOPSIS) evaluation method based on combination weighting, which integrates factor analysis with hesitant intuitionistic fuzzy expert scoring, is designed to quantify resilience. Finally, the obstacle degree model is utilized for identifying resilience constraints as the input of a long short-term memory (LSTM) model to predict the resilience variation trend. The fast road network of Shanghai in China is adopted as a case study, and the results indicate that road network resilience embodies significant spatial distribution characteristics. Road length, number of tractors, perception and response and disposal time of traffic accidents cast notable effects on resilience. Additionally, some roads are forecast to show descending resilience. The proposed method is valuable for helping policymakers identify current and potential vulnerable roads and to formulate proposals to effectively improve the resilience of urban agglomerations and promote sustainable cities. [ABSTRACT FROM AUTHOR]

Participation in online activities offers older adults enhanced opportunities to cope with age-related limitations and live a socially connected life. For investigating the factors explaining whether older adults use the internet or not, logistic regression has been used, which requires considerable care in the computation and reporting of regression models. The objective of this review is to assess the extent to which the empirical literature examining internet use among older adults (aged 55 +) addresses commonly recommended quality criteria for logistic regression analysis. We carried out a systematic search in Scopus and PubMed for English-language peer-reviewed articles reporting the application of logistic regression, published between 2010 and 2020. Thirty-six articles were eligible for inclusion. We evaluated the articles for six analytic and three documentation criteria. Every article described the selection of independent variables and their coding. Most studies had sufficient events per independent variable (83%), reported point and interval estimates of effect sizes (81%), and stated the fitting procedure used (81%). The reporting rates were lower for the assessment of model fit (53%), consideration of interactions (44%), and testing for conformity with linear gradient (42%) and collinearity (31%). This review provides comprehensive insights into the state of adoption of logistic regression analysis. We suggest improvements for reporting on the studies specific to older adults' internet use, which can promote the accurate interpretation of articles and the integration of evidence from single studies. [ABSTRACT FROM AUTHOR]

As global urban infrastructure renewal progresses, the urgent need for sustainability-driven urban renewal intensifies amidst resource scarcity and environmental concerns. Effective evaluation and decision making regarding urban road renewal schemes are prerequisites for their successful implementation. However, variation in the prioritization of indicators in project evaluations and the poor adaptability of existing frameworks hinder the quick assessment of diverse projects. To address this issue, this paper proposes a scheme evaluation framework with embedded renewal project features comprising four modules. Following the initial construction of a sustainability-driven evaluation system, an indicator-filtering mechanism combining the Latent Dirichlet Allocation (LDA) model with a text similarity algorithm is developed. The Entropy Weight-–TOPSIS method is then employed to derive the final optimal decision based on selected indicators. Applying the decision framework to the G15 Jialiu Widening and Reconstruction Project in Shanghai, China, indicators are reduced by 48.3%, with the optimal scheme decision consistent with the traditional Entropy Weight–TOPSIS method. The framework is robust and enhances decision efficiency, filling theoretical gaps in existing indicator-filtering mechanisms. [ABSTRACT FROM AUTHOR]