Coastal cities exposed to extreme wind events are facing increasing challenges in emergency management under climate change. Accurate and high-resolution wind environment information over complex urban terrain is essential for disaster risk assessment and evidence-based emergency planning; however, such information is often unavailable in conventional management practices. This study proposes an integrated UAV–CFD framework to support urban wind risk assessment by combining multi-source geospatial data and high-resolution numerical simulation. A refined urban terrain model with a spatial resolution of 0.5 m was constructed through the fusion of Google Earth data and UAV oblique photogrammetry, and subsequently coupled with a computational fluid dynamics (CFD) model to analyze the urban wind environment. Field measurements obtained from a 50 m wind observation tower were used to validate the simulation results. The results reveal significant wind speed amplification caused by complex terrain and building configurations, with a maximum amplification factor of 1.95 due to the canyon effect. The relative errors between simulated and measured wind speeds and turbulence intensity were generally within 15%, demonstrating the reliability of the proposed framework. By providing high-resolution and spatially explicit wind risk information, this study offers practical decision-support for emergency management, urban planning, and resilience-oriented disaster mitigation in coastal cities.

With the rapid development of e-commerce, the design quality of e-commerce platform is increasingly emphasized by scholars and e-commerce workers. Many e-commerce companies emphasize platform operation and promotion to attract consumers and improve conversion rates, while ignoring the improvement of the design quality of the e-commerce platform. Therefore, the purpose of this study is to investigate the impact of three dimensions of e-commerce platform design quality (aesthetic quality, functional quality, and symbolic quality) on consumer satisfaction, as well as the impact of consumer satisfaction on consumer purchase intention and e-word of mouth. Using an online survey, data were obtained from 1000 online shoppers in Chinese, using structural equation modeling to validate hypotheses. The results show that the aesthetic and functional quality of e-commerce platform significantly positively affect consumers' purchase intention, and the aesthetic and symbolic quality significantly positively affect electronic word-of-mouth; Consumer satisfaction plays a mediating role between the functional quality, symbolic quality, and purchase intention, electronic word-of-mouth of e-commerce platforms; Consumer experience plays a mediating role between functional quality, symbolic quality, and consumer satisfaction.

Glass curtain walls are widely used in the enclosure structure of airport terminals due to their advantages of lightweight and beautiful appearance, good lighting, and easy installation. However, coastal areas are constantly affected by typhoons, and under the influence of strong winds, complex pressure distributions are generated on the surface of curtain walls. Therefore, studying the wind pressure distribution characteristics of glass curtain walls is crucial for the structural safety and durability of coastal airport terminals. Based on this, accurately predicting wind pressure distribution not only helps to improve the design safety of airport terminals but also effectively prevents potential damage under strong wind conditions. To achieve effective prediction of wind pressure on glass curtain walls, this paper adopts a combination of wind tunnel tests and neural network prediction models. Real wind pressure coefficient data is obtained through wind tunnel tests, and a CNN–Transformer combination model is proposed to predict wind pressure coefficients. The results show that the prediction accuracy of the combined model is higher than that of the CNN and Transformer single models. MAE is optimized by 0.04~0.10 compared with the former and 0.16~0.34 compared with the latter; RMSE has been optimized by 0.02–0.10 and 0.30–0.34, respectively. This article can provide reference for the prediction research of wind pressure on the surface of glass curtain walls in airport terminals.

This study aimed to assess the knowledge on human immunodeficiency virus (HIV) and factors related to HIV stigma among college students to enlighten them on the development of HIV prevention strategies and better understand the additional benefit of HIV risk reduction, supplied fundamental data for the emergency management of infectious diseases in higher educational institutions. This cross-sectional study enrolled students from 10 universities in southwest China ( n = 4,133). Survey questions included demographic information, HIV knowledge, HIV stigma, and self-esteem. Descriptive and inferential statistics were applied to summarize the data. Logistic regression was used to analyze factors related to HIV knowledge and stigma. The knowledge level of respondents on HIV was 74.2%. Stigma was highly prevalent in the form of fear of casual transmission (79.8%), moral judgment (71.1%), personal stigma (72.2%), and perceived community stigma (71.8%). The findings demonstrated that a high level of relevant knowledge regarding HIV was consistently associated with lower stigma levels in four dimensions, and that seven variables—, namely, gender, ethnicity, grade, only-child or not, sexual orientation, awareness of the HIV/acquired immunodeficiency syndrome epidemic, and self-esteem—, played different roles in affecting various dimensions of HIV stigma. The level of HIV knowledge was low whereas HIV-associated stigma was high among college students in southwest China. Addressing HIV in colleges should incorporate efforts for reducing stigma associated with HIV. For effective infectious disease emergency management in academic settings, this study underscores the necessity of integrating stigma-reduction strategies into institutional preparedness plans. Addressing these barriers is essential for optimizing risk communication, intervention uptake, and response efficacy during public health emergencies.