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With the advent of the era of Industry 4.0, big data and the Internet of Things came into being. The rise of big data and the Internet of Things has had an impact on all walks of life. The development of big data and the Internet of Things provides an opportunity for the evolution of street form. With the rapid development of smart cities, the street shape is also changing more and more towards the direction of intelligence. Taking Chunxi Road in Chengdu as an example, this paper studies the generation mechanism of street morphology. The factors influencing the generation of street form are divided into two categories: (1) legal factors. (2) Architectural design factors. By building a model, the article quantitatively analyzes the impact of these two types of factors on street form. At the same time, the article conducts an in-depth study on the evolution of ancient Chinese street morphology. The ancient Chinese street form is divided into four stages, namely the Tang and Song Dynasties, the Yuan, Ming and Qing Dynasties, the Late Qing Dynasty, and the founding of New China. The influencing factors of street shape are divided into four categories, namely, the influence of commodity economy, the influence of foreign culture, the influence of building materials, and the influence of traffic. This paper elaborates the influence mechanism of these four factors on the street form in China. The article finally puts forward the development trend of my country's future street form, and points out that the evolution of my country's street form will develop in the direction of intelligence, and intelligent transportation, intelligent garbage classification system, etc. will be applied. The number of brick-and-mortar stores in my country's street layout may decrease. [ABSTRACT FROM AUTHOR]

Objective: This paper aimed to assess rural-to-urban male migrant workers' HIV vulnerability and prevention needs in a Chinese context, specifically in the city of Chengdu, capital of the south-western province of Sichuan. Participants: The primary sample group were 23 male migrant workers recruited from textile factories and construction sites. In addition, a total of 16 key informants (e.g., factory managers, healthcare providers and policy makers) and seven community members participated in the qualitative phase. Methods: Qualitative methods included semi-structured interviews with male migrant workers and key informants, focus group discussions with migrant workers and local community members, observation, and review of key policy and programmatic documents related to HIV prevention and/or migrant workers. Results: Findings highlight migrant workers' vulnerability to HIV for a variety of reasons. Their migrant status rendered them economically marginalised and socially isolated. HIV knowledge was poor and discriminatory attitudes towards infected people commonplace. Perceptions of personal HIV risk were low, even though study participants reportedly engaged in sexual behaviours that placed them at risk of infection. Conclusions: A number of interrelated factors contributed to male rural-to-urban migrant workers' vulnerability to HIV infection. Targeted HIV prevention programs for male migrant workers in Chengdu are urgently needed. [ABSTRACT FROM AUTHOR]

As China's tourism industry is on the right track, the country has gradually paid more attention to the ecological protection of tourism areas. Under the concept of sustainable development, the research on environmental adaptability of tourist attractions has become a hotspot. This study took Huanglongxi Ancient Town in Shuangliu District, Chengdu City, Sichuan Province as the research object, and determined seven ecological protection spaces of Huanglongxi Ancient Town by MSPA method, and then used the landscape connectivity method to identify the priority of ecological sources. The high green space and water are the "source", and finally the path network is constructed using space syntax, and the relationship between the flow of people and the path resistance disturbance is calculated. After analysis, it is concluded that Huanglongxi Ancient Town has 2 green spaces with higher priority and 1 water area with higher priority. The route layout can meet the current annual reception volume and will not cause obvious congestion during the daily peak. Huanglongxi Ancient Town has 6 enterprises above designated size and 20,000 square kilometers of arable land. The average dLLC of the green space in Huanglongxi Ancient Town is 19.10, the average dPC is 20.92, the maximum time resistance is 0.951 + 1.703*10 - 7 *V 151.3 , and the maximum time resistance disturbance is 0.999. Huanglongxi Ancient Town can pass between paths 7–8. Add new paths to improve the path situation. [ABSTRACT FROM AUTHOR]