Chengdu City Research Articles

The influence of parents’ oral health literacy and behavior on oral health of preschool children aged 3–6 years- evidence from China

BackgroundDirect and indirect associations have been identified among health literacy, health behavior, and health status. Thus, we aimed to investigate the influence of oral health literacy and behaviors in parents on their children's oral health status. Moreover, we aimed to analyze the mentioned mediating effects through oral health behavior management.MethodsOral health information of 1,102 preschool children aged 3 to 6 years was collected from five primary schools in Jinjiang District, Chengdu City, Sichuan Province, China. The decay-missing-filled teeth (DMFT) index and soft scale plaque index (PI) were used by professional dentists aided by school teachers to assess caries and periodontal health among the children. Simultaneously, we conducted a questionnaire-based survey among the parents to determine their oral health literacy and health behavior and their children's oral health behavior. The probit model, instrumental variables, and mediation effect model were used to evaluate the association of parents' oral health literacy and behavior with their children's oral health status.ResultsThe DFMT index was 1.58 among the children, with zero caries in 646 (58.6%) children. The PI was 0.68, with zero gum disease in 517 (46.9%). The univariate analysis suggested that the parents' health literacy and behavior were correlated with their children's oral health status (P < 0.01). Parents' oral health behavior significantly affected their children's oral health status. Simultaneously, a stronger correlation was observed upon using parents' health literacy as an instrumental variable to assess the endogeneity, indicating endogeneity problems. Parents' health-related behaviors exerted a mediating effect on children's oral health, with parents helping children brush their teeth demonstrating the strongest effect.ConclusionParents' oral health-related behaviors can affect their children's oral health status. We recommend enhancing parents' oral health literacy to improve children's oral health status.

Analysis of deviant behaviors and family functions in the population at risk of internet addiction among primary and secondary school students in Chengdu city, Sichuan province of China

BackgroundThis study explores the correlation between internet addiction (IA) and deviant behaviors among primary and secondary school students. It analyzes the impact of family functional factors, such as family relationships, parent–child communication, and parental control, on IA. The findings aim to provide a scientific basis for educators and parents to develop targeted preventive and intervention measures.MethodsA cross-sectional survey was conducted using self-administered questionnaires among 8,816 students from five primary and secondary schools in Chengdu. The questionnaire included basic information about students and their families, Young’s Internet Addiction Scale, Shek’s Deviant Behavior Scale, and the Chinese Family Assessment Instrument (C-FAI). Chi-square tests and t-tests were used to compare differences between the at-risk group for internet addiction and the normal population. Statistically significant variables were extracted and included in the hierarchical regression model, with the level of significance set at α = 0.05.ResultsThe detection rate of IA risk among primary and secondary school students was 14.11%, and the detection rate of deviant behaviors in this group was 85.21%. Deviant behaviors such as deceit (r = 0.201), running away from home (r = 0.215), and damaging others’ property (r = 0.209) showed a weak correlation with the risk of internet addiction, and the differences were statistically significant (p &amp;lt; 0.05). The results of the hierarchical regression analysis showed that all five dimensions of family environment and delinquency scores positively predicted internet addiction. Specifically, the change in R2 was 8.7% for mutual concern among family members and 9.7% for student delinquency behavior. Together, family environment and delinquency behavior explained 22.1% of the variance.ConclusionPrimary and secondary school students at risk of IA are more likely to exhibit deviant behaviors, which show a weak correlation with IA. Gender and grade level significantly impact the risk of IA, indicating that male students and those in higher grades require more attention. Strengthening family interventions, especially in areas of mutual communication, family conflict resolution, and parental control, can help prevent IA among primary and secondary school students.

The impact of reform of medical insurance payment method on medical service pricing—based on empirical analysis of matched medical finance comprehensive data

BackgroundThe medical insurance payment method (MIPM) has an important impact on medical service pricing (MSP) in China. The objective of this study is to examine the impact of medical insurance payment method on medical service pricing with the hope of providing insights into appropriate MSP and resource allocation.MethodFrom the perspective of information asymmetry, using the matched medical finance comprehensive data of Chengdu City, our study empirically analyzed the effect of fixed payment by disease (FPD) on MSP by the difference in difference (DID) model.ResultsThe study found that FPD not only optimizes the allocation of medical resources, saves a large amount of medical insurance funds, but also reduces the personal burden of patients. FPD is adjusted by optimizing the structure of medical expenses and medical insurance compensation, which has certain effects on saving medical insurance funds, improving the quality of medical services, and reducing the burden on patients. It has achieved the goal of medical insurance payment method reform, and make the mechanism of MSP relatively more reasonable.ConclusionThis study provided policy implications for the government to implement multiple and compound medical insurance payment method and establish a more scientific and reasonable pricing mechanism for medical services.

Structural equation model study on the correlation between sense of coherence, job stressors and mental health of nurses practitioners

Objective: To investigate the sense of coherence, job stressors and mental health status of nurses practitioners, and analyze the correlation among them. Methods: In September 2020, nurses practitioners in Chengdu City, Sichuan Province were selected as the research objects by convenience sampling method. The Sense of Coherence Scale, Nurses' Job Stressors Scale and SCL-90 were used to investigate their sense of coherence, job stressors and mental health status, respectively. Pearson correlation test was used to analyze the correlation among them, and the structural equation model was constructed to explore the mechanism of them. Results: A total of 1693 nurse practitioners were included. The total scores of sense of coherence, job stressors and SCL-90 were (65.00±14.01) points, (69.08±18.38) points and (129.68±52.99) points, respectively. The mean scores of all dimensions of sense of coherence of nurse practitioners were negatively correlated with the mean scores of all dimensions of job stressors and SCL-90 (P<0.001). And there were positive correlations between the mean scores of all dimensions of job stressors and the mean scores of all dimensions of SCL-90 (P<0.001). The structural equation model fitted well. The path coefficient between job stressors and sense of coherence was -0.372 (P<0.001), and the path coefficient between sense of coherence and SCL-90 score was -0.647 (P<0.001) . Conclusion: The sense of coherence plays a significant buffering role in job stressors and mental health of nurses practitioners. Nursing managers should be committed to improving the level of sense of coherence of nurses, enhance the happiness of nurses at work, and improve their mental health level.

Spatiotemporal Changes and Trends in Ecological Quality Based on the GEE: A Case Study of Chengdu City, China

Spatiotemporal Changes and Trends in Ecological Quality Based on the GEE: A Case Study of Chengdu City, China

First Report of Leaf Blight of Ginkgo biloba L. Caused by Neopestalotiopsis clavispora G.F. Atk. in Sichuan, China.

Ginkgo (Ginkgo biloba L.), the oldest existing tree species in the world, is an important ornamental and medicinal plant, widely planted in China. In October 2022, a new leaf blight disease was observed in Chengdu city (30°05'to 31°26'N, 102°54'to 104°53'E). Disease incidence averaged 82.5% across five foci. The typical symptomatology begins when leaf margins turn yellow and small black spots appear at the edge of the leaf, chlorotic areas turn brown, dry and deformed. Gradually, the necrotic lesions spreads to the middle of the leaf and eventually the whole leaf falls off. Infected tissues from ten leaves were cut into small pieces (5 × 5 mm); surface sterilized for 30 s in 3% sodium hypochlorite; 60 s in 75% ethanol; rinsed three times in sterile water; placed onto potato dextrose agar (PDA) amended with streptomycin sulfate (50 μg/mL); and incubated at 25°C for 3 to 8 days. A hyphae was removed from the edge of the fungal colony and placed onto potato dextrose agar (PDA) plates. After incubation at 25℃ with a 12-hour light/dark cycle for 8 days, the colony diameter reached 77.5 to 81.5 mm. Colonies grown on PDA were white, cotton, flocculent, undulating on the surface, dense in aerial hyphae and light yellow on the back. Black pycnidia formed superficially, scattered over the PDA, following two weeks of incubation. Pycnidia contained sticky black conidia. The spores were were spindle shaped, with five cells, and four septations measuring 20.9 to 34.8 µm × 6.8 to 8.8 µm (avg. 28.4 × 7.6 µm; n=40). The three median cells were versicolored, typically two dark brown cells and one light brown cell, whereas the basal and apical cells were hyaline. Conidia had a single basal appendage (2.87 to 4.1 µm long; n = 40) and two to three apical appendages (18.3 to 29.1 µm long; n = 40). Based on colony and conidial morphology, the isolate was identified as N. clavispora (Maharachchikumbura et al. 2014). The partial sequence of the internal transcribed spacer (ITS), β-tubulin gene (TUB2), and translation elongation factor subunit 1-a gene (TEF1) were amplified and sequenced using the universal primer pairs ITS1/ITS4(Zhang et al. 2022), BT2A/BT2B (Li Yuan et al. 2022), and EF1-526F/EF1-1567R (Maharachchikumbura et al. 2012), respectively. Sequences of representative isolate LQYX were deposited in GenBank (ITS: OQ152504, TUB: OQ168328, and TEF1: OQ168329). BLAST results indicated that the ITS, TUB, and TEF1-α sequences showed 99 to 100% identity with N. clavispora sequences at NCBI (GenBank MG729689, MG740735, and MG740758). Identification was confirmed by Bayesian inference using Mr. Bayes. Next, inoculations were conducted on leaves of ten G. biloba in the field to verify the pathogenicity of LQYX. Ten healthy leaves of each plant were surface sterilized with 75% ethanol, and the wound was rubbed out on the leaf edge on the sterilized sanding paper. A conidia suspension (1 × 107 ml-1) was sprayed on the leaves, aseptic water was used as the control, and the transparent plastic bag was used to maintain relative humidity. After 14 days (26 ℃, 14 hours light / 10 hours dark), the inoculated leaves had similar symptoms as the original diseased plants, whereas controls were asymptomatic. The N. clavispora was re-isolated from the infected leaves and identified by morphological characteristics and DNA sequence analysis. The pathogenicity test was repeated three times with similar results, confirming Koch's postulates. To our knowledge, this is the first report of leaf blight of G. biloba caused by N. clavispora in China, which has greatly affected the appearance of the city and should be further studied. This report can help identify this disease and further develop effective control measures.

Analysis of risk factors and establishment of early warning model for recent postoperative complications of colorectal cancer.

This study aimed to analyze factors associated with recent complications after colorectal cancer surgery, constructing a nomogram to aid gastrointestinal surgeons in preoperative decision-making for patients at risk of such complications. In this retrospective study, clinical data were collected from patients undergoing radical colorectal cancer surgery at the Department of Gastrointestinal Surgery of the Affiliated Cancer Hospital of Guizhou Medical University and the Second People's Hospital of Chengdu from November 1, 2021, to January 26, 2024. Univariable and multivariable logistic regression analyses were conducted to assess risk factors for recent postoperative complications and develop a prediction model. External validation was performed using data from 48 postoperative colorectal cancer patients in the Second People's Hospital of Chengdu City from January 1, 2023, to May 30, 2023. Evaluation included receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis using R4.2.2 statistical software. A total of 324 patients who underwent radical colorectal cancer surgery were enrolled. The training cohort (n=176) identified four independent risk factors for recent complications: PNI ≥45 (OR=4.17, P<0.001), Albumin <40 g/L (OR=3.9, P<0.001), ASA score III-IV (OR=6.29, P<0.001), and Tumor diameter ≥5 cm (OR=4.24, P<0.001). A nomogram was constructed incorporating these factors. The AUC of the nomogram model in the training cohort was 0.835, with subsequent internal and external validation cohort AUCs of 0.815 and 0.819, respectively, indicating strong discriminatory ability. The calibration curve demonstrated good consistency, and decision curve analysis indicated high clinical utility. PNI ≥45, Albumin <40 g/L, ASA score III-IV, and Tumor diameter ≥5 cm emerged as independent risk factors for recent complications following colorectal cancer surgery. We developed a nomogram model for these complications, potentially aiding gastrointestinal surgeons in preoperative patient evaluation and treatment planning for colorectal cancer surgery.

A Typology and Lead Isotope and Cultural Exchange Study on Bronze Knives from Shuangyuan Cemetery, Chengdu City, Southwest China

Background: Bronze knives, which have been excavated in large quantities and acquired hierarchical significance, are essential artifacts in Shu State in Southwest China. Building upon previous typological analyses of bronze knives, it is hypothesized that Shu culture may have imported foreign-style bronze knives. However, further demonstration of the provenance of metal materials, the typology of knives, and the cultural exchange necessitates a comprehensive examination through the lens of scientific analysis. The purpose of this study is to investigate the differences in the manufacturing processes and metal resources of Shu bronze knives with various cultural styles and whether bronze knives in the foreign styles were imported or locally imitated. Methods: In this study, the typology, portable X-ray fluorescence spectrometry and multi-collector inductively coupled plasma mass spectrometry were used to analyze twenty-four bronze knives unearthed from Shuangyuan cemetery, a cemetery of the Eastern Zhou Dynasty in Chengdu City, Sichuan Province, Southwest China. Results: The results of the study show that the knives of Shuangyuan Cemetery can be classified typologically into five types, encompassing both local and foreign styles. The predominant alloy composition of these knives is lead-tin bronze, characterized by a notably high tin content. Lead isotope ratios indicate that metal materials from the South China geochemical province and Yangtze geochemical province were mainly used to manufacture the bronze knives unearthed from the Shu state Conclusion: While the majority of foreign-style knives with ring-shaped heads were likely imported from neighboring regions like Chu state, distinctively styled type D and type E bronze knives appear to have been locally imitated by the Shu, showcasing a blend of external influences and indigenous innovation. The combination of typology and scientific analysis of the bronze knife may shed new light on the study of the Shu culture of the Eastern Zhou period.

Identification and Spatiotemporal Evolution Analysis of the Urban–Rural Fringe in Polycentric Cities Based on K-Means Clustering and Multi-Source Data: A Case Study of Chengdu City

Urban fringe areas, serving as transitional zones between urban and rural landscapes, are characterized by their transitional nature, high dynamics, and spatial heterogeneity. Identifying the extent of an urban–rural fringe (URF) and analyzing its evolutionary characteristics are crucial for urban planning and development. However, limited research exists regarding the identification of a URF and the analysis of its spatiotemporal evolution in polycentric cities. Using Chengdu as a case study, this research employed the K-means clustering method to identify the spatial extent and evolution patterns of the URF in Chengdu from 2010 to 2020 based on the spatiotemporal characteristics of multi-source data. The results indicate that (1) the K-means clustering method can reasonably and efficiently identify URF in polycentric cities; (2) Chengdu exhibited a polycentric urban structure with a “main center-subcenter” pattern, where the URF was adjacent to the main and subcenters, assuming an overall annular wedge shape; (3) there was a significant expansion of the URF in the northeast–southwest direction from 2010 to 2020, accompanied by substantial land use changes. The evolution of the URF was driven by the dual mechanisms of urban suburbanization and rural urbanization, exhibiting characteristics such as singular urban functions, dispersed and chaotic land use, fragmented landscapes, and increasing complexity. This study extended the research on URFs, aiding in the understanding of urban spatial growth patterns and providing decision support for the integrated development of urban and rural areas.

A hierarchical deep reinforcement learning method for solving urban route planning problems under large-scale customers and real-time traffic conditions

As urbanization and economic growth advance, large-scale customers and real-time traffic conditions have become crucial factors in urban route planning. Deep reinforcement learning is considered the most effective method for solving urban route planning problems involving large-scale customers and real-time traffic conditions. Due to memory usage limitations, existing deep reinforcement learning methods cannot identify candidate customers or determine optimal travel routes in large-scale and real-time environments. To tackle these problems, this study introduces a hierarchical deep reinforcement learning method utilizing an improved transformer model (HDRLITF) based on the divide-and-conquer concept. Graph attention networks and gate mechanisms are integrated into the transformer model to capture dynamic features and improve the model’s performance. A two-stage training method, based on the actor-critic algorithm, is proposed to determine the optimal policy function. To evaluate the HDRLITF method, experiments were conducted using datasets from the cities of Shenzhen and Chengdu in China. The experimental results suggest that the HDRLITF method can effectively interact with real-time traffic environments and obtain high-quality solutions compared to other deep reinforcement learning methods. The robustness and reliability of HDRLITF were further validated across multiple traffic scenarios and indicators.

Assessment of Ventilation Potential and Construction of Wind Corridors in Chengdu City Based on Multi-Source Data and Multi-Model Analysis

The establishment of urban ventilation corridors (UVCs) aims to mitigate the urban heat island effect. While most studies focus on the construction and assessment of the environmental benefit of UVCs, they often overlook the analysis of UVCs’ topological features. This research integrates multi-source data including 3D urban buildings, historical meteorological observations, high-resolution remote sensing, and land use planning, combined with multiple models, including geographic information system spatial analysis, circuit theory, and complex networks. Based on an assessment of urban ventilation potential, the circuit model was applied to extract UVCs aligned with the prevailing wind direction for both summer and winter seasons. Complex network modeling was employed to analyze the topological features of the ventilation network. From the analytical results, a multi-level wind corridor system for Chengdu was quantitatively developed. The results indicate that the city’s overall ventilation resistance is high, with notable spatial clustering, and the southeastern region faces substantial ventilation obstructions. A total of 143 critical ventilation nodes were identified, with the number of air inlets and outlets in summer being significantly fewer than in winter. However, the cooling effect of ventilation corridors in the prevailing summer wind direction is superior to that in winter. The ventilation network comprises 16 communities with distinct ventilation characteristics, exhibiting moderate connectivity, lacking small-world properties, and showing congestion and instability.

Prospects for Long-Distance Cascaded Liquid—Gaseous Hydrogen Delivery: An Economic and Environmental Assessment

As an important energy source to achieve carbon neutrality, green hydrogen has always faced the problems of high use cost and unsatisfactory environmental benefits due to its remote production areas. Therefore, a liquid-gaseous cascade green hydrogen delivery scheme is proposed in this article. In this scheme, green hydrogen is liquefied into high-density and low-pressure liquid hydrogen to enable the transport of large quantities of green hydrogen over long distances. After long-distance transport, the liquid hydrogen is stored and then gasified at transfer stations and converted into high-pressure hydrogen for distribution to the nearby hydrogen facilities in cities. In addition, this study conducted a detailed model evaluation of the scheme around the actual case of hydrogen energy demand in Chengdu City in China and compared it with conventional hydrogen delivery methods. The results show that the unit hydrogen cost of the liquid-gaseous cascade green hydrogen delivery scheme is only 51.58 CNY/kgH2, and the dynamic payback periods of long- and short-distance transportation stages are 13.61 years and 7.02 years, respectively. In terms of carbon emissions, this scheme only generates indirect carbon emissions of 2.98 kgCO2/kgH2 without using utility electricity. In sum, both the economic and carbon emission analyses demonstrate the advantages of the liquid-gaseous cascade green hydrogen delivery scheme. With further reductions in electricity prices and liquefication costs, this scheme has the potential to provide an economically/environmentally superior solution for future large-scale green hydrogen applications.

Identification and Spatial Characterization of suburban areas in Chengdu

As transitional territories where urban and rural functions interpenetrate, suburban areas have multiple values such as recreation, ecology, agriculture and landscape. Promoting their benign development is the key to realizing global sustainable development of urban and rural areas. Planning control is based on precisely defining the spatial extent of suburban areas, and understanding suburban area differentiation and its driving forces scientifically is a key component in raising the bar for focused planning. However, there are currently few research on fine-scale quantitative identification of suburban regions because of their spatial complexity, ambiguous boundaries, and structural dynamic features. Based on this, this paper develops a multi-dimensional identification index system for suburban areas by using multi-source big data and remote sensing information technology, employs the random forest model and the K-Medoids clustering algorithm, identifies the distribution of suburban areas and their subdivided types, analyzes spatial differentiation characteristics, and conducts empirical research using Chengdu City as an example. The findings demonstrate that: (1) The majority of suburban areas in Chengdu City are concentrated in groups or belts surrounding the urban centers of various districts and counties, and the higher the functional class of a district or county, the denser the distribution of suburban areas. (2)The distribution pattern of suburban areas in Chengdu basically conforms to its planned urban hierarchy system.(3)Urban-oriented, suburban-interacted and rural-oriented suburban areas have their own characteristics in land use level, economic development and regional population characteristics.(4)Regional openness, government behavior, social development and geographical location are the core driving factors of spatial differentiation of suburban areas in Chengdu, and the interaction between urban and rural systems, the flow of social resources and the transformation of development models are the spatial mapping dimensions that affect its differentiation.(5)Chengdu can draw up detailed regulatory planning of suburban units to standardize and guide the overall development of suburban areas. In support of the global sustainable development goals, this study offers a methodology for precisely and impartially defining suburban areas, assisting in the implementation of integrated urban-rural development globally.

The Impact of Family Cultural Capital, School Environment, and Peer Relationships on Scientific Literacy among Primary School Students

This study explores the influence of family cultural capital, school environment, and peer relationships on the scientific literacy of primary school students in Chengdu City, China. As scientific literacy becomes increasingly vital for students to navigate the complexities of modern society, this study examines how these socio-cultural factors collectively impact students' understanding and engagement with science. Family cultural capital, including parental education and home resources, plays a critical role in shaping scientific literacy. Simultaneously, the school environment and quality of science education, along with peer relationships, significantly influence students' academic motivation and performance in science. By analyzing these interactions, this paper provides valuable insights into the socio-cultural determinants of scientific literacy, offering practical recommendations for educators and policymakers to foster improved educational outcomes in Chengdu and similar urban settings.1

Application of BIM and Virtual Reality of System Integration Design and Development in Medical Building Projects: A Case Study in China

Design outcomes in the Medical Building Projects (MBPs) must satisfy the demand of the medical staff and stakeholders. However, they often do not have the relevant engineering expertise, so the design team is prone to misunderstandings when communicating with them using traditional two-dimensional (2D) Computer-Aided Design (CAD) drawings. The medical staff may not readily visualize and understand the design and then provide feedback to the designer through professional medical requirements or advice, which results in the need to redesign and carry out additional work during the design phase, thus delaying the progress of the MBPs. To address these challenges, this study aims to develop an integrated system based on BIM, advanced rendering engines, and VR technology for use in non-immersive and immersive VR environments. Moreover, in this study, the integrated system was applied to the infection-building project of the People's Hospital of Qingbaijiang District, Chengdu City, and semi-structured interviews were distributed to 16 engineers, designers, contractors, and medical staff who had been involved in the whole project to validate the practicality and effectiveness of the integrated system. The results indicate that this system integration is an efficient visual communication and simulation tool in medical design. Key advantages include enhanced communication efficiency between the design team and medical stakeholders, improved visual interaction, and streamlined decision-making processes within a 3D VR/BIM environment. The successful implementation of this integrated system is expected to significantly aid design teams and stakeholders in effectively managing medical design tasks in future projects.

Research and Application of Traffic Flow Prediction in Chengdu City Based on Neural Network Algorithms

As urban traffic systems increase in complexity, accurately predicting traffic flow has become a critical task in traffic management and planning. This paper employs neural network technologies, specifically Graph Convolutional Networks (GCN) and Long Short-Term Memory networks (LSTM), to develop a traffic flow prediction model for Chengdu that incorporates spatio-temporal characteristics. Through empirical analysis, the model demonstrates high accuracy and good generalization capability, effectively predicting and analyzing traffic flow at different times and regions. Additionally, this study explores the application of the prediction model in traffic law regulation and policy formulation, providing data support and scientific basis for advancing smarter traffic systems.

The performance evaluation of homestead exit under the background of rural revitalization

The reform of rural residential land system was piloted in 2015. Then, the scope of the pilot was expanded in 2020. An important part of the reform of the homestead system is the homestead exit, which is also a basic and important front-end link in the reform of the homestead system. In this study, the four pilot area: Pengshan District, Ziyang City, Cuiping District and Luxian District, which are close to Chengdu City of Sichuan Province, were investigated and questionnaires were distributed to the farmers. Based on the research data, from the perspective of farmers, this study selects indicators from three aspects including economic benefits, social benefits and living environment to make sub-objective evaluation and comprehensive evaluation of homestead exit performance. In the calculation process, the entropy weight method is used to calculate the weight of each index and the fuzzy comprehensive evaluation method is used to calculate the performance score. The research results show that the comprehensive performance of homestead exit in the surveyed areas is “good”, and the performance evaluation results are “average”, “good” and “good” respectively from the three aspects of economic benefits, social benefits and living environment.

Combining human perception and street accessibility to provide information for better street construction: a case study of Chengdu City, China

ABSTRACT High-quality street spaces have a positive impact on residents’ lives. Revealing the differences in human perception and walkability across street spaces can highlight priority areas for street quality enhancement and provide valuable insights that help urban managers make informed decisions. This study first utilised machine learning models (SegNet) to extract visual elements from street view images and collected volunteers’ ratings of six perceptual dimensions of street scenes. Subsequently, it employed random forest algorithms and spatial autocorrelation models to predict and analyse overall street perception. Furthermore, principal component analysis was used to consolidate the six perceptual scores, coupled with an analysis of street walkability, to identify streets that most required quality enhancement. Finally, correlation and regression analyses were conducted between human perception ratings and street visual elements. The results indicated that buildings positively influence perceptions of wealth, safety, liveliness, and beauty and are the most significant positive perception elements. Conversely, walls were the most significant negative perception elements. Additionally, trees positively impacted perceptions of liveliness and beauty. Lastly, streets categorised as “high walkable-low perception” exhibited a radial dispersion from the city centre. In conclusion, the findings of this study provide valuable insights for enhancing street-space quality in Chengdu and other cities.

Exploring the Influence of Family Cultural Capital, School Environment, and Peer Relationships on the Scientific Literacy of Primary School Students: A Conceptual Analysis in Chengdu City, China

This paper explores the impact of blended education on the quality of college student learning in Southwest China during the post-epidemic era. The study highlights the potential of blended learning to enhance student engagement, adaptability, and learning outcomes through the integration of digital tools with traditional teaching methods. It identifies critical factors such as institutional support, technological infrastructure, and faculty training as essential for maximizing the benefits of blended education. Additionally, the paper examines the unique socio-cultural context of Southwest China, emphasizing the need to address regional disparities in digital access to ensure educational equity. The findings suggest that blended education can serve as a transformative model for higher education in the region, fostering essential 21st-century skills and reducing educational inequalities. The paper concludes with recommendations for policymakers and educators to support the sustainable implementation of blended education, contributing to a more resilient and inclusive higher education system.

Comparison of Three Influenza Surveillance Data Sources for Timely Detection of Epidemic Onset - Chengdu City, Sichuan Province and Beijing Municipality, China, 2017-2023.

The syndromic surveillance system, exemplified by the influenza-like illness (ILI) surveillance system, has long been crucial in providing early warnings of influenza epidemics. The analysis revealed that employing reported influenza case data from the nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS) enhanced the early detection of influenza epidemics, particularly within the context of multiple respiratory pathogens circulating concurrently. The NIDRIS, characterized by its extensive coverage, obligatory reporting, high specificity, and real-time data transmission, offers a valuable tool for the effective early detection of influenza epidemics. Utilizing this system could enhance preparedness and responses to such health crises, potentially mitigating their impact on public health.