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The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence of users in the Beijing city area and obtain commuting data of the employed to measure the employment center system in Beijing. Firstly, the employment density distribution is generated using the data of the working places of the employed persons, and the employment centers are identified based on the employment density of Beijing. Then, we use the business registration data of employment centers to measure the industrial diversity within the employment centers by using the ecological Shannon Wiener Diversity Index, and combine the commuting links between employment centers and places of residence to measure the energy level of each employment center, analyze the hinterland and sphere of influence of each center, and finally using the industrial diversity index of employment centers and the average commuting time of employed persons, combined with the K-Means clustering algorithm, to classify the employment centers in Beijing. The employment center identification and classification method based on big data constructed in this study can help solve the limitations of the previous employment center system research in terms of center identification and commuting linkage measurement due to large spatial units and lack of commuting data to a certain extent. The study can provide reference for the regular understanding and technical analysis of employment centers and provide help for the employment multi-center system in Beijing in terms of quantifying the employment spatial structure, guiding the construction of multi-center system, and adjusting the land use rules. [ABSTRACT FROM AUTHOR]

Under the background of global climate change, rainstorm and flood disasters have become the most serious cataclysm. Under the circumstances of an increasingly severe risk situation, it is necessary to enhance urban disaster resilience. Based on the disaster resilience process of prevention, absorption, and enhancement, and considering the safety factors such as personnel, facility, environment and management, this paper forms a dual dimension of the urban disaster resilience assessment model covering the key elements of urban disaster response and the core capacity of urban disaster recovery. Furthermore, if taking into account the characteristics of rainstorm and flood disasters, the paper screens the key indicators to build up an assessment index system of an urban rainstorm and flood disaster. The practical application was implemented in Beijing to have an assessment of the ability to recover from rainstorm and flood disasters in all districts of Beijing. And then, some pertinent suggestions for enhancing the resilience of Beijing to rainstorm and flood disasters were proposed. [ABSTRACT FROM AUTHOR]

Understanding air quality requires a comprehensive understanding of its various factors. Most of the association rule techniques focuses on high frequency terms, ignoring the potential importance of low- frequency terms and causing unnecessary storage space waste. Therefore, a dynamic genetic association rule mining algorithm is proposed in this paper, which combines the improved dynamic genetic algorithm with the association rule mining algorithm to realize the importance mining of low- frequency terms. Firstly, in the chromosome coding phase of genetic algorithm, an innovative multi-information coding strategy is proposed, which selectively stores similar values of different levels in one storage unit. It avoids storing all the values at once and facilitates efficient mining of valid rules later. Secondly, by weighting the evaluation indicators such as support, confidence and promotion in association rule mining, a new evaluation index is formed, avoiding the need to set a minimum threshold for high-interest rules. Finally, in order to improve the mining performance of the rules, the dynamic crossover rate and mutation rate are set to improve the search efficiency of the algorithm. In the experimental stage, this paper adopts the 2016 annual air quality data set of Beijing to verify the effectiveness of the unit point multi-information coding strategy in reducing the rule storage air, the effectiveness of mining the rules formed by the low frequency item set, and the effectiveness of combining the rule mining algorithm with the swarm intelligence optimization algorithm in terms of search time and convergence. In the experimental stage, this paper adopts the 2016 annual air quality data set of Beijing to verify the effectiveness of the above three aspects. The unit point multi-information coding strategy reduced the rule space storage consumption by 50%, the new evaluation index can mine more interesting rules whose interest level can be up to 90%, while mining the rules formed by the lower frequency terms, and in terms of search time, we reduced it about 20% compared with some meta-heuristic algorithms, while improving convergence. [ABSTRACT FROM AUTHOR]

Government-enterprise-university synergy (GEUS) is an effective way to mobilize government, enterprises, and universities to collaborate on education, but these three parties involved in GEUS may, out of bounded rationality, choose to collaborate in ways that benefit themselves and harm others. To guide the three parties to better cooperation, this study creates an evolutionary game model among the three parties and evaluates the applicability and validity of the model by selecting the educational cooperation data in Beijing. It is shown that participation in education cooperation is the best course of action for all three parties. The intensity of willingness to participate in the GEUS is on the order of high to low for universities, enterprises, and the government. If the three parties wish to accomplish education collaboration sooner, they can increase default payments, boost government revenues, raise corporate participation in distribution, and reduce government and government spending. These results highlight the inherent regularities of GEUS and provide concrete implementation strategies to improve the efficiency of education cooperation. [ABSTRACT FROM AUTHOR]

Urban last-mile express delivery in China encounters several challenges. This paper presents the establishment of a sharing logistics center aimed at enhancing the overall efficiency of urban last-mile express delivery while optimizing the utilization of essential resources. The successful implementation of shared delivery within sharing logistics center necessitates the creation of a robust collaborative mechanism. Recognizing that cooperative benefit allocation is dynamically influenced by factors such as resource input, operational efficiency, risk management, and other cost-related considerations, this study introduces a multi-weight H-Shapley value method for benefit allocation. By conducting empirical analyses of urban last-mile express delivery in Beijing within a sharing logistics service framework, our findings reveal that the revised benefit allocation model better aligns with the interests of participating entities and positively correlates with their contributions. Analyzing the impact of delivery volume and express operational costs changes, it is found that when the delivery volume and express operational costs of the sharing logistics center change, the benefits of participating enterprises move in the same direction. The benefit allocation model established in this study enriches the existing body of research in the field of shared delivery and offers valuable insights for benefit allocation issues that necessitate consideration of the dynamic effects of multiple parameter variations. [ABSTRACT FROM AUTHOR]

The vegetable sector is a vital pillar of society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. In this paper, we exploit the average daily price data of six distinct types of vegetables sourced from seven key wholesale markets in Beijing, spanning from 2009 to 2023. Upon training an LSTM model, we discovered that it exhibited exceptional performance on the test dataset. Demonstrating robust predictive performance across various vegetable categories, the LSTM model shows commendable generalization abilities. Moreover, LSTM model has a higher accuracy compared to several machine learning methods, including CNN-based time series forecasting approaches. With R2 score of 0.958 and MAE of 0.143, our LSTM model registers an enhancement of over 5% in forecast accuracy relative to conventional machine learning counterparts. Therefore, by predicting vegetable prices for the upcoming week, we envision this LSTM model application in real-world settings to aid growers, consumers, and policymakers in facilitating informed decision-making. The insights derived from this forecasting research could augment market transparency and optimize supply chain management. Furthermore, it contributes to the market stability and the balance of supply and demand, offering a valuable reference for the sustainable development of the vegetable industry. [ABSTRACT FROM AUTHOR]

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5. [ABSTRACT FROM AUTHOR]

The production connection is a crucial component of the Inter City Association. An urban network based on the enterprise perspective better reflects the structural characteristics of regional cities. Based on data gathered from the headquarters and branches of the listed manufacturing enterprises in 2020, this paper analyzes the county-level administrative units in the Beijing-Tianjin-Hebei region of China. Using the subordinate connection model and the social network analysis method, this paper examines the spatial structural characteristics and factors of urban networks in the Beijing-Tianjin-Hebei region. The results suggest that resource allocation in the Beijing-Tianjin-Hebei region is unbalanced, with a significant difference in urban radiation and agglomeration capacity. As the administrative centers, Beijing, Tianjin, and Shijiazhuang show a strong ability to allocate resources within the network. The overall network density in the region was shown to be relatively low, with the main links being of low or medium level. The urban network is defined by the network connection led by Beijing and Tianjin with Beijing-Tianjin-Tangshan and Beijing-Baoding-Shijiazhuang as the main axis. These cities exhibit a "dense southeast and sparse northwest" pattern. From a hierarchical perspective, high-level network connections are based mainly on spatial proximity. Analyzing the agglomerative subgroups, the study found that the inner and outer connections of the core subgroups were relatively high. Semi-marginal subgroups generally accepted the radiation of core subgroups, while marginal subgroups had little connection with other subgroups in the region. The results of the QAP analysis show that the administrative relationship, spatial distance, city size difference, economic development level difference, industrial structure difference, and labor cost difference have a significant influence on the urban network of the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

This paper constructs a matching index model to research the matching degree of embodied carbon trade and value-added trade among eight regions and 31 provinces in China in 2012 and 2015. The study finds that (1) At the regional level, a mismatch is shown between embodied carbon trade and value-added trade among regions, for example, in 2015, the northwest region has output embodied carbon to the north coast, while input the value-added trades from the north coast. (2) At the provincial level, a mismatch is displayed between embodied carbon transaction and value-added trade, for example, Beijing had a net shift of embodied carbon from Xinjiang in 2015, but Xinjiang had a net transfer of added value from Beijing. Therefore, the Chinese government needs to establish an ecological compensation mechanism to improve the mismatch between embodied carbon trade and value-added trade among Chinese regions (provinces). [ABSTRACT FROM AUTHOR]

In the process of development, global economies are prioritizing environmental protection and firms are also recognizing the importance of minimizing environmental impact during production along with maximization of profits through green investments. It is vivid that green investments are vital for environmental preservation. So this paper contributes to literature by investigating the role of internal and external factors affecting the decision making of Chinese firms regarding adoption of green investments and impact of green investments on environmental, social, and economic performance of firms. The data is collected from directors/senior managers of the firms. We received 463 valid responses from listed companies with Shenzhen, Beijing, and Shanghai Stock Exchange. The "structural equation modeling" with "maximum likelihood estimation" is employed for empirical analysis. The empirical findings reveal that adaptation to climate change and its mitigation is the most important driver of green investment. Moreover, green investment positively contributes to enhancing the social, economic, and environmental performances of Chinese firms. Based on the findings of the study, green investment should be adopted as a corporate strategy by firms for profit maximization, competitive advantage, and improvement in social well-being without compromising the environment. Policy makers can promote green investment by offering policy instruments such as tax incentives, guaranteed credits, grants, and investor education. Training courses may be offered to raise environmental awareness among firms and the general public. [ABSTRACT FROM AUTHOR]

The transportation industry has entered a new stage from quantity expanding to structure optimization, quality and efficiency improvement, and from respective governance to integrative development. This indicates that the traditional corridor mode allocation dominated by quantity equilibrium can no longer meet the requirements of the new stage. In this paper, we propose a multi-entity programming model based on the economic equilibrium between supply and demand. It not only ensures the economic equilibrium in the market, but also maximizes the social benefits of the whole system, thereby realizing the sustainable development of the transportation system. Also, the Globalsearch algorithm and intlinprog algorithm are designed to solve the problem. The actual case of Beijing-Shanghai corridor shows that the model and algorithms are effective, providing decision support for the optimal allocation of regional transport network resources. [ABSTRACT FROM AUTHOR]

This paper examines whether mega-events-initiated planning regulations improved air quality in Chinese cities and explores the driving forces of the enforcement of such regulations. Using the 2008 Beijing Olympics as an example, we find that mega-events serve as an opportunity for cities to combat air pollution. The 2008 Olympics prompted a handful of Chinese cities to cut pollution and sustain a blue sky: Cities with air quality regulated for the Olympics cut their Air Pollution Index by about 16 points during the Games, compared to non-regulated cities, and 60% of that effect remained four years after the event. These achievements are obtained through effective mobilization of city leaders by associating air quality with their political careers. This study reveals that 1) a mega-event may improve urban environmental quality beyond the host cities and the event period, and 2) successful implementation of environmental regulations hinges on incentivizing local leaders. [ABSTRACT FROM AUTHOR]

Industrial upgrading and transfer is one of the three key areas in the coordinated development of Beijing-Tianjin-Hebei Region. Meetings, incentives, conferences and exhibitions (MICE) are important means of promoting industrial upgrading. Urban MICE industry, as an important carrier of event activities, become an important gripper for coordinated development of Beijing-Tianjin-Hebei Region. City exhibition space structure plays an dominant role in regional economic development, and it will greatly promote smooth implementation of the coordinated development strategy of Beijing-Tianjin-Hebei Region. In this paper, 13 prefecture-level cities in Beijing, Tianjin and Hebei were selected as research objects, and the data from 2012 to 2018 were selected to establish a gravity model of the attractiveness of MICE cities. With the help of UCINET software, the network density, centrality, cohesive subgroup and core-edge of nodes researches were obtained to analyze the spatial structure characteristics of the attractiveness of MICE cities in Beijing-Tianjin-Hebei Region. The influencing factors of the spatial characteristics of MICE city attractiveness are analyzed by using geographically weighted regression model. The results show that: (1) Beijing, as the overall core area, act as a prominent role. Beijing strengthens the attraction to the superior resources of the surrounding areas, but the network of MICE cities tends to be unbalanced. (2) Overall space forms a subgroup from a single independent subgroup to a subgroup that is spatially separated from each other and acts as an intermediary channel to connect each other, and the core region decreases from 3 to 2. Langfang was removed from the list, leaving Beijing and Tianjin as the core. (3) The influence of supporting facilities, urban environment and population factors on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is increasing gradually. The influence of tourism development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is decreasing gradually. The influence of economic development level and Internet development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region remains unchanged. [ABSTRACT FROM AUTHOR]

Whether the place-based industrial policy promotes regional economic growth is a hot issue in the field of regional industrial economic practice. As a major national strategy in China, the Beijing-Tianjin-Hebei industrial coordinated development policy has been implemented more than 8 years. Verifying its effect on regional economic growth and revealing the policy action path will help to further optimize the policy implementation process through feedback. In this paper, the policy effect and its differentiation are empirically studied from 'quality' and 'quantity' respectively by establishing a growth model using the Dual Differences method. The results show that the Beijing-Tianjin-Hebei industrial coordinated development policy improves total factor productivity by 2.26% in terms of 'quality', and reduces GDP growth rate by 4.65% in terms of 'quantity'. For the different region, the GDP growth rate increased by 1.28%, while total factor productivity decreased by 2.63% in Beijing, the GDP growth rate decreased by 3.17% and total factor productivity increased by 0.87% in Tianjin, and the GDP growth rate increased by 2.56% and total factor productivity increased by 1.58% in Hebei. The policy is mainly realized by fixed asset investment, capital deepening degree and enterprise scale expansion, while the effect of labor input, R&D investment and enterprise number is not significant. The policy is to give full play to the driving role of fixed asset investment such as "new infrastructure", increase investment in labor and research and development in the region, strengthen the construction of a competitive market environment, and stabilize the 'quality' and 'quantity' to further release policy dividends. [ABSTRACT FROM AUTHOR]

After the cold war, some countries gradually seek to regional cooperation when they could not handle various transnational challenges alone. Shanghai Cooperation Organization (SCO) is a good example. It brought Central Asian countries together. This paper applies the text-mining method, using co-word analysis, co-occurrence matrix, cluster analysis, and strategic diagram to analyze the selected articles from newspapers quantitatively and visually. In order to investigate the Chinese government's attitude toward the SCO, this study collected data from the China Core Newspaper Full-text Database, which contains high-impact government newspapers revealing the Chinese government's perception of the SCO. This study characterizes the changing role of SCO as perceived by the Chinese government from 2001 to 2019. Beijing's changing expectations in each of the three identified subperiods are described. [ABSTRACT FROM AUTHOR]

Objective: While growing psychological health issues among pregnant women during the COVID-19 pandemic have been clearly validated, most research was conducted in countries with relatively lax quarantine measures. This study aimed to compare the prevalence of prenatal depression among pre-, peak-, and post-COVID-19 in Beijing, the region with a stringent response policy in China. We also explore predictors of prenatal depression throughout the outbreak. Methods: We investigated prenatal depression among 742 pregnant women who received antenatal checkups in Beijing from March 28, 2019 to May 07, 2021 using the Edinburgh Postnatal Depression Scale and associative demographic, pregnancy-related, and psychosocial characteristics were measured. The phase was divided into pre-, peak-, and post-COVID-19 in light of the trajectory of COVID-19. Pearson's Chi-square test was used after the examination of confounders homogeneity. The bivariable and multivariable logistic regression was conducted to explore predictors. Results: The pooled prevalence of prenatal depression was 11.9% throughout the COVID-19 pandemic. Rates at different phases were 10.6%, 15.2%, and 11.1% respectively and no significant difference was observed. Multivariable logistic regression revealed that history of mental illness, number of boy-preference from both pregnant women and husband's family, social support, occupation, and living space were independent predictors of prenatal depression in Beijing. Conclusion: Our data suggested that the impact of this pandemic on prenatal depression in Beijing appears to be not significant, which will strengthen confidence in adhering to current policy for decision-makers and provide important guidance for the development of major outbreak control and management policies in the future. Our findings may also provide a more efficient measure to identify high-risk pregnant women for professionals and help raise gender equity awareness of pregnant women and their husbands' families. Future studies should focus on the value of targeted care and family relations on the mental health of pregnant women. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the underlying factors driving the onset of myopia, specifically the role of the ciliary muscle's contraction in the elongation of the axial length of the eye. Methods: The retrospective study was conducted utilizing data from three ophthalmic centers in Shanghai and Beijing. Both Chinese and Caucasian children were involved. The axial length of the subjects' eyes was measured in both relaxed and contracted state of the ciliary muscle. A comprehensive mechanical model was also developed to observe the influence of ciliary muscle contraction on the axial length. Results: This study included a sample of 198 right eyes of 198 myopic children. Of these, 97 were male and 101 were female, 126 were of Chinese ethnicity and 72 were Caucasian. The age of onset for myopia ranged from 5.9 to 16.9 years old. The axial length of the eye decreased 0.028 ± 0.007mm following dilation, indicating relaxation of the ciliary muscle (t paired student = 15.16, p = 6.72 x 10−35). In contrast, ciliary muscle contraction resulted in an increase in axial length. Considering proportionality, a significant 90.4% (179 eyes) exhibited a reduced axial length, while a minor 9.6% (19 eyes) demonstrated an increase post-mydriasis. Finite element modeling demonstrated that muscle contraction caused a tension force that transmits towards the posterior pole of the eye, causing it to extend posteriorly. Conclusion: The contraction of the ciliary muscle leads to an extension of the axial length. This could potentially be the initiating factor for myopia. [ABSTRACT FROM AUTHOR]

Beijing plain is a strong earthquake tectonic area in China. There was a Sanhe-Pinggu earthquake with Ms8 that happened in1679. The seismogenic fault of this earthquake is called Xiadian fault. Our work found fault with a similar strike and opposite dip in the west of the Xiadian fault, which is called the Xiadian west fault in this paper. Six shallow seismic profiles have been constructed to determine the location of the fault in Sanhe city, and the late Quaternary activity of the fault is studied with the method of combined drilling, magnetic susceptibility logging, and luminescence dating. The results of shallow seismic exploration show that the fault is zigzag and generally strikes NE and inclines NW. According to the core histogram and logging curves of ten boreholes and eight effective dating data, the buried depth of the upper breakpoint of the concealed fault is about 12 m, which dislocates the late Pleistocene strata. The effective dating result of this set of strata is 36.52 ±5.39 ka. The vertical slip rate has been about 0.075± 0.023 mm/a since the late Pleistocene and about 0.058 ± 0.030 mm/a since the late period of the late Pleistocene. It can be inferred that the Xiadian west fault is probably a part of the seismogenic structure of the Sanhe-Pinggu Ms8 earthquake that happened in 1679. In a broad sense, the Xiadian fault zone is likely to extend to the southwest along the Xiadian west fault. [ABSTRACT FROM AUTHOR]

In regional land-use planning, many different demands for often-limited land resources must be weighed against each other. Analysis of the benefits of different land-use types is of great significance in land-use design. However, a good evaluation methodology does not exist. To facilitate a comparative analysis of land-use benefits, this paper presents an evaluation system consisting of four steps: (1) Connotation dissection to determine the land-use benefits, (2) construction of a land-use benefit classification system to summarize a limited number of land-use benefit types by an inductive method, (3) land-use benefit valuation, which includes a biophysical model, direct and indirect market valuations, and The Economics of Ecosystems and Biodiversity value conversion method, and (4) case analysis of the evaluation results according to local conditions. Empirical results from a case study of Mentougou District, Beijing, China, show that (i) the evaluation results of land-use benefit groups provides information on each land-use type and the spatial distribution of land-use benefits in Mentougou District, (ii) the topography of Mentougou District has an important influence on economic and ecological land-use benefits, and (iii) there is a synergistic effect of economic and social land-use benefits. [ABSTRACT FROM AUTHOR]

COVID-19 leads small and medium-sized enterprises (SMEs) to survive very hard. The development difficulties of SMEs lead to weak employment and GDP growth in various countries. In the process of COVID-19's continuous spread, what is the major reason for the difficulties of SMEs? This paper hopes to answer this question by studying SMEs in Beijing. On this basis, this paper uses structural equation model (SEM) to study the relatively fast recovery of SMEs in Beijing, China, to explore the factors affecting SMEs in the pandemic. After detailed desk research and interviews with relevant entrepreneurs, this paper collects 234 valid questionnaires from SMEs in various industries in Beijing with the help of Federation of Industry and Commerce and Chamber of Commerce in Beijing. Then the data is analyzed with the SEM, which shows the relationship between cash flow from financing activities, markets, employees, costs, government policies and the impact of the pandemic. Finally, an impact model of the pandemic on SMEs is established. The result of the model indicates that the direct effect of the pandemic on the market is the most prominent, and government policies can significantly reduce the negative impact of the pandemic on SMEs indirectly. Based on this, this paper puts forward some policy suggestions, such as the targeted issuance of consumption vouchers and the reduction of administrative barriers. This will enable megacities in various countries to improve policy support for SMEs and promote the recovery and development of SMEs. [ABSTRACT FROM AUTHOR]

China has set a goal to achieve peak CO2 emissions before 2030 and carbon neutrality by 2060. To achieve the goals of carbon peak and carbon neutrality, China needs to address the challenge of the large and still growing CO2 emission base. This paper investigated the energy consumption and CO2 emission in Beijing from 2020–2035 based on the energy elasticity coefficient and contribution value of the sub-energy increment (CVSI) method. Beijing is one of the first cities in China to propose the "carbon peak" target as of 2020. From 2020 Beijing will strive to achieve the goal of carbon neutrality. The results show that in 2035 the CO2 emission in Beijing may drop to 50% of 2020. This decline would be affected by economic growth, energy efficiency and the proportion of renewable energy use. Beijing's energy supply mainly comes from outside the region. Therefore, for Beijing, in addition to increasing the proportion of renewable energy sources outside the region, its own energy acceptance also needs to be strengthened, including strengthening energy storage construction, actively researching and promoting carbon capture and utilization of gas-fired units, which are effective ways to achieve carbon neutrality target. [ABSTRACT FROM AUTHOR]

As urbanization speeds up, the concept of healthy cities is receiving more focus. This article compares Chongzuo and Nanning in Guangxi with Beijing to assess the development gaps in cities in Guangxi. An indicator system for healthy cities was designed from six dimensions—healthy economy, healthy population, healthy healthcare, healthy environment, healthy facilities, and healthy transportation—and 26 secondary indicators, which were selected from 2005 to 2022, and an improved factor analysis was used to synthesize a healthy city index (HCI). The number of factors was determined by combining characteristic roots and the variance contribution rate, and the HCI was weighted using the entropy-weighted Topsis method. A comprehensive evaluation of the urban health status of these cities was conducted. The results showed that extracting six common factors had the greatest effect, with a cumulative variance contribution rate of 93.83%. Chongzuo city scored higher in the field of healthcare. The healthy environment score of Nanning was relatively high, which may be related to continuous increases in green measures. In terms of the healthy economy dimension, Beijing was far ahead. However, in recent years, the healthy economy level in Chongzuo has increased, and the GDP growth rate has ranked among the highest in Guangxi. In addition, the growth rate of healthy facilities in Nanning was relatively fast and has been greater than that in Chongzuo in recent years, which indicates that the Nanning Municipal Government believes urban construction and municipal supporting facilities are highly important. In terms of healthy transportation, Chongzuo and Nanning scored higher than Beijing. This may be because the transportation in these two cities is convenient and the traffic density is more balanced than that in Beijing, thereby reducing traffic congestion. Chongzuo had the highest score for a healthy population, and a steadily growing population provides the city with stable human resources, which helps promote urban economic and social development. Finally, relevant policy recommendations were put forwards to enhance the health level of the cities. [ABSTRACT FROM AUTHOR]

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided. [ABSTRACT FROM AUTHOR]

Little information exists on the variation in morphological characteristics, nutritional value, ruminal degradability, and molecular structural makeup of diverse whole-plant silage corn (WPSC) cultivars among different growing regions. This study investigated the between-regions (Beijing, Urumchi, Cangzhou, Liaoyuan, Tianjin) discrepancies in five widely used WPSC cultivars in China (FKBN, YQ889, YQ23, DK301 and ZD958), in terms of 1) morphological characteristics; 2) crude protein (CP) chemical profile; 3) Cornell Net Carbohydrate and Protein System (CNCPS) CP subfractions; 4) in situ CP degradation kinetics; and 5) CP molecular structures. Our results revealed significant growing region and WPSC cultivar interaction for all estimated morphological characteristics (P < 0.001), CP chemical profile (P < 0.001), CNCPS subfractions (P < 0.001) and CP molecular structural features (P < 0.05). Except ear weight (P = 0.18), all measured morphological characteristics varied among different growing regions (P < 0.001). Besides, WPSC cultivars planted in different areas had remarkably different CP chemical profiles and CNCPS subfractions (P < 0.001). All spectral parameters of protein primary structure of WPSC differed (P < 0.05) due to the growing regions, except amide II area (P = 0.28). Finally, the area ratio of amide I to II was negatively correlated with the contents of soluble CP (δ = -0.66; P = 0.002), CP (δ = -0.61; P = 0.006), non-protein nitrogen (δ = -0.56; P = 0.004) and acid detergent insoluble CP (δ = -0.43; P = 0.008), in conjunction with a positive correlation with moderately degradable CP (PB1; δ = 0.58; P = 0.01). In conclusion, the cultivar of DK301 exhibited high and stable CP content. The WPSC planted in Beijing showed high CP, SCP and NPN. The low rumen degradable protein of WPSC was observed in Urumchi. Meanwhile, above changes in protein profiles and digestibility were strongly connected with the ratio of amide I and amide II. [ABSTRACT FROM AUTHOR]

In China, few molecular epidemiological data on hepatitis C virus (HCV) are available and all previous studies were limited by small sample sizes or specific population characteristics. Here, we report characterization of the epidemic history and transmission dynamics of HCV strains in China. We included HCV sequences of individuals belonging to three HCV surveillance programs: 1) patients diagnosed with HIV infection at the Beijing HIV laboratory network, most of whom were people who inject drugs and former paid blood donors, 2) men who have sex with men, and 3) the general population. We also used publicly available HCV sequences sampled in China in our study. In total, we obtained 1,603 Ns5b and 865 C/E2 sequences from 1,811 individuals. The most common HCV strains were subtypes 1b (29.1%), 3b (25.5%) and 3a (15.1%). In transmission network analysis, factors independently associated with clustering included the region (OR: 0.37, 95% CI: 0.19–0.71), infection subtype (OR: 0.23, 95% CI: 0.1–0.52), and sampling period (OR: 0.43, 95% CI: 0.27–0.68). The history of the major HCV subtypes was complex, which coincided with some important sociomedical events in China. Of note, five of eight HCV subtype (1a, 1b, 2a, 3a, and 3b), which constituted 81.8% HCV strains genotyped in our study, showed a tendency towards decline in the effective population size during the past decade until present, which is a good omen for the goal of eliminating HCV by 2030 in China. [ABSTRACT FROM AUTHOR]

As for the problem that the traditional single depth prediction model has poor strain capacity to the prediction results of time series data when predicting lake eutrophication, this study takes the multi-factor water quality data affecting lake eutrophication as the main research object. A deep reinforcement learning model is proposed, which can realize the mutual conversion of water quality data prediction models at different times, select the optimal prediction strategy of lake eutrophication at the current time according to its own continuous learning, and improve the reinforcement learning algorithm. Firstly, the greedy factor, the fixed parameter of Agent learning training in reinforcement learning, is introduced into an arctangent function and the mean value reward factor is defined. On this basis, three Q estimates are introduced, and the weight parameters are obtained by calculating the realistic value of Q, taking the average value and the minimum value to update the final Q table, so as to get an Improved MIMO-DD-3Q Learning model. The preliminary prediction results of lake eutrophication are obtained, and the errors obtained are used as the secondary input to continue updating the Q table to build the final Improved MIMO-DD-3Q Learning model, so as to achieve the final prediction of water eutrophication. In this study, multi-factor water quality data of Yongding River in Beijing were selected from 0:00 on July 26, 2021 to 0:00 on September 5, 2021. Firstly, data smoothing and principal component analysis were carried out to confirm that there was a certain correlation between all factors in the occurrence of lake eutrophication. Then, the Improved MIMO-DD-3Q Learning prediction model was used for experimental verification. The results show that the Improved MIMO-DD-3Q Learning model has a good effect in the field of lake eutrophication prediction. [ABSTRACT FROM AUTHOR]

The emergence of Chinese opera animation allows a wider audience, especially a younger audience, to access and embrace the art of opera heritage. This study used a two-way mixed-design ANOVA to explore the effect of Chinese opera animation on schoolchildren's viewing motivation; the independent variables were the children's grade level and the opera genre of the animation. Grade level was divided into three groups: lower, middle, and upper (grades 2, 4, and 6, respectively). Opera genre consisted of Peking, Yue, and Henan opera. The dependent variable, viewing motivation, comprised six dimensions: entertainment and relaxation, learning knowledge, escapist pastime, aesthetic appreciation, empathic identification, and socializing and sharing. After statistically analyzing the evaluations of 457 participants, the results showed the following: (1) Peking and Yue opera animation had a better entertainment and relaxation effect on the lower and middle groups. Henan opera had a better escapist pastime effect on the upper group but less effect on the lower group. (2) In terms of learning knowledge, empathic identification, aesthetic appreciation, and overall performance, Yue and Henan opera animations were more effective for enhancing viewing motivation compared with Peking opera animation. (3) The middle and lower groups showed higher viewing motivation than the upper group in the learning knowledge, empathic identification, and socializing and sharing dimensions. Overall, grades 2 and 4 were appropriate stages for schoolchildren to engage with opera animation. Our findings can provide a reference for promoting cultural heritage sustainability and support follow-up research on integrating opera animation into children's education. [ABSTRACT FROM AUTHOR]

Exploring the operation status and patterns of urban land markets is an important theoretical and practical topic for promoting coordinated socio-economic development. In this study, the operation status of the residential land market in the Beijing-Tianjin-Hebei region and the characteristics of its pattern were analyzed using the composite index method and the 3σ rule of the normal distribution and taking the 174 counties in Beijing, Tianjin, and Hebei, China, as the research objects. The results show that ① Beijing, Tianjin, Langfang, Zhangjiakou, and Baoding residential land market state composite indexes are all in the middle to upper levels in the Beijing-Tianjin-Hebei city cluster, while Qinhuangdao, Handan, and Chengde residential land market state composite indexes are generally low. The harmony between the residential land price and national economy, the market supply and demand balance, and the structural balance may become the main factors affecting the healthy development of the residential land market in Beijing and Tianjin. ② The proportion of counties with "healthy" residential land market in all dimensions and overall market status reached over 64%, and the residential land market in the Beijing-Tianjin-Hebei region is running well. The rapid increase in residential land prices from 2016 to 2020 was an important driver of the increased heat in the residential land market across the region. ③ The residential land market in the counties around Beijing and Tianjin is significantly hotter than in other regions, and there is an obvious polarization effect in the operation state of the residential land market in the Beijing-Tianjin region. The residential land market is generally cold in the counties in the southern and northeastern parts of the region and other peripheral areas, and there is a risk of marginalization in the development of the residential land market in the counties in the peripheral areas. ④ Both the hot and cold residential land market states exhibit spatial clustering characteristics. Most of the clusters are not consistent with the municipal administrative boundaries, and the states of the residential land market in neighboring counties are very similar. [ABSTRACT FROM AUTHOR]

With the advent of Big Data technology and the Internet of Things, Intelligent Transportation Systems (ITS) have become inevitable for future transportation networks. Travel time prediction (TTP) is an essential part of ITS and plays a pivotal role in congestion avoidance and route planning. The novel data sources such as smartphones and in-vehicle navigation applications allow traffic conditions in smart cities to be analyzed and forecast more reliably than ever. Such a massive amount of geospatial data provides a rich source of information for TTP. Gated Recurrent Unit (GRU) has been successfully applied to traffic prediction problems due to its ability to handle long-term traffic sequences. However, the existing GRU does not consider the relationship between various historical travel time positions in the sequences for traffic prediction. We propose an attention-based GRU model for short-term travel time prediction to cope with this problem enabling GRU to learn the relevant context in historical travel time sequences and update the weights of hidden states accordingly. We evaluated the proposed model using FCD data from Beijing. To demonstrate the generalization of our proposed model, we performed a robustness analysis by adding noise obeying Gaussian distribution. The experimental results on test data indicated that our proposed model performed better than the existing deep learning time-series models in terms of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R2). [ABSTRACT FROM AUTHOR]

Early detection of Mycobacterium tuberculosis (Mtb) in clinical specimens, its susceptibility to anti-TB drugs and disruption of infection transmission to new hosts are essential components for global tuberculosis (TB) control efforts. This study investigated major Mtb genotypes circulating in Kuwait and evaluated the performance of REBA MTB-MDR (REBA) test in comparison to GenoType MTBDRplus (gMTBDR+) assay for rapid detection of resistance of Mtb to isoniazid and rifampicin (MDR-TB). M. tuberculosis isolates (n = 256) originating predominantly from expatriate patients during a 6-month period were tested by spoligotyping and a dendrogram was created by UPGMA using MIRU-VNTRplus software. Phenotypic drug susceptibility testing (DST) was performed by MGIT 960 system. Genotypic DST for isoniazid and rifampicin was done by REBA and gMTBDR+ assays. Spoligotyping assigned 188 (73.4%) isolates to specific spoligotype international type (SIT) while 68 isolates exhibited orphan patterns. All major M. tuberculosis lineages were detected and EAI, CAS and Beijing families were predominant. Phylogenetic tree showed 131 patterns with 105 isolates exhibiting a unique pattern while 151 isolates clustered in 26 patterns. Fifteen isolates were resistant to one/more drugs. REBA and gMTBDR+ detected isoniazid resistance in 11/12 and 10/12 and rifampicin resistance in 4/5 and 4/5 resistant isolates, respectively. The diversity of SIT patterns are highly suggestive of infection of most expatriate patients with unique Mtb strains, likely acquired in their native countries before their arrival in Kuwait. Both, REBA and gMTBDR+ assays performed similarly for detection of resistance of Mtb to isoniazid and rifampicin for rapid detection of MDR-TB. [ABSTRACT FROM AUTHOR]

Rapid urbanisation has highlighted problems in the urban ecological environment and stimulated research on the evaluation of urban environments. In previous studies, key factors such as greenness, wetness, and temperature were extracted from satellite images to assess the urban ecological environment. Although air pollution has become increasingly serious as urbanisation proceeds, information on air pollution is not included in existing models. The Sentinel-5P satellite launched by the European Space Agency in 2017 is a reliable data source for monitoring air quality. By making full use of images from Landsat 8, Sentinel-2A, and Sentinel-5P, this work attempts to construct a new remote sensing monitoring index for urban ecology by adding air quality information to the existing remote sensing ecological index. The proposed index was tested in the Beijing metropolitan area using satellite data from 2020. The results obtained using the proposed index differ greatly in the central urban region and near large bodies of water from those obtained using the existing remote sensing monitoring model, indicating that air quality plays a significant role in evaluating the urban ecological environment. Because the model constructed in this study integrates information on vegetation, soil, humidity, heat, and air quality, it can comprehensively and objectively reflect the quality of the urban ecological environment. Consequently, the proposed remote sensing index provides a new approach to effectively monitoring the urban ecological environment. [ABSTRACT FROM AUTHOR]

Beijing and Tianjin are two of the largest cities in northern China with high population densities and highly developed manufacturing industries. In the past decade, some authors have reported their PAH concentrations in surface soils, identified their sources and quantitatively reported their health risks. However, the contributions of different PAH sources to their toxicity have not been reported thus far. In this study, we reviewed the PAH concentrations, contributions of different sources to the toxicity, and cancer risks in soils from different land use types found within Beijing and Tianjin from data gathered by 41 studies. The total PAH concentration varied in the range of 175.7–1989.0 ng g-1 with a higher median PAH concentration detected in urban soils (789.7 ng g-1), followed by suburban soils (647.3 ng g-1) and rural soils (390.8 ng g-1). Source identification using diagnostic ratios and principal component analysis (PCA) suggested that the PAHs in all three land use types mainly originated from biomass and coal combustion, vehicular emissions, and petrogenic processes with contributions varying from 13% to 62%. Furthermore, results from a positive matrix factorization (PMF) model suggested that vehicular emissions and coal combustion in urban soils, and the vehicular emissions, coal combustion and biomass combustion in suburban and rural soils dominated the total PAH concentrations (>85%). These results were consistent with those of the PCA model. Results of the additional toxicity apportionment performed using the PMF model suggested that vehicular emissions and coal combustion contributed the most to the toxic equivalent quantity for Benzo(a)Pyrene (BaPTEQ) and, by extension, to the carcinogenic potencies. The incremental lifetime cancer risk (ILCR) values suggested a low risk level for adults exposed to PAHs in the different land use types found within Beijing and Tianjin. [ABSTRACT FROM AUTHOR]

Background: This study investigated different patterns of emotional labor among community nurses in China and analyzed the relationships between the sense of career success and emotional labor. Methods: A total of 385 community nurses from Beijing participated in this investigation. Latent class analysis was used to identify meaningful subgroups of participants, and analysis of variance was used to analyze relationships between emotional labor classes and the sense of career success. Results: Emotional labor among community nursing staff in China was divided into three latent classes: active (n = 90, 25.6%), apathetic (n = 65, 18.5%), and moderate (n = 197, 55.9%). The active emotional labor classes had significantly higher career success (p<0.05). The "gaining recognition" dimension showed significant differences across the three classes. Conclusion: Our findings suggested managers to implement a variety of measures to strengthen interventions for employees' emotional labor that are targeted to incentive mechanisms, which will improve nurses' sense of career success. [ABSTRACT FROM AUTHOR]

With the steady increase in passenger volume of high-speed railways in China, some high-speed railway sections have faced a difficult situation. To provide more transport services, it is necessary to add as many trains as possible in a section to increase capacity. To solve this problem, a compressed multilayer space-time network model is constructed with the maximum number of trains that can be scheduled in the train timetable as the objective. The combination of the train stop plan and speed level is represented by the layer of network where the train is located, and constraints such as train selection, train safety, train overtake and cross-line trains are considered. A method based on timing-cycle iterative optimization is designed to decompose the original problem into multiple subproblems, and the solving order of the subproblems is determined by a heuristic greedy rule. Taking the Beijing-Jinan section of the Beijing-Shanghai high-speed railway as an example, the maximum number of trains was increased by 12.5% compared with the timetable before optimization. The saturated timetables provide detailed schedules, which helps decision-makers better adjust the timetable to run more trains. [ABSTRACT FROM AUTHOR]

Urban public parks can provide convenience for residents to get close to nature and provide places for daily ecosystem services. It is of practical and theoretical significance to choose urban public parks as the entry point to explore the changing trends and supply paths of urban residents' daily ecosystem service consumption. Based on the government 's research? of urban public parks in Beijing from 1993 to 2018, this study explores the residents' ecosystem services consumption demands and the contributions of park constructions to these demands. The results show that: (1) in the past 25 years, the frequency, duration, participation rate, and evaluation of people's daily ecosystem service consumption have increased significantly. In other words, the ecosystem services demands are increasing. (2) different constructions of a park have distinct contributions to the increasing demands of ecosystem service consumption. The contributions from constructions of the natural landscape and the infrastructure have been in decline since 1993, yet they contribute the most to the demands of residents' ecosystem services consumption until 2018. The contributions made by constructions of management and maintenance, and transportation around urban public parks have been on the rise and the significant points occurring after the 2008 Olympic Games. Our research proposes a method to determine the relation between the demands of residents' ecosystem services consumption and the contributions of park constructions to these demands, which has significant implications for optimizing the constructions of urban public parks to better meet the demands of ecosystem services consumption. [ABSTRACT FROM AUTHOR]

In face of high-investment and low-revenue crisis, it is critical for new-born car-sharing companies to focus on niche market. Existing literatures have already discussed the niche market of car sharing based on people's irregular travel demands and scenarios; however, current research findings are still lack of adequate travel data support. Aiming to solve this problem, we develop a travel scenarios mining method that first define land usage types of travel Origin-Destination (OD) locations using spatial clustering analysis of city's Points of interests (POI) data, and then discover the most representative travel scenarios using association rules mining method with car-sharing records data. Applying this approach to the car-sharing service case in Beijing, China, we find that: day-time business trips and evening entertainment trips around the city centre, commuting trips in off-peak time, and short-distance city travel for tourism are three travel scenarios suitable for car sharing's niche in the initial stage of market entering. Furthermore, spatio-temporal consumption profiles and competitive advantages of car sharing in the three travel scenarios are analyzed. Finally, theoretical and managerial implications are discussed. In this study, we address the question of finding niche market and suggest that it is critical for car sharing industry treading through the crisis in the early stage of development. [ABSTRACT FROM AUTHOR]

With the development of economic integration, Beijing has become more closely connected with surrounding areas, which gradually formed the Beijing metropolitan area (BMA). The authors define the scope of BMA from two dimensions of space and time. BMA is determined to be the built-up area of Beijing and its surrounding 10 districts. Designed questionnaire survey the personal characteristics, family characteristics, and travel characteristics of residents from 10 districts in the surrounding BMA. The statistical analysis of questionnaires shows that the supply of public transportation is insufficient and cannot meet traffic demand. Further, the travel mode prediction model of Softmax regression machine learning algorithm for BMA (SRBM) is established. To further verify the prediction performance of the proposed model, the Multinomial Logit Model (MNL) and Support Vector Machine (SVM), model are introduced to compare the prediction accuracy. The results show that the constructed SRBM model exhibits high prediction accuracy, with an average accuracy of 88.35%, which is 2.83% and 18.11% higher than the SVM and MNL models, respectively. This article provides new ideas for the prediction of travel modes in the Beijing metropolitan area. [ABSTRACT FROM AUTHOR]