The Influencing Legal and Factors of Migrant Children’s Educational Integration Based on Convolutional Neural Network

This research aims to analyze the influencing factors of migrant children’s education integration based on the convolutional neural network (CNN) algorithm. The attention mechanism, LSTM, and GRU are introduced based on the CNN algorithm, to establish an ALGCNN model for text classification. Film and television review data set (MR), Stanford sentiment data set (SST), and news opinion data set (MPQA) are used to analyze the classification accuracy, loss value, Hamming loss (HL), precision (Pre), recall (Re), and micro-F1 (F1) of the ALGCNN model. Then, on the big data platform, data in the Comprehensive Management System of Floating Population and Rental Housing, Student Status Information Management System, and Student Information Management System of Beijing city are taken as samples. The ALGCNN model is used to classify and compare related data. It is found that in the MR, STT, and MPQA data sets, the classification accuracy and loss value of the ALGCNN model are better than other algorithms. HL is the lowest (15.2 ± 1.38%), the Pre is second only to the BERT algorithm, and the Re and F1 are both higher than other algorithms. From 2015 to 2019, the number of migrant children in different grades of elementary school shows a gradual increase. Among migrant children, the number of migrant children from other counties in this province is evidently higher than the number of migrant children from other provinces. Among children of migrant workers, the number of immigrants from other counties in this province is also notably higher than the number of immigrants from other provinces. With the gradual increase in the years, the proportion of township-level expenses shows a gradual decrease, whereas the proportion of district and county-level expenses shows a gradual increase. Moreover, the accuracy of the ALGCNN model in migrant children and local children data classification is 98.6 and 98.9%, respectively. The proportion of migrant children in the first and second grades of a primary school in Beijing city is obviously higher than that of local children (p < 0.05). The average final score of local children was greatly higher than that of migrant children (p < 0.05), whereas the scores of migrant children’s listening methods, learning skills, and learning environment adaptability are lower, which shows that an effective text classification model (ALGCNN) is established based on the CNN algorithm. In short, the children’s education costs, listening methods, learning skills, and learning environment adaptability are the main factors affecting migrant children’s educational integration, and this work provides a reference for the analysis of migrant children’s educational integration.

Seasonal Disparity in the Effect of Meteorological Conditions on Air Quality in China Based on Artificial Intelligence

Air contamination is identified with individuals’ wellbeing and furthermore affects the sustainable development of economy and society. This paper gathered the time series data of seven meteorological conditions variables of Beijing city from 1 November 2013 to 31 October 2017 and utilized the generalized regression neural network optimized by the particle swarm optimization algorithm (PSO-GRNN) to explore seasonal disparity in the impacts of mean atmospheric humidity, maximum wind velocity, insolation duration, mean wind velocity and rain precipitation on air quality index (AQI). The results showed that in general, the most significant impacting factor on air quality in Beijing is insolation duration, mean atmospheric humidity, and maximum wind velocity. In spring and autumn, the meteorological diffusion conditions represented by insolation duration and mean atmospheric humidity had a significant effect on air quality. In summer, temperature and wind are the most significant variables influencing air quality in Beijing; the most important reason for air contamination in Beijing in winter is the increase in air humidity and the deterioration of air diffusion condition. This study investigates the seasonal effects of meteorological conditions on air contamination and suggests a new research method for air quality research. In future studies, the impacts of different variables other than meteorological conditions on air quality should be assessed.

Identification of Policies Based on Assessment-Optimization Model to Confront Vulnerable Resources System with Large Population Scale in a Big City

The conflict between excessive population development and vulnerable resource (including water, food, and energy resources) capacity influenced by multiple uncertainties can increase the difficulty of decision making in a big city with large population scale. In this study, an adaptive population and water–food–energy (WFE) management framework (APRF) incorporating vulnerability assessment, uncertainty analysis, and systemic optimization methods is developed for optimizing the relationship between population development and WFE management (P-WFE) under combined policies. In the APRF, the vulnerability of WFE was calculated by an entropy-based driver–pressure–state–response (E-DPSR) model to reflect the exposure, sensitivity, and adaptability caused by population growth, economic development, and resource governance. Meanwhile, a scenario-based dynamic fuzzy model with Hurwicz criterion (SDFH) is proposed for not only optimizing the relationship of P-WFE with uncertain information expressed as possibility and probability distributions, but also reflecting the risk preference of policymakers with an elected manner. The developed APRF is applied to a real case study of Beijing city, which has characteristics of a large population scale and resource deficit. The results of WFE shortages and population adjustments were obtained to identify an optimized P-WEF plan under various policies, to support the adjustment of the current policy in Beijing city. Meanwhile, the results associated with resource vulnerability and benefit analysis were analyzed for improving the robustness of policy generation.

Therapeutic effect of Xuezhitong capsule on microvascular angina

Purpose: To determine the therapeutic effect of Xuezhitong capsule in patients with microvascular angina (MVA), and its impact on vascular endothelial function.Methods: In total, 172 MVA patients treated in Beijing City Fengtai District Nanyuan Hospital from September 2017 to September 2019 were selected and randomized into control group which received conventional treatment, and treatment group which received Xuezhitong capsules plus. There were 86 patients in each group. Therapeutic effect, levels of inflammatory factors, i.e., high-sensitivity C- reactive protein (hs-CRP), interleukin-(IL-6), tumor necrosis factor-α (TNF-α), and vascular endothelial factors such as nitric oxide (NO), thromboxane B2 (TXB2) and endothelin (ET), were determined.Results: Markedly higher total treatment effectiveness was observed in the treatment group than in the control group (89.53 % vs. 72.94 %; p < 0.05). In both groups, treatment reduced the levels of hs-CRP, IL-6, TNF-α, TXB2 and ET, but elevated NO, with better results for treatment group than the control group (p < 0.05). Better optimizations of total cholesterol (TC), triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein (HDL) were observed in the treatment group, relative to the control group (p < 0.05). Patients in the treatment group experienced fewer (8.14%) adverse reactions than those in control group (21.18 %, p < 0.05).Conclusion: Xuezhitong capsule, when combined with conventional treatment, exerts high therapeutic effectiveness and safety in MVA patients by inhibiting inflammatory reactions, optimizing endothelialfunction, reducing blood lipid levels, and decreasing the incidence of cardiovascular adverse events. Thus, the combination therapy is a potentially superior therapeutic strategy to the conventional approach for the management of MVA patients.

Sr Isotopic Composition of NIES Certified Reference Material No. 28 Urban Aerosols

An interlaboratory study of the National Institute for Environmental Studies (NIES) certified reference material (CRM) No. 28 Urban Aerosols collected from the filters of a central ventilating system in a building in the Beijing city center from 1996 to 2005 was performed to obtain an information value of the Sr isotopic composition. The Sr isotopic composition was measured using multi-collector-inductively coupled plasma-mass spectrometry (MC-ICP-MS) to confirm the CRM’s within- and between-bottle homogeneity, and the results showed a 87Sr/86Sr ratio of 0.710227 ± 0.000019 (2SD, n = 18). The Sr isotopic compositions were intercompared using thermal ionization mass spectrometry (TIMS), which showed good agreement with values obtained at NIES. Subsequently, a consistent 87Sr/86Sr ratio was observed between two dissolution (hotplate vs. high-pressure bomb) and Sr separation (Sr spec resin vs. cation exchange resin) methods. To validate and reproduce the accuracy of our analytical methods, the Sr isotopic compositions of secondary reference materials, JB-1b and JA-2, were also measured. Our results showed that NIES CRM No. 28 is appropriate for the quality control of Sr isotope measurements of particulate matter analyses for environmental and geochemical studies.

Social Network Structure as a Moderator of the Relationship between Psychological Capital and Job Satisfaction: Evidence from China

Although networking is reported to be a job search strategy in the literature, research on the interaction between social networking and other personal resources and its effect on job satisfaction is scarce. In the perspective of social networks, the present study explored whether the social network structure, which consists of network size and tie strength, moderates the relationship between psychological capital and job satisfaction. By using a two-wave longitudinal design, we collected the quantitative data (survey of 344 undergraduate students who were about to graduate soon) from 19 universities in Beijing city, Shandong Province, and Jiangsu Province in Eastern China. Factor analysis and hierarchical regression analysis were adopted to analyze the data of the survey. We found that psychological capital has a positive impact on job seekers’ job satisfaction. Furthermore, smaller networks and weaker ties in social networks both render the positive effect of psychological capital on job satisfaction even stronger.

The organization of masses’ spontaneous sports activities based on BP neural network model

Chinese government has made huge efforts in improving people’s spiritual and cultural life, but effects are far from satisfactory. The organization of masses’ spontaneous sports activities is the basic countermeasure to improve this situation, for it can not only reduce the government economic investment, but also meet the needs of people’s physical exercises. This paper takes five parks – Sunrise Park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park – in Beijing city as research objects, and makes the research on the current developing situations of the organization of masses’ spontaneous sports activities. Based on BP neural network model, the paper makes analysis according to the masses’ weekly exercises frequency and duration in the above-mentioned five parks. The results show that the organization of masses’ spontaneous sports activities in Temple of Heaven Park and Beihai Park is going quite well, while the situation of Sunrise Park and Purple Bamboo Park is far from that good.

Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas

Recent studies have shown that the high-resolution satellite Landsat-8 has the capability to retrieve aerosol optical depth (AOD) over urban areas at a 30 m spatial resolution. However, its long revisiting time and narrow swath limit the coverage and frequency of the high resolution AOD observations. With the increasing number of Earth observation satellites launched in recent years, combining the observations of multiple satellites can provide higher temporal-spatial coverage. In this study, a fusing retrieval algorithm is developed to retrieve high-resolution (30 m) aerosols over urban areas from Landsat-8 and Sentinel-2 A/B satellite measurements. The new fusing algorithm was tested and evaluated over Beijing city and its surrounding area in China. The validation results show that the retrieved AODs show a high level of agreement with the local urban ground-based Aerosol Robotic Network (AERONET) AOD measurements, with an overall high coefficient of determination (R2) of 0.905 and small root mean square error (RMSE) of 0.119. Compared with the operational AOD products processed by the Landsat-8 Surface Reflectance Code (LaSRC-AOD), Sentinel Radiative Transfer Atmospheric Correction code (SEN2COR-AOD), and MODIS Collection 6 AOD (MOD04) products, the AOD retrieved from the new fusing algorithm based on the Landsat-8 and Sentinel-2 A/B observations exhibits an overall higher accuracy and better performance in spatial continuity over the complex urban area. Moreover, the temporal resolution of the high spatial resolution AOD observations was greatly improved (from 16/10/10 days to about two to four days over globe land in theory under cloud-free conditions) and the daily spatial coverage was increased by two to three times compared to the coverage gained using a single sensor.

Outpatient Antibiotic Prescribing Patterns and Appropriateness for Children in Primary Healthcare Settings in Beijing City, China, 2017–2019

(1) Background: Few studies have focused on antibiotic use and appropriateness in children in primary health institutions (PHIs). This study aimed to identify the patterns and appropriateness of antibiotic use for children in PHIs in Beijing, China. (2) Methods: Outpatient prescriptions of 327 PHIs from 2017 to 2019 for patients < 18 years old were collected. Prescriptions were described using quantity indicators. Antibiotics were categorized according to ATC classification J01 and Access, Watch, Reserve grouping. Appropriateness was reviewed by experts using three subtypes of irrational prescriptions (irregular, inappropriate, and abnormal). (3) Results: 20,618 prescriptions were collected in total. The antibiotic prescription rate (APR) was 15.1% (N = 3113). Among antibiotic prescriptions, J01FA Macrolides were the most used (N = 1068, 34.9%). The Watch group constituted 89.0% (N = 2818) of total antibiotic use. Bronchitis (N = 1059, 35.2%) was the most common diagnosis. A total of 292 instances of irrational antibiotic use were identified, with inappropriate prescriptions being the most prevalent subtype (N = 233, 79.8%). (4) Conclusion: Although APR for children in PHIs in Beijing was relatively low, the pattern of antibiotic use differed from other countries. Further studies are needed to optimize antibiotic use for children in PHIs under different levels of economic development.