Bureau Of China Research Articles

Advancing green innovation through the establishment of data regulatory bodies: Insights from the Big Data Bureau in China

Digital technology serves as a significant catalyst for green innovation (GI), intricately linked with policy guidance and strategic planning. Recently, a notable strategic approach fostering the evolution of digital technology is the establishment of Data Regulatory Bodies (DRBs). Leveraging data from 293 cities between 2010 and 2020, this paper employs a difference-in-differences methodology to investigate the impact of DRB establishment on GI. The results reveal a substantial increase in GI levels following DRB establishment. This enhancement is facilitated by improved administrative efficiency, the cultivation of digital finance, and the advancement of enterprise digitization. Furthermore, the effectiveness of these effects is optimized when DRBs are established through the integration of existing departments’ functions into a new department, particularly in cities with stable power and high marketization levels. These findings provide actionable insights for governmental initiatives aimed at fostering GI.

Does artificial ecosystem recharge make sense? based on the coupled water orbit research framework

By formulating an innovative Coupled Water Orbit Research Framework (CWORF) in cohesion with the modified Hypothesis Extraction Method (HEM), this study undertakes a comprehensive examination and assessment of the Autonomous Water Orbit (AWO) linkages within each sector. Building upon this foundation, the CWROF also integrates Structure Path Analysis (SPA) to scrutinize the critical paths of the AWO in each sector. Additionally, the framework quantifies specific water consumption at different layers of the production chain, enabling a more precise assessment of water consumption and inter-sectoral water usage linkages compared to existing studies. By applying this framework, existing water conservation policies can be refined, thereby achieving enhanced environmental sustainability. The study utilizes six Input-Output (IO) tables and water resource bulletins spanning from 2002 to 2020, as published by the China Bureau of Statistics. It is instrumental in dissecting the current interplay between water resource utilization and economic development. This research aims to analyze the structural nuances of water consumption and the dependency characteristics across diverse sectors within the production chain. It strategically identifies pivotal paths and sectors in the production chain where water consumption is most pronounced, and highlights critical chains contributing to water stress. The results indicate that sectors such as “Farming, Forestry, Animal Husbandry, Fishery, and Water Conservancy” exhibit high water consumption. Furthermore, light industries, represented by “Food and Tobacco” and “Textile Product” sectors, significantly impact indirect water usage across sectors. The study also reveals that the strength of the water feedback loop in the economic system diminishes as the number of layers increases, with the aforementioned sectors frequently appearing in transmission paths and serving as key interface nodes. This research underscores the critical interconnections between water usage and economic activities providing a foundational framework for refining water conservation policies and enhancing water allocation and management capabilities. The introduced CWORF extends beyond conventional methods, offering a more precise and nuanced approach to measuring inter-sectoral water utilization.

Government Digital Transformation and Corporate ESG: Insights from the Big Data Bureau in China

Government Digital Transformation and Corporate ESG: Insights from the Big Data Bureau in China

Bayesian Algorithm for The Construction of Logistics Node Delay Model and Its Impact on Subsequent Nodes in Supply Chain

The logistics nodes delay of supply chain has become a focus of customer complaints at the State Post Bureau of China in recent years. Nodes delay usually also brings uncertain business loss. The purpose of this paper is to explore propagation of nodes delay and make it precisely controllable. To address this, Netica software is used and a hybrid strategy of genetic algorithm (GA) and tabu search algorithm (TS) validated by datasets is utilized to optimize the Bayesian algorithm model. Bayesian algorithm model of logistics nodes delay of supply chain is constructed through parameter learning. The empirical analysis is conducted on the basis of three types of nodes delay with 2041 sets of data for cargo departures and arrivals, upstream nodes delay, and nodes delay of supply chain. The results show that the nodes delay of supply chain gradually decreases from upstream to downstream; there are strong correlations between propagation probability and transfer time of nodes delay; the effects of initial node delay are the maximum, after 3 transitions, still having 30% probability to affect the succeeding nodes. Therefore, some suggestions, such as controlling the transfer points and transfer time and strengthening the management of initial node delay, are given.

Does Digital Government Transformation Inhibit Corporate Environmental Violations? Evidence From the Big Data Bureau in China

Does Digital Government Transformation Inhibit Corporate Environmental Violations? Evidence From the Big Data Bureau in China

Research on Influencing Factors of the Real Estate Market in Beijing

As a large-scale real estate industry, the real estate industry plays an important role in regulating the world economy. As a pillar industry in my countrys development, it plays an important role in promoting my country's GDP growth. Consumption and investment demand for real estate also have a significant impact on overall consumer demand. Many scholars at home and abroad have conducted relevant research on real estate demand factors. This article uses annual data from the China Bureau of Statistics and Beijing, selects Beijings GDP, per capita disposable income of all residents, etc. as explanatory variables, and uses the commercial housing sales area sarea as the explained variable. A multiple regression model was established to analyze the influencing factors of Beijing's real estate market demand. The results show that policy, income, population and housing price factors have a significant impact on demand. Among them, GDP, population change, and policy dummy variable factors have a positive impact, while housing prices and per capita income have a negative impact. Based on the conclusion, this article puts forward suggestions for narrowing the income gap, further curbing real estate speculation, maintaining a balance between supply and demand, paying attention to policy regulation, and using precise and powerful policies to regulate the entire industry, which has served as a reference for the development of the real estate industry.

Simulation of Thinning by Integrating Tree Competition and Species Biodiversity for Target Tree-Based Management of Secondary Forests

This study presents auxiliary support techniques for tree selection strategies based on the spatial structure indices and three competition indices in secondary forests, and discusses the importance of tree competition in forest management. The spatial structure parameter in the structured management is used as a quantitative index—the uniform angle index and three competition indices are used in the design of the algorithm for selective thinning for secondary forest. Based on the target tree-based management principles, simulation of selective thinning was carried out using GIS and C# programming languages. Data for this study were collected from experimental sample plots at Jilin Wangqing Forestry Bureau in China. The simulation results strongly support the use of auxiliary technology for scientifically selecting trees for thinning, avoiding the subjectivity of the traditional manual selection. Selection is largely based on the uniform angle index and competition index. Hegyi’s competition index and its improved version used in the algorithm provided almost identical simulation results, i.e., thinning intensities suggested by these indices for the first sample plot are 21.8% and 21.5%, respectively, and for the second plot are 21.3% and 21.1%, respectively. Thus, one of these competition indices can be used to select trees for thinning. The comprehensive competition index (CCI, a combination of an improved version of Hegyi’s competition index with tree species mingling) can avoid the selection of individual trees with high mingling and help maintain the tree species diversity. CCI suggests thinning intensities of 18.3% and 18.4% for the first and second sample plots, respectively. Presented methods and results may provide auxiliary supports for scientific thinning and help promote the application of information technology in forest management.

Impact of job demands on police stress response—the roles of basic psychological needs and job autonomy

BackgroundPoliceofficers are a high-stress group with special job characteristics, and the Chinese police management system places particularly high demands on police officers. Whether the influence of job demands on officers’ job burnout can be deduced to general stress response needs to be verified. Based on the JD-R model, the study aims to explore the impact of job demands on police stress response, whether job autonomy as a job resource has a moderating effect, and whether basic psychological needs mediate this effect.MethodsA total of 251 police officers in a district-level public security bureau of China, were surveyed using Chinese-language versions of the Job Demands Scale, the Stress Response Scale, the Job Autonomy Scale, and the Basic Psychological Needs Scale. The mediating effect of basic psychological needs and the moderating effect of job autonomy were tested by regression analysis and bootstrap test.ResultsJob demands increase police officers’ stress response, and job autonomy does not play a buffer role but enhances this impact, and job demands can partially reduce the police stress response through the satisfaction of basic psychological needs, that is, there is a masking effect of basic psychological needs.ConclusionsAdjusting and optimizing the ratio of job demands and autonomy in police work to provide high guidance under high demands is of great value to reduce the negative stress responses among police officers.

산업연관분석을 통한 물류산업의 경제적 효과에 대한 분석

The purpose of this study is to make econometric analysis on the economic effects of China’s logistics industry by using the China industry association table, and provide help for the promotion of China’s logistics industry policy in the future. For this reason, 17 industrial fields, including 5 fields of transportation equipment and 12 fields of transportation service industry, are classified as logistics industry in the 2020 industrial association table issued by the China Bureau of statistics in 2022, and the industrial association table of China’s logistics industry for all 28 industries is compiled and analyzed. The analysis results show that, first of all, the production inducement coefficient of China’s logistics industry is 2.7956, and the line cooperation coefficient is 4.6270, indicating that China’s logistics industry is a basic strategic industry supporting the development of national economy. Second, the influence coefficient (backward chain effect) of China’s logistics industry is 1.0466, and the sensitivity coefficient (forward chain effect) is 1.7322, both greater than 1. China’s logistics industry is an intermediate demand manufacturing industry. Third, the final demand of China’s logistics industry is 8382 billion yuan for input into the national economy. The total production induced amount is 626916.8 trillion yuan (38783.5 trillion yuan, 6.2%) and the value-added induced amount is 224227.75 billion yuan (13718.8 trillion yuan, 6.1%) respectively. The income induced amount is 11420.4 trillion yuan (691.34 billion yuan, 6.1%) respectively, The induced amount of production tax is 23469.2 billion yuan (1379.3 trillion yuan, 5.9%) in the logistics industry. Fourth, China’s logistics industry has a total of 30627 labor inducing effects, including 849 direct labor inducing personnel and 29778 indirect labor inducing personnel, showing its role as an employment creating industry.

Discovering Spatio-Temporal Co-Occurrence Patterns of Crimes with Uncertain Occurrence Time

The discovery of spatio-temporal co-occurrence patterns (STCPs) among multiple types of crimes whose events frequently co-occur in neighboring space and time is crucial to the joint prevention of crimes. However, the crime event occurrence time is often uncertain due to a lack of witnesses. This occurrence time uncertainty further results in the uncertainty of the spatio-temporal neighborhood relationships and STCPs. Existing methods have mostly modeled the uncertainty of events under the independent and identically distributed assumption and utilized one-sided distance information to measure the distance between uncertain events. As a result, STCPs detected from a dataset with occurrence time uncertainty (USTCPs) are likely to be erroneously assessed. Therefore, this paper proposes a probabilistic-distance-based USTCP discovery method. First, the temporal probability density functions of crime events with uncertain occurrence times are estimated by considering the temporal dependence. Second, the spatio-temporal neighborhood relationships are constructed based on the spatial Euclidean distance and the proposed temporal probabilistic distance. Finally, the prevalent USTCPs are identified. Experimental comparisons performed on twelve types of crimes from X City Public Security Bureau in China demonstrate that the proposed method can more objectively express the occurrence time of crimes and more reliably identify USTCPs.

Impact of digitalization on retailers and its future trends

People in today's world are getting used to buying the products they need to shop online. They don't need to go much more than beyond to shop online. They can easily access online stores or put mobile devices in place and arrange what you want. Our research is about online vs offline purchasing preference. What customers prefer to buy online or offline? And also, we demonstrate the future scenario of the retail market. So that we explore the online-offline model prediction in the future scenario followed by Barbara thau. We took sales data from national china bureau statistics. We analyze the sales of more than 6 years of data for the research. Our claim is an assumption, so we use a hypothesis model for the proof of our Claims. As well as we discuss the factor of purchasing behavior from the customer for consumer goods. Our claim is an assumption, so we use a hypothesis model for the proof of our Claims. As well as we discuss the factor of purchasing behavior from the customer for consumer goods. As we find our analysis results are positive so we make some business solution suggestions for our business people in suggestions and conclusions.

Improving Vegetable Safety in China: Does Co-Regulation Work?

In the last decade, vegetable safety issues have received growing attention from both consumers and public authorities in China, as vegetable safety hazards pose a serious threat to public health. In 2017, the Industry & Trade Bureau in China implemented a “Market Renovation Program”. This program includes the renovation of wholesale and wet markets, the formal registration of all stallholders in these markets and the introduction of a rapid test for pesticides residues. We apply the co-regulation framework to assess the implementation and results of the renovation program on the safety of vegetables. A mixed methods approach is used to investigate the effects of the renovation program. The qualitative study elaborates on the implementation of the renovation program and the behavioural changes of stakeholders in handling vegetables through interviews and field observations. The quantitative results confirm that the renovation program has a positive impact on vegetable safety. In conclusion, this study shows that the key factor for the success of the renovation program is the transition of authority from the local, public authority to the market management.

Epidemiology of 2019 novel coronavirus in Jiangsu Province, China after wartime control measures: A population-level retrospective study.

BackgroundA novel coronavirus emerged in China in December 2019, and human-to-human transmission was previously identified. This study aimed to compare the epidemiological characteristics in Jiangsu Province and assess whether so-called wartime control measures changed the trend of coronavirus disease 2019 (COVID-19) in the province.MethodsEpidemiological data were obtained from the websites of China's Bureau of Health and the People's Government of Jiangsu Province and informal online sources from January 22 to February 20, 2020.ResultsThe cumulative number of patients in Jiangsu Province (over 79 million people) was 613. The number of daily confirmed new cases reached the inflection point on January 31 with the maximum of 39 cases. The temporal number of patients peaked from January 29 to February 9. The proportion of confirmed cases who were residents or travelers to Hubei Province was 100.0%–58.8% before January 31 and then gradually declined. The proportion of close contacts increased gradually from January 27 to February 17. The geographical distribution of COVID-2019 cases showed that all 13 cites reported confirmed new cases after only five days of the first confirmed new case in Suzhou. The cases were concentrated in Nanjing, Suzhou, and Xuzhou with a high population density (over eight million people). The epidemiological features of COVID-2019 cases in Wuxi, Jiangsu showed that seven confirmed cases were tourists from others areas beyond Hubei Province. The longest incubation period of COVID-2019 was 19 days based on the onset of laboratory-confirmed cases.ConclusionThe number of daily confirmed new cases in Jiangsu Province peaked around January 31 and then declined. This result emphasized that wartime control measures, such as putting cities on lockdown to limit population mobility in Jiangsu Province, resulted in dramatic reductions in COVID-19 cases.

A High-Precision Fatigue Detecting Method for Air Traffic Controllers Based on Revised Fractal Dimension Feature

As air traffic volume increases, the air traffic controller (ATC) fatigue has become a major cause for air traffic accidents. However, the conventional fatigue-detecting methods based on speech are neither effective nor accurate because the speech signals are nonlinear and complicated. In this paper, an ATC fatigue-detecting method based on fractal dimension (FD) is proposed. Firstly, a special speech database of ATC radiotelephony communications is constructed. These radiotelephony communications are obtained from Air Traffic Management Shandong Bureau of China. Then, speech signals implement a wavelet decomposition and FD calculation. The calculation result shows the significant difference among the FD of the speech signal before and after fatigue. Furthermore, a novel fatigue feature of the ATC based on the FD of speech is built. A series of experiments are conducted to detect the ATC fatigue with the fatigue feature comparison process and a support vector machine (SVM). The results show that the accuracy in detecting ATC fatigue based on FD was 92.82%, which are higher than the state-of-the art methods. The research provides a theoretical guidance for Air Traffic Management Authority on detecting ATC’s fatigue, while it may provide reference for the fatigue assessment in other professional fields of civil aviation.

Comparative study of the forward and backward methods for calculating jet properties in pp collisions at √s=7 TeV * * Supported by the National Natural Science Foundation of China (11477130, 11775094), the 111 project of the foreign expert bureau of China. YLY, AL and YY acknowledge the financial support from Suranaree University of Technology and the Office of the Higher

We propose a forward method based on PYTHIA6.4 to study the jet properties in ultra-relativistic pp collisions. In the forward method, the partonic initial states are first generated with PYTHIA6.4 and then hadronized in the Lund string fragmentation model, and finally the hadronic jets are constructed from the created hadrons. Jet properties calculated with the forward method for pp collisions at =7 TeV are comparable to those calculated with the usual anti- algorithm (backward method) in PYTHIA6.4. The comparison between the backward and forward methods may contribute to the understanding of the partonic origin of jets in the backward method.

A fault prediction method for catenary of high-speed rails based on meteorological conditions

Fault frequency of catenary is related to meteorological conditions. In this work, based on the historical data, catenary fault frequency and weather-related fault rate are introduced to analyse the correlation between catenary faults and meteorological conditions, and further the effect of meteorological conditions on catenary operation. Moreover, machine learning is used for catenary fault prediction. As with the single decision tree, only a small number of training samples can be classified correctly by each weak classifier, the AdaBoost algorithm is adopted to adjust the weights of misclassified samples and weak classifiers, and train multiple weak classifiers. Finally, the weak classifiers are combined to construct a strong classifier, with which the final prediction result is obtained. In order to validate the prediction method, an example is provided based on the historical data from a railway bureau of China. The result shows that the mapping relation between meteorological conditions and catenary faults can be established accurately by AdaBoost algorithm. The AdaBoost algorithm can accurately predict a catenary fault if the meteorological conditions are provided.

(2679) Proposal to conserve the name Talauma fistulosa (Lirianthe fistulosa, Magnolia fistulosa) (Magnoliaceae) with a conserved type

(2679) Proposal to conserve the name <i>Talauma fistulosa</i> (<i>Lirianthe fistulosa</i>, <i>Magnolia fistulosa</i>) (<i>Magnoliaceae</i>) with a conserved type

English

The aim of this study is to analyze teacher education systems in China and Japan, and compare the findings with teacher education in Turkey, thus contribute to the developments in teacher education in Turkey. The research was based on the years 2000 to 2017. Document analysis method, which is one of the qualitative data collection methods, is used in this research. Within the scope of the document review, official sources such as education ministries of the countries, internet pages of universities and internet pages of international education organizations are used; and educational policies, entrance conditions of teacher education institutions, the structure of these institutions and teacher education programs are examined. The collected data are analyzed by content analysis. In conclusion, the continuous policy changes regarding teacher training in Turkey are found to be detrimental to teacher training and prevent the implementation of research focused teacher education programs. For practice courses, both course hours and the cooperation between faculty and practice schools are found to be insufficient. The Education Bureau in China is the institution responsible for education policy, education program, teacher education and legislation. Though teacher education programs vary in different states, generally, those who have high school diploma may enter teacher education institutions after passing and practice-based evaluation system. It is found that the teaching profession is given a great importance in Japan, and that there is no specific policy in pedagogical formation education, and therefore, pedagogical formation education needs to be reviewed and updated. Turkey, China and Japan have taken inspiration from progressive education philosophy, one of the modern education philosophies, for their teacher education systems. Key words: Teacher education, teacher education in Turkey, teacher education in China, teacher education in Japan.

Operation-oriented reliability and availability evaluation for onboard high-speed train control system with dynamic Bayesian network

The reliability and availability of the onboard high-speed train control system are important to guarantee operational efficiency and railway safety. Failures occurring in the onboard system may result in serious accidents. In the analysis of the effects of failure, it is significant to consider the operation of an onboard system. This article presents a systemic approach to evaluate the reliability and availability for the onboard system based on dynamic Bayesian network, with taking into account dynamic failure behaviors, imperfect coverage factors, and temporal effects in the operational phase. The case studies are presented and compared for onboard systems with different redundant strategies, that is, the triple modular redundancy, hot spare double dual, and cold spare double dual. Dynamic fault trees of the three kinds of onboard system are constructed and mapped into dynamic Bayesian networks. The forward and backward inferences are conducted not only to evaluate the reliability and availability but also to recognize the vulnerabilities of the onboard systems. A sensitivity analysis is carried out for evaluating the effects of failure rates subject to uncertainties. To improve the reliability and availability, the recovery mechanism should be paid more attention. Finally, the proposed approach is validated with the field data from one railway bureau in China and some industrial impacts are provided.

Hybrydowa diagnostyka uszkodzeń zwrotnic kolejowych w oparciu o segmentację krzywych prądowych

Switches are one of the most important pieces of infrastructure in railway signal systems, and they significantly influence the efficiency and safety of train operation. Currently, the identification of switch failures mainly depends on the experience of railway staff and the use of simple thresholding methods. However, these basic methods are highly inaccurate and frequently result in false and missing alarms. This paper aims to develop a hybrid fault diagnosis (HFD) method for railway switches. The method is an intelligent diagnosis method that uses massive current curves collected by microcomputer monitoring systems. We first divide the switch operation current curves into three segments based on the three mechanical processes that occur during switch operation. Then, a standard curve is selected from the fault-free curves, and common typical faults are ascertained through a microcomputer monitoring system. Finally, derivative dynamic time warping and a quartile scheme are employed to identify fault curves. An experiment based on current curves collected from the Guangzhou Railway Bureau in China demonstrates that the HFD method is extremely accurate and has low false and missing alarm rates. HFD performs better than the studied support vector machine (SVM) and dynamic time warping (DTW) methods, which are widely used for fault diagnosis.