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Anemia is a global public health problem, especially common among children in developing countries, which affects their physical and mental health development. However, there is currently a lack of research on the relationship between anemia and academic performance. The objective of this study was to explore the association between anemia and academic performance, and the possible factors mediating this association among Chinese children. The data for this study came from the baseline survey of the Chinese Education Panel Survey Elementary School Cohort. The cohort was conducted from September 2018 to June 2019 in 160 elementary schools, covering 20 provinces and 40 counties/districts throughout China. Paper-based questionnaires were used, completed by 4th grade students, parents, head teachers, main teachers, and principals. The data used included questionnaire responses, physical measurements, and academic performance of 17,695 students. Based on students' hemoglobin levels and school altitude data, we grouped them into anemia and nonanemia categories using WHO criteria. The anemia group had 1,154 individuals, while the nonanemia group had 16,541 individuals. An ordinary least squares regression and mediation effect analysis were conducted. Our findings found the prevalence of anemia was 6.52% among Chinese Grade 4 students. Students without anemia had a higher average test score for three academic subjects than students with anemia (P < 0.001); their test scores for Chinese, Mathematics, and English were also higher (P < 0.05). Multivariate regression analysis showed a negative association between anemia and average test scores as well as individual test scores for the three subjects. Mediation analysis found that anemia affected academic performance directly (P < 0.05), and indirectly by decreasing the cognition score (P < 0.05). The indirect effect was 19.9% of the total effect. Findings highlighted anemia affected academic performance both directly and indirectly. Nutrition-related interventions should be implemented to prevent a decrease in academic performance among students with anemia. [ABSTRACT FROM AUTHOR]

Through the analysis of the risk transmission mechanism of chemical substances in toys, this paper identifies risk sources, transmission carriers, key nodes, and risk recipients, and draws a risk transmission path diagram. Taking the risk factors in the supply chain system as the research subject, this paper constructs a risk index system for chemical substances' limit in toys, and calculates the probability of risk and the degree of influence by the fuzzy evaluation method. Based on the Bayesian network model, this paper analyzes the causality of risk transmission effects. Through the comprehensive use of fuzzy evaluation and Bayesian network methods, a relatively complete chemical substance risk transmission path assessment system has been established using China's Guangdong toy companies as the data store to provide a feasible basis for responding to the risk control measures of toxic and hazardous chemical substances in toys. [ABSTRACT FROM AUTHOR]

China has always attached great importance to food security issues; especially in today's changeable world, it is particularly important to build a feasible and accurate food security early warning system. According to the influencing factors in food security, this paper uses the PCA method and the AHP method to construct a food security early warning index system that includes 4 secondary indicators and 13 tertiary indicators of total security, trade security, ecological security, and food security. There are four security levels of no warning, light warning, moderate warning, and heavy warning, and finally the comprehensive evaluation of food security from 2000 to 2019 and the specific early warning levels of various indicators are obtained. This paper constructs a food security evaluation system from the perspective of data, breaks through the limitations of existing research, and improves the completeness of food security early warning indicators. Because the BP neural network is a multilayer feedforward neural network with strong adaptability, it is one of the most widely used and successful neural network models at present. Finally, BP neural network is used to simulate China's food security early warning system and design standardized risk prevention and control processes and classified response strategies—routine monitoring, risk control, and emergency response—to provide signal guidance and reference for China's food security to respond to risks early. [ABSTRACT FROM AUTHOR]

This paper combines principal component analysis, a BP neural network, and a simulated annealing algorithm, to construct a PCA-SA-BPNN risk forecast model to evaluate and predict the RMB internationalization risk status of China. First, we analyze the risk of RMB internationalization and its transmission mechanism from the perspective of the economic characteristics of neighboring countries and trading partner countries. Second, we use the FASP index system construction method for reference to construct a forecast index system for macro- and microrisks brought about by RMB internationalization. Then, the weight of each index is determined through index common degree analysis and principal component analysis, and the risk of RMB internationalization is divided. On this basis, the risks of RMB internationalization in China from 2000 to 2019 are divided into four categories. Based on the BP neural network algorithm optimized by the simulated degradation algorithm, the PCA-SA-BPNN model of RMB internationalization risk forecast is constructed. Finally, the validity of the model is verified by experimental verification, and the risk status of RMB internationalization in 2020 is simulated and predicted. The research results show that the risk status of RMB internationalization in 2020 is basically safe, and the risks of RMB internationalization mainly come from macroeconomic growth risks and systemic risks of the financial system. [ABSTRACT FROM AUTHOR]

Power transmission and transformation projects (PTTPs) under new energy grid connections are different from ordinary engineering construction projects. With large investment amounts, various supporting facilities, and high safety and quality requirements, PTTPs are vulnerable to the volatility of new energy power generation, climate, geological conditions, geopolitical environment, technological changes, and other kinds of uncertain factors. Therefore, the investment risk of PTTPs under new energy grid connection is particularly considerable in the project management. For the owner of PTTPs, adopting the engineering-procurement-construction (EPC) mode is an effective attempt to solve the project construction problems faced by the owners. Thus, this paper deeply excavates the key risk points of PTTPs in the initial investment phase under the EPC mode and constructs the novel risk evaluation index system from the perspectives of economy, management, policy, society, and environment. An assessment model is established based on triangle fuzzy number-hesitant fuzzy linguistic term sets (HFLTS-TFNs), the entropy method, and the fuzzy comprehensive evaluation method, which is used to evaluate the investment risk of PTTPs to provide reference for power grid corporations to control project risks. Finally, a case study in the Hexi Corridor region, Gansu Province, China, is illustrated to demonstrate the rationality of the decision model and find management risks are the most vital risk factors for PTTPs under EPC mode. [ABSTRACT FROM AUTHOR]

With the proposal of "One Belt One Road" initiative, more and more technology-driven enterprises in China are going abroad for foreign direct investment (FDI). But at the same time, due to the special geographical location of the countries along the "Belt and Road," the turbulent geopolitical pattern, weak economic growth, and constant conflicts between religious civilizations, all these will make Chinese technology-driven enterprises' investment in the countries along the "Belt and Road" face a nonnegligible risk. Thus, how to correctly assess and reasonably prevent OFDI risk has become urgent task for enterprises. This paper takes 20 countries along the "Belt and Road" as the research object and combines the characteristics of technology-oriented enterprises to determine the risk assessment indicators at all levels from four aspects: politics and policy, economy and finance, society and culture, and technological risks. Using fuzzy cluster analysis, the countries along the "Belt and Road" are classified into four groups: low, medium-low, medium-high, and high risks and corresponding countermeasures are proposed. Technology-oriented enterprises should raise their political risk awareness, comprehensively assess the economic and financial environment of host countries before making FDIs, implement "localized" operation and management, and pay attention to the protection of intellectual property rights. [ABSTRACT FROM AUTHOR]

There are a series of problems in China, such as low farmers' income, difficulty in financing for farmers, and relatively lag in rural financial reform. The mortgage financing of farmland management rights is one of the important ways to solve these thorny problems and promote economic development. From the perspective of farmers, combined with empirical analysis, this paper fully considers farmers' ideas, carries out risk identification and risk assessment for the mortgage loan of farmland management rights, and continuously improves the relevant risk prevention mechanism to reduce the operation risk of farmers' farmland mortgage. This paper expounds the establishment principles of the risk evaluation index system in detail, lays a theoretical foundation for the selection of indicators, determines the risk evaluation system of land management right mortgage financing from the perspective of farmers, and builds a fuzzy-level comprehensive evaluation model. Based on the practical research data, the fuzzy hierarchy (F-AHP) comprehensive evaluation method is used to conduct an empirical comprehensive evaluation on the risk of the mortgage loan of the farmland management right and analyze the evaluation results. Among the surveyed farmers in the survey area, 242 have not actually participated in the mortgage loan of farmland management rights, accounting for 94.16% of the sample farmers. However, there are only 15 farmers who actually use the farmland management right for mortgage financing, accounting for 5.84% of the sample. [ABSTRACT FROM AUTHOR]

In order to control the risks of Chinese enterprises in infrastructure investment in developing countries, the corresponding evaluation system is constructed through a structural equation model algorithm to analyze these risks, so as to achieve risk prediction and risk controllability. Structural equation modeling is a method to establish, estimate, and test causality. It can replace multiple regression, path analysis, factor analysis, covariance analysis, and other methods and clearly analyze the effect of individual indicators on the population and the interrelationship between individual indicators. It is a multivariate statistical modeling technology mainly applied to confirmatory model analysis. Due to the guidance of national policies, there are more and more opportunities for Chinese enterprises to invest abroad. However, due to the influence of political, economic, and environmental factors, overseas investment is facing many difficulties. This paper analyzes the risks from four aspects: bilateral policy risk, legal difference and litigation risk, international economic risk, and technical risk through structural equation model algorithm. Aiming at these risks, the simulation software of the algorithm is constructed in MATLAB big data analysis software, and the risk control measures are put forward. Finally, with the support of China's policies, in order to ensure the investment income, we should carry out risk intervention for the foreseeable risk and reduce the impact of risk on the investment income as much as possible, so as to improve the risk prevention and management awareness of overseas investment business. By analyzing the characteristics of venture capital and the various kinds of risks affecting venture capital, the risk structure model estimation of risk sneak attack is established by using the principle of structural equation model, and the impact of various risks on investment risks can be analyzed, so that the risk measurement and control of venture capital provides the basis of theoretical knowledge. [ABSTRACT FROM AUTHOR]

This paper investigates whether firms' participation in the global value chain (GVC) weakens the exchange rate risk and its mechanism. Based on Powers and Riker's (2013) expanding exchange rate risk model, this paper matches data from China's refined input-output table, the customs database, and the industrial enterprise database from 2002 to 2009 to measure the firms' GVC forward linkages and backward linkages and therefore empirically tests the relationship between participation in the GVC and the exchange rate risk. The results show that participation in the GVC reduces firms' exchange rate risk through a "comovement effect" for forward linkages and a "hedging effect" for backward linkages; differences in a firm's position in the GVC affect the extent of reduction in the exchange rate risk. Encouraging firms to participate in the GVC and strengthening GVC relationship with high-income countries in particular play an important role in minimizing the exchange rate risk. [ABSTRACT FROM AUTHOR]

In order to make safety risk assessment more accurately and more reasonably for high-speed railway station in China, this paper analyzes risk factors of fault tree and transfers the fault tree of risk accident into fuzzy petri net and then builds the FPN-FTA model by combining the dynamic weighting fuzzy petri net (FPN) and fault tree analysis (FTA) based on the latter. This paper simulates the FTA-FPN model with Stateflow of Matlab software. Then, it builds up a bi-objective risk control model, making the minimum safety risk level and minimum necessary cost as the objectives, and it designs discrete particle swarm optimization algorithm to solve the risk control model. Finally, this paper selects stampede accident of Shijiazhuang high-speed railway station as an example in case study for assessing stampede risk level and gets the risk control schemes for this station. The results verify the feasibility and validity of the model and algorithm. [ABSTRACT FROM AUTHOR]

With the decline of China's economic growth rate and the uproar of antiglobalization, the textile industry, one of the business cards of China's globalization, is facing a huge impact. When the economic model is undergoing transformation, it is more important to prevent enterprises from falling into financial distress. So, the financial risk early warning is one of the important means to prevent enterprises from falling into financial distress. Aiming at the risk analysis of the textile industry's foreign investment, this paper proposes an analysis method based on deep learning. This method combines residual network (ResNet) and long short-term memory (LSTM) risk prediction model. This method first establishes a risk indicator system for the textile industry and then uses ResNet to complete deep feature extraction, which are further used for LSTM training and testing. The performance of the proposed method is tested based on part of the measured data, and the results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Many deep mining mines in southwestern Shandong Province of China are covered with thick loose layers. When mining near the loose layers, there is a risk of water and sand inrush, which threatens the personal safety of miners. The prediction of sudden water and sand inrush is difficult due to the comprehensive influence of many factors, and the influencing factors are fuzzy and random. To solve this problem, in this paper, a new risk assessment method of water and sand inrush based on comprehensive weight and cloud model was proposed. Seven factors are selected as indexes: the aquifer thickness, the thickness ratio of sand layer to clay layer, the thickness of bottom clay layer, the coal seam thickness, the percentage of core recovery, the geological structure, and the bedrock thickness. The assessment index system is established, and the index is divided into three grades. A comprehensive weighting method, which combines analytic hierarchy process (AHP), entropy weight method (EWM), and minimum entropy principle, is used to reasonably assign the weight of index. Based on the cloud generator equation, the membership function is obtained. The assessment result of the assessment object is obtained by combining the membership degree and the weight of index. The comprehensive weight-cloud model assessment method is applied to the risk assessment of water and sand inrush in the 6311-2 working face in the sixth mining area of Baodian Coal Mine. According to the assessment results, the following conclusions can be drawn: (1) the bedrock thickness and the coal seam thickness are the main factors of water and sand inrush under loose layer mining; (2) the assessment results obtained by the comprehensive weight-cloud model method are consistent with the actual situation. The assessment method can provide scientific reference for the safe mining under the thick loose layer in the deep mines of southwest Shandong. [ABSTRACT FROM AUTHOR]

Coal chemical enterprises have many risk factors, and the causes of accidents are complex. The traditional risk assessment methods rely on expert experience and previous literature to determine the causes of accidents, which has the problems such as lack of objectivity and low interpretation ability. Analyzing the accident report helps to identify typical accident risk factors and determines the accident evolution rule. However, experts usually judge this work manually, which is subjective and time-consuming. This paper developed an improved approach to identify safety risk factors from a volume of coal chemical accident reports using text mining (TM) technology. Firstly, the accident report was preprocessed, and the Term Frequency Inverse Document Frequency (TF-IDF) was used for feature extraction. Then, the K-means algorithm and apriori algorithm were developed to cluster and for the association rule analysis of the vectorized documents in the TF-IDF matrix, respectively to quickly identify the hidden risk factors and the relationship between risk factors in the accident report and to propose targeted safety management measures. Using the sample data of 505 accidents in a large coal chemical enterprise in Western China in the past seven years, the enterprise accident reports were analyzed by text clustering analysis and association rule analysis methods. Through the analysis, six accident clusters and 13 association rules were obtained, and the main risk factors of each accident cluster were further mined, and the corresponding management suggestions were put forward for the enterprise. This method provides a new idea for coal chemical enterprises to make safety management decisions and helps to prevent safety accidents. [ABSTRACT FROM AUTHOR]

Rockburst is one of the main dynamic disasters in coal mines; it is of great significance to accurately evaluate the risk zoning of rockburst for mine safety construction and pressure relief design. Taking the Gaojiapu coal mine in the Bingchang mining area of Shaanxi Province as the study area, this paper quantifies the complex geological structure based on fractal theory and establishes the zoning evaluation model of rockburst risk index in the mining area by LS-FAHP-CRITIC method in combination with the distribution characteristics of field stress field, the distribution of geological structure, and the sedimentary environment of coal seam overburden. A new evaluation method of rockburst risk zoning in the coal mine is proposed, and the rockburst risk in the study area was evaluated. The results show that the dangerous areas in the study area are widely distributed, mainly in the area near the structure with high maximum horizontal principal stress. On the basis of the actual rockburst of the Gaojiapu coal mine, the areas where rockburst occurs are all located in dangerous area and high dangerous area, which verifies the accuracy and rationality of the zoning evaluation results of the new method. This method can be used to guide the safety production of similar mines or adjacent coalfaces. [ABSTRACT FROM AUTHOR]

At present, percutaneous nephrolithotomy has become an option for hospitals increasingly to treat calculus. However, due to the certain risk of percutaneous nephrolithotomy, it may lead to postoperative complications. Analyzing the preoperative factors of septic shock after percutaneous nephrolithotomy can provide guidance for reducing the incidence of septic shock after PCNL. This article establishes a logistic regression model based on preoperative factors, uses statistical methods, and uses the professional statistical software SPSS to create a database and analyze the data. The method of classification data analysis was used to determine various influencing factors including patient factors, stone factor, and preoperative factors and combined B-ultrasound guidance and percutaneous nephrolithotomy to reduce the risk of surgery. The experimental results found that the percutaneous nephroscope laser lithotripsy guided by the smart Internet of Things can effectively perform lithotripsy; in this paper, the preoperative data of different complications are obtained, and the risk of surgery is closely related to the operation time. The operation time exceeds 90 minutes and causes the risk of severe bleeding after PCNL. It is twice the operation time of less than 90 minutes and 5 times the operation time of less than 60 minutes. [ABSTRACT FROM AUTHOR]

The local government bond system of China has experienced a series of changes from its initial creation to its abolition and then to a recovery again. During the period, the central government always dominated the changing direction of the local government bond system. However, as fiscal decentralization reform has progressed, the institutional needs of local governments and investors have gradually gained attention. As a result, the size and variety of local government bonds are expanding. Through the introduction of analysis of system change based on situation structure performance (SSP), this paper uses Machine Learning (ML) approaches to predict the risk of government debt of China in the context of changing the local government bond system. Besides, this research work includes the comprehensive weight assignment for government debt hazard, fiscal revenue forecasting, default risk calculation, and finally an analysis of the validity of government debt hazard. The system may provide financial signal advice and strategy reference for dealing with hazards in early payment, organizing debt repayment significance order, optimizing fiscal revenue and cost structure, and so on. [ABSTRACT FROM AUTHOR]

Comprehensive evaluation of the geological disaster risk of super long tunnels is significant for safety construction. In this paper, we establish a comprehensive evaluation system based on the cloud model and analytic hierarchy process (AHP) theory, considering four kinds of geological hazards, such as water and mud inrush, large deformation, rock burst, and collapse. Then, based on a super long highway tunnel of the Chizhou-Qimen expressway in China, the construction risk evaluation is carried out. The results show that the evaluation system can accurately judge the disaster risk level of the tunnel under different conditions surrounding a rock. The cloud model theory can realize the mutual transformation of qualitative indicators and quantitative indicators and avoid the problem of intense subjectivity of evaluation indicators. The evaluation system can be used as a new approach to evaluate tunnel risks in similar projects. [ABSTRACT FROM AUTHOR]

The bond market is an important part of China's capital market. However, defaults have become frequent in the bond market in recent years, and consequently, the default risk of Chinese credit bonds has become increasingly prominent. Therefore, the assessment of default risk is particularly important. In this paper, we utilize 31 indicators at the macroeconomic level and the corporate microlevel for the prediction of bond defaults, and we conduct principal component analysis to extract 10 principal components from them. We use the XGBoost algorithm to analyze the importance of variables and assess the credit debt default risk based on the XGBoost prediction model through the calculation of evaluation indicators such as the area under the ROC curve (AUC), accuracy, precision, recall, and F1-score, in order to evaluate the classification prediction effect of the model. Finally, the grid search algorithm and k -fold cross-validation are used to optimize the parameters of the XGBoost model and determine the final classification prediction model. Existing research has focused on the selection of bond default risk prediction indicators and the application of XGBoost algorithm in default risk prediction. After optimization of the parameters, the optimized XGBoost algorithm is found to be more accurate than the original algorithm. The grid search and k -fold cross-validation algorithms are used to optimize the XGBoost model for predicting the default risk of credit bonds, resulting in higher accuracy of the proposed model. Our research results demonstrate that the optimized XGBoost model has a significantly improved prediction accuracy, compared to the original model, which is beneficial to improving the prediction effect for practical applications. [ABSTRACT FROM AUTHOR]

Coal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index S was proposed by considering acoustic emission and electromagnetic emission signal characteristics in mine shocks. Combined with indices E (energy of microseisms) and N (frequency of microseisms) of microseismic monitoring, a static and dynamic coal bump risk assessment and prediction model was established. We studied coal bump events that occurred during extraction in 311305 working face of Bayangale coal mine in Inner Mongolia, China. We obtained the acoustic emission and electromagnetic emission signal distribution and change law, using principal component analysis method and density ellipse to establish the index S. A typical precursory of coal bumps is that AE and EME strength has obvious fluctuation period of 3-4 days, index S showing an obvious decreasing trend, while the time-series curve of the microseismic energy is relatively stable, and the vibration frequency curve has a significant upward trend. After predict the potential coal bump risk and its area of occurrence, large diameter drilling (Φ150 mm) on-site was used to relief pressure concertation in coal seam and roof. The results demonstrate that this model based on multiparameter indices is capable of quantitatively prewarning rock burst risk. [ABSTRACT FROM AUTHOR]

With the increase in construction scale and difficulty of large and complex bridges in China, it has become increasingly difficult to assess the safety risks of bridges during the construction period. Therefore, how to reasonably assess the safety risk of large, complex bridges during construction has become particularly important. Existing assessment methods are subjective in assigning weights, and it is difficult to select representative important factors to focus on for the prevention and control of numerous risk sources; they do not comprehensively consider the correlation of various risk sources during the construction period. To address the above shortcomings, a safety risk assessment of large and complex bridges during the construction period based on the Delphi-improved fuzzy analytic hierarchy process (FAHP) factor analysis method is proposed in this paper. First, the Delphi method was used to conduct a general survey of safety risk factors during the bridge construction period, and then the work breakdown structure-risk substructure (WBS-RBS) was used to establish the evaluation index system. Second, the improved FAHP was combined with it to calculate the weight of each risk factor. Finally, the factor analysis method was used to determine the correlation degree of each risk factor, and representative factors were selected to express the risk degree of the object to be evaluated to screen out major risk factors in the construction process. Finally, the feasibility and practicality of the method are verified by combining an actual engineering case with AHP (analytic hierarchy process) to perform a comparative study, which provides a reference basis for subsequent bridge construction risk prevention. [ABSTRACT FROM AUTHOR]

This study investigates the water supply risk of Panjiakou reservoir in the Luanhe River basin of China during 1956–2016 under environmental change. Since the monthly runoff series during 1956–2016 is a time series with change points, it is necessary to find a new stochastic streamflow series generation approach to preserve the statistical characteristics of the original series and to refine the reliability of water supply risk analysis. This paper improves a known stochastic streamflow simulation method of previous research to better reflect the characteristics of series with change points. And this paper simulates the monthly runoff series with change point of Panjiakou reservoir during 1956–2016 by three different methods, including Thomas–Fiering model, copula function stochastic simulation method, and copula function stochastic simulation method with the mixed distribution model. Among the three methods, the copula function stochastic simulation method with the mixed distribution model which is improved on the basis of copula function stochastic simulation method in this study performs best in simulating the observed monthly runoff series during 1956–2016, and the water supply risk indices including reliability (time-based and volume-based), resilience, vulnerability, drought risk index (DRI), and sustainability index (SUI) are evaluated for Panjiakou reservoir and analyzed by using the stochastic simulation results. By comparing with the previous studies, all indicators are between the corresponding results of 1956–1979 and 1980–2016 with stationary inflows; it can be seen that change point seriously affects the water supply risk of Panjiakou reservoir. These results make it easy to formulate water supply strategies and schemes in changing environment for water resources managers. [ABSTRACT FROM AUTHOR]

The paper aims to propose a new method to state the credit risk characteristics of the regional listed companies in China and makes the listed companies avoid involving in credit crisis. The paper selects fifty-four listed companies of Hebei Province as the research sample and establishes the index system of listed company's credit risk evaluation from four financial index categories which included profitability, operating capacity, solvency, and growth capability. The paper first filtrates fifteen indexes by using the gray clustering method from the four financial categories and finds out the effective variables of the prediction model. Then the paper predicates the credit risk probability of the listed companies by using the logistic regression model. Finally, by analyzing the financial data of annual reports of fifty-four listed companies in Hebei Province from 2012 to 2017 as sample data, the simulation experiment empirical test is carried out by using SPSS software. The results show that the logistic regression model with gray clustering analysis has high predictive accuracy and has a strong predictive ability to evaluate the credit risk of listed companies. The gray logistics evaluation plays a very good role in financial early warning for regional listed companies in China. [ABSTRACT FROM AUTHOR]

Public-private partnership (PPP) projects require comprehensive risk assessment and management, including Urban Rail Transit (URT). A more effective risk management can benefit from an accurate understanding of the two-way influence of PPP project risk factors. This paper uses the content analysis method to filter out, compare, and analyze PPP-related literature; 12 categories of 22 PPP risk factors are extracted and identified, and the possible correlations between these risk factors are judged preliminarily. With the knowledge and advice provided by PPP experts, the initial risk relationships are adjusted and supplemented, which then help to determine a reasonable logical relationship among risk factors. The logical relationship helps analyze the risk factors based on the ISM model analysis method and builds a hierarchical structure relationship of risk factors including 6 levels. Finally, the direct, intermediate, and autonomous factors that lead to problems or failures in PPP projects are analyzed which explains in detail the paths of risk transmission and risk prevention measures of PPP companies operating URT. It lays a foundation for PPP project companies operating URT to recognize, manage, and control risks in a targeted and systematic manner. [ABSTRACT FROM AUTHOR]

Casing deformation is a key issue that restricts the efficient development of shale gas in the Sichuan Basin, southwest China. In this study, we take the Ning209 block as an example to analyze the characteristics of casing deformation distribution and the mitigation effect of using reduced treating parameters on casing deformation. The geological structure and in-situ stress characteristics of this block indicate that the high horizontal stress difference and high pore pressure may be the main cause of casing deformation. Hence, based on the fault likelihood and 3D in-situ stress model, a geomechanical probability model of fault slip is established to identify the areas with high risk of faults to explain the distribution of casing deformation and investigate the impact of reducing pumping rate on fault slip. The results show that the faults in the upper region of the block have a higher slip probability than the faults in the lower region, consistent with field casing deformation observation. The high stress difference and high pore pressure are the main factors causing a high slip probability of faults. After reducing pumping rate, slip probability is found to change from medium risk to low risk for faults in the lower region, which led to a significant reduction of casing deformation in the lower region. Reducing pumping rate can play a significant role in mitigating casing deformation caused by medium-risk faults, which has been proved by the field practices. This paper proposes a comprehensive method for preventing casing deformation by combining the fault slip risk assessment with the treating parameters optimization, which bridges the gap between prediction and control for mitigating casing deformation in the field. [ABSTRACT FROM AUTHOR]

Constructing a shield tunnel that crosses under a river poses considerable safety risks, and risk assessment is essential for guaranteeing the safety of tunnel construction. This paper studies a risk assessment system for a shield tunnel crossing under a river. Risk identification is performed for the shield tunnel, and the risk factors and indicators are determined. The relationship between the two is determined preliminarily by numerical simulation, the numerical simulation results are verified by field measurements, and a sample set is established based on the numerical simulation results. Fuzzy comprehensive evaluation and a backpropagation neural network are then used to evaluate and analyze the risk level. Finally, the risk assessment system is used to evaluate the risk for Line 5 of the Hangzhou Metro in China. Based on the evaluation results, adjustments to the slurry strength, grouting pressure, and soil chamber pressure are proposed, and the risk is mitigated effectively. [ABSTRACT FROM AUTHOR]

Metro tunnel sections in China can generally be divided into two types, those in granite formations (D = 6.0 m) and those in soft soils (D = 6.2 m), to which the same shield tunnel machine cannot be applied. The consequent low rate of machine utilization needs to be addressed. One solution is to modify shield machines which tend to tunnel granite strata with varying degrees of weathering (D = 6.0 m) into those applicable in soft soils (D = 6.2 m). Shield tunneling is a complex operation accompanied by potential risks, and accordingly it is demanded in risk evaluation and management. Hence, according to the construction features of modified shield machines in soft soil areas, this paper identifies relevant risks before establishing a specific model of risk evaluation by virtue of a fuzzy comprehensive evaluation method. This model weighs risk factors by triangular fuzzy numbers, and the membership function included is of L-R type that is frequently used in engineering. This risk evaluation model is applied to one section tunnel (Binhai New Town-Lianhua) of Metro Line 6 in Fuzhou City. Tunneling tests in the field uncover problems of the modified shield machine, including inappropriate tunneling parameters, segment dislocation, segment damage, and inadequate grouting. The result conforms to that produced by the risk evaluation model, which in turn proves the reliability of this model. Field data are also analyzed to address existing problems and to determine the appropriate tunneling parameters. The validity of these tunneling parameters is verified when surface settlement is measured. [ABSTRACT FROM AUTHOR]

Risk management is a key factor for smart city running. There are many risk events in a strict process like transportation management of a smart city or a medical surgery in a smart hospital, and every step may lead to one kind of risk or more. In view of the fact that the occurrence of the flow risks follows the sequence formed by each process step, this paper presents a Bayesian network under strict chain (BN_SC) to model this situation. In this model, the probabilistic reasoning formula is given according to the sequence of process steps, and the probabilities given by the model can do risk factor analysis to support the system to find an effective way to improve the process like machine manufacturing or a medical surgery. Finally, an example is analyzed based on the information given by doctors according to the situation of LC in their hospital located in Sichuan Province of China, which shows the effectiveness and rationality of the proposed BN_SC model. [ABSTRACT FROM AUTHOR]

In the regional multiairport system, the contradiction between the limited operating resources and the large flight flow is serious, and the flight delays can easily lead to the occurrence of unsafe events. This paper investigates the abnormal flight recovery method in regional multiairport system based on risk control. The focus is to reschedule arrival-departure flights in real time with minimized delay time and risk probability. In this study, the risk about terminal area control and scene operation was considered in the analysis of the risk control model (RCM), which includes six key risk points: airspace control, flight conflict, ground service, apron support, ground control, and taxiing conflict. The mathematical model on flight recovery was constructed to solve minimized delay time and risk probability with MSINS (multistart algorithm with intelligent neighborhood selection). The data of a typical regional multiairport system in China were selected for experimental verification in order to compare the RCM with the traditional recovery model (TRM). The experimental results show that first, there are some hidden dangers in the traditional recovery methods of flight delay. Flight conflict and apron support are the risk points that need to be controlled most in the multiairport system. Secondly, for the effective solution with the shortest delay time, the RCM can reduce the overall operation risk of the system, but the flight delay time is a little longer. For the effective solution with the lowest risk probability, RCM can reduce the risk of system operation and the delay time of flights at the same time. Therefore, RCM can improve the security level of the system during abnormal flight recovery and ensure or even improve the recovery efficiency. [ABSTRACT FROM AUTHOR]

With the vigorous development of major engineering projects in China, the social risks associated with major construction projects not only challenge the success of projects but also threaten social harmony and stability. Therefore, it is of great practical significance to assess and manage social risks. This paper aims to identify and evaluate the social risk factors by conducting a survey and assess the overall risk level of major construction projects (MCPs) with fuzzy integrated approach. First, 35 social risk factors and related stakeholders were identified based on literature analysis and case study. Then, 18 critical social risk factors (CSRFs) were selected and classified into six groups (CSRGs) based on a questionnaire survey. Next, using fuzzy integrated method, the probability of occurrence (PO), magnitude of impact (MI), the integrated risk level (IRL) of each CSRF and CSRG, and the overall risk of MCPs were calculated. As a result, "unfair compensation for housing demolition and land requisition" was the most critical social risk factor, and "policy/legal risk" was the most critical social risk group. The overall risk of MCPs was between moderate and high. At last, a social risk synthetic management framework was established, which can provide reference for policymakers and project decision makers to effectively manage the social risks. [ABSTRACT FROM AUTHOR]

According to statistics released by the WHO, China has the highest prevalence of myopia in the world, with a frequency that is 1.5 times higher than the global average. Asians have the highest prevalence of myopia worldwide. The Ministry of Education and the State General Administration of Sports "2010 National Student Physical Fitness and Health Research Results" show that the incidence of poor vision among primary and secondary school students in China is 67.3%, and elementary school students' vision has decreased by 40.9%. Low vision among youth has become a major cause of affecting the quality of the population and improving national physical fitness; therefore, how to improve and enhance the vision level of youth has become a major issue for the government, sports, and educators face as a major issue. In order to address this issue, this research suggests a deep learning-based vision monitoring and risk prediction model for high myopia eyes and develops a deep artificial neural network that unsupervised learns essential characteristics of physiological time-series data. [ABSTRACT FROM AUTHOR]

To address the problem that the accuracy of the SVM algorithm is affected by random parameters at the input end, a financial crisis early warning model (FCEWM) based on PSO-SVM is constructed based on the nonequilibrium sample characteristics of different financial conditions of listed companies in China's gem. The model uses the PSO algorithm to optimize the parameters of SVM and selects 24 financial risk evaluation indexes as the input to predict the financial crisis. The results show that the proposed model is superior to other models in prediction accuracy and robustness. [ABSTRACT FROM AUTHOR]

Vehicle-pedestrian accidents are one of the main types of road traffic accidents in China because of their mixed traffic features. By analyzing the characteristics of vehicle-pedestrian accidents, the head injury criterion (HIC) was selected as a quantitative index of pedestrian head injury risk, and vehicle-pedestrian collision simulation tests were carried out using PC-Crash. From the collected test data, the multivariate relationship models between the HIC, vehicle speed, and collision angle were fitted for different vehicle types. A risk assessment method for vehicle-pedestrian accidents based on the HIC was proposed by the Fisher optimal segmentation algorithm. Finally, a new index for evaluating the accuracy of accident risk classification, the degree of error classification, was proposed to verify the validity of the accident risk assessment method. The results show that vehicle speed, collision angle, and vehicle type play a key role in pedestrian injury. Flat-headed vehicles are more likely to cause head injuries to pedestrians than high-headed and low-headed vehicles. Rear-end collisions cause more injuries to pedestrians than side collisions. The research results can provide guidance and a basis for accident liability determination, speed limit management, vehicle safety design, and human injury mechanism analysis. [ABSTRACT FROM AUTHOR]

Aim. To compare the clinical characteristics of survival and nonsurvival patients with severe acute pancreatitis (SAP) and explore the risk of mortality in SAP patients. Methods. This was a single-center retrospective study performed in a severe acute pancreatitis diagnosis and treatment center. According to the outcome, SAP patients were divided into survival group and nonsurvival group. One-way ANOVA or independent t -test was used to compare the clinical characteristics of two groups of patients. Multivariate retrospective analysis was used to identify risk factors for mortality in SAP patients. Results. A total of 486 SAP patients were included in the study, and the 90-day mortality for SAP patients was 13.58%. The common etiologies of SAP are biliary tract diseases (69.75%) and hyperlipidemia (17.28%). The most common complications caused by SAP were organ failure (55.14%), ARDS (50.62%), AKI (30.45%), sepsis (27.16%), and abdominal fluid collection (27.57%). There were differences in age, complications, and medical intervention between the nonsurvival group and the survival group. The main causes of death were infection (46.97%), abdominal bleeding (28.79%), and organ failure (9.09%). The binary logistic regression analysis showed that there were significant differences in age, AKI, sepsis, abdominal hemorrhage, organ failure, laparotomy, creatinine, and APTT between the nonsurvival group and the survival group. Conclusion. Age, AKI, sepsis, abdominal hemorrhage, and organ failure are risk factors for mortality in SAP patients. SAP patients with high creatinine and prolonged APTT upon admission require doctors to be vigilant. The main cause of death in SAP patients is pancreatitis-related organ failure and secondary infection. [ABSTRACT FROM AUTHOR]

This research studies the strategy of risk evaluation of China government bonds with the latest data. The angle of evaluation focuses on the interest rate and the stability risk, employing the EWMAVaR and SVM methods. The weights of each risk indicator are determined by the entropy method. Experimental results show that the risk of government bonds is stable in recent years. However, the impact of COVID-19 cannot be ignored because the risk level increased in the year 2020. The issuing of one trillion special antipandemic bonds could explain the fluctuation of the market because the fiscal incomes of Chinese government decreased in 2020 and could not be recovered in a short time. The experimental results show that the method proposed in this paper has a better performance than the existing methods, and it can help well in realizing the risk assessment of government bonds. [ABSTRACT FROM AUTHOR]

Risk assessment of public-private partnership projects has been recently acknowledged as a crucial issue in infrastructure projects. Objective assessment of risk status is conducive to the establishment of scientific and reasonable management measures. The particularity of evaluating water environment treatment PPP projects means that random errors in the evaluation index and the threshold fuzziness of evaluation degrees are issues that require attention. This paper uses the Pythagorean fuzzy cloud model to process the randomness and fuzziness of the indicators. This study assessed the risks of an iconic water environment treatment PPP project inn mid-China. The risk ranks were evaluated in terms of five dimensions: political, economic, construction completion, operational, and ecological. Moreover, the results of the evaluation were compared with results derived using a regular cloud model. It was found that the Pythagorean fuzzy cloud model produced results consistent with the regular method, while also having the advantage of reflecting the randomness and fuzziness of the evaluation indicators. According to the evaluation data in this case, the project risks were ranked as follows: political > construction completion > operational > ecological > economic. The overall project risk was medium. This study's results could provide technical support for water treatment PPP project risk assessment, indicator measurement, and statistical error control. [ABSTRACT FROM AUTHOR]

Understanding the sideslip risks of various trajectory patterns, as well as the impact of rainfall on them, is critical for improving road safety. However, the lack of precise classification indicators hampers systematic analysis of the variations in vehicle trajectory patterns. To address this, this study proposes a parameterized classification method for trajectories on curved segments, employing the radius and offset of the trajectory as the primary classification features and dividing the trajectories into nine patterns. These patterns represent variations from smaller to larger radii and inside to outside lane offsets, reflecting different driving behaviors and vehicle stability during vehicle cornering. Concurrently, the friction coefficient utilization rate is used to effectively compare vehicles' sideslip risk under different weather conditions. Based on this, we construct a framework using computer vision technology for automatically identifying trajectory patterns and measuring sideslip risk. We conducted an empirical study on a highway-curved segment with high sideslip risk in China and collected two datasets under clear and rainy conditions for analysis. The classification results show that the proposed method can effectively classify trajectories according to nine trajectory patterns. Comparative analysis reveals that vehicle trajectories in both the inside and outside lanes are notably more affected by rainfall compared to the middle lane. Meanwhile, trucks demonstrate a higher susceptibility to rainfall than cars. In addition, the analysis of the sideslip risk for different trajectory patterns discovers several high-risk patterns. This study provides an effective approach for monitoring and analyzing the sideslip risk on curved segments, thereby contributing to the enhancement of road design and traffic safety management. [ABSTRACT FROM AUTHOR]

The implementation of public–private partnership (PPP) is perturbed by multiple factors, and it is difficult for the Chinese government to fully control the risks of PPP projects. Based on the DPSIR model, this study constructed the PPP projects risk evaluation index system by using the TOPSIS method. Then the spatial variation, standard deviation ellipse, and gray dynamic model were used to analyze the spatial–temporal dynamic evolution characteristics of the risk level of PPP projects from 2003 to 2019 and to make reasonable predictions of the future spatial distribution pattern. This study yielded the following five results: (1) the average risk level of China's PPP projects is 0.722, with a decreasing trend of fluctuation and relatively stable risk; (2) high-risk provinces for PPP projects decrease, medium-risk provinces increase; (3) the spatial variability of risk is increasing, and the spatial differentiation is significant, showing a spatial evolution pattern of "west > central > east," but areas with low-risk values are clearly migrating to the east; (4) the spatial distribution pattern of risk has a north-easterly orientation, with a "north-west to north-east" trend in the path of movement; (5) There are differences in the spatial distribution patterns in the east–west and north–south directions, and the spatial spillover effect is not obvious. Based on the above results, the risk center of China's PPP projects will be shifted to the northeast in 2025–2035. Our study captures the evolution of PPP project risks in China in both temporal and spatial dimensions, which can provide lessons for optimizing global PPP project risk management. [ABSTRACT FROM AUTHOR]

The number of road maintenance operations in China is increasing. Work zones can interfere with everyday driving and bring significant safety hazards to the throughput vehicles and construction personnel. However, there is currently a lack of effective methods to conduct a dynamic risk assessment of work zones and provide control guidance when necessary. Therefore, this study proposes a dynamic risk assessment and control framework for the work zones. The framework adopts a closed-loop control and dynamic monitoring architecture. A massive amount of microscopic data on vehicles' behavior is obtained based on advanced data collection technologies (including multicamera multiobject tracking, naturalistic driving, and microscopic traffic simulation). Traffic conflicts between single vehicle and two- or multivehicle are detected using vehicle behavior analyzing technology and the surrogate safety assessment model. A comprehensive assessment index, i.e., UTECN (unit total equivalent conflict number), is established that can consider the severity and possibility of accidents caused by conflicts based on the vehicle collision energy theory, probability theory, and risk management theory. A risk assessment standard is established based on the level of safety service. The framework is first implemented in a simulation environment, and its feasibility and effectiveness are verified by taking a work zone of Shanghai Waihuan Expressway S20 as a case study. The result shows that the framework has good practicality. Under a moderate traffic level, the risk of the work zone can be assessed within 20 minutes. It can be quickly and effectively controlled at an acceptable level after several iterations, which is of great significance for ensuring the safety of life and property of throughput vehicles and construction personnel within the work zone. [ABSTRACT FROM AUTHOR]

To achieve the strategic target of energy conservation and emission reduction, China is vigorously developing its large-scale and distributed renewable energy power generation industry, dominated by wind power and photovoltaic power generation. In the new situation of renewable energy power interconnection, the grid company in China must fully consider the risks caused by renewable energy when making power purchase optimization decisions. This paper sets up a power purchasing model considering the risks of the renewable energy power interconnection and testifies to the effectiveness of the model through a case study. On this basis, this paper puts forward several reasonable suggestions to help the grid company make power purchase decisions under different risk preferences. [ABSTRACT FROM AUTHOR]

Based on the perspective of cost risk management of the entire process of power grid construction project, the WBS-RBS risk identification method is applied. The risk factors of power grid engineering cost are comprehensively identified from the five major engineering cost formation stages: investment decision estimate stage, design estimate stage, bidding price stage, construction budget stage, and final account stage. Combined with the basic data obtained from the questionnaire, the membership degree method is adopted to screen the key indicators of the preliminary factors of cost risk and then eliminate the redundant indicators. Furthermore, a set of simple and efficient risk evaluation index system for power grid engineering cost is constructed in order to improve the risk evaluation and management level of power grid construction project in China. [ABSTRACT FROM AUTHOR]

Urban regional risk is a complex nonlinear problem that encounters insufficient information, randomness, and uncertainty. To accurately assess the overall urban risk, a regional risk assessment model for urban public safety was proposed by using the information diffusion theory. The entropy theory was employed to optimize the information diffusion model to reduce the uncertainty. A framework of urban regional risk assessment model based on information diffusion and entropy was constructed. Finally, a case study of Hangzhou city in China was presented to demonstrate the performance of the proposed method. Results showed that the proposed method could successfully estimate the urban regional risk of Hangzhou city. The risk levels and probabilities of different hazard indicators were basically consistent with reality. The hazards with respect to industrial and mining accidents and road traffic accidents were extremely serious. More than 80 deaths from industrial and mining accidents would occur almost every 3 years, and more than 400 deaths of RTA would occur almost every 2.6 years. Moreover, centralized intervals of the risk level associated with five hazards were found, where urban risks were more likely to happen and had higher vulnerability. It could provide guidance for the government's urban safety management and policy-making. [ABSTRACT FROM AUTHOR]

Objective. Glaucoma in individuals who tested positive for the coronavirus disease 2019 (COVID-19) during the pandemic outbreak has not been comprehensively studied. Therefore, this study aimed to analyze the characteristics and risk factors of glaucoma during the COVID-19 pandemic in Huizhou. Methods. Retrospective data from outpatients with glaucoma at the Huizhou Hospital Affiliated with Guangzhou Medical University and Longmen County People's Hospital were collected during two periods: the COVID-19 pandemic period (Phase A: December 1, 2022, to January 19, 2023) and the prevention and control period (Phase B: December 1, 2021, to January 19, 2022). The demographic characteristics of the outpatients during both phases were compared. The characteristics of glaucoma in patients with COVID-19 during Phase A were examined. Multivariate logistic regression analysis was used to identify factors influencing the development of acute angle-closure glaucoma (AACG) in Phase A patients. Results. The proportion of patients with glaucoma was significantly higher during Phase A than during Phase B at both hospitals. No statistically significant differences were observed between patients with glaucoma during Phases A and B for age, sex, and region. A high COVID-19-positive rate was associated with old age, females, AACG, newly diagnosed glaucoma, and binocular involvement during phase A. Females testing positive for COVID-19, glaucoma that started after testing positive for COVID-19, and a history of medication use were associated with a higher proportion of AACG in phase A. Multivariable logistic regression analysis identified testing positive for COVID-19 as an independent potential risk factor for developing AACG. Conclusion. In summary, during the COVID-19 pandemic in Huizhou, patients with COVID-19 were primarily affected by AACG, especially females, older individuals, and those with binocular involvement. Testing positive for COVID-19 increases the risk of developing AACG. [ABSTRACT FROM AUTHOR]

Background. Reliable epidemiologic data on the present burden of hypertension are needed in developing region-specific strategies since previous studies have suggested that China is lagging in risk factor management. Objective. The study aimed at exploring the prevalence of hypertension and its associated factors among adult residents in Ganzhou, China. Methodology. A multistage, stratified, and cluster random sampling method was used to conduct the cross-sectional survey. The study selected four county-level districts in Ganzhou City, China, as the investigation area. Permanent residents aged ≥18 years who have settled in the area for 6 months or more were selected. A total of 7430 residents were involved in the study. Univariate and multivariate logistic regression analysis was carried out to identify predictors of hypertension. Results. The prevalence of hypertension in Ganzhou was 28.5%, and the age-standardized prevalence of hypertension was 22.4%. Univariate logistic regression analysis revealed that multiple variables have a statistically significant effect on the prevalence of hypertension. The elderly (odds ratio [95% CI]: 2.791 [2.594–3.004]), men (1.805 [1.583–2.058]), lower educated (0.848 [0.805–0.893]), a family history of hypertension (4.575 [3.900–5.368]), higher body mass index (1.344 [1.215–1.488]), central obesity (1.532 [1.304–1.799]), and less vegetable intake (1.150 [1.023–1.294]) were the major risk factors for hypertension. Conclusion. Hypertension is a major public health problem in Ganzhou and requires much effort to reduce its prevalence. An effective multifaceted implementation strategy is highly desirable to combat the emerging burden of hypertension. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the main etiological factors and visual outcomes in patients with dense vitreous hemorrhage (DVH) aged ≥80 years. We retrospectively included patients with DVH aged ≥80 years who were admitted to our ophthalmology department between January 1, 2010, and December 31, 2019. All patients underwent pars plana vitrectomy (PPV). Data regarding demographic characteristics; preoperative and postoperative best-corrected visual acuity (BCVA), intraocular pressure (IOP), and ophthalmic B-scan ultrasonography findings; intraoperative conditions; and postoperative complications were collected and analyzed. A total of 44 patients (44 eyes) were enrolled, with a median age of 82 years; among them, 25 patients (56.82%) were men. The median preoperative BCVA was 2.3 (1.1–3.0). The main etiological factors included retinal vein occlusion (RVO) (20 eyes, 45.45%), polypoidal choroidal vasculopathy (PCV) (15 eyes, 34.09%), proliferative diabetic retinopathy (PDR) (7 eyes, 15.90%), retinal arterial macroaneurysm (RAM) (1 eye, 2.27%), and posterior vitreous detachment (PVD) (1 eye, 2.27%). The median final BCVA was 1.92 (0.5–2.6). There was a significant postoperative improvement in the BCVA; moreover, branch RVO (BRVO) had a better postoperative visual prognosis than central RVO (CRVO), PCV, and PDR (P < 0.05). The final postoperative BCVA was significantly better when the initial BCVA was above hand motion (HM) than when it was HM or lower (P < 0.05). Our findings indicate that RVO, PCV, and PDR were the main causes of DVH. Microinvasive PPV is a safe and effective method that can clarify diagnosis and improve BCVA. Patients with BRVO and preoperative BCVA > HM may have a relatively good visual prognosis. For patients aged ≥80 years who have an appropriate general condition, PPV can be timely performed to treat DVH. [ABSTRACT FROM AUTHOR]

This study classifies risk factors and establishes the risk-evaluation index system for an urban river ecological management project. That system includes construction personnel risk, construction technology risk, construction management factor risk, construction duration factor risk, and other risks. A total of 23 indicators determine the level and standard of each indicator. This study proposes a risk index system that uses the cloud model evaluation method and explains that model's process. To demonstrate the risk evaluation methodology, it was applied to the ecological management project of Jinghe River in Jinghe New City, China. The results showed that: (1) the urban river ecological management project was subject to "a medium level of personnel risk, management risk, and construction period risk and a relatively high level of technical risk and other risks." According to the evaluation results, the overall risk level of the project was medium, which is consistent with the risk level of the Jinghe River ecological management project at the current stage. (2) The limitation of the subjective qualitative concept caused by the traditional fuzzy comprehensive evaluation was fully considered in the improved method, and the application of the cloud-model based improved method in risk evaluation of the urban river ecological management project significantly improved the reliability and visualization of the evaluation results. Finally, the urban river ecological management project in China was adopted as an example to prove that the model boasts high stability, and some corresponding countermeasures were also proposed. The research results are expected to provide valuable references and scientific criteria for implementing urban river ecological management projects. [ABSTRACT FROM AUTHOR]

The mean seismic probability risk model has widely been used in seismic design and safety evaluation of critical infrastructures. In this paper, the confidence levels analysis and error equations derivation of the mean seismic probability risk model are conducted. It has been found that the confidence levels and error values of the mean seismic probability risk model are changed for different sites and that the confidence levels are low and the error values are large for most sites. Meanwhile, the confidence levels of ASCE/SEI 43-05 design parameters are analyzed and the error equation of achieved performance probabilities based on ASCE/SEI 43-05 is also obtained. It is found that the confidence levels for design results obtained using ASCE/SEI 43-05 criteria are not high, which are less than 95%, while the high confidence level of the uniform risk could not be achieved using ASCE/SEI 43-05 criteria and the error values between risk model with target confidence level and mean risk model using ASCE/SEI 43-05 criteria are large for some sites. It is suggested that the seismic risk model considering high confidence levels instead of the mean seismic probability risk model should be used in the future. [ABSTRACT FROM AUTHOR]

Background. Burnout is a common psychological syndrome among nurses, especially in the first few years of working. However, limited studies have evaluated the factors related to burnout among junior nurses. Aims. To investigate the levels of psychological flexibility, stress, and burnout among junior nurses and examine the role of demographic and workplace relationship factors, psychological flexibility, and perceived stress on burnout among junior nurses. Materials and Methods. A convenience sample of 481 junior nurses was recruited from three tertiary hospitals in China from July 2021 to August 2022. Data were collected, including demographic data, workplace relationships, psychological flexibility (measured by experiential avoidance and cognitive fusion), perceived stress, and burnout. The Independent t-test, one-way ANOVA, Wilcoxon–Mann–Whitney test, Kruskal–Wallis test, Spearman correlation, and hierarchical regression were used to analyze the data. Results. Junior nurses had a high level of burnout in different dimensions. Nurses with an undergraduate education, nurses working in the first year, and a lack of support from supervisors and poor colleague (nurse-nurse and nurse-doctor) relationships had the lowest level of psychological flexibility and the highest level of perceived stress and burnout. Spearman correlation indicated that experiential avoidance, cognitive fusion, perceived stress, and burnout were positively associated with each other. The regression model showed that psychological flexibility (especially cognitive fusion) and perceived stress influenced burnout in junior nurses. Conclusions. Higher psychological flexibility and lower perceived stress appear to improve burnout in junior nurses. Therefore, interventions targeting these two factors may provide a viable direction for the reduction of burnout among junior nurses. Implications for Nursing Management. Hospital authorities should create a harmonious working environment and provide some psychology training programs for junior nurses. [ABSTRACT FROM AUTHOR]

Aim. To develop a valid, reliable assessment tool to measure risk factors associated to low back pain (LBP) in intensive care unit (ICU) nurses. Background. LBP is defined as the pain extending from the 12th rib to the iliac crest and often coexists with buttock pain. Nursing has been identified among the top professions at risk of LBP. A mean of 70% prevalence per year in ICU nurses was reported, exceeding those employed in heavy industry. Environmental factors in workplace were also most important risks related to LBP in this population except factors including individual, physical, psychosocial, and lifestyle. However, there is lack of tools to assess environmental risk related to LBP for nurse managers currently. Methods. Focus group interviews, field research, and panel discussion were used to develop item pool. Two-round expert reviews and preinvestigation were carried out to form initial scale named Environmental Risk Assessing Instrument-Occupational Low Back Pain in Nurses (ERAI-N). A cross-sectional survey with 188 ICU participants in Hunan Province in China was implemented to collect data. Cronbach's alpha, split-half reliability, and test-retest reliability were used to test ERAI-N's reliability. Expert review was performed to test ERAI-N's content validity, and confirmatory factor analysis (CFA) was performed to assess its construct validity, being carried out in IBM SPSS Amos 26 Graphics. Results. Final version of ERAI-N scale had five dimensions with 18 items that were space, equipment, belief, guideline, and safe culture. ERAI-N scale's score of Cronbach's alpha, Guttman split-half, and intraclass correlation coefficient (ICC) was 0.958, 0.927, and 0.994, respectively. Item-level content validity scores ranged from 0.89 to 1.0, and scale-level content validity was 0.983. Standardized factor loadings ranged from 0.567 to 0.974. Model adjusted fit statistics were as follows: the chi-square statistic and degrees of freedom (χ2/df) = 3.943, root mean square error of approximation (RMSEA) = 0.071, incremental fit index (IFI) = 0.905, comparative fit index (CFI) = 0.904, parsimony normed fit index (PNFI) = 0.641, and parsimonious comparative fit index (PCFI) = 0.661. Conclusions. ERAI-N scale had moderate reliability, content validity, and construct validity. Implications for Nursing Management. Designers may use ERAI-N scale to plan the interior layout when design a new ICU. Nurse managers might utilize this instrument as a managing tool to assess whether there is environmental risk factors related to LBP in ICU. [ABSTRACT FROM AUTHOR]

Objective. This study focuses on the identification of risk factors, classification of stroke level, and evaluation of the importance and interactions of various patient characteristics using cohort data from the Second Hospital of Lanzhou University. Methodology. Risk factors are identified by evaluation of the relationships between factors and response, as well as by ranking the importance of characteristics. Then, after discarding negligible factors, some well-known multicategorical classification algorithms are used to predict the level of stroke. In addition, using the Shapley additive explanation method (SHAP), factors with positive and negative effects are identified, and some important interactions for classifying the level of stroke are proposed. A waterfall plot for a specific patient is presented and used to determine the risk degree of that patient. Results and Conclusion. The results show that (1) the most important risk factors for stroke are hypertension, history of transient ischemia, and history of stroke; age and gender have a negligible impact. (2) The XGBoost model shows the best performance in predicting stroke risk; it also gives a ranking of risk factors based on their impact. (3) A combination of SHAP and XGBoost can be used to identify positive and negative factors and their interactions in stroke prediction, thereby providing helpful guidance for diagnosis. [ABSTRACT FROM AUTHOR]

Background. To establish a depression risk warning model for patients with pulmonary nodules and to provide a theoretical basis for medical staff to identify high-risk patients early and quickly and take timely intervention measures. Methods. A total of 535 hospitalized patients with pulmonary nodules were selected, and the relevant data were analyzed by single-factor analysis. Binary logistic regression analysis was used to determine the independent risk factors for depression in patients with pulmonary nodules and to establish a risk warning model. The Hosmer−Lemeshow test and receiver operating characteristic (ROC) curve were used to evaluate the goodness of fit and prediction effect of the model, and the cross-validation method was used to verify the efficacy of the model. Results. The prevalence of depression in patients with pulmonary nodules was 47.29%. Univariate analysis showed that CRP, albumin, creatinine, phosphorus, calcium, triglyceride, cholesterol, low-density lipoprotein, high-density lipoprotein, β2-microglobulin, objective support, social support, and education level were related to depression in patients with pulmonary nodules P < 0.05 . Binary logistic regression analysis showed that serum CRP, calcium, social support, and education level were independent risk factors for depression in patients with pulmonary nodules. The area under the ROC curve/sensitivity/specificity of serum CRP, calcium, social support, and education level was 0.78/86.88%/80.65%, 0.79/84.40%/75.59%, 0.83/89.91%/80.22%, and 0.81/85.96%/79.19%, and the accuracy of cross-checked risk warning model was 84.97%. In the Hosmer−Lemeshow test, P = 0.926, area under the ROC curve was 0.98, sensitivity was 98.17%, and specificity was 93.55%. The accuracy of the cross-checked risk warning model was 84.97%, indicating that the prediction effect of the model was good. Conclusions. Serum CRP, calcium, social support, and education level are the independent risk factors of depression in patients with pulmonary nodules, and the risk warning model based on them has a good early warning effect on depression in patients with pulmonary nodules. The risk warning model established in this study has a good predictive effect on depression in patients with pulmonary nodules. [ABSTRACT FROM AUTHOR]