Osthole, a Coumarin from Cnidium monnieri: A Review on Its Pharmacology, Pharmacokinetics, Safety, and Innovative Drug Delivery Platforms.

Osthole, a coumarin compound mainly derived from Cnidium monnieri (L.), has attracted much interest from the scientific community owing to its multiple therapeutic properties. However, its pharmacological mechanism, pharmacokinetics, and toxicological effects are far from clear. Furthermore, the potential drug delivery platforms of osthole remain to be comprehensively delineated. The present review aimed to systematically summarize the most up-to-date information related to pharmacology, pharmacokinetics, and safety issues related to osthole, and discuss the investigations of novel drug delivery platforms. The information herein discussed was retrieved from authoritative databases, including PubMed, Web of Science, Google Scholar, Chinese National Knowledge Infrastructure (CNKI) and so on, reviewing information published up until February of 2024. New evidence shows that osthole induces a sequence of therapeutic actions and has a moderate absorption rate and rapid metabolic characteristics. In addition, this phytoconstituent possesses potential hepatotoxicity, and caution should be exercised against the risk of the drug combination. Furthermore, given its needy solubility in aqueous medium and non-organizational targeting, novel drug delivery methods have been designed to overcome these shortcomings. Given the properties of osthole, its therapeutic benefits ought to be elucidated in a greater array of comprehensive research studies, and the molecular mechanisms underlying these benefits should be explored.

Evaluating the safety and efficiency of nanomaterials: A focus on mitochondrial health.

Nanomaterials (NMs) have extensive application potential in drug delivery, tissue engineering, and various other domains, attributable to their exceptional physical and chemical properties. Nevertheless, an increasing body of literature underscores the diverse safety risks are associated with NMs upon interaction with the human body, including oxidative stress and programmed cell death. Mitochondria, serving as cellular energy factories, play a pivotal role in energy metabolism and the regulation of cell fate. Organs with substantial energy demands, including the heart and brain, are highly sensitive to mitochondrial integrity, with mitochondrial impairment potentially resulting in significant dysfunction and pathologies such as as heart failure and neurodegenerative disease. This review elucidates the pathways by which NMs translocate into mitochondria, their intracellular dynamics, and their impact on mitochondrial morphology, respiratory chain activity, and metabolic processes. We further investigate associated molecular mechanisms, including mitochondrial dynamic imbalance, calcium overload, and oxidative stress, and elucidate the pivotal roles of mitochondria in different forms of programmed cell death such as apoptosis and autophagy. Finally, we offer recommendations regarding the safety and efficacy of NMs for medical applications. By systematically analyzing the interactions and molecular mechanisms between NMs and mitochondria, this paper aims to enhance the toxicological evaluation framework of NMs and provide a foundational reference and theoretical basis for their clinical utilization.

Towards safer tower crane operations: An innovative knowledge-based decision support system for automated safety risk assessment.

INTRODUCTION: Tower cranes are commonly employed in construction projects, despite presenting significant hazards to the workforce involved. METHOD: To address these safety concerns, a Knowledge-Based Decision-Support System for Safety Risk Assessment (KBDSS-SRA) has been developed. The system's capacity to thoroughly evaluate associated risks is illustrated through its utilization in various construction endeavors. RESULTS: The system accomplishes the following goals: (1) compiles essential risk factors specific to tower crane operations, (2) identifies critical safety risks that jeopardize worker well-being, (3) examines and assesses the identified safety risks, and (4) automates the labor-intensive and error-prone processes of safety risk assessment. The KBDSS-SRA assists safety management personnel in formulating well-grounded decisions and implementing effective measures to enhance the safety of tower crane operations. PRACTICAL APPLICATIONS: This is facilitated by an advanced computerized tool that underscores the paramount significance of safety risks and suggests strategies for their future mitigation.

Research on coal mine safety risk evolution and key hidden dangers under the perspective of complex network.

In order to find out the main causes of coal mine safety accidents and improve the pertinence of coal mine safety risk management and control, the identification and analysis of coal mine safety risks and hidden dangers are carried out based on the analysis of coal mine accident reports. Combing the complex network theory, a complex network model for the evolution of coal mine safety risks is constructed. The key elements that affect coal mine safety risk accidents are obtained through quantitative research on the characteristic indicators of the complex network model of coal mine safety risks. And the key nodes of coal mine safety risk spread network are obtained through network interference to the overall efficiency. The research results show that the complex network of coal mine safety risks illustrate the characteristics of a small-world network, and the spread of a certain risk is likely to cause coal mine safety accidents. Strengthening the risk management and control of hidden dangers with higher intermediate centrality can isolate the spread of coal mine safety risks and reduce the possibility of coal mine accidents.

Safety risk assessment of reservoir dam structure: an empirical study in China.

Reservoir dam structure is critical to protect public life and property and has always been attention worldwide. However, a systematic approach to assessing the safety risks of reservoir dam structure (RDS) is still required. This study presents a holistic framework for evaluating the safety risk of RDS and develops an evaluation index system. A risk assessment model is constructed based on the cloud and Dempster-Shafer (D-S) evidence theories. The model's validity is confirmed through an empirical analysis of the XY reservoir project. This study offers theoretical insights and practical solutions for managers to facilitate decision-making and supports the advancement of industry standards.

Classification and Prediction of Food Safety Policy Tools in China Based on Machine Learning.

Governments use policy interventions to mitigate food safety risks. Despite its crucial role, empirical studies evaluating the effectiveness of China's food safety policy tools are scarce. Drawing on a dataset encompassing 11,236 food safety policy texts from 2005 to 2021 and the incidence of problematic food products in the Eastern, Central, and Western regions of China, this study employs Latent Dirichlet Allocation (LDA) and eXtreme Gradient Boosting (XGBoost) models to facilitate the classification of policy tools and forecast the effectiveness of policy combinations. The study reveals that (1) local governments have gradually become an important supplementary maker of food safety policies, and have issued an increasing number of policy tools year by year. (2) Mandatory policy tools are predominant in number and have the highest legal hierarchy and authority levels, followed successively by guiding policy and voluntary policy tools. (3) Mandatory policy tools demonstrated the most effective intervention results, followed successively by guiding policy and voluntary policy tools. (4) The forecast analysis reveals that combinations of policies within high-growth frameworks and those driven by mandatory regulations emerge as the most effective. Therefore, the balance of policy tools in terms of type, effectiveness, and quantity, as well as their applicability in different situations, should all be taken into account.

Ordered weighted evaluation method of lifting operation safety risks considering coupling effect.

In order to accurately evaluate the safety risk degree of lifting operations and improve the safety control level of lifting operations, firstly, Work Breakdown Structure (WBS) is used to decompose the construction process of lifting operations, Risk Breakdown Structure (RBS) is used to decompose the safety risk, 16 safety risk factors of lifting operations are identified, and the risk evaluation system is constructed. Then, the safety risk assessment model of lifting operations is constructed by integrating risk coupling theory, joint ordered weighting operators, and an interaction matrix to identify key risk factors and safety risk levels. Finally, taking the lifting operation construction project of Yangfanggou Hydropower Station as an example, the evaluation index system and method are applied. The results show that the high-risk safety risks of the lifting operation construction of the project are: 'Low safety awareness causes workers to operate illegally X23', 'Operation error caused by illegal command X33', 'Workers' risky work caused by low safety awareness X34', 'Edge, high and climbing operation protection is not in place X36', and 'Improper binding of components caused by workers' illegal operation X25'. The construction of the lifting operation poses a significant risk level, and the evaluation results are consistent with the actual situation. The rationality of the evaluation system and model constructed in this paper can provide a reference for the safety management and control of the construction site of the lifting operation and the safety of the lifting operation.

[Reflections on the safety regulation of commercialization of synthetic biology products].

With the rapid development of synthetic biology, lots of synthetic biology technology achievements in various application fields have been commercialized, generating broad market prospects. The commercialization of products employing synthetic biology technology (hereinafter referred as synthetic biology products) has brought benefits to human beings, but it has also produced potential safety risks. At present, relevant laws and standards for regulation of biotechnology or genetically modified organisms have been adopted to regulate the safety risks of commercialization of synthetic biology products (CSBP). However, due to the complexity and uncertainty of synthetic biology, the safety risks of CSBP cannot be comprehensively regulated by these laws and standards. Therefore, it is of great significance to formulate specific supervision and management measures for regulating the safety risks of CSBP. This paper summarized the situation of CSBP in the fields of food, medical care, agriculture, environment, energy and materials, analyzed the safety risks existing in the CSBP, and sorted out current supervision situation of its safety risks in European countries, United States, as well as in China. We further proposed suggestions on the safety supervision and management measures on the safety risks of CSBP, including classified examination and approval, classified identification of products, and strict screening and approval of market entities before entering the market, and strengthening safety supervision and emergency treatment as well as accident responsibility investigation after entering the market. This whole-process safety regulation might provide support for the safety of CSBP and promote the healthy and long-term development of synthetic biology industry.

On the impact of on-road partially-automated driving on drivers' cognitive workload and attention allocation.

The use of partially-automated or SAE level-2 vehicles is expected to change the role of the human driver from operator to supervisor, which may have an effect on the driver's workload and visual attention. In this study, 30 Ontario drivers operated a vehicle in manual and partially-automated mode. Cognitive workload was measured by means of the Detection Response Task, and visual attention was measured by means of coding glances on and off the forward roadway. No difference in cognitive workload was found between driving modes. However, drivers spent less time glancing at the forward roadway, and more time glancing at the vehicle's touchscreen. These data add to our knowledge of how vehicle automation affects cognitive workload and attention allocation, and show potential safety risks associated with the adoption of partially-automated driving.

Quantitative assessment of food safety interventions for Campylobacter spp. and Salmonella spp. along the chicken meat supply chain in Burkina Faso and Ethiopia.

Rural and small-scale chicken farming is a major source of income in most African countries, and chicken meat is an important source of nutrients. However, chicken meat can be contaminated with Campylobacter spp. and Salmonella spp., pathogens with a high reported burden of foodborne illnesses. Therefore, it is essential to control these pathogens in chicken meat. Quantitative microbial risk assessments (QMRA) can aid the development of effective food safety control measures and are currently lacking in chicken meat supply chains in the African context. In this study, we developed stochastic QMRA models for Salmonella spp. and Campylobacter spp. in the chicken meat supply chain in Burkina Faso and Ethiopia employing the modular process risk model in @Risk software. The study scope covered chicken farming, transport, slaughtering, consumer handling, and consumption. Effectiveness of candidate interventions was assessed against baseline models' outputs, which showed that the mean annual Campylobacter spp. risk estimates were 6482 cases of illness per 100,000 persons and 164 disability adjusted life years (DALYs) per 100,000 persons in Burkina Faso, and 12,145 cases and 272 DALYs per 100,000 persons in Ethiopia. For Salmonella spp., mean annual estimates were 2713 cases and 1212 DALYs per 100,000 persons in Burkina Faso, and 4745 cases and 432 DALYs per 100,000 persons in Ethiopia. Combining interventions (improved hand washing plus designated kitchen utensils plus improved cooking) resulted in 75 % risk reduction in Burkina Faso at restaurants and 93 to 94 % in Ethiopia at homes for both Salmonella spp. and Campylobacter spp. For Burkina Faso, adding good hygienic slaughter practices at the market to these combined interventions led to over 91 % microbial risk reduction. Interventions that involved multiple food safety actions in a particular step of the supply chain or combining different interventions from different steps of the supply chain resulted in more risk reduction than individual action interventions. Overall, this study demonstrates how diverse and scanty food supply chain information can be applied in QMRA to provide estimates that can be used to stimulate risk-based food safety action in African countries.

Safety risk assessment of subway shield construction under-crossing a river using CFA and FER.

Numerous subway projects are planned by China's city governments, and more subways can hardly avoid under-crossing rivers. While often being located in complex natural and social environments, subway shield construction under-crossing a river (SSCUR) is more susceptible to safety accidents, causing substantial casualties, and monetary losses. Therefore, there is an urgent need to investigate safety risks during SSCUR. The paper identified the safety risks during SSCUR by using a literature review and experts' evaluation, proposed a new safety risk assessment model by integrating confirmatory factor analysis (CFA) and fuzzy evidence reasoning (FER), and then selected a project to validate the feasibility of the proposed model. Research results show that (a) a safety risk list of SSCUR was identified, including 5 first-level safety risks and 38 second-level safety risks; (b) the proposed safety risk assessment model can be used to assess the safety risk of SSCUR; (c) safety inspection, safety organization and duty, quicksand layer, and high-pressure phreatic water were the high-level risks, and the onsite total safety risk was at the medium level; (d) management-type safety risks, environment-type safety risks, and personnel-type safety risks have higher expected utility values, and manager-type safety risks were expected have higher risk-utility values when compared to worker-type safety risks. The research can enrich the theoretical knowledge of SSCUR safety risk assessment and provide references to safety managers for conducting scientific and effective safety management on the construction site when a subway crosses under a river.

An interpretable XGBoost-based approach for Arctic navigation risk assessment.

The Northern Sea Route (NSR) makes travel between Europe and Asia shorter and quicker than a southern transit via the Strait of Malacca and Suez Canal. It provides greater access to Arctic resources such as oil and gas. As global warming accelerates, melting Arctic ice caps are likely to increase traffic in the NSR and enhance its commercial viability. Due to the harsh Arctic environment imposing threats to the safety of ship navigation, it is necessary to assess Arctic navigation risk to maintain shipping safety. Currently, most studies are focused on the conventional assessment of the risk, which lacks the validation based on actual data. In this study, actual data about Arctic navigation environment and related expert judgments were used to generate a structured data set. Based on the structured data set, extreme gradient boosting (XGBoost) and alternative methods were used to establish models for the assessment of Arctic navigation risk, which were validated using cross-validation. The results show that compared with alternative models, XGBoost models have the best performance in terms of mean absolute errors and root mean squared errors. The XGBoost models can learn and reproduce expert judgments and knowledge for the assessment of Arctic navigation risk. Feature importance (FI) and shapley additive explanations (SHAP) are used to further interpret the relationship between input data and predictions. The application of XGBoost, FI, and SHAP is aimed to improve the safety of Arctic shipping using advanced artificial intelligence techniques. The validated assessment enhances the quality and robustness of assessment.

Research on risk assessment and operation safety management of magnetic resonance imaging equipment based on work chain and extension matter-element model / 中国医学装备

Objective:To construct a safe operation management path based on work chain and extension matter-element model,and to explore its application effect in clinical management of magnetic resonance imaging(MRI)equipment.Methods:The safety risk evaluation indicators was developed from the perspective of MRI equipment work chain at the levels of personnel,equipment,environment and system.The rating of safety characteristic indicators of equipment was carried out and risk control management strategy was formulated by adopting extensible matter element model.The MRI equipment in clinical use in the Imaging Department of Shucheng People's Hospital from January 2019 to December 2021 was selected,and the standard process management mode(referred to as standard process mode)and risk assessment control mode(referred to as risk control mode)were adopted respectively for equipment operation management.The safety risk event control rate,safety operation management standardization and professional capability of staff of MRI equipment under two different management modes were compared.Results:Among 62 safety risk events of MRI equipment managed by risk control mode,the control rates of extremely dangerous,highly dangerous and significant dangerous events were 1.61%(1/62),4.84%(3/62)and 8.06%(5/62),respectively,which were lower than those of the standard process mode,the difference was statistically significant(x2=5.613,4.567,9.241,P<0.05).Among 480 cases of safety operation inspection carried out by risk control mode management,the standardization of patient reception,equipment use,operating environment and management system were 96.25%(462/480),98.96%(475/480),99.17%(476/480)and 97.50%(468/480),respectively,which were higher than those of the standard process mode,the difference was statistically significant(x2=18.631,17.563,7.353,8.789,P<0.05).The annual assessment scores of MRI technicians,nurses and medical engineering engineers of the imaging department adopting risk control mode were(91.87±4.56)points,(94.54±3.27)points and(91.45±4.95)points,respectively,which were higher than those of the standard process mode,the difference was statistically significant(t=3.291,4.277,4.292,P<0.05).Conclusion:The risk control management mode based on work chain and extension matter-element model can comprehensively explore the factors affecting the safe operation of MRI equipment,effectively control the incidence of high-risk events,improve the quality of clinical operation and operation management of MRI equipment.

Advancing food safety risk assessment in China: development of new approach methodologies (NAMs).

Novel techniques and methodologies are being developed to advance food safety risk assessment into the next-generation. Considering the shortcomings of traditional animal testing, new approach methodologies (NAMs) will be the main tools for the next-generation risk assessment (NGRA), using non-animal methodologies such as in vitro and in silico approaches. The United States Environmental Protection Agency and the European Food Safety Authority have established work plans to encourage the development and application of NAMs in NGRA. Currently, NAMs are more commonly used in research than in regulatory risk assessment. China is also developing NAMs for NGRA but without a comprehensive review of the current work. This review summarizes major NAM-related research articles from China and highlights the China National Center for Food Safety Risk Assessment (CFSA) as the primary institution leading the implementation of NAMs in NGRA in China. The projects of CFSA on NAMs such as the Food Toxicology Program and the strategies for implementing NAMs in NGRA are outlined. Key issues and recommendations, such as discipline development and team building, are also presented to promote NAMs development in China and worldwide.

Comprehensive safety risk evaluation of fireworks production enterprises using the frequency-based ANP and BPNN.

The fireworks industry has long struggled with the problem of safety. Scientific, reasonable, and operable evaluation models are prerequisites of reducing risk. Based on the data from over 100 fireworks production safety accidents in China from 2010 to 2022, two evaluation models were established from the perspective of safety risk definition. Firstly, a weight calculation derivative method, the frequency-based analytic network process (ANP), was proposed creatively. This method optimized the importance ranking index calculation process in the ANP by considering the causal frequency of risk factors in the historical accident samples, thus determining how much each indicator affects the likelihood of accidents. Secondly, utilizing the historical accident samples as the dataset, a back propagation neural network (BPNN) model was developed to extract the mathematical relationship between each risk factor and the severity of accident consequence. Finally, the frequency-based ANP and BPNN models were combined to determine the safety risk level of the fireworks production enterprises. Meanwhile, the safety evaluation research samples were used as the comparison set for empirical study with historical accident samples, involving 100 fireworks production enterprises in China evaluated from 2017 to 2020. The significance result of zero shows that there is a statistically significant difference between the likelihood evaluation results of the accident and non-accident companies. Additionally, the severity evaluation model exhibits an excellent result, revealing a classification accuracy of 98.21 %, a mean square error of 8.97 × 10-4, a percent bias of 1.24 %, and a correlation coefficient and Nash-Sutcliffe efficiency coefficient both of 0.96. The frequency-based ANP and BPNN models integrate self-learning, self-adaptive, and fuzzy information processing, obtaining more accurate and objective evaluation results. This work provides a new strategy for the promotion and application of artificial intelligence in the field of safety risk evaluation, thus offering real-time safety risk evaluation and decision support of the safety management for the enterprises.

Economic Growth, Income Inequality and Food Safety Risk.

Food safety risk, as an implicit cost of social and economic development, endangers the health of global residents, including China. To systematically understand the impact of socioeconomic development on food safety risk and to establish a sound modern governance system of food safety in China, this paper uses provincial panel data from 2011 to 2020 to explore the relationship between food safety risk and socio-economic development factors such as economic growth and income inequality by employing a two-way fixed effect model and moderating effect model. The results show that the food safety risk is a Kuznets curve, and the turning point is about RMB 58,104.59 per capita GDP (based on prices in 2011). However, under the moderating effect of income inequality, the turning point of the Kuznets curve of food safety risk will shift to the right, and the curve will be flattened. In other words, income inequality has a negative moderating effect on the "inverted U-shaped" relationship between economic growth and food safety risk. When dealing with food safety problems, the goal of stable and sustained economic growth and common prosperity should be incorporated into policy formulation to enhance the governance effectiveness of food safety risk.

Safety risk assessment for autonomous vehicle road testing.

OBJECTIVE: Road testing can accelerate the development and validation of autonomous vehicles (AVs). AV road testing can come with high safety risks, particularly in a complex road traffic environment, due to the immaturity of AV technology. A priori safety risk assessments of the road traffic environment before AV road testing are of great importance, allow the quantifying of risk levels in different road scenarios, and provide guidelines for AV road testing in low to high-risk environments. METHODS: This study proposes a framework, namely Safety Risk Assessment for AV road testing (SRAAV), based on the probability and severity of five categories of potential AV accidents. Four groups of influencing factors are considered comprehensively in assessing AV safety risk, and their impacts are quantified using impact coefficients derived from a Bayesian network and empirical AV road testing data. The safety risk is assessed on a road section level, based on which an overall risk level is defined for a corridor and a region. Afterwards, the quantified safety risk is classified into four levels according to expert experience and knowledge, through a questionnaire survey. RESULTS: Applications of the proposed SRAAV framework are conducted for urban roads in Shanghai, and expressways in Shanghai and Gothenburg. The assessment results are validated using disengagement data from AV road testing. The results show that the SRAAV framework and its models could estimate the safety risk levels of road traffic environments for AV road testing in a sound way and have the flexibility for further extensions to be made. CONCLUSIONS: The framework and assessment results can provide technical support for determining where and when to grant permission for public roads to be used for AV road testing, and how to choose public roads from a low to a high risk level, guaranteeing the safety of AV public road testing.

Prediction of Food Safety Risk Level of Wheat in China Based on Pyraformer Neural Network Model for Heavy Metal Contamination.

Heavy metal contamination in wheat not only endangers human health, but also causes crop quality degradation, leads to economic losses and affects social stability. Therefore, this paper proposes a Pyraformer-based model to predict the safety risk level of Chinese wheat contaminated with heavy metals. First, based on the heavy metal sampling data of wheat and the dietary consumption data of residents, a wheat risk level dataset was constructed using the risk evaluation method; a data-driven approach was used to classify the dataset into risk levels using the K-Means++ clustering algorithm; and, finally, on the constructed dataset, Pyraformer was used to predict the risk assessment indicator and, thus, the risk level. In this paper, the proposed model was compared to the constructed dataset, and for the dataset with the lowest risk level, the precision and recall of this model still reached more than 90%, which was 25.38-4.15% and 18.42-5.26% higher, respectively. The model proposed in this paper provides a technical means for hierarchical management and early warning of heavy metal contamination of wheat in China, and also provides a scientific basis for dynamic monitoring and integrated prevention of heavy metal contamination of wheat in farmland.

Vasovagal Syncope at Work: A Narrative Review for an Occupational Management Proposal.

Syncope is a complex clinical manifestation that presents considerable diagnostic difficulties and, consequently, numerous critical issues regarding fitness for work, especially for high-risk tasks. To date, it is impossible to quantify the exact impact of syncope on work and public safety since it is highly improbable to identify loss of consciousness as the fundamental cause of work or driving-related accidents, especially fatal injuries. Working at high-risk jobs such as public transport operators, in high elevations, or with exposure to moving parts, construction equipment, fireworks, or explosives demand attention and total awareness. Currently, no validated criteria or indicators are available for occupational risk stratification of a patient with reflex syncope to return to work. By drawing inspiration from the updated literature, this narrative review intends to summarise the leading knowledge required regarding the return to work for subjects affected by syncope. According to the available data, the authors highlighted some key findings, summarised in macro-items, such as defined risk stratification for vasovagal accidents, return to work after a critical event, and a focus on pacemaker (PM) implementation. Lastly, the authors proposed a flowchart for occupational physicians to help them manage the cases of workers affected by syncope and exposed to levels of risk that could represent a danger to the workers' health.

Dynamic assessment and system dynamics simulation of safety risk in whole life cycle of coal mine.

Based on the accident causation theory, the mechanism and inducement of construction safety risk in mining enterprises are clarified. The safety risk system of mining enterprises is divided into five subsystems: personnel, material equipment, technology, environment, and management by rough set theory. The comprehensive weight of each risk factor is calculated by network analytic hierarchy process and fuzzy comprehensive evaluation method. Taking a mine in Shanxi Province as the research object, the causal traceability diagram and stock flow diagram of the risk system of mining enterprises are constructed by means of system dynamics model. The influence of various risk factors of the mine on the overall safety risk management level of the enterprise is simulated, and the numerical value of key personnel influence factors is adjusted. The sensitivity changes of safety productivity and safety risk management level of mining enterprises in different situations are analyzed. The results show that: (1) the management and personnel subsystem has the greatest impact on the safety risk management of mining enterprises, followed by the technology, material equipment, and environment subsystem. (2) Increasing safety input can improve the safety level and reduce the expected safety value time, otherwise it will reduce the safety level and delay the expected safety value time. (3) Further simulation of the personnel subsystem, it is found that the factors affecting the safety level of mining enterprises contain six factors, namely, the technical level of construction personnel, the management level of manager, the conduct code of construction personnel, the safety consciousness of practitioners, the basic quality of construction personnel, and the physical and mental state of construction personnel. (4) The conversion rate of personnel safety input to manager's management level and the safety consciousness of practitioners presents a steep decline-slow rise-gradually steady development trend, which mainly because the benefits of safety input have certain time delay and lag.