Institutional quality,financial development and sustainable economic growth among lower income countries

This article postulates strong endogenous relationships in lower income countries between institutional quality, financial development and sustained economic growth. These associations were investigated using the vector-error correction model (VECM) and Granger causality method for a sample of 79 countries from 2005 to 2022. The findings show that (1) these variables reinforce each other in the short run. (2) In the long run, both institutional quality and financial development can fuel economic growth. (3) The positive effect of institutional quality on economic growth is greater than that of financial development. Policy implications of these findings are that careful attention should be paid to co-development policies to enhance the institutional quality and the financial system in these economies. Policies should also consider economic growth strategies to enable sustainable economic growth rates.     

Performance assessment system of health,safety and environment based on experts' weights and fuzzy comprehensive evaluation

Performance evaluation of Health, Safety and Environment (HSE) is the measurement of a company's achievement in HSE management. In order to receive a comprehensive and objective evaluation result, it is necessary to consider all evaluation factors and experts at different levels when HSE performance assessment is conducted. To improve conventional HSE performance evaluation, where weighted average method was used, a Fuzzy Comprehensive Evaluation (FCE) method is used in this study by taking experts' weights into account. Further, an HSE operating performance assessment system is designed to simplify manual and complex assessment process and generate charts and analysis reports automatically. Finally, a case of petrochemical enterprise is used to illustrate the effectiveness of the method and system.     

Development and evaluation of RAMP I – a practitioner’s tool for screening of musculoskeletal disorder risk factors in manual handling

RAMP I is a screening tool developed to support practitioners in screening for work-related musculoskeletal disorder risk factors related to manual handling. RAMP I, which is part of the RAMP tool, is based on research-based studies combined with expert group judgments. More than 80 practitioners participated in the development of RAMP I. The tool consists of dichotomous assessment items grouped into seven categories. Acceptable reliability was found for a majority of the assessment items for 15 practitioners who were given 1?h of training. The usability evaluation points to RAMP I being usable for screening for musculoskeletal disorder risk factors, i.e., usable for assessing risks, being usable as a decision base, having clear results and that the time needed for an assessment is acceptable. It is concluded that RAMP I is a usable tool for practitioners.     

Safety assessment of the film boiling chemical vapor infiltration (FB-CVI) process through a system-theoretic accident model and process (STAMP)

Film boiling chemical vapor infiltration (FB-CVI) is considered as one of the fastest process methodologies for manufacturing carbon-carbon (C–C) composite products and possesses various advantages compared to conventional methodologies. However, there are safety concerns associated with this process for large-scale manufacturing, mainly owing to the intrinsic nature of the precursor and the process conditions. Considering the multifunctional interactions of the various systems during the process, a system-theoretic process analysis (STPA)/system theoretic accident model and process (STAMP) model is used to perform a safety analysis of the hazardous states of the FB-CVI process at the system level. As a case study, the FB-CVI process equipment employed for the manufacturing of C–C composites is considered. The safety constraints present in the system are assessed for adequacy through a hazard analysis by STPA/STAMP. The analysis through STPA/STAMP demonstrated the capability to create proactive strategies for the design and realization of process equipment that can be employed to manufacture C–C composite products through the FB-CVI process.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Toward harmonizing prospective effectiveness assessment for road safety: Comparing tools in standard test case simulations

Abstract

Objective: With the overall goal to harmonize prospective effectiveness assessment of active safety systems, the specific objective of this study is to identify and evaluate sources of variation in virtual precrash simulations and to suggest topics for harmonization resulting in increased comparability and thus trustworthiness of virtual simulation-based prospective effectiveness assessment.

Methods: A round-robin assessment of the effectiveness of advanced driver assistance systems was performed using an array of state-of-the-art virtual simulation tools on a set of standard test cases. The results were analyzed to examine reasons for deviations in order to identify and assess aspects that need to be harmonized and standardized. Deviations between results calculated by independent engineering teams using their own tools should be minimized if the research question is precisely formulated regarding input data, models, and postprocessing steps.

Results: Two groups of sources of variations were identified; one group (mostly related to the implementation of the system under test) can be eliminated by using a more accurately formulated research question, whereas the other group highlights further harmonization needs because it addresses specific differences in simulation tool setups. Time-to-collision calculations, vehicle dynamics, especially braking behavior, and hit-point position specification were found to be the main sources of variation.

Conclusions: The study identified variations that can arise from the use of different simulation setups in assessment of the effectiveness of active safety systems. The research presented is a first of its kind and provides significant input to the overall goal of harmonization by identifying specific items for standardization. Future activities aim at further specification of methods for prospective assessments of the effectiveness of active safety, which will enhance comparability and trustworthiness in this kind of studies and thus contribute to increased traffic safety.     

A proactive process risk assessment approach based on job hazard analysis and resilient engineering

Complex systems often experience a long period of incubation before accidents occur. Therefore, a proactive risk assessment is essential for process safety. The conventional job hazard analysis (JHA) method has been an effective tool to conduct a process risk assessment in the high-risk industrial field. However, the conventional JHA is inadequate for the proactive risk assessment since it is usually conducted during and before one specific operation process. Operations such as startup and maintenance are performed repeatedly on the lifecycle of a plant. Therefore, the risk reduction measures for the industrial process should include not only preventive actions obtained from the conventional JHA but also recovery ones. Resilience engineering (RE) has proven to be helpful for the recovery analysis of a complex system. The objective of this paper is to propose a proactive and comprehensive process risk assessment approach based on JHA and RE. The mechanism of applying RE to address operation process risk is illustrated. The integrated approach can provide guidelines to establish proactive risk reduction measures as well as maintain a low-risk level. Finally, a gas transmission startup process risk assessment case is presented to demonstrate its applicability.     

河口切变锋引起的滩槽泥沙交换效应

切变锋是河口湾锋系中最为常见和最易观察到的锋面类型。本文对长江口的切变锋进行现场观察和滩，槽同步水文资料分析，简述了长江口切变锋发生的部分和基本特性，提出了切变锋引起的滩，槽泥沙呈现螺旋形交换形式等论点。     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability