Quantitative Risk Assessment System Research Articles

A Novel Global Probabilistic Fuzzy System for Occupa-tional Risk Assessment (GPFSORA)

Occupational risk assessment is the process of estimating the magnitude of risks that cannot be avoided. Then, the corresponding assessment is carried out, using comparative tables with different evaluation methods. Current risk assessment techniques enable the individual assessment of each potential risk, but there is no method to globally assess potential risks in an organization. The motivation of this research was to develop an objective and quantitative risk assessment system through a diffuse probabilistic model integrating stochastic and non-stochastic uncertainty. To this effect, an empirical collective record was used, whose attribute of interest was the occurrence of different accident types over a period of 52 weeks. Here, each of the collectives represented a linguistic input variable. In the probabilistic fuzzification stage, the frequentist probability of the occurrence of accidents was determined. One of our most important contributions to probabilistic fuzzy systems lies in our classification of language labels based on the linguistic projection of frequentist probabilities via a projection membership function determined by experts. The use of the total probability theorem in the implication stage is also proposed. The output of the system determines the type of risk, its evaluation, and the probability of its occurrence, vital factors to be considered in prevention work. The system’s stages are explicitly described and applied to real data corresponding to construction materials distribution company. One of the relevant conclusions of this research is that the integration of stochastic and imprecise uncertainty allows for a more reliable risk assessment system.

Construction and application of a quantitative risk assessment system for potential pathogen of introduced marine animals

Biological invasion is considered to be an important factor in destroying the biodiversity of global aquatic ecosystems. Invasive alien species (IAS) not only directly affect the development of agriculture, animal husbandry and fisheries worldwide, but also the potential pathogens carried by IAS may cause even greater damage to aquaculture development, human health, and the ecological environment. Therefore, risk assessment of potential pathogens that may be carried by IAS is particularly important. In this study, we focused on marine ecosystems and based our analysis on the characteristics of marine ecosystems. We analyzed the characteristics of commonly introduced marine animals and their pathogens worldwide and constructed a potential pathogen risk assessment system for introduced marine animals with five primary assessment indicators, 14 secondary assessment indicators and 55 tertiary assessment indicators based on the analytic hierarchy process (AHP). Concurrently, this assessment system would be used to conduct quantitative risk assessments on six representative pathogens introduced by alien marine animals (widely distributed and including bacteria, fungi, viruses, parasitic protozoa, etc.) in the People's Republic of China. The quantitative potential pathogen risk assessment of the introduced marine animals via the risk assessment model system can efficiently and accurately grasp the risks of unknown pathogens that may be introduced, providing a solid theoretical basis for a scientific introduction of this topic and providing a practical and feasible decision-making basis for preventing the transmission of pathogens from introduced marine animals and for the protection of marine ecological environments.

Reactive oxygen species metabolism-based prediction model and drug for patients with recurrent glioblastoma.

Background: Tumor recurrence is the main cause of poor prognosis of GBM. Finding the characteristics of recurrent GBM that provide early warning of tumor recurrence can provide guidance for the clinical treatment of recurrent GBM.Results: Reactive oxygen species (ROS) biosynthetic processes was significantly elevated in recurrent GBM. The recurrent risk score based on the ROS biosynthetic process was closely related to tumor purity and tumor immune functions. The quantitative risk assessment system could be used to predict the recurrence time of GBM. Gallic acid, a compound with high anti-oxidation activity and low cytotoxicity, was screened as a potential chemotherapy sensitizer for recurrent GBM.Conclusion: The quantitative risk assessment system based on ROS biosynthetic process could be used for early warning of GBM recurrence. Combination of low-dose gallic acid and temozolomide could improve therapeutic outcomes in recurrent GBM.Methods: A total of 663 primary and recurrent GBM samples with clinical and microarray data were included in this study. GSVA, LASSO-COX, and Kaplan-Meier survive curve were performed to construct and verify a quantitative risk assessment system for GBM recurrence prediction. An antioxidant capacity test and cell viability test were used to discover potential drugs for recurrent GBM.

A quantitative risk-assessment system (QR-AS) evaluating operation safety of Organic Rankine Cycle using flammable mixture working fluid

Mixture of hydrocarbon and carbon dioxide shows excellent cycle performance in Organic Rankine Cycle (ORC) used for engine waste heat recovery, but the unavoidable leakage in practical application is a threat for safety due to its flammability. In this work, a quantitative risk assessment system (QR-AS) is established aiming at providing a general method of risk assessment for flammable working fluid leakage. The QR-AS covers three main aspects: analysis of concentration distribution based on CFD simulations, explosive risk assessment based on the TNT equivalent method and risk mitigation based on evaluation results. A typical case of propane/carbon dioxide mixture leaking from ORC is investigated to illustrate the application of QR-AS. According to the assessment results, proper ventilation speed, safe mixture ratio and location of gas-detecting devices have been proposed to guarantee the security in case of leakage. The results revealed that this presented QR-AS was reliable for the practical application and the evaluation results could provide valuable guidance for the design of mitigation measures to improve the safe performance of ORC system.

FDA-iRISK—A Comparative Risk Assessment System for Evaluating and Ranking Food-Hazard Pairs: Case Studies on Microbial Hazards

Stakeholders in the system of food safety, in particular federal agencies, need evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions. FDA-iRISK (referred to here as iRISK), a Web-based quantitative risk assessment system, was developed to meet this need. The modeling tool enables users to assess, compare, and rank the risks posed by multiple food-hazard pairs at all stages of the food supply system, from primary production, through manufacturing and processing, to retail distribution and, ultimately, to the consumer. Using standard data entry templates, built-in mathematical functions, and Monte Carlo simulation techniques, iRISK integrates data and assumptions from seven components: the food, the hazard, the population of consumers, process models describing the introduction and fate of the hazard up to the point of consumption, consumption patterns, dose-response curves, and health effects. Beyond risk ranking, iRISK enables users to estimate and compare the impact of interventions and control measures on public health risk. iRISK provides estimates of the impact of proposed interventions in various ways, including changes in the mean risk of illness and burden of disease metrics, such as losses in disability-adjusted life years. Case studies for Listeria monocytogenes and Salmonella were developed to demonstrate the application of iRISK for the estimation of risks and the impact of interventions for microbial hazards. iRISK was made available to the public at http://irisk.foodrisk.org in October 2012.

Pest risk assessment of Dendroctonus valens, Hyphantria cunea and Apriona swainsoni in Beijing

According to the international methods of pest risk analysis and urban forestry characteristics in Beijing, a quantitative risk assessment system in Beijing for three primary non-indigenous pests was proposed. This system was used to analyze three major non-indigenous species, Dendroctonus valens, Hyphantria cunea, and Apriona swainsoni. The results show that the risks of these three pests in the Beijing area were 2.46, 2.30, and 2.02, which were all highly risky. Based on the result and extensive risk communications, combined with the management experience of the Beijing Forest Protection Station, the authors proposed some effective control measures to prevent the invasion of the three pests into Beijing.

QRAS—the quantitative risk assessment system

This paper presents an overview of QRAS, the Quantitative Risk Assessment System. QRAS is a PC-based software tool for conducting Probabilistic Risk Assessments (PRAs), which was developed to address risk analysis needs held by NASA. QRAS is, however, applicable in a wide range of industries. The philosophy behind the development of QRAS is to bridge communication and skill gaps between managers, engineers, and risk analysts by using representations of the risk model and analysis results that are easy to comprehend by each of those groups. For that purpose, event sequence diagrams (ESD) are being used as a replacement for event trees (ET) to model scenarios, and the quantification of events is possible through a set of quantification models familiar to engineers. An automated common cause failure (CCF) modeling tool further aids the risk modeling. QRAS applies BDD-based algorithms for the accurate and efficient computation of risk results. The paper presents QRAS' modeling and analysis capabilities. The performance of the underlying BDD algorithm is assessed and compared to that of another PRA software tool, using a case study extracted from the International Space Station PRA.

Probabilistic risk analysis for the NASA space shuttle: a brief history and current work

While NASA managers have always relied on risk analysis tools for the development and maintenance of space projects, quantitative and especially probabilistic techniques have been gaining acceptance in recent years. In some cases, the studies have been required, for example, to launch the Galileo spacecraft with plutonium fuel, but these successful applications have helped to demonstrate the benefits of these tools. This paper reviews the history of probabilistic risk analysis (PRA) by NASA for the space shuttle program and discusses the status of the on-going development of the Quantitative Risk Assessment System (QRAS) software that performs PRA. The goal is to have within NASA a tool that can be used when needed to update previous risk estimates and to assess the benefits of possible upgrades to the system.