Application Of Risk Assessment Research Articles

A fire risk assessment system and application for process industry using fuzzy Petri net and HAZID method

The safety risk assessment of process industries can determine the degree of safety risk and remind or warn safety management personnel to take corresponding measures according to the probability of accidents. In this paper, hazard identification (HAZID) method is combined with fuzzy Petri net to construct a hybrid safety assessment system. Firstly, the fire risk factors of HAZID are determined according to the fire statistics data. By dividing the whole industrial process into four stages, the complex hazard sources in the factory are investigated item by item, thus the fuzzy Petri net of real-time risk assessment is constructed. Taking an acetic acid enterprise as a case, this paper introduces how to construct such a risk assessment system in detail, and the system can dynamically predict the risk with changes in process conditions. This also demonstrates the feasibility of this method, which can be used as a reference for related research.

P25-04: Case Studies Illustrating Tiered Refinement of Consumer Exposure to Cosmetic Ingredients for Application in Risk Assessment

P25-04: Case Studies Illustrating Tiered Refinement of Consumer Exposure to Cosmetic Ingredients for Application in Risk Assessment

Risk Assessment in Periodontal Disease – A New Way of Predicting the Periodontal Disease Outcome

The present review aims to assess the clinical significance of the risk assessment tool, in periodontal diagnosis.Periodontal disease is a multi-factorial disease. It has been proven that certain risk factors are associated with diseasedevelopment. In addition, host-microbiome interaction is associated with periodontal disease. So, treating a disease requires adifferent approach. Risk assessment in periodontics estimates the risk of susceptibility to periodontal disease. It consists ofassessing the level of bleeding on probing, pocket depth, tooth loss, radiographic bone loss, loss of attachment, patient age,systemic condition of the patients, and finally, an evaluation of environmental and behavioral factors. All these factors areevaluated together. This helps determine the patient's risk for periodontal disease and its progression for an individual approach.Evaluating the likelihood of developing periodontal disease can play a vital role in clinical decision-making by providing valuableinformation to design appropriate treatment plans. However, controlling risk factors should become a more explicit focus inmany dental practices. This article reviews the application of risk assessment in clinical setup and periodontal diseasemanagement to the population and groups at risk of developing periodontal disease. This review addresses gaps in previousarticles by comprehensively covering all aspects of periodontal disease. Most of the review studies focus on epidemiology andmanagement of the disease, so by proper awareness about a disease and its management, the burden of the disease and its illeffects can be reduced. Based on the article's findings, implementing healthy dietary habits, making lifestyle changes, and managingrisk factors can effectively control the increasing incidence of periodontal disease and reduce the likelihood of developing it.

Risk Assessment Method and Application of Urban River Ecological Governance Project Based on Cloud Model Improvement

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.

Application of internal fire probabilistic risk assessment in design optimization for marine SMR

Abstract Small Modular Reactors (SMR) have attracted more and more attention. It can provide economic, stable and clean power for remote areas. It is also a reliable solution in satisfying the power supply of small and medium grids, as well as comprehensive energy supply including heat, electricity, water and steam, and distributed energy supply. Internal Fire Probabilistic Risk Assessment (PRA) is a system analysis method of assessing fire risk for a nuclear power plant, which plays a more and more important role. It can provide an overall understanding of the internal fire risk for SMR. Corresponding design optimization suggestions can be obtained through further analysis of the fire areas with major fire risk, which can help reduce the risk of internal fire and improve the safety of reactor. The paper introduces the basic information of marine SMR and development of internal fire PRA. Then the internal fire risk for marine SMR have been analyzed by this method. The results show that marine SMR have high safety with a Core Damage Frequency (CDF) for internal fire risk of less than 1.0 × 10−7 per year.

Are Indicator Microorganisms Predictive of Pathogens in Water?

The microbiological quality assessment of drinking water (DW) and drinking water sources (DWSs) is based on the detection of indicator microorganisms (IMs). However, the relationship between IMs and pathogens has been questioned, as pathogens have been detected even in the absence of IMs, and vice versa. Therefore, the aim of this review was to evaluate the reliability of IMs by analysing the correlation between the presence of IMs and pathogens in water. This review focused on studies that reported statistical analyses of the relationship between traditional and alternative IMs and enteric pathogens in DWSs (groundwater, surface water, and rainwater) and in DW. Additionally, the main DW guidelines and regulations, along with a focus on the application of Quantitative Microbial Risk Assessment (QMRA), were also reported. The overall analysis of publications revealed a controversial correlation, characterised by high spatiotemporal variability, indicating the impossibility of identifying a reliable IM for any specific pathogen or water type. The association was also influenced by numerous factors, such as intrinsic characteristics of microorganisms, seasonal variations, sample number, water sample volume, and the detection method used. In conclusion, the detection of IMs should be considered complementary to, rather than a substitute for, the detection of pathogens.

Connection number structure-based information diffusion model for agricultural drought disaster risk assessment: A case study in Jianghuai watershed area

The information diffusion model is widely used in natural disaster risk assessment because of its operationalization, low data requirements and clear significance of the evaluation results. However, the commonly used normal information diffusion model is based on an average distance assumption, and the diffusion widow with h is directly affected by sample size and extreme values, especially when the sample size is more than 11, which may lead to unstable results of normal diffusion, with typical uncertainty. Considering the influence of the whole samples on the diffusion points, incorporating the connection number method, a connection number structure-based information diffusion model was proposed, and also a relative connection number method is proposed to calculate the connection number, which was applied to the risk assessment of drought disasters in Jianghuai watershed area. The results show that the connection number structure-based information diffusion model reduces the direct influence of sample extremes and sample size, eliminates the constraint of the average distance assumption in the traditional model, and performs more consistently with increasing sample size for risk assessment. And the relative connection number method can contain the traditional connection number expression and offers a wider application. A study of drought risk in the Jianghuai watershed shows that the indices of agriculture drought-suffered, drought-affected and drought-damaged fluctuated greatly, but the trends were generally consistent with each other from 1990 to 2020. It is more likely to suffer from drought in the area, but the disaster rate after drought tends to decrease over time. With the increase in drought intensity, the disaster risk will decrease significantly compared to the drought risk. The connection number structure-based information diffusion model has no two-point proximity principle and the average distance assumption, with better stability in the disaster risk assessment for different samples size compared with the traditional model, which will have more extensive application in risk assessment.

Supply Chain Risk Mitigation for Logistics Service Companies

The increasing use of expedition services due to the Covid-19 pandemic has also increased various types of risks in companies. This study discusses solutions to the complexity of supply chain management in the expedition services industry due to pandemic Covid-19. This study aims to analyze the risk of security management systems based on every activity in the supply chain of an expedition company. The method used in this study is the matrix risk assessment to determine the risk ranking by multiplying the possibilities and consequence values. Descriptive analysis approaches and in-depth interviews are needed to identify the types of risks in the supply chain of PT.X. The application of risk assessment consists of five stages: development mapping of supply chains, risk identification, risk assessment, risk response development, and risk response control. The results of this study indicate that three types of extreme risks need to be handled in priorities by providing proposed mitigation, namely bad weather, road accidents, and damaged items. Risk mitigation strategies are carried out to prevent the types of extreme risks in the company.

Application of hydraulic modelling and quantitative microbial risk assessment (QMRA) for cloudburst management in cities with combined sewer systems.

Urban cloudburst management may include the intentional temporary storage of flood water in green recreational areas. In cities with combined sewers, this will expose the population visiting the area to sewage and increase the risk of diarrhoeal disease. We present a unique approach to estimate the risk of diarrhoeal disease after urban flooding. The exposure scenario was: rainwater mixed with sewage flows into a park; sewage with pathogens deposit on the grass; after discharge, a baby plays on the grass and is exposed to the pathogens in the deposited sewage by hand-to-mouth transfer. The work included modelling the transport of sewage into four parks intended to be flooded during future cloudbursts. A flood simulation experiment was conducted to estimate the deposition of pathogens from sewage to grass and transfer from grass to hand. Hand-to-mouth transfer, based on literature values, was used to estimate the ingested dose of pathogens. The probability of illness was estimated by QMRA. The estimated average probability of illness varied between 0.03 and 17%. If the probability of illness is considered unacceptable, the cloudburst plans should be changed, or interventions, e.g. informing the public about the risk or restricting access to the flooded area, should be implemented.

Elemental Profile and Health Risk of Fruška Gora Wines.

The elemental composition of wine is influenced by endogenous sources and interventions from winemakers. The ICP-MS analysis of Fruška Gora wines (113) from vintages spanning across a decade (2011-2020), produced by 30 wineries and representing 18 autochthonous and international wine varieties, allowed a comprehensive insight into their elemental composition. Based on the mean concentrations of 23 investigated elements, B, Fe, and Mn, which were determined in mg per L of wine regardless of its colour or origin, were the most abundant. Red and white wines showed significant concentration differences in the case of B, Mn, and Sr (higher in red) as well as Be, Al, V, As, Mo, and Pb (higher in white). The elements of the highest toxicological concern were found in all (Pb and As) or almost all of the samples (Cd and Hg). Pb levels (maximum 47.1, 61.6, and 73.2 μg/L in red, rose, and white, respectively) were well below the legal limit. The applied risk assessment approaches (hazard quotient and index, margin of exposure) revealed no health concerns associated with consumption of Fruška Gora wines, except for a slightly increased lifetime cancer risk in the case of high wine consumption, and thus supported the promotion of Fruška Gora wines in the highly competitive international market.

Experimental exposure assessment for in vitro cell-based bioassays in 96- and 384-well plates.

In vitro cell-based bioassays have great potential for applications in the human health risk assessment of chemicals. The quantification of freely dissolved concentrations (C free) in in vitro assays is essential to generate reliable data for in vitro-to-in vivo extrapolation. Existing methods for the quantification of C free are limited to low-throughput microtiter plates. The present study is a proof of principle for the applicability of a solid-phase microextraction (SPME) method for the determination of C free in the peroxisome proliferator-activated receptor gamma (PPARγ) bioassay run in 384-well plates with 80µL medium per well. The effect concentrations obtained from 384-well plates were compared with those obtained from 96-well plates in a previous study. Nominal effect concentrations obtained using 96- and 384-well plates agreed with each other within a factor of three, and freely dissolved effect concentrations agreed within a factor of 6.5. The good degree of agreement in the results from both plate formats proves the general applicability of the SPME method for the determination of C free for bioassays in 384-well plates, making the present study a first step toward exposure assessment in high-throughput bioassays.

Novel inflammatory biomarkers associated with stroke severity: results from a cross-sectional stroke cohort study

BackgroundStroke is a leading cause of mortality and disability worldwide and its occurrence is expected to increase in the future. Blood biomarkers have proven their usefulness in identification and monitoring of the disease. Stroke severity is a major factor for estimation of prognosis and risk of recurrent events, but knowledge on respective blood biomarkers is still scarce. Stroke pathophysiology comprises a multitude of ischemia-induced inflammatory and immune mediated responses. Therefore, the assessment of an immune-related panel in correlation with stroke severity seems promising.MethodsIn the present cross-sectional evaluation, a set of 92 blood biomarkers of a standardized immune panel were gathered (median 4.6 days after admission) and related to stroke severity measures, assessed at hospital admission of acute stroke patients. Multivariable logistic regression models were used to determine associations between biomarkers and modified Rankin Scale (mRS), linear regression models were used for associations with National Institute of Health Stroke Scale.Results415 patients (mean age 69 years; 41% female) were included for biomarker analysis. C-type lectin domain family 4 member G (CLEC4G; OR = 2.89, 95% CI [1.49; 5.59], padj = 0.026, Cytoskeleton-associated protein 4 (CKAP4; OR = 2.38, 95% CI [1.43; 3.98], padj = 0.019), and Interleukin-6 (IL-6) (IL6; OR = 1.97, 95% CI [1.49; 2.62], padj < 0.001) were positively associated with stroke severity measured by mRS, while Lymphocyte antigen 75 (LY75; OR = 0.37, 95% CI [0.19; 0.73], padj = 0.049) and Integrin alpha-11 (ITGA11 OR = 0.24, 95% CI [0.14, 0.40] padj < 0.001) were inversely associated. When investigating the relationships with the NIHSS, IL-6 (β = 0.23, 95% CI [0.12, 0.33] padj = 0.001) and ITGA11 (β = − 0.60, 95% CI [− 0.83, − 0.37] padj < 0.001) were significantly associated.ConclusionsHigher relative concentrations of plasma CLEC4G, CKAP4, and IL-6 were associated with higher stroke severity, whereas LY75 and ITGA11 showed an inverse association. Future research might show a possible use as therapeutic targets and application in individual risk assessments.

Multi-criteria decision analysis in assessing watershed scale pollution risk: a review of combined approaches and applications

Decision-making tools have become a prominent methodology in watershed management for many years due to the complexity of environmental systems and requirement for multi-disciplinary expertise. Multi-Criteria Decision Analysis (MCDA) is a systematic methodology, which combines hierarchical structures of a problem and priorities for the alternatives in many fields. This study reviews MCDA applications in pollution risk assessment in the abiotic environments of watersheds for multi-pollutants. Over 80 papers published between 2000 and 2021 are identified in three categories of the Web of Science Core Collection database: “Environmental Sciences”, “Environmental Studies”, and “Water Resources”. The publications are further classified according to different environmental compartments: surface water, groundwater, and soil to investigate MCDA applications in these matrices. Finally, the distribution of the publications according to contaminants and MCDA methods used are also examined. The results reveal that the number of the studies focusing on pollution risk assessment within watersheds has been significantly increasing, especially over the last decade. However, there are still limited MCDA applications linking environmental compartments. Despite several MCDA studies focusing on the vulnerability of watersheds to multiple pollutants, studies related with emerging pollutants are scarce. Moreover, compared to non-point source pollution, studies adopting MCDA to investigate pollutant concentrations coming from point sources are relatively few. According to the overall distributions of MCDA methods, Analytic Hierarchy Process, a commonly found method in the literature that adopts a technique of pairwise comparison to prioritize criteria of prominence, dominates 34% of the publications.

Innovative tools and methods for toxicity testing within PARC work package 5 on hazard assessment.

New approach methodologies (NAMs) have the potential to become a major component of regulatory risk assessment, however, their actual implementation is challenging. The European Partnership for the Assessment of Risks from Chemicals (PARC) was designed to address many of the challenges that exist for the development and implementation of NAMs in modern chemical risk assessment. PARC's proximity to national and European regulatory agencies is envisioned to ensure that all the research and innovation projects that are initiated within PARC agree with actual regulatory needs. One of the main aims of PARC is to develop innovative methodologies that will directly aid chemical hazard identification, risk assessment, and regulation/policy. This will facilitate the development of NAMs for use in risk assessment, as well as the transition from an endpoint-based animal testing strategy to a more mechanistic-based NAMs testing strategy, as foreseen by the Tox21 and the EU Chemical's Strategy for Sustainability. This work falls under work package 5 (WP5) of the PARC initiative. There are three different tasks within WP5, and this paper is a general overview of the five main projects in the Task 5.2 'Innovative Tools and methods for Toxicity Testing,' with a focus on Human Health. This task will bridge essential regulatory data gaps pertaining to the assessment of toxicological prioritized endpoints such as non-genotoxic carcinogenicity, immunotoxicity, endocrine disruption (mainly thyroid), metabolic disruption, and (developmental and adult) neurotoxicity, thereby leveraging OECD's and PARC's AOP frameworks. This is intended to provide regulatory risk assessors and industry stakeholders with relevant, affordable and reliable assessment tools that will ultimately contribute to the application of next-generation risk assessment (NGRA) in Europe and worldwide.

Soil Moisture Retrieval in Bare Agricultural Areas Using Sentinel-1 Images

Soil moisture maps are essential for hydrological, agricultural and risk assessment applications. To best meet these requirements, it is essential to develop soil moisture products at high spatial resolution, which is now made possible using the free Sentinel-1 (S1) SAR (Synthetic Aperture Radar) data. Some soil moisture retrieval techniques using S1 data relied on the use of a priori weather information in order to increase the precision of soil moisture estimates, which required access to a weather-forecasting framework. This paper presents an improved and fully autonomous solution for high-resolution soil moisture mapping in bare agricultural areas. The proposed solution derives a priori weather information directly from the original Sentinel images, thus bypassing the need for a weather forecasting framework. For soil moisture estimation, the neural network technique was implemented to ensure the optimum integration of radar information. The neural networks were trained using synthetic data generated by the modified Integral Equation Model (IEM) model and validated on real data from two study sites in France and Tunisia. The main findings showed that the use of a radar signal averaged over grids of a few km2 in addition to radar signal at plot scale instead of a priori weather information provides good soil moisture estimations. The accuracy is even slightly better compared to the accuracy obtained using a priori weather information.

FEDERATED LEARNING TECHNIQUES APPLIED TO CREDIT RISK MANAGEMENT: A SYSTEMATIC LITERATURE REVIEW

The control of credit risk is a crucial task for financial institutions. Various subjective and quantitative indicators are used to forecast credit risks. Machine learning technology uses customer data to create accurate predictive models due to current AI/ML breakthroughs. Data from many institutions can be used to improve models. Nevertheless, exchanging data across numerous organizations incurs significant communication costs and compromises the privacy of client data. Credit institutions and financing solution providers benefit from expanded data sources via the arrival of technological developments (AI and Machine Learning, Deep learning). The possibilities to increase customer knowledge and improve their credit risk assessment and management system are increased. This research study explores federated learning techniques for credit risk management. The literature review covers research papers published between 2018 and 2022 and presents different federated learning techniques and their applications in credit risk assessment. The study shows that the choice of technique depends on the application’s specific requirements.

An accurate and efficient method for simultaneous determination of 16 trichothecenes in maize and wheat by UHPLC-Q-Orbitrap-HRMS combined one-step pretreatment with a novel isotope multipoint calibration strategy

Trichothecenes are mycotoxins generated by Fusarium species that are toxic to humans and animals and frequently contaminate cereals. Herein, we present an UHPLC-Q-Orbitrap-HRMS method using one-step pretreatment for simultaneous detection of 16 type A and B trichothecenes in maize and wheat. A calibration strategy based on natural isotopic distribution was adopted and validated to replace traditional time-consuming and laborious multipoint external calibration curves. Various conditions influencing the method were studied. The recoveries of spiked analytes at three different concentrations ranged from 74.2% to 105.3% and the inter-day relative standard deviations were 0.5–15.6%. The limits of quantitation were 4.4–108.8 μg/kg. Moreover, the current methodology was applied to the evaluation of type A and B trichothecenes present in samples from major wheat production areas in China. This study provides a facile methodology for type A and B trichothecenes analysis and presents promising applications for exposure risk assessment of trichothecenes in cereals.

The Validity of Violence Risk Assessment in Young Adults: A Comparative Study of Juvenile and Adult Risk Assessment Tools

Few studies have addressed the application of violence risk assessment for individuals transitioning from youth to adulthood. For 202 young adults released from Dutch juvenile justice institutions this study investigated the predictive validity and potential disparities in impact of juvenile risk assessment tools (i.e., SAVRY [Structured Assessment of Violence Risk in Youth], and SAPROF-YV [Structured Assessment of Protective Factors for violence risk-Youth Version]), and comparable adult risk assessment tools (i.e., HCR-20V3 [Historical Clinical Risk management-20 Version 3], and SAPROF [Structured Assessment of Protective Factors for violence risk]). Assessments with juvenile and adult risk assessment tools yielded similar predictive validity for violent and non-violent recidivism. Risk and protective factors related to treatability, parents, community participation, resilience, and personality showed individual predictive validity. These findings offer flexibility when applying risk assessment in clinical practice. The choice between youth and adult assessment tools should be made considering the individual’s developmental stage.

Explore the Dosimetric Relationship between the Intake of Chemical Contaminants and Their Occurrence in Blood and Urine.

The dosimetric relationship between the human intake dose of a chemical contaminant (an "external dose") and its concentrations in bodily fluids such as blood and urine (related to an "internal dose"), often characterized by a dose-to-concentration ratio, has critical applications in exposure science, toxicology, and risk assessment, especially in the "new approach methods" era. However, there is a lack of a mechanistic, systematic understanding of how such a dosimetric relationship depends on fundamental chemical properties, such as partition coefficients and biotransformation half-lives. Here, we investigate this issue using a well-evaluated toxicokinetic model, which links external and internal doses by quantifying the absorption and elimination of chemicals. Results are visualized in a series of chemical partitioning space plots, whereby a chemical's dose-to-concentration ratio can be approximately predicted based on its partitioning between air, water, and octanol phases. Our results indicate that when taken in equal doses, chemicals with low volatility and moderate to high hydrophobicity exhibit the highest concentrations in the blood, and chemicals undergoing significant biotransformation tend to exhibit lower concentrations in comparison to their counterparts undergoing negligible biotransformation but possessing similar partitioning properties. Chemicals with high hydrophilicity have the highest concentrations in urine. Such revealed property dependence is similar for both adults and children and for individuals with normal body weights and with obesity. Overall, insights gained from this study are important in predicting blood and urinary concentrations from exposure information and in determining the exposure rate that produces the blood or urinary concentrations observed in biomonitoring studies.

Variations of different PAH fractions and bacterial communities during the biological self-purification in the soil vertical profile

Wild PAH-contaminated sites struggle to provide continuous and stable monitoring, resulting in the potential risks of contaminated soil utilization could not be evaluated effectively. This work provided a 9-months laboratory simulation which was close to the natural ecological process. These results believed that PAH-degrading bacteria (PDB) preferred to degrade organic extracted PAH (PAH_OS) and fresh bound-PAH (79.36–99.97%). The formation and migration efficiency of PAH binding with HA humic acid (HA) (PAH_HA) was lower than that of PAH binding with fulvic acid (FA) and humin (HM) (PAH_FA and PAH_HM), leading to PAH_HA had more persistent retention and influenced bacterial communities in shallow soils. Besides, phylum Proteobacteria gradually dominated the bacterial community and decreased 12.05–20.48% diversity at all depths during the biological self-purification process. Although the effect of this process enhanced the abundance of 28 genes 16 s rRNA and three PAH-degrading genes (PDGs) by 5.91–2047.34 times (phe, nahAc and nidA), the top 30 genera maintained their ecological characteristics. This study provided insights into the important influencing factor and mechanism of the biological self-purification processes and discerned the linkages between bacterial communities and environmental variables in the vertical profile, which is important to the isolation and application of PDB and ecological risk assessment.