Risk Ranking Research Articles

Risk Categorization of Foods of Non-Animal Origin Subject to United Kingdom Import Controls.

Significant volumes of foods are traded between countries and this trade brings with it opportunities for foodborne hazards to cross borders and pose a public health risk. The Competent Authority in the importing country has a duty to protect its population from these foodborne hazards. Due to the high volumes of imported food as well as World Trade Organization requirements, border checks need to be prioritized in a risk-based manner. This represents an enormous practical challenge to which efficient solutions are required. This paper describes an approach to risk categorization and ranking of imported Foods of Non-Animal Origin on a food/country of origin/hazard (combination) basis. Combinations were scored using data on product characteristics, hazard characteristics and import volumes, with weightings applied following external consultation. The described approach differs from most others in that it categorizes and ranks microbiological, mycotoxin and chemical hazards with a single approach and on the same scale, allowing for meaningful comparison between the combinations. The output is a risk categorization, a relative risk ranking and a heat map, all of which provide information that can be used alongside other data by risk managers when prioritizing interventions at the border.

Using a Flexible Risk Priority Number Method to Reinforce Abilities of Imprecise Data Assessments of Risk Assessment Problems

Risk priority number (RPN) is the most commonly used failure risk ranking method among all risk assessment methods. However, the traditional RPN method not only cannot handle incomplete information and hesitation information (such as hesitation information between the s5=Low and s6=Moderate) provided by experts, but it also does not consider the objective weights of risk assessment factors. These reasons will lead to biased conclusions, causing decision makers to make wrong judgments. To address the limitations of the traditional RPN technique, the aim of this paper is to propose the flexible RPN assessment method under an uncertain environment. The flexible RPN assessment method is an extension of the traditional RPN technique. The flexible RPN method integrates the traditional RPN method and interval-valued 2-tuple weighted average method, and, simultaneously, considers subjective weights and objective weights. In the numerical verification, this study has adopted the example of stages of treatment planning for proton beam radiation therapy to verify the correctness and validity of the proposed flexible RPN technique. The numerical results show that the proposed flexible RPN technique not only handles the hesitation and incomplete information provided by experts but also considers the subjective and objective weights of risk assessment factors, providing more reasonable ranking results in the risk analysis.

Perspectives of physicians on risk factors for patient aggression and violence against physicians in Chinese hospitals: a Q-methodology study

BackgroundThe prevalence of patient (and their relatives/friends) aggression and violence against healthcare professionals in general, and physicians in particular, is a recognized problem worldwide. While numerous risk factors for such aggression and violence from patients (and their relatives/friends) have been identified, little is known about which risk factors are perceived as relatively most important in a specific context and among a particular group, and about the potentially differing views on the relative importance. This lack of insight prohibits preventive measures being tailored to address the main risk factors.MethodWe conducted a Q-methodology study to investigate physicians’ perspectives on risk factors for aggression and violence from patients (and their relatives/friends) against physicians in Chinese hospitals. A total of 33 physicians from public Chinese hospitals participated in this study and were asked to rank 30 risk factors according to their importance in triggering violent incidents. In addition, respondents were asked to explain their ranking of most and least important risk factors.ResultsBy employing a by-person factor analysis, four distinct perspectives on the importance of risk factors were identified: (1) unmet expectations of treatment and lack of resources; (2) perpetrator’s educational background and personal characteristics; (3) distrust and limited protection measures; and (4) perpetrator’s emotional well-being and poor interaction. There was a consensus across perspectives that failure to meet perpetrator’s expectations is one of the most important risk factors and that physician’s gender is one of the least important risk factors in the occurrence of patient (and their relatives/friends) aggression and violence against physicians in Chinese hospitals.ConclusionsThis study has identified four distinct perspectives held among physicians on the risk factors for patient aggression and violence against physicians in Chinese hospitals. These insights enable the development and prioritization of targeted measures to address specific risk factors according to the dominant views among physicians.

A spatial triage of at-risk conifer forests to support seed collection efforts and sustainable forestry.

At-risk conifer stands growing in hot, arid conditions at low elevations may contain the most climate change-adapted seeds needed for sustainable forestry. This study used a triage framework to identify high-priority survey areas for Pinus ponderosa (Pipo) within a large region, by intersecting an updated range map with a map of seed zones and elevation bands (SZEBs). The framework assesses place-based climate change and potential wildfire risks by rank-order across 740 potential collection units. The study separately combined three operational measures of cone priority SEZBs from a government reforestation nursery in California - current inventory, target seed supply levels, and areas with high seed demand - to create operational SZEB priority rankings. Combining the risk and operational SZEB rankings permitted an overall priority ranking of survey areas, and road extents within each SZEB's Pipo area indicate accessibility. Pipo's California range covers 62,456.9km2, which intersects 740 of 1212 total SZEBs. Of these, 43 have high climate exposure under baseline (1980-2010) conditions, and 139 more become highly exposed by the end of the century. Of these 182 highly climate-exposed SZEBs, our index of high-intensity fire risk indicates 42 were also at high risk of stand replacing fire at the beginning of the 2023 fire season. Of these 42, only 4 are currently represented in the seed lot inventory. In contrast, the top 73 operational priority SZEBs all have relatively low risk rankings. Integrating models of landscape risk with operational seed collection priorities can direct collection efforts to high-risk stands before those are lost, and improve spatial coverage in seed bank inventories. The triage framework can provide spatial guidance for cone crop surveying efforts, and has the potential to improve forest nursery and field management. Triage elements can be updated or added to provide more comprehensive tracking over time. For example, wildfire perimeters and seed inventories could be updated annually and fuels reduction treatments, cone crop survey routes, annual assessments of cone crop condition, and additional seedbanks (e.g. for the USDA Forest Service) could be included.

Risk analysis is a dynamic process: has the risk ranking of the non-native freshwater fishes in England and Wales changed over the past 15 years

Risk analysis is a dynamic process: has the risk ranking of the non-native freshwater fishes in England and Wales changed over the past 15 years

Enhanced risk assessment framework integrating distribution dynamics, genetically inferred populations, and morphological traits of Diploderma lizards.

Assessing the threat status of species in response to global change is critical for biodiversity monitoring and conservation efforts. However, current frameworks, even the IUCN Red List, often neglect critical factors such as genetic diversity and the impacts of climate and land-use changes, hindering effective conservation planning. To address these limitations, we developed an enhanced extinction risk assessment framework using Diploderma lizards as a model. This framework incorporates long-term field surveys, environmental data, and land-use information to predict distributional changes for 10 recently described Diploderma species on the Qinghai-Xizang Plateau, which hold ecological significance but remain underassessed in conservation assessment. By integrating the distribution data and genetically inferred effective population sizes ( Ne), we conducted scenario analyses and used a rank-sum approach to calculate Risk ranking scores (RRS) for each species. This approach revealed significant discrepancies with the IUCN Red List assessments. Notably, D. yangi and D. qilin were identified as facing the highest extinction risk. Furthermore, D. vela, D. batangense, D. flaviceps, D. dymondi, D. yulongense, and D. laeviventre, currently classified as "Least Concern", were found to warrant reclassification as "Vulnerable" due to considerable threat from projected range contractions. Exploring the relationship between morphology and RRS revealed that traits such as snout-vent length and relative tail length could serve as potential predictors of extinction risk, offering preliminary metrics for assessing species vulnerability when comprehensive data are unavailable. This study enhances the precision of extinction risk assessment frameworks and demonstrates their capacity to refine and update risk assessments, especially for lesser-known taxa.

Medical Waste Management Based on an Interval-Valued Fermatean Fuzzy Decision-Making Method

Due to its infectious and hazardous nature, medical waste poses risks to people and the environment. For patients to receive medical attention and recover in a safe environment, waste must be disposed of correctly. Improper medical waste disposal poses a severe risk to society, which can accelerate the development of various pandemics and epidemics. In this case, medical waste disposal should be handled appropriately. This study presents an integrated multi-criteria decision-making method consisting of entropy, the Pivot Pairwise Relative Criteria Importance Assessment, and Measurement of Alternatives and Ranking according to Compromise Solution methods based on an interval-valued Fermatean fuzzy set. This method can guarantee high safety and security for health practitioners and society through effective modeling and ranking of risks associated with medical waste disposal. Five alternatives and eight criteria were determined. According to the results, incineration is the most suitable disposal process for medical waste. The performance was then assessed and validated using a sensitivity analysis. A sensitivity analysis has been conducted across the range of values for the $\alpha$ parameter. It was examined whether the rankings of the alternatives changed when the $\alpha$ values in the integrated weight determination model for sensitivity analysis were altered. When the different $\alpha$ values were reviewed with the selected $\alpha$ value in the application example, it was seen that incineration was the first alternative. In addition, the study's findings and their consequences for lawmakers, businesspeople, technologists, and practitioners are examined. In the future, these stakeholders can concentrate on these deficiencies and provide long-term remedies.

Fuzzy Failure Modes, Effect and Criticality Analysis on Electromechanical Actuators

The electromechanical servo is the preferred aviation servo actuator system now. EMA (electromechanical actuators), especially EMA of airplanes, will inevitably occur a variety of faults. FMECA (Failure Modes, Effect and Criticality Analysis) is commonly used to analyze the failure mode of the product. However, traditional FMECA is easily affected by subjective factors, and previous studies on FMECA have not focused on the EMA of airplanes. Therefore, this paper was carried out to provide a method of EMA failure modes analysis to find out the most vulnerable part of EMA. Firstly, we analyzed the PMSM using traditional FMECA to obtain a preliminary result for further examination. Then, we used fuzzy comprehensive evaluation to quantify qualitative evaluation indicators and build a fuzzy FMECA model based on fuzzy comprehensive evaluation, which can directly obtain the risk ranking of each failure mode. At the same time, the model was used on PMSM, which is an important part of EMA, to give an example of using this method. Finally, two results were compared to verify the accuracy of the improvement method. The main contribution of the article was to propose a model that can rank the risk levels of all components in EMA on airplanes based on fuzzy FMECA.

Risk Assessment of Small-Diameter Shield Construction in a Deep Drainage Tunnel Based on an ISM–CRITIC–Cloud Model

The deep drainage tunnel project is an important measure to alleviate urban waterlogging. The construction of a deep drainage tunnel is a complicated process, involving many influencing factors, and there are correlations among these influencing factors, so the risk assessment is difficult. In this study, the ISM method, CRITIC method and cloud model are combined to build a risk assessment model for the small-diameter shield construction of a deep drainage tunnel. Firstly, the risk index system of small-diameter shield construction in a deep drainage tunnel is put forward. Secondly, the ISM method is used to divide the risk indicators and extract the key risk factors. Then, these key risk factors are weighted with the CRITIC method, and the cloud model is used to evaluate the construction risk of a small-diameter shield of a deep drainage tunnel. Finally, the feasibility and accuracy of the proposed method are verified by a practical case. It was found that the risk assessment method proposed in this study can not only effectively assess the level of security risk, but also identify the key risk factors and rank the importance of these factors. The results of this study can reduce the interference items and workload of risk assessment to a certain extent, and help provide managers with an accurate decision-making basis.

Volcanic risk ranking and regional mapping of the Central Volcanic Zone of the Andes

Abstract. The Central Volcanic Zone of the Andes (CVZA) extends from southern Peru, through the Altiplano of Bolivia, to the Puna of northern Chile and Argentina, between latitudes 14–28° S of the Andean cordillera, with altitudes rising up to more than 4000 m above sea level. Given the large number of active volcanoes in this area, which are often located close to both urban areas and critical infrastructure, prioritization of volcanic risk reduction strategies is crucial. The identification of hazardous active volcanoes is challenging due to the limited accessibility, the scarce historical record, and the difficulty in identifying relative or absolute ages due to the extreme arid climate. Here, we identify the highest-risk volcanoes combining complementary strategies: (i) a regional mapping based on volcanic hazard parameters and surrounding density of elements at risk and (ii) the application of the recently developed volcanic risk ranking (VRR) methodology that integrates hazard, exposure, and vulnerability as factors that increase risk and resilience as a factor that reduces risk. We identified 59 active and potentially active volcanoes that not only include the volcanic centres with the most intense and frequent volcanic eruptions (e.g. the El Misti and Ubinas volcanoes, Peru) but also the highest density of exposed elements (e.g. the cities of Arequipa and Moquegua, Peru). VRR was carried out for 19 out of the 59 volcanoes, active within the last 1000 years or with unrest signs, highlighting those with the highest potential impact (i.e. Cerro Blanco in Argentina and Yucamane, Huaynaputina, Tutupaca, and Ticsani in Peru) and requiring risk mitigation actions to improve the capacity to face or overcome a disaster (e.g. volcanic hazard and risk/impact assessments, monitoring systems, educational activities, and implementation of early warning systems).

Risk ranking of mycotoxins in plant-based meat and dairy alternatives under protein transition scenarios

While reducing the consumption of animal-source foods is recommended for planetary and human health, potential emerging food safety risks associated with the transition to dietary patterns featuring plant-based meat (PBMA) and dairy alternatives (PBDA) remain unexplored. We assessed the exposure to mycotoxins and ranked the associated health risks related to the consumption of PBMA and PBDA. We simulated diets by replacing animal-source proteins with their plant-based alternatives. A risk ratio method, based on the hazard quotient (HQ), was applied to rank mycotoxin-related food safety risks. An aggregated dataset containing contamination data of 45 mycotoxins distributed over 182 PBDA and 131 PBMA samples, collected and analyzed in Europe, representing a convenience sample, was used as input in our risk assessment. The highest risk mycotoxins identified for PBMA in the lower bound scenario (LB) were the sum of aflatoxins (sum AF), alternariol monomethyl ether (AME), aflatoxin B1 (AFB1) and alternariol (AOH), with HQs for children of 121.3, 66.8, 24.0 and 4.3, respectively. In the milk substitution model (LB), HQs of 4.9 (sum AF) and 1.4 (AFB1) were calculated for children, indicating a potential food safety risk. Further analysis demonstrated that soy-based meat alternatives are the highest risk food products, in particular for sum AF, AME, AOH and AFB1. With regard to PBDA, highest HQs were found for sum AF in almond and oat drink, and AFB1 in oat drink. This research presents an approach to overcome the lack of data in the assessment of emerging risks associated with the shift to more sustainable dietary patterns.

Morphometric Characterization and Dual Analysis for Flash Flood Hazard Assessment of Wadi Al-Lith Watershed, Saudi Arabia

Flash floods are one of the most hazardous natural events globally, characterized by their rapid onset and unpredictability, often overwhelming emergency preparedness and response systems. In the arid environment of Saudi Arabia, Wadi Al-Lith watershed is particularly prone to flash floods, exacerbated by sudden storms and the region’s distinct topographical features. This study focuses on the morphometric characterization and comparative analysis of flash flood risk within the Wadi Al-Lith basin. To assess flood susceptibility, two widely adopted methodologies were employed: the morphometric ranking approach and El-Shamy’s method. A 12.5-m resolution ALOS PALSAR digital elevation model (DEM) was used to delineate the watershed and generate a detailed drainage network via Arc-Hydro tools in the ArcGIS 10.4 software. Fifteen morphometric parameters were analyzed to determine their influence on flood potential and hazard prioritization. The findings of this study provide crucial insights for regional flood risk management, offering an improved understanding of flash flood dynamics and assisting in developing effective mitigation strategies for Wadi Al-Lith and similar environments. The findings reveal that Wadi Al-Lith comprises multiple sub-catchments with varying degrees of vulnerability to flash flooding. According to the morphometric hazard analysis (MHA), certain sub-catchments, including sc-2, sc-4, sc-5, sc-6, sc-10, sc-12, sc-13, and sc-15, emerge as highly susceptible to flood hazards, while others (sc-1 and sc-9) fall into moderate risk categories. In contrast, the application of El-Shamy’s method provides a different ranking of flood risks across the watershed’s sub-catchments, offering a comparative view of flood susceptibility. The insights gained from this dual-analysis approach are expected to support the development of targeted flood prevention and mitigation strategies, which are essential for minimizing the future impacts of flash flooding in the Wadi Al-Lith watershed and ensuring better preparedness for local communities.

Are local species prioritization lists sufficient for protecting endangered plants? Israeli red list as a test case

AbstractConserving species from extinction requires risk assessment and ranking for conservation priorities. The IUCN criteria of extinction risk are currently accepted globally, but only a small fraction of species were evaluated. When assessing species' extinction risk, sufficient information, in particular rate of population decline, is often partial or missing. Here we utilized the red list of Israeli endangered plant species, which prioritizes them for conservation, and evaluated their local extinction risk using IUCN criteria for local assessment. We found a relatively high similarity between the Israeli red number value and the IUCN assessments. Most pronouncedly, the habitat vulnerability index, used in the Israeli method, is correlated with the IUCN parameter of extinction rate in the last decade. We conclude that in the case of Israel, prioritization ranking of endangered species based on locally available information is a powerful tool for conservation even when some species information is lacking, facilitating local decision‐making. This finding may apply also to other countries using a local assessment system.

MetaCompare 2.0: differential ranking of ecological and human health resistome risks.

While numerous environmental factors contribute to the spread of antibiotic resistance genes (ARGs), quantifying their relative contributions remains a fundamental challenge. Similarly, it is important to differentiate acute human health risks from environmental exposure, versus broader ecological risk of ARG evolution and spread across microbial taxa. Recent studies have proposed various methods for achieving such aims. Here, we introduce MetaCompare 2.0, which improves upon original MetaCompare pipeline by differentiating indicators of human health resistome risk (potential for human pathogens of acute resistance concern to acquire ARGs) from ecological resistome risk (overall mobility of ARGs and potential for pathogen acquisition). The updated pipeline's sensitivity was demonstrated by analyzing diverse publicly-available metagenomes from wastewater, surface water, soil, sediment, human gut, and synthetic microbial communities. MetaCompare 2.0 provided distinct rankings of the metagenomes according to both human health resistome risk and ecological resistome risk, with both scores trending higher when influenced by anthropogenic impact or other stress. We evaluated the robustness of the pipeline to sequence assembly methods, sequencing depth, contig count, and metagenomic library coverage bias. The risk scores were remarkably consistent despite variations in these technological aspects. We packaged the improved pipeline into a publicly-available web service (http://metacompare.cs.vt.edu/) that provides an easy-to-use interface for computing resistome risk scores and visualizing results.

Integrated Fuzzy Technique for Order Preference by Similarity to Ideal Solution and Emotional Artificial Neural Network Model for Comprehensive Risk Prioritization in Green Construction Projects

With the rapid growth of green construction projects (GCPs) in Saudi Arabia, managing the associated risks has become crucial to ensuring project success and sustainability. These projects face a range of challenges, including socio-economic, environmental, and technical risks that need to be carefully identified and prioritized. This study systematically identifies and prioritizes the risks in GCP using a hybrid model combining fuzzy TOPSIS and an Emotional Artificial Neural Network (EANN). The focus of this study is on the risk management of the green construction industry in Saudi Arabia. Based on expert evaluations, low-quality materials and equipment (Likert scale mean is 4.71) and stakeholder resistance to adopting green ideas (4.67) emerged as the most critical risks. The fuzzy TOPSIS analysis assigned the highest weight to risk probability (0.174), followed by outcome (0.137), and vulnerability (0.123). The EANN refined the risk rankings, confirming the importance of these risks. The findings suggest that risk management strategies should prioritize material quality and stakeholder engagement, while environmental risks, ranked lower, are less of a concern. This hybrid model provides a robust framework for effective risk management, with practical implications for enhancing the sustainability and success of GCP.

A FMEA Optimization Method Based on TODIM and Best Worst Method-Water Filling Theory in Pythagorean Fuzzy Language Environment for Reliability Assessment of Industrial Robot

Abstract In view of the shortcomings of traditional failure modes and effects analysis (FMEA) in risk evaluation language, weight information, risk priority number (RPN), this paper proposes an FMEA optimization method. First, using the Pythagorean fuzzy language as the evaluation language, the hesitation psychology of the evaluator is truly reflected. Then, the best worst method (BWM) is used to calculate the weight of the evaluator, it can reduce the number of pairwise comparison evaluations. Second, water filling theory (WFT) uses mean values instead of extreme values to determine the discreteness of evaluation information, which is more consistent with FMEA. Therefore, WFT is used to calculate the weight of influencing factors. Finally, the tomada de-decisao iterativa multicriterio (TODIM) method is used for compromise calculation to obtain the risk ranking of failure modes. Compared with RPN, TODIM can avoid the situation that the failure mode scores are the same. At the end of the paper, the robustness and superiority of the new method are verified by taking the reliability assessment of reversing system of industrial robots as an example.

An approach to the microbiological risk ranking of cheeses

An approach to the microbiological risk ranking of cheeses

Viral community and antibiotic resistance genes carried by virus in soil microbial fuel cells

Soil microbial fuel cells (MFCs) can control the horizontal transfer of antibiotic resistance genes (ARGs) by reducing the abundance of mobile genetic elements. However, little is known about the effect of soil MFCs on the horizontal transfer pathway of ARGs transduced by viruses. In this study, the average abundance of ARGs in soil MFCs was 11% lower than that in the open-circuit control. Lower virus abundance in soil MFCs suggested less detriment of microbial communities. The structure of the viral community was respectively shifted by the introduction of electrodes and the stimulation of biocurrent, especially for the top three viral genera Oslovirus, Tequatrovirus and Incheonvrus in soil. The ARGs aac(6)-I, cat chloramphenicol acetyltransferase, qnrA and vanY were found as the highest health risk (Rank I), and their total abundance showed the lowest in MFCs, with a decrease of 91-99% compared to the controls. As the main carrier of ARGs, the abundance of Caudoviricetes showed a significant positive correlation with ARGs. Viral integrase was identified respectively coexisting with arnA and vanR (Rank III) in the same contig, which might aggravate their horizontal transfer. Proteobacteria was the main host of viruses carrying ARGs, which exhibited the lowest abundance in the soil MFC. The genus Pseudomonas was the host of viruses carrying ARGs, whose amount reduced by soil MFCs. This study provides an insight into the bioelectrochemical control of ARGs horizontal transfer.

Risk ranking of microbial hazards from consumption of ready-to-eat fresh produce (RTEFP)

Risk ranking of microbial hazards from consumption of ready-to-eat fresh produce (RTEFP)

Assessment of the occupational health risk of workers in the production of mechanical engineering

Most jobs in the automotive industry are characterized by the impact on workers of the entire complex of harmful production factors: noise, vibration, chemicals, the severity of the labor process, etc. Calculations of individual risk (IR) make it possible to carry out risk ranking in the course of research with an analysis of working conditions and health indicators and further use the data to develop preventive programs. According to the results of this study, high, medium and low levels of individual occupational risk for employees of various professions were determined according to the total assessment of the class of harmfulness and danger of automotive production. It was revealed that the priority is the average level of IR, which was established in 62.5 % — 77.2 % of workers who are in production conditions of harmful class 3 1–2 degrees of harmfulness. A low level of risk was diagnosed in a small number of employees of all groups. At the same time, in the group of workers in the conditions of a harmful third class of the 2nd degree of harmfulness, IR indicators corresponding to a high risk were established: among MSR locksmiths, every third employee had 31,0 %, and in the group of painters and laboratory assistants, every four th had 25,0 %.