Hazard Ranking Research Articles

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

The consumption of contaminated Ready-To-Eat Fresh Produce (RTEFP), especially minimally processed leafy green vegetables and fruits, is increasingly recognised as a source of foodborne illnesses, posing a significant safety risk to human health. RTEFP can become contaminated with enteric foodborne pathogens via different sources. Water used during the pre-harvest (irrigation) and post-harvest (washing water) has been identified as a potentially important transmission route for foodborne pathogens entering horticultural crops. The objective of the present study was to (i) evaluate human exposure to indicator microorganisms, which may act as a surrogate to assess potential exposure to harmful pathogens, and (ii) create a Quantitative Microbial Risk Assessment (QMRA) to assess the human health safety risks (infection or illness) from foodborne pathogens following the application of treated irrigation (sprinkler) water to RTEFP and assess potential microbial intake through the consumption of RTEFP grown on irrigated land. A QMRA based on published literature was constructed to analyse microbial daily/annual risk to foodborne enteric pathogens associated with consuming ready-to-eat fresh produce. The likelihood of exposure to target pathogens was determined using different model parameters. The results show that the pathogens were prioritised as Shigella spp., Cryptosporidium parvum, Salmonella spp., Giardia lamblia based on probability of illness and Campylobacter spp., norovirus, adenovirus and rotavirus based on probability of infection. Sensitivity analysis revealed that the consumption of RTE fresh produce and cumulative decay constant of pathogens are the most sensitive parameters of the QMRA model, followed by the initial concentration of pathogens, chlorine treatment, growth on shelves, and finally, the effect of cold storage. This study highlighted that chlorine used pre and post-harvest was an effective remedial measure to assist food safety. The study highlights the need for risk-benefit in balancing potential chemical (chlorine) human exposure and the benefits of reduced microbial loads on RTEFP.

Into the Jungle of Biological Agents of Foodborne Diseases: Time to Put Some Order for the French Risk Manager.

Consumers can be exposed to many foodborne biological hazards that cause diseases with varying outcomes and incidence and, therefore, represent different levels of public health burden. To help the French risk managers to rank these hazards and to prioritize food safety actions, we have developed a three-step approach. The first step was to develop a list of foodborne hazards of health concern in mainland France. From an initial list of 335 human pathogenic biological agents, the final list of "retained hazards" consists of 24 hazards, including 12 bacteria (including bacterial toxins and metabolites), 3 viruses and 9 parasites. The second step was to collect data to estimate the disease burden (incidence, Disability Adjusted Life Years) associated with these hazards through food during two time periods: 2008-2013 and 2014-2019. The ranks of the different hazards changed slightly according to the considered period. The third step was the ranking of hazards according to a multicriteria decision support model using the ELECTRE III method. Three ranking criteria were used, where two reflect the severity of the effects (Years of life lost and Years lost due to disability) and one reflects the likelihood (incidence) of the disease. The multicriteria decision analysis approach takes into account the preferences of the risk managers through different sets of weights and the uncertainties associated with the data. The method and the data collected allowed to estimate the health burden of foodborne biological hazards in mainland France and to define a prioritization list for the health authorities.

Systematic risk ranking of microbiological hazards in infant foods

Ensuring food safety, particularly for vulnerable groups, like infants and young children, requires identifying and prioritizing potential hazards in food chains. We previously developed a web-based decision support system (DSS) to identify specific microbiological hazards (MHs) in infant and toddler foods through a structured five-step process. This study takes the framework further by introducing systematic risk ranking (RR) steps to rank MH risks with seven criteria: process survival, recontamination, growth opportunity, meal preparation, hazard-food association evidence, food consumption habits of infants and toddlers in the EU, and MH severity. Each criterion is given a semi-quantitative or quantitative score or risk value, contributing to the final MH risk calculation via three aggregation methods: semi-quantitative risk scoring, semi-quantitative risk value, and outranking multi-criteria decision analysis (MCDA). To validate the criteria and ranking approaches, we conducted a case study to rank MH risks in infant formula, compared the results of the three risk ranking methods, and additionally evaluated the ranking results against expert opinions to ensure their accuracy. The results showed strong agreement among the three methods, consistently ranking Salmonella non-Typhi and Cronobacter spp. and Shiga-toxin-producing Escherichia coli as the top MH risks in infant formulae, with minor deviations. When MHs were ranked after an initial hazard identification step, all three methods produced nearly identical MH rankings, reinforcing the reliability of the ranking steps and the selected criteria. Notably, the risk value and MCDA methods provided more informative MH rankings compared to the risk scoring method. The risk value and risk scoring methods were implemented into an online tool, called the MIcrobiological hazards risk RAnking decision support system (Mira-DSS), available at https://foodmicrobiologywur.shinyapps.io/MIcrobial_hazards_RAnking/. In conclusion, our framework enables the ranking of MH risks, facilitating intervention comparisons and resource allocations to mitigate MH risks in infant foods, with potential applicability to broader food categories.

Quantitative assessment of whether phosphorus-based flame retardants are optimizing or degrading the fire hazard of aircraft carbon fiber/epoxy composites

Fire hazards are a primary concern in aircraft accidents, and controlling combustible materials is pivotal in managing cabin fire risks. This work aims to elucidate the impact of widespread measures that introduce phosphorus-based flame retardants (PFRs) on the fire safety of carbon fiber epoxy composites (CF/EP). Firstly, the hazardous indicators for flame retardant CF/EP composites exhibit two categories of optimization and degradation, which are caused by the intrinsic feature, pyrolysis characteristics and chemical valence states of PFRs. Secondly, the fire hazards of composites are assessed by fusing the analytic network process and information weights guided by Nash Equilibrium theory. The method combines the merits of subjective and objective weights from dimensions of intrinsic hazards, interrelationships and data dispersion of indicators. Finally, the assessed fire hazard rankings under 35 and 65 kW/m2 both are EP > CF/EP16%DOPO-HQ > CF/EP > CF/EP7%DPO. In conclusion, DOPO-HQ (+1) primarily increases the fire hazard of CF/EP due to gas-phase flame-retardant effects, while DPO (+3) predominantly reduces the fire hazard of CF/EP by contributing to condensed-phase effects. This work highlights the contradictory effects of PFRs on the fire safety of CF/EP composites due to structure and thermal stability. The proposed ANP and IW hybridization method provides a theoretical foundation for selecting flame retardants and assessing material fire hazards comprehensively.

Effects of capacity on the thermal runaway and gas venting behaviors of large-format lithium iron phosphate batteries induced by overcharge

Large-capacity lithium iron phosphate (LFP) batteries are widely used in electric bicycles. However, while crucial, thermal runaway (TR) behaviors under overcharge conditions have rarely been studied, leading to frequent fire accidents. This paper investigates the overcharge behavior and TR characteristics of four LFP batteries with the same components and materials but varying capacities (86, 100, 120, and 140 Ah). Overcharge tests were conducted in a customized apparatus, and the surface temperature, mass loss, and gas venting phenomenon were recorded. The results revealed that under the same overcharge conditions, the TR early warning temperature can differ considerably with respect to battery capacity, highlighting the importance of selecting the appropriate early warning temperature in real-time temperature monitoring based on the capacity of the LFP battery. Three characteristic times were used to describe the thermal behavior of the batteries, namely, the time to reach the voltage plateau (tPV), the time when the safety valve opens (tSV), and the start time of TR (tTR). Analysis of critical heat accumulation indicated that the 86 Ah LFP battery has the lowest tolerance to overcharge and, thus, the highest TR risk. However, after TR, the 86 Ah LFP battery exhibited the smallest maximum temperature (Tmax), maximum temperature increase rate (Rmax), maximum total mass loss, and maximum mass loss rate (Mmax) among all the batteries, suggesting the least TR hazard. Consequently, a safety evaluation and scoring system using these six parameters was established considering the overcharge behavior and TR characteristics of LFP batteries. The results indicated that the TR risk ranking of LFP batteries with different capacities was 86 Ah LFP > 100 Ah LFP > 140 Ah LFP > 120 Ah LFP, while the TR hazard ranking was 140 Ah LFP > 120 Ah LFP > 100 Ah LFP > 86 Ah LFP. This comparative study of LFP batteries with varying capacities enhances our understanding of their overcharge behavior and TR characteristics, and a safety evaluation and scoring system can also be used for risk and hazard assessments of other types of batteries.

Fuzzy reliability evaluation and machine learning-based fault prediction of wind turbines

The swift growth of the wind power industry necessitates comprehensive evaluation and efficient fault prediction of wind turbines. Given the challenges of integration and optimization of reliability evaluation and fault prediction models, a systematic method of reliability fuzzy evaluation and fault prediction based on the Supervisory Control and Data Acquisition (SCADA) data is proposed. A mid-to-long-term reliability fuzzy evaluation model is constructed using Fuzzy Comprehensive Evaluation (FCE). The mid-term evaluation results in ten failure modes reveal that the model's hazard ranking results match the situation better than the RPN method. And the long-term evaluation results of 5 years in the operating mode show that the model effectively gathers the evaluation information each year and provides a clear and accurate reflection of reliability. Meanwhile, fault prediction is studied using alarm logs because they are better at expressing the status of wind turbines than monitoring data. And the tree-based algorithms and unsupervised statistical learning methods are used to mine the mapping relationship between input variables and predefined tags. The fault prediction achieves both accuracy and recall of 0.784 and saves over 163k Euros based on local wind turbine maintenance expenditures. Overall, the reliability evaluation and fault prediction complement each other, which may either affect future wind farm management or prevent unnecessary maintenance costs.

A novel approach to hazard evaluation for MASS operation based on a hesitant fuzzy linguistic term set

Expert judgment has been widely utilized in ship risk assessment. The traditional method is believed to be capable of processing only designated linguistic variables, which fails to capture the degree of expert hesitation in assessing a complex system. A novel model, the bi-independent hesitant fuzzy linguistic term set (BHFLTS), based on the hesitant fuzzy linguistic term set (HFLTS), is proposed to incorporate this hesitation. This paper also identifies ten navigational hazards to maritime autonomous surface ship (MASS) operation based on a literature review. In addition, the BHFLTS approach combined with the technique for order preference by similarity to an ideal solution (TOPSIS) is utilized for hazard assessment and ranking, and with this method, “Collision avoidance decision algorithm malfunction”, “Ship situation awareness system failure” and “Command transmission system failure” are rated as the top three navigational hazards that threaten MASS operation.

Spatial Optimism and Cross-Over Effects in the Perceptions of Interconnected Wildfire, Flood, and Mudslide Hazards

Communities near the wildland urban interface (WUI) are exposed to a mix of three interconnected hazards (wildfire, flood, and mudslide), and understanding multi-hazard perceptions is critically important for emergency preparation and hazard mitigation—particularly given the WUI’s rapid expansion and intensifying environmental hazards. Based on a survey of residents living near recent burn scars in Southern California, we document cross-over effects in hazard perceptions, where resident experience with one hazard was associated with greater hazard rankings for other hazards. Additionally, for all three hazards analyzed we document perceptions of increasing hazard levels with increasing spatial scales (home, near-home, neighborhood, and community), providing evidence of spatial optimism, or the tendency to discount proximate hazards. This study stresses the importance of using a multi-hazard and multi-scale approach for understanding and responding to local level environmental hazards.

Thermal Risk Assessment and Optimization of Hazard Ranking for Aromatic Nitro Compounds: Multiparameterization and Quantitative Structure–Property Relationship Modeling

Thermal Risk Assessment and Optimization of Hazard Ranking for Aromatic Nitro Compounds: Multiparameterization and Quantitative Structure–Property Relationship Modeling

基于模糊综合评判的 FMECA 脱粒清选系统可靠性分析

Aiming at the traditional FMECA (Failure Modes, Effect and Criticality Analysis) results of the threshing and cleaning system, which are strongly influenced by subjective factors, imprecise and easy to repeat, the fuzzy comprehensive evaluation method is introduced to quantify the results of the expert evaluation and reduce the subjective influence. Analytic Hierarchy Process (AHP) is used to assign weights to each influencing factor, and by calculating the comprehensive hazard level index, the hazard ranking of each failure mode is carried out, from which the critical failure modes are identified as the focus of improvement, so as to improve the reliability of the system. Comparison shows that the improved method effectively makes up for the shortcomings of the traditional FMECA analysis method, and it is easier to find out the critical failure modes, which provides a theoretical basis for practical application.

Risk ranking of chemical hazards in food and feed – A case study in cereals in the Netherlands

Monitoring programs for food safety hazards in feed and food are increasingly performed on a risk-basis. Various methods are available to rank hazard-product combinations to be included in risk-based monitoring programs. Such methods have been developed for either feed or food, but until now these do not consider hazards in both feed and food simultaneously. Based on available time, budget and data, two methods, i.e. a scoring method and a risk ratio method, were selected that are capable of incorporating both food and feed products for ranking chemical hazards. These methods were compared by applying a case study on chemical hazards in cereals in the Netherlands for various animals and human age groups, using available data on concentrations, consumption available in national databases and toxicity. Results showed that both methods resulted in the highest ranking for the mycotoxins deoxynivalenol, aflatoxin B1 and zearalenone. Maize and wheat products were most frequently included in the top 50 ranked hazard-product combinations. Both methods showed to be capable of ranking hazard-product combinations for various animal and human groups. The risk ratio method provided a more objective and accurate outcome since it is based on actual data. Nevertheless, the risk scoring method may be preferred as it allows more flexibility in type of input data used. Also, it allows for the inclusion of country of origin of the materials used, which is relevant for imported products. This study showed that the risk ratio and the scoring method can successfully be used to rank both food and feed products simultaneously.

Reliability Study of an Intelligent Profiling Progressive Automatic Glue Cutter Based on the Improved FMECA Method

This study introduces the fuzzy theory approach as an enhancement to the traditional failure mode, effect, and criticality analysis (FMECA) method in order to address its limitations, which primarily stem from subjectivity and a lack of quantitative analysis. The proposed method, referred to as FMECA improvement based on fuzzy comprehensive evaluation, aims to quantify the qualitative aspect of the analysis and provides a detailed outline of the analysis procedure. By applying the enhanced FMECA method to assess the reliability of an intelligent profiling progressive automatic rubber cutter, the hazard ranking for each failure mode of the cutter can be determined, thereby identifying areas that require reliability improvement. The analysis outcomes demonstrate that this method establishes a theoretical foundation for subsequent cutter improvement designs, enables early identification of potential failures, and consequently leads to a reduced failure rate and an enhanced reliability level for the intelligent profiling progressive automatic cutter. Furthermore, this innovative agricultural equipment reliability analysis and testing approach holds significant value in elevating the reliability standards of agricultural equipment as a whole and can be explored and implemented in other agricultural machinery contexts.

HSE hazard ranking of chemicals related to Petroleum Drilling Laboratory of University using Fuzzy TOPSIS

HSE hazard ranking of chemicals related to Petroleum Drilling Laboratory of University using Fuzzy TOPSIS

Prioritization of vegetable-borne biological hazards in Argentina using a multicriteria decision analysis tool.

Vegetables, especially those eaten raw, have been implicated in several foodborne disease outbreaks. Since multiple vegetable matrices and hazards are involved, risk managers have to prioritize those with the greatest impact on public health to design control strategies. In this study, a scientific-based risk ranking of foodborne pathogens transmitted by leafy green vegetables in Argentina was performed. The prioritization process included hazard identification, evaluation criteria identification and definition, criteria weighting, expert survey design and selection and call for experts, hazard score calculation, hazard ranking and variation coefficient, and result analysis. Regression tree analysis determined four risk clusters: high (Cryptosporidum spp., Toxoplasma gondii, Norovirus), moderate (Giardia spp., Listeria spp., Shigella sonnei), low (Shiga toxin-producing Escherichia coli, Ascaris spp., Entamoeba histolytica, Salmonella spp., Rotavirus, Enterovirus) and very low (Campylobacter jejuni, hepatitis A virus and Yersinia pseudotuberculosis). Diseases caused by Norovirus, Cryptosporidium spp. and T. gondii do not require mandatory notification. Neither viruses nor parasites are included as microbiological criteria for foodstuff. The lack of outbreak studies did not allow to accurately identify vegetables as a source of Norovirus disease. Information on listeriosis cases or outbreaks due to vegetable consumption was not available. Shigella spp. was the main responsible for bacterial diarrhea, but it has not been epidemiologically associated with vegetable consumption. The quality of the available information for all hazards studied was very low and low. The implementation of good practice guidelines throughout the entire vegetable production chain could prevent the presence of the identified hazards. The current study allowed the identification of vacancy areas and could help reinforce the need for performing epidemiological studies on foodborne diseases potentially associated with vegetable consumption in Argentina.

115 Fibre-Aerogel-Mats for façade Insulation: How to Guide SSbD Development by Screenings?

Abstract The HARMLESS project focusses upon assessment approaches to support Safe-and-Sustainable-by-Design (SSbD) development of advanced materials (AdMa). Case studies comprise several industry sectors. Specifically for the construction sector we study façade insulation by fibre-aerogel-mats. Beyond the relatively simpler mono-component organic aerogels presented earlier (Keller et al. 2021), here we deal with multi-component materials: Glass fibers provide structural integrity for the silica-based aerogel that provides the thermal insulation performance, though is coated by organosilane as a hydrophobizing agent to prevent moisture uptake. Optionally, an additional inorganic coating can be applied to enhance mechanical stability. Here we explored this wide SSbD design space by four industrially relevant SSbD-versions of fibre-aerogel-mats; these were ranked and compared against each other as well as conventional insulation material (i.e. stone wool). We assessed the release by performing several typical occupational operations under clean-air conditions within a laboratory setting. Up to 106/ccm particles are released, with respirable aerodynamic diameters. We collected the dust and assessed the structure and behavior with respect to its biological reactivity and biodissolution, focusing on the screening and ranking of inhalation hazards. The data on exposure and hazard was complemented by data on functionality in the intended use, where all SSbD versions performed significantly better than the conventional alternative. The new data refines the risk screening and categorisation schemes for advanced materials, including Early4AdMa (RIVM 2022), AdmGRID (Kennedy et al. 2019), InnoMat.Life (Wohlleben et al. 2022) and an environmental risk screening (Arvidsson et al. 2022).

The Devastation of Waste Plastic on the Environment and Remediation Processes: A Critical Review

The devastating effect of plastic waste on the ecosystem due to the rapid increase in population has been a concern. Although stakeholders and governments invested in efforts to mitigate plastic waste, their exertions have limited to no effects as the demand for plastic increases annually. Emerging practical advancements in recycling plastic have been critical for achieving a sustainable circular economy. This study reviews the adverse effect of plastic waste on the environment and the inhabiting creature, the regulation for managing plastic waste, and their limitations. This scoping review also provides information on the current route for reducing plastic waste by defining its sources and their applications. After identifying the generation of plastic waste, the plastic polymers are categorized according to the hazard ranking of their monomers according to their environmental toxicity, damaging the inhabiting creature. The discharge pathways of plastic waste into the environment and aquatic systems leading to white pollution and climate change were also determined. Conversion of plastic waste through the remedial channel by manufacturing value-added products using techniques such as reusing, recycling, and energy recovery, reducing the disposal of plastic waste in landfills is outlined. The information on remedial processes provided in this study will help reduce plastic waste from the environment. In addition, correctly applying these suggestions may help reduce environmental pollution and the death of inhabiting creations. Further research is necessary to convert plastic waste as raw materials into high-value products to achieve a circular economy.

Comparison of different objective weighting methods in a multi‐criteria model for watershed prioritization for flood risk assessment using morphometric analysis

AbstractMorphometric analysis of watersheds coupled with multi‐criteria decision making (MCDM) techniques is a widely used approach in identifying and prioritizing subwatersheds for flood risk assessment. Finding the appropriate weight for each morphometric parameter is one of the most important steps in MCDM methods. The present research focuses on analyzing the effect of using objective weighting methods in watershed prioritization in Daroungar Watershed in Northeast of Iran. To this aim, the weights of morphometric parameters were determined using six objective weighting methods and were used for ranking subwatersheds based on flood generation by a multi‐criteria model. Study results show that the highest weight in various methods belonged to different parameters. Comparison of flood susceptibility ranking maps indicated, except standard deviation method, there is a significant correlation among WM, preference selection index, criteria importance through intercriteria correlation, entropy, and method based on the removal effects of criteria methods; however, the distribution of flood susceptibility classes is not the same in the six weighting methods. The flood hazard ranking map using aggregation methods depicts that subwatersheds 6, 74, 27, and 67 which have high priority for flood hazard, have the same rank in all aggregation methods. Overall, in the present study, the importance of choosing the appropriate weighting method in prioritizing watersheds was emphasized.

Distribution and risk assessment of microplastics in Liujiaxia Reservoir on the upper Yellow River

Microplastics (MPSs) distribution in global freshwater systems is extensively reported, but the distribution of MPSs in reservoirs of the Yellow River has rarely been studied. To fill in this gap, we systematically investigated the distribution of MPSs in surface water and bank sediments gleaned from Liujiaxia Reservoir of the upper Yellow River for the first time and conducted an ecological risk assessment in succession in this work. The results showed that the main polymer types of MPSs in the surface water and bank sediments of Liujiaxia Reservoir were polyethylene terephthalate (PET), polystyrene (PS), and polypropylene (PP), and the abundance of MPSs in the reservoir surface water and bank sediments ranged from 4.48 to 12.09 item/L and 447.27 to 1543.80 item/kg (dry weight), respectively. Further physical morphology analysis of MPSs in the samples revealed that MPSs in the surface water and bank sediments of Liujiaxia Reservoir were predominantly fibrous with small particle sizes (<1 mm), and there was abundant color, mainly exhibiting transparent, black, and blue. The results of the MPS pollution load index (PLI>1) and the hazard ranking of MPSs (HZone = 10.20 for surface water and HZone = 14.06 for bank sediments) yielded a hazard class II for MPS pollution in Liujiaxia Reservoir, the combined pollution risk index (PRIZone = 17.05 for surface water and PRIZone = 31.25 for bank sediments) stated clearly the potential ecological risk in the Liujiaxia Reservoir. Briefly, this study supplemented and enriched the data on the distribution of MPSs in the reservoirs of the Yellow River basin, and provide a benchmark for future pollution control and management in the reservoir area.

Risk Ranking of Chemical and Microbiological Hazards in Foods ‐ Research Project and International Workshop

The purpose of this project was to improve the ability to perform risk ranking of current chemical and microbiological hazards in foods. The work was performed in three work packages (WPs) comprising an overview of chemical and microbiological risk assessment (WP1), development of methods for risk ranking (WP2), and the organisation of an international workshop (WP3). The developmental work consisted of 1) a method for chemical hazards that was also adapted for newer toxicological effect data, and 2) an exposure model applicable to both types of hazards in its design. Conclusions at the workshop included that risk ranking fundamentally would provide added support to risk management and risk communication. Both probability and severity of a health effect was regarded to be relevant to incorporate in the metric used for risk ranking. Measures of health burden were regarded as useful by many participants but there was no consensus on the most preferable metric. The value of other metrics, including less data intensive ones, was also noted. While risk ranking should be based on risk assessment principles, management aspects would ultimately need to be considered on top of this. Participants were positive to a joint framework for both chemical and microbiological hazards, but several challenges were identified. In the face of a general lack of desired data it was regarded to be important to make efficient use of the available information, and it may be advantageous if methods are compatible with different sets of evidence. It is recommended that the common metric for risk ranking is further resolved in terms of what aspects it should account for, the usefulness of particular or different metrics, as well as the concept of a tiered approach. Development of an overarching guidance for risk ranking addressing the many types of rankings possible is proposed.

A novel risk assessment model for work-related musculoskeletal disorders in tea harvesting workers

Work-related musculoskeletal disorders (WMSDs) are the most common occupational health problems in agriculture workers due to repetitive and excessive force movement activities involved in their job processes. The Fine-Kinney method has been commonly used as a quantitative evaluation method in risk assessment studies. Classically, the risk value via Fine–Kinney is calculated by the mathematical multiplication irrespective of the degree of importance of each risk parameter (probability (P), exposure (E), and consequence (C)). Hence, a novel risk management model was proposed based on integrating Fine-Kinney and spherical fuzzy AHP-TOPSIS. First, each risk parameter is weighted using the spherical fuzzy AHP (SF-AHP). Second, the spherical fuzzy TOPSIS (SF-TOPSIS) method is used for hazard ranking. The proposed model is applied to evaluate risks in tea harvesting workers for work-related musculoskeletal disorders. Subsequently, a sensitivity analysis is carried out to test the proposed model. Finally, we compare the proposed model’s applicability and effectiveness with the spherical fuzzy COmbinative Distance-based ASsessment (SF-CODAS) method based on Fine-Kinney. The ranking similarity between the proposed Fine-Kinney-based SF-TOPSIS and SF-CODAS methods is checked by applying Spearman’s rank correlation coefficient, in which 92% of rankings are matched.