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Currently, there is increasing concern about the safety and leakage of process industries. Therefore, the present study aims to prioritize control measures before and after the leakage scenario by using the Hendershot theory and MCDM techniques. In this study, two proactive and reactive layers were selected before and after leakage of tanks, respectively. Then, criteria and alternatives were selected to perform fuzzy TOPSIS (FTOPSIS) and find the best alternative based on the literature review and Hendershot approach. The linear model of the fuzzy Best-Worst method (FBWM) was constructed and resolved using Lingo 17 software. Subsequently, criteria were assigned weights based on thorough calculations of the inconsistency rate. The weight of study experts was equal to 0.25. The results of FBWM showed that the reliability index with a weight of 0.3727 was ranked first and the inconsistency rate ([Formula: see text]) was calculated to be equal to 0.040. Inherent Safety Design (ISD) (0.899) and passive safety (0.767) also ranked first before and after tank leaks, respectively. Using the FBWM method leads to fewer pairwise comparisons and at the same time more stability. Although ISD and passive strategies are more valid and strict, elements of all strategies are necessary for a comprehensive process safety management program.

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Cognitive workload has been known as a key factor in traffic accidents, which can be highly increased by talking on the phone while driving. A wide range of studies around the world investigated the effects of mobile phone conversations on driving performance and traffic accidents. But less noticed is the durability of cognitive effects of mobile phone conversations. This study aimed to determine the effects of different types of mobile phone conversations on physiological response and driving performance during and after the conversation. Heart rate, heart rate variability (physiological response), Standard deviation of lane position (SDLP), and the relative distance between two cars (driving performance) of 34 samples (male and female) in the driving simulator were recorded. In this study, three types of conversations (neutral, cognitive, and arousal) were used. Neutral conversation did not pursue specific purpose questions. Cognitive conversations were simple mathematical problem-solving questions and arousal conversations aimed at arousing participant emotions. Each conversation was used as a secondary task in a condition. The study had three conditions; in each condition the participant drove for 15 min. Each condition consisted of 5 min of driving (Background), 5 min of driving and conversation (dual tasks) and 5 min of driving after conversation to trace the effects of the conversation. Vehicle speed was 110 km/h in each of the three conditions using car-following scenario. The results showed that neutral conversations had no significant effects on physiological response. Though, arousal conversations had significant effects on physiological responsiveness and driving performance during conversations, where it was even more significant after disconnection. Therefore, the content of the conversation determines the amount of cognitive load imposed on the driver. Considering the persistence of cognitive effects caused by conversation, the risk of traffic accidents is still high even after disconnection.

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Analytical models and the prediction of accidents and their consequences are important tools for preventing accidents in the industry. Therefore, the present study was conducted to review process accident consequence modeling in Iran (2006-2022), helping improve incident modeling, and creating a context for preventing these accidents. In this study, the articles of 5 international Embase Medline/PubMed databases, ProQuest, Scopus, Google Scholar, and Web of Science, and four Iranian databases SID, MagIran, IranMedex, and IranDoc were examined using the PRISMA checklist. After reviewing the studies, 40 articles were included in the final analysis. The results showed that 25 studies used PHAST software, 11 studies used ALOHA software and 4 studies used ALOHA and PHAST software together. The highest number of studies was conducted in Imam Khomeini Port and Asaluyeh city, respectively. In addition, the number of studies published in Persian was more than in other studies. There was no similar agreement between the results of the two software in providing correct results at low concentrations. PHAST software also provided more accurate results than ALOHA over longer distances in stable and relatively stable weather conditions. The study and identification of hazards and scenarios in the studies that used PHAST software were more, more accurate and more coherent than in the studies that used ALOHA software. It is suggested that in future studies the same scenario can be compared with PHAST, ALOHA, and newer modeling software such as Fire Dynamics Simulator (FDS).

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Bachground: Noise is one of the most important harmful factors in the environment. There are limited studies on the effect of noise loudness on brain signals and attention. The main objective of this study was to investigate the relationship between exposure to different loudness levels with brain index, types of attention, and subjective evaluation. Methods: Four noises with different loudness levels were generated. Sixty-four male students participated in this study. Each subject performed the integrated visual and auditory continuous performance test (IVA-2) test before and during exposure to noise loudness signals while their electroencephalography was recorded. Finally, the alpha-to-gamma ratio (AGR), five types of attention, and the subjective evaluation results were examined. Results: During exposure to loudness levels, the AGR and types of attention decreased while the NASA-Tax Load Index (NASA-TLX) scores increased. The noise exposure at lower loudness levels (65 and 75 phon) leads to greater attention dysfunction than at higher loudness. The AGR was significantly changed during exposure to 65 and 75 phon and audio stimuli. This significant change was observed in exposure at all loudness levels except 85 phon and visual stimuli. The divided and sustained attention changed significantly during exposure to all loudness levels and visual stimuli. The AGR had a significant inverse correlation with the total score of NASA-TLX during noise exposure. Conclusions: These results can lead to the design of methods to control the psychological effects of noise at specific frequencies (250 and 4000 Hz) and can prevent non-auditory damage to human cognitive performance in industrial and urban environments.

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Various subdisciplines of ergonomics science have emerged during the past decades as our insight has been broadened of human and performance. The three main branches of ergonomics have evolved over time focusing on the physical, cognitive, and organizational aspects. But the question is, can these disciplines focus and research enough on the ergonomic aspects of cyberspace and Industry 4.0 technologies? Cyber-technologies of the Fourth Industrial revolution are dramatically imposing themselves on our life and work. This has been led to emerging cyber-aspects for human work and life. Hence, many sciences, mainly applied ones, have upgraded to their cyber versions to deal with the emergent issues, usually with a new name, including the cyber prefix. Cyber-medicine, cyber-health, cyber-commerce, and cyberpsychology are some examples. Also, ergonomics requires a similar look. Ergonomic benefits and threats of Industry 4.0 technologies must be considered in an integrated manner. This paper addresses this issue. First, the emergence and development of ergonomics and its subdisciplines chronologically is reviewed. Then, Cybergonomics as a new name and concept is proposed and defined as the ergonomics of Industry 4.0 era. Justification for this portmanteau is described, and an outline of the new realm is explained. Finally, a research road map is proposed for this new subdiscipline of ergonomics.

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This study aims to assess the risk of chemicals warehouse using a Bayesian networks (BNs) and computational fluid dynamics (CFD). A methodology combining Bow-Tie (BT), fuzzy set theory (FST), and Bayesian network was employed, in which the BT was drawn for chemical spill scenarios. FST was utilized for the estimation of the basic events (BEs) occurrence probability, and the probability of interaction among a set of variables was obtained using BNs. Pool fire scenario radiation heat flux was evaluated using CFD code, fire dynamic simulator (FDS), and the solid flame model (SFM). Fail in forklift brake system (BE1), was the most significant cause for a chemical spill. Based on the CFD model, the heat flux is 31 kW/m2 at a distance of 3.5 m from the fire, decreasing to 6.5 m gradually. The maximum safety distance of 4 m is predicted by the CFD for heat flux that exceeds 12.5 kW/m2; however, SFM predicts approximately 4.5 m. According to the results, the amount of posterior risk is higher than the prior value. The framework presented in the chemicals warehouse for consequence analysis and dynamic risk assessment (DRA) of pool fire could be used for preventing the accidents and domino effects in the chemicals warehouse.

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In this study, a fuzzy Bayesian network (FBN) approach was proposed to analyze the domino effects of pool fire. Failure probabilities were calculated using triangular fuzzy numbers, the combined center of area (CoA)/sum-product method and the BN approach. Consequence modeling, probit equations and leaky-noisy-OR (L-NOR) gates were used to analyze the domino effects, and modify conditional probability tables (CPTs). Methanol storage tanks were selected to confirm the practical feasibility of the suggested method. The domino probability using bow-tie analysis (BTA) and FBN in the first and second levels was compared, and the ratio of variation was used for sensitivity analysis. Probability of the domino effect in the first and second levels (FBN) was 0.0071472631 and 0.0090630640, respectively. The results confirm this method is a suitable tool for analyzing the domino effects and that using FBN and L-NOR gate is a good way to assess the reliability of tanks.

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BACKGROUND: The structure of buildings is in degradation over time, monitoring their safety status and providing timely warnings is crucial. Therefore, an efficient visual inspection of the building's safety has intrinsic value to give early warnings to owners and managers. OBJECTIVE: This study aimed to provide an audit tool for evaluation of the administrative in-operation buildings' safety status. METHODS: Factors affecting the administrative buildings' safety status was determined based on the National Building Regulations of Iran (NBRI) and other studies. Checklist items and their guidelines were prepared. Face validity (quantitative and qualitative), Content Validity Ratio (CVR), and Content Validity Index (CVI) were calculated for the checklist. The Intra-class Correlation Coefficient (ICC) used for inter-rater reliability and Cronbach's α was used to evaluate internal consistency of the checklist. RESULTS: Forty-seven items related to in-operation building safety were extracted from literature review. Based on the results of the psychometric analysis, 5 items were removed and 42 items remained. The values of different psychometric indices for the other items indicated their acceptable validity (α= 0.82, ICC≥0.75). CONCLUSION: The designed checklist had a good level of validity and reliability for inspecting architectural, technical services, and managerial safety aspects of administrative in-operation buildings. Stakeholders can use it for quick and comprehensive assessment of building safety. Use of this checklist are expected to give early warnings about the safety of buildings to the stakeholders.

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Background: Ventilation system besides other prevention strategies such as surface disinfecting and personal protective equipment (PPE) decrease the risk of coronavirus disease 2019 (COVID-19) infection. This study aimed to examine the ventilation system of an intensive care unit (ICU) in a hospital in Tehran, Iran to evaluate the potency of heating, ventilation, and air conditioning system (HVAC) for COVID-19 spread. Materials and Methods: Contamination of air turnover caves was evaluated in supplier diffuser and extractor grills of negative pressure HVAC by ten samples. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the samples was evaluated by the real time reverse transcription-polymerase chain reaction (PCR). Moreover, air conditioning and sick building syndrome (SBS) was assessed according to MM040EA questioning from health care workers. Results: In the health care workers, respiratory effects were more prevalent compared to other signs. Despite suitable air conditioning, this study highlighted carrier potency of ICU workers for SARS-COV-2. Conclusion: According to our results, although the HVAC of ICU ward had an appropriate air movement, it was not safe enough for health care workers.

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INTRODUCTION: The use of mobile phones while driving is known to be a distraction factor and a cause of accidents. The way in which different kinds of conversations affect the behavioral performance of the driver as well as the persistence of the effects are not yet fully understood. METHOD: In this study, in addition to comparing brain function and behavioral function in dual task conditions in three conversations types, the persistent effects of these types of conversations have also been traced. RESULTS: The results show that the content of the mobile phone conversation while driving is the cause of the persistent changes in behavioral and brain functions. Increased time headway and lane departure was observed during and up to 5 min after the emotional conversation was finished. EEG bands also varied in different types of conversations. Cognitive conversations caused an increase in the activity of the alpha and beta bands while emotional conversations enhanced the rate of gamma and beta bands. A meaningful correlation was found between changes in the theta and alpha bands and changes in behavioral performance both during the dual task condition and after the conversation was finished, was also observed. CONCLUSIONS: The content of the conversation is one of the most important factors that increase the risk of road accidents. This can also deteriorate the behavioral performance of the driver and can have persistent effects on behavioral performance and the brain. Practical applications: The findings of this study provide a basis to measure and tracing drivers' cognitive distractions induced by different levels of mental workload through physiological and behavioral performances.

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BACKGROUND: Increasing the establishment of integrated management systems (IMSs) is done with the purpose of leaving traditional management methods and replacing them with modern management methods. Thus, the present study sought to analyze the events and investigate the impact of IMS on health and safety performance indices in an Iranian combined cycle power plants. METHODS: This case study was conducted in 2012 in all units of the Yazd Combined Cycle Power Plant on accident victims before and after the implementation of IMS. For data analysis and prediction of indices after the implementation of IMS, descriptive statistics and Kolmogorov-Smirnov test, Chi-square, linear regression, and Cubic tests were conducted using SPSS software. RESULTS: The number of people employed in the power plant in an 8-year period (2004-2011) was 1,189, and 287 cases of work-related accidents were recorded. The highest accident frequency rate and accident severity rate were in 2004 (32.65) and 2008 (209), respectively. Safe T-score reached to below -3 during 2010-2011. In addition, given the regression results, the relation between all predictor variables with outcomes was significant (p < 0.05), except for the variable X1 belonging to the accident severity rate index. CONCLUSION: The implementation of safety programs especially that of IMS and its annual audits has had a significant impact on reducing accident indices and improving safety within the study period. Accordingly, health and safety management systems are appropriate tools for reducing accident rate, and the use of regression models and accident indices is also a suitable way for monitoring safety performance.

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OBJECTIVE: Lane departure, caused by inattention, distraction, drowsiness, or any unusual driver behavior, is a typical risk threatening the driver as well as other road users. Accurate perception of such situations through effective warnings would help drivers to avoid serious consequences. With regard to critical functions of warning symbols for risk communication, the present study focused on providing effective and easily perceivable symbols, compatible with human cognitive capabilities. Thus, the main purpose of the present study was to design and cognitively appraise 6 newly designed dynamic symbols, candidates for a new type of lane departure warning system. METHODS: Simplicity, familiarity, concreteness, meaningfulness, and semantic closeness were the major assessment criteria, defining cognitive features by the earlier researchers in the field. A total number of 187 driving license applicants, with a mean age of 20.58 years (SD = 3.20), participated in the present survey. The participants rated cognitive features of the 6 dynamic symbols along a 0-100 scale. RESULTS: Significant main effect of the element factor type of the designed symbols on rating cognitive features revealed that the existence of car element was the best predictor for illustrating lane departure. The interaction of both element factor and location of element factor significantly affected the ratings. However, the location of element factor did not solely have any strong effect on the ratings. The results also demonstrated that semantic closeness received the highest overall mean score across symbols (M = 61.80), especially within the symbols that include the car element (M = 75.67). Moreover, a significant difference was observed between the average ratings of the cognitive features, despite the fact that a significant correlation was found between cognitive features. CONCLUSION: The most considerable result of the current study was the match between the symbol with the highest ratings and the International Organization for Standardization (ISO)-related icon in appearance. Because previous studies demonstrated a strong correlation between comprehension scores of the symbol and both semantic closeness and meaningfulness, high-level comprehensibility of the best ranked symbol is expected.

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OBJECTIVE: Previous studies on factors affecting drivers' decisions to use their mobile phones while driving are mostly focused on psychological and sociocultural contexts. Few investigations have been carried out on the role of traffic circumstances on drivers' decisions to use or not to use a mobile phone. METHODS: In this research, the effects of headway distance, speed, and the type of road as well as individual variables including age and driving experience are investigated. Forty-two subjects participated in observing 24 scenarios in a driving simulator. RESULTS: Logistic regression models showed that car speed, headway distance, and age can predict whether drivers' answer an incoming call while driving. The results indicated that traffic circumstances at the onset of phone calls are stronger predictors of drivers' decisions to answer a cell phone compared to driver-related variables. CONCLUSIONS: Headway distance and car speed can be used by in-vehicle information systems (IVIS) to warn drivers against using a mobile phone in certain traffic situations. Traffic safety campaigns for young drivers should focus on keeping safe headway distance and speed while driving.

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