ABSTRACT
This article discusses the importance of identifying and preventing human error in industrial environments, specifically in the sugar production process. The article emphasizes the importance of choosing the right technique for risk assessment studies resulting from human errors. A cross-sectional study was conducted using a multi-stage approach - Hierarchical Task Analysis (HTA), Human Error Calculator (HEC), and Predictive Human Error Analysis (PHEA) - to identify potential human errors in the sugar production process. The HTA, HEC, and PHEA techniques were employed to evaluate each stage of the process for potential human errors. The results of the HTA technique identified 35 tasks and 83 sub-tasks in 14 units of the sugar production process. According to HEC technique 4 tasks with 80 % probability of human error and 2 tasks with 50 % probability of human error had the highest calculated error probabilities. The factors of individual skill, task repetition and importance were the most important factors of human error in the present study. The analysis of PHEA worksheets showed that the number of human errors identified in the tasks with highest probability were 8 errors, of which 50 % were action errors, 25 % checking errors, 13 % selection errors, and 12 % retrieval errors. To mitigate the consequences of human error, it was recommended training courses, raising operator awareness of error consequences, and installing instructions in the sugar production process. Based on the findings, the article concludes that the HEC and PHEA techniques are applicable and effective in identifying and analyzing human errors in process and food industries.
ABSTRACT
Cardiovascular (CVD) + Respiratory diseases are recognized as the main cause of death worldwide. Fluctuations in temperature and air pollution have been reported as one of the most important causes of cardiovascular & respiratory diseases. Therefore, in the current study, we assessed the relationship between ambient air temperature and pollution on the number of total emergency hospital admission due to cardiovascular and respiratory conditions in the City of Bojnord, northeastern Iran. The meteorological data, including daily temperature, relative humidity and concentrations of five air pollutants CO, NO2, NOX SO2, and PM10 were obtained from online electronic sensors at the Bojnurd meteorological station from 21th March 2018 to 20th March 2020. Statistical analysis, penalized distributed lag non-linear method was applied using R Software. Also, sensitivity analysis test was calculated by using appropriate application. The results of the study revealed that the effect of higher and lower temperatures was observed immediately from the first day and the second week, respectively. Also result showed with increase and decrease temperature, significantly increased the risk of hospitalization by 36% (RR, 1.36; 95% CI (1), 0.95 to 1.95) and 17% (RR, 1.17; 95% CI (1), 0.88 to 1.55) until the lag 25th day, respectively. Based on the results, increasing temperature significantly increased the hospitalization rate of cardiopulmonary patients, but the effect of cold was not significant on the population as well as age and gender subgroups. Study have also proved that there is no significance correlation between air pollutant and Cardiovascular & respiratory diseases.
ABSTRACT
This study aimed to investigate the influence of physical and mental workload on safe behavior of employees in the automobile industry. The 150 workers of the two industries of machining and foundry of an automobile parts manufacturer participated in this correlational study. Safety behavior, NASA-TLX, and Borg scale questionnaires were used to collect data. Independent t-test, analysis of variance and Pearson correlation coefficient applied to the analysis of data. The NASA-TLX showed that the dimensions of physical and mental demand had the highest score and the performance had the lowest score. Excessive physical pressure was also reported among workers. The Score of safety observance, safety participation, and safety behavior were at a moderate level. There was a significant difference in the physical workload of employees who had an accident and did not have an accident (P = 0.001). The results showed that if the same mental workload had been imposed on workers and simultaneously more physical workload had been experienced, the probability of an accident increased. The overall mental workload and physical pressure among workers were reported at a high level. Safe behaviors were moderate among employees. Therefore, the implementation of effective intervention programs to adjust workload, participatory ergonomics, provide workload balance to improve job satisfaction, eliminate inappropriate working conditions and increase the number of operators, management programs such as job rotation between Machining and Foundry and other workshops, increase rest time and creation of a strong teamwork safety climate can reduce physical and mental workload and prevent accident among workers, improve their performance and wellbeing.
ABSTRACT
Penicillin G (PG) is one of the most widely used antibiotics around the world. The release of PG in an aqueous solution leads to contamination of water resources. This study aimed to determine the efficiency of modified Eskanbil activated carbon for the removal of PG from aqueous solutions. The NH4Cl-induced activated carbon was synthesized by a simple method and used for the degradation of PG in contaminated water. Activated carbon was characterized by Fourier transform infrared spectroscopy (FTIR), Field emission scanning electron microscopy (FESEM), and Brunauer-Emmett-Teller (BET) surface area analysis. The four main reaction parameters optimized in this study were pH, time, the concentration of the EAC (Eskanbil Activated Carbon), and initial PG concentration. The synthesized carbon was characterized and the results showed it as a mesoporous material with the BET specific surface area of 1473 m2/g and pore volume of 0.81 cm3/g. The maximum PG adsorption onto EAC was observed at the pH of 6. The PG removal of 33% at an EAC concentration of 0.1 g/L increased to 99.98% at an activated carbon concentration of 0.5 g/L. The isotherm and kinetic studies of PG removal by EAC showed that the Freundlich model (R2 > 0.995) and the pseudo-second-order (R2 > 0.983) equation represented the best fit with the adsorption data. EAC is recommended as a suitable and cost-efficient adsorbent for removing poisons, pharmaceuticals, and other emerging contaminants from water resources.
ABSTRACT
Exposure to air pollution has been associated with adverse health effects while exposure to greenspace has been associated with public health benefits. However, the available evidence on the association of exposure to air pollution with ovarian reserve markers is still scarce, with no study on such an association with greenspace exposure. Therefore, this study aimed to investigate the association of exposure to particulate matter with diameter of less than 1, 2.5 and 10 µm (PM1, PM2.5, PM10), traffic indicators (distance from women's residence to major roads and total street length in different buffers around women's residential address) and greenspace indicators (residential surrounding greenspace and distance to green spaces) with serum levels of anti-müllerian hormone (AMH) and follicle stimulating hormone (FSH) as markers of ovarian reserve. This cross-sectional study was based on 67 women residing in Sabzevar, Iran (2018). Basal serum levels of FSH and AMH were measured by the enzyme-linked immunosorbent assays (ELISA). Land use regression models were used to estimate PMs concentrations at residential addresses and the average of normalized difference vegetation index (NDVI) in different buffers was used to characterize residential surrounding greenspace. Multiple linear regression models were developed to estimate the association of AMH and FSH with exposure to air pollution, traffic, and greenspace (one at a time) controlled for relevant covariates. In fully adjusted models, there was an inverse association between exposure to PM1, PM2.5 as well as total street length in 100 m buffer around women's residence and AMH level (ß = -0.89, 95% confidence interval (CI): -1.43, -0.35, P-value ≤ 0.01, ß = -1.11, 95% CI: -1.67, -0.55, P-value ≤ 0.01 and ß = -0.76, 95% CI: -1.48, -0.50, P-value = 0.03, respectively). Moreover, increase in distance from home to nearest major road as well as residential surrounding greenspace (100 m buffer) and decrease in residential distance to a green space larger than 5000 m2 were associated with increase in serum level of AMH. However, we did not observe any significant association between exposure to air pollution, traffic, and greenspace with FSH level. Overall, our findings supported a beneficial association of exposure to greenspace and detrimental association of exposure to air pollution with ovarian reserve.
