مجله بهداشت و ایمنی کار
سال سیزدهم شماره 2 (تابستان 1402)

Given the high prevalence of low back pain in manual handling activities, its known relationship with spinal loads, and the role of muscular fatigue and the body’s adaptive mechanisms to counteract fatigue, this study investigated the effect of repetitive lifting tasks on trunk muscular fatigue and the kinematics of the spine and load-in-hand.

Eighteen male volunteers lifted a box from the floor to their waist height at a pace of ten lifts per minute until they could no longer continue the task and reported the highest level of exhaustion. Kinematic data and muscle electromyographic activity were simultaneously recorded using a motion capture system and an electromyography device. In this study, average trunk flexion angle and trunk angular velocity were calculated as trunk kinematic variables, while average box vertical travel distance, average box horizontal displacement from L5-S1, and average box vertical displacement velocity were considered as box kinematic variables. The median frequency of electromyographic signals from selected muscles was quantified as a muscle fatigue indicator. Since subjects performed different lifting cycles, the total number of cycles was divided into five distinct blocks for data analysis.

The results showed significant effects of lifting trial blocks on trunk angle (p=0.004) and vertical box displacement (p<0.001). Median frequency was significantly affected by lifting blocks for right (p=0.016) and left erector spinae (p=0.014), right (p=0.021) and left multifidus (p<0.001), right latissimus dorsi (p=0.001), and left rectus abdominis (p=0.039).

Overall, the results highlight variations in most kinematic parameters and a reduction in the frequency content of EMG signal spectra. These changes serve as indices of the central nervous system’s control over lifting behavior under dynamic conditions. A better understanding of these central nervous system adaptations could have practical applications in interventions such as workstation design, exoskeleton development, and worker training to manage musculoskeletal disorders.

The important parameters for evaluating the performance of particle filtering respirators in international standards are the filtration efficiency and respiratory resistance of the mask filter against airflow passage. To improve nanofiber filtration efficiency while creating the least breathing difficulty for the wearer, various research has been or is being conducted worldwide. This study investigated the effect of using polyacrylonitrile (PAN) nanofiber composite membrane and montmorillonite clay nanoparticles (MMT) in enhancing particle-filtering respirators’ filter performance, achieving higher filtration efficiency while maintaining optimal respiratory resistance conditions.

First, PAN polymer solution containing zero, 1%, 2%, 3%, and 5% MMT nanoparticles was prepared, and then PAN/MMT nanofiber composite membrane was synthesized in an electrospinning machine. Filtration efficiency was measured in diameter range of 0.3, 0.5, 1, and 3 microns using sodium chloride aerosol. Additionally, filter breathing resistance was measured at flow rates of 30, 85, and 95 liters per minute.

The efficiency of synthesized composite nanofilters for particle purification can be improved by adding MMT nanoparticles to PAN nanofibers. Optimal MMT concentration was found to be 2%. This addition resulted in an increase in filtration efficiency for particles with sizes of 0.3, 0.5, 1, and 3 microns by 4.2%, 4.88%, 3.77%, and 2.75% respectively without causing significant difference in respiratory resistance. Improved filtration efficiency can be attributed to enhanced morphology of composite nanofilters resulting from addition of MMT nanoparticles. Adding 2% MMT nanoparticles to PAN nanofibers resulted in uniform distribution and smaller fiber dimensions which did not significantly affect Packing density and porosity.

If 2% of MMT nanoparticles are added to PAN nanofibers and used to produce particle respirators, resulting respirator will exhibit a 4.2% increase in particle filtration efficiency without increasing breathing difficulty for user. This result can help protect users from particulate pollutants in air pollution conditions.

Colored noises with acoustic and psychoacoustic characteristics have several biological effects on human or animal health. While studies on auditory effects focus on noise’s physical aspects, its psychoacoustic aspects can also result in health and safety risks. Therefore, this study aims to investigate frequency-based damages due to exposure to colored noise in an animal model.

Twenty-four male Wistar rats were randomly divided into four groups (6 in each group). The groups included the control (no exposure) and three exposure groups (white, pink, and violet). The rats were exposed to 110 dB SPL for 4 hr/day for 14 consecutive days. Auditory brainstem responses (ABR) with click and tone-burst stimuli were recorded one day before (baseline), 7, and 14 days after exposure. Statistical analyses were conducted using ANOVA and repeated measures ANOVA.

There was a statistically significant increase in ABR threshold values in exposure groups (p<0.05). Hearing threshold shifts in the white noise group showed a homogeneous pattern, violet noise showed an increasing pattern, and pink noise showed a decreasing pattern in low frequencies and a homogeneous pattern with increasing frequency. The highest shift in hearing threshold was observed in exposure groups from day 0 to 14. Additionally, the shift in hearing threshold in the second week was less than in the first one.

The current study observed that noise’s power spectral density affected hair cells’ damage severity. Accordingly, pink noise causes less damage to the cochlea compared to white and violet. Over time after noise exposure, cochlear pathogenesis gradually decreases and hair cell lesions become stable.

Reliability is always of particular importance in system design and planning; thus, improving reliability is among the approaches for achieving a safe system. Simulation methods are widely used in system reliability assessment. Therefore, this study aims to assess the reliability of the City Gate Gas Station (CGS) using Monte Carlo Simulation (MCS).

This descriptive and analytical study was conducted in one of the CGSs of North Khorasan Province in 2021. The CGS process was carefully examined and its block diagram was plotted. Then, failure time data of CGS equipment were collected over 11 years and time between failures of subsystems was calculated. The failure probability distribution function of subsystems was determined using Easy Fit software and Kolmogorov-Smirnov test. Moreover, subsystems’ reliability was estimated by MCS. Finally, station reliability was calculated considering the series-parallel structure of the CGS.

The results revealed that the failure probability density distribution function of CGS subsystems was based on gamma and normal functions. The reliabilities of filtration, heater, pressure reduction system, and odorize were calculated as 0.97, 0.987, 0.98, and 0.992 respectively, and their failure rates were 0.000003477, 0.0000014937, 0.0000023062, and 0.0000009169 failures per hour respectively. The station reliability was calculated as 0.93.

The failure probability distribution function and reliability assessment of subsystems were determined by data modeling and MCS respectively. Filtration and pressure reduction systems had the highest failure rate and required a proper maintenance program.

Fire in hospitals and medical centers can lead to unfortunate and dire accidents due to the immobility of most patients, the presence of expensive medical equipment, and the essential role of hospitals in providing health services to people. This study aims to increase fire safety in a healthcare training center in Qazvin.

The latest NFPA 101A was used for fire risk assessment in seven departments of an educational hospital in Qazvin City in 2021-2022. The study calculated the residential risk factor for residents of each area, examined fire safety parameters and determined their risk factor, calculated the obtained points of the area under evaluation, determined the minimum required points in different areas of fire safety, and estimated the fire risk level.

  ICU 1 and 2 departments, CCU 1 and 2, central warehouse, pharmacy warehouse, and hospital facilities were selected for fire risk assessment. The ICU building had the best condition with a total fire safety point of 21.1. The facility building, with a total fire safety point of -14.5, was in the worst condition.

The results showed the need for more attention from researchers to conduct studies in outdoor environments, in various parts of the country, on development and validation of novel heat stress indices, and on implementation and evaluation of control measures in environments with high heat stress.

Many general indicators have been proposed to assess an organization’s safety performance. However, due to their holistic nature, these indicators may not always reflect safety-specific aspects of an organization’s performance. In other words, the nature of an organization’s activities necessitates the use of specific criteria to better reflect safety performance. This study aimed to identify and measure key safety performance indicators using the Delphi method in Alborz Province Electric Power Distribution Company.

This descriptive, survey-based study utilized the Delphi method to collect the opinions of 11 safety experts in the electric power distribution industry. Opinions were gathered in four phases, and key indicators were determined in the last phase of the study. These indicators were subsequently used to evaluate the safety performance of Alborz Electric Power Distribution Company for three months.

This study identified and documented 34 safety activities. The expert group proposed 20 indicators in the first phase of the Delphi method. In the second and third phases, four and one indicators were eliminated, respectively, because they did not receive the required score. The content validity ratio (CVR) and content validity index (CVI) were calculated for the remaining 15 indices in the fourth phase. The results revealed that the mean quarterly performance scores of Alborz Province electric power distribution districts and departments in 2016, including Nazarabad, Savojbolagh, Mehrshahr, Fardis, West, East, Taleghan, and Eshtehard, were 78.9, 54.7, 78.8, 75.9, 75.7, 80.8, 61, and 83.5 out of 100 points, respectively.

The Delphi method is useful for identifying key safety performance indicators. The indicators discovered using this technique are active indicators (pre-accident) that are crucial in determining Alborz Electric Power Distribution Company’s safety performance. These indicators are suggested for use in evaluating the safety performance of other electric power distribution companies.

Physical fatigue is one of the major risk factors for work-related musculoskeletal disorders and has many life and financial costs. The impact of physical/biomechanical, psychosocial, environmental, and individual risk factors on muscle fatigue is undeniable. The aim of this study is to model the phenomenon of muscle fatigue (as output) in the hand in work environments based on these risk factors (as input) using soft computing methods.

In the first step, associated risk factors of fatigue for 156 subjects (in three job categories) were assessed using Copenhagen environmental, psychosocial, demographic, and Man-TRA tools. Then, the Roman-Liu equation and mean square amplitude of acceleration waves were used to measure fatigue with a dynamometer and a three-axis accelerometer, respectively. Finally, according to the nature of risk factors and the phenomenon of fatigue, six categories (24 methods) of supervised machine learning (SML) based on classification were selected. MatLab software (MatLab R2017b, The Mathworks Inc., MA, U.S.A.) was used to fit the models using SML.

The best-fitted models in the first and second half of the work shift were obtained using support vector machine methods. Physical risk factors had a significant impact on physical fatigue. After filtering low-priority risk factors, in the first half of the work shift, the most optimal model had an accuracy of 71.8%, precision of 72.5%, sensitivity of 76.9%, specificity of 70.8%, and discrimination power equal to 73%. In the second half of the work shift, the accuracy, precision, sensitivity, and specificity of the optimized model were 60.3%, 57.5%, 50%, and 46.9%, respectively, and the discrimination power was obtained at about 62%.

The fitted models for hand fatigue had acceptable performance in both sections of the shift but can still be optimized. Therefore, it is necessary for future studies to improve the quality of input and output data and include other dimensions affecting fatigue such as cognitive workload and type of work shift in future models.

Numerous studies have been conducted on the development of modern insulators, including nano-insulators. However, a comprehensive study has yet to be performed to review and investigate the thermal properties of these insulators. Consequently, this study aimed to examine the effect of nanomaterials on thermal insulation function.

In this review, articles were searched for in English databases (PubMed, Web of Science, and ScienceDirect), Persian databases (Magiran, SID), and Google Scholar. The keywords used in the search were Nano Material, Nano Insulation, Thermal Insulation, Thermal Insulator Stability, and Thermal Conductivity in both English and Persian.

Of the 4068 studies identified through search databases, 15 were selected according to the entry criteria. Among the studies, the three types of silicone, composite, and aerogel insulation had the highest frequency (each 26.67%), and SiO2 nanoparticles were the most prevalent nanomaterial (26.67%). According to the studies, the type of nanomaterial used in insulation will improve its properties such as thermal resistance, mechanical strength, dielectric strength, tensile strength, elasticity, and hardness.

The results of this study showed that using nanotechnology could be an effective step in improving the properties of insulation materials, the most important of which is increased thermal resistance. Moreover, nanotechnology insulators can prevent thermal energy loss, reduce costs, and provide safety and comfort.

Pipelines are widely used to transport large volumes of oil and gas over long distances. Risk assessment can help identify risk factors and create an appropriate action plan and strategy to reduce or eliminate them. The main goal of this research is to provide a method for assessing the risk of pipelines based on the Fuzzy Inference System (FIS), creating a systematic format that is expected to be a more effective, accurate, and reliable model for controlling risks related to oil and gas pipelines.

In this article, fuzzy logic is used to model uncertainty and present a model for assessing pipeline risk. The Muhlbauer method, one of the most common risk assessment methods for oil and gas pipelines, has been employed to determine critical factors affecting the lines. This method has been implemented using the Mamdani algorithm and based on expert knowledge in the fuzzy logic toolbox of MATLAB software. To validate the results of the proposed model, data from the interphase pipelines of the fifth refinery of the South Pars Gas Field have been used as a study sample.

The findings from the implementation of the model created in South Pars Phases 9-10 pipelines (on shore) show that the studied pipelines are divided into three parts (A, B, and C) based on indicators such as population density and equipment deployment. Part C of the pipeline has the highest risk, with third-party damage and design being the most important factors affecting it. Part B has the lowest level of risk and results in the fewest consequences for human accidents. It was also observed that corrosion is essential in increasing leakage and risk in all three pipeline parts.

To verify the developed model, the inter-phase shore pipe of phase 9-10 refinery in the South Pars Gas Field was considered as a case study. The findings indicate that the proposed method provides more accurate and reliable results than traditional methods. Factors such as improper operation, dispersion, receptors, leakage volume, and product risk, which are other factors affecting pipeline risk, were not considered in traditional methods. Therefore, the risk level of oil and gas pipelines can be calculated using this model as a comprehensive and intelligent tool.

In many occupations, users must sit for prolonged periods during their job activities. Prolonged sitting is associated with fatigue, leading to postural changes that can increase spinal loads. Despite the importance of this topic in terms of the extent of prolonged sitting and its subsequent adverse consequences, little attention has been given to this occupational activity. Hence, this study investigates changes in neck, trunk, and muscle activities and fatigue levels in prolonged sitting computer tasks.

Twenty healthy subjects (gender-balanced) from the student community with at least five years of experience in computer work aged between 20-30 years were asked to randomly perform three types of computer tasks for 90 minutes (each task for 30 minutes). Electromyographic (EMG) activities of right and left cervical (ESCR and ESCL), thoracic (ESTR and ESTL), and lumbar (ESLR and ESLL) erector spine and upper trapezius (UTR and UTL) muscles were continuously recorded. Root mean square (RMS) and median frequency were extracted as EMG metrics. Subjects also rated their perceived discomfort using a Visual Analogue Scale (VAS). The effect of time, gender, and their interaction on muscle EMG activities, fatigue, and discomfort were explored.

Time had a statistically significant effect on UTR, ESCR, and ESTR muscle activities. UTL and ESCR muscle activities significantly differed between male and female subjects. Further, the findings confirmed the interactive effect of time and gender on ESTR muscle activity. UTR, ESCR, ESCL, ESTL, and ESLL muscles’ fatigue index changed statistically over time.

The findings confirmed neck and trunk muscles’ fatigue by increasing muscular activity and reducing frequency contents over time, per the subjective rating of discomfort.

With the spread of the COVID-19 pandemic and the lack of adequate protection by existing protective equipment, many researchers’ attention has turned to developing improved respiratory protection equipment. Considering their special properties and nanoscale dimensions, electrospun nanofibers are a suitable option for improving operational characteristics of substrates used in conventional facemasks. This study aimed to optimize the electrospinning process of polyacrylonitrile nanofibers (PAN) containing ZIF8 and use the optimized substrate in medical facemasks to increase their protective performance.

This study employed an environmentally friendly method to synthesize ZIF8 in an aqueous environment. Then, PAN/ZIF8 polymer solutions were prepared in dimethylformamide. The effects of electrospinning parameters, including electrospinning voltage, polymer solution concentration, electrospinning distance, and polymer injection flow rate on diameter and uniformity of nanofibers were investigated. Electrospinning conditions were optimized using response surface methodology (RSM) and central composite design (CCD) to obtain desired values for response (dependent) variables. Finally, optimized PAN/ZIF8 and PAN nanofibers were electrospun on spun-bond substrate. Base weight, average diameter of fibers, filtration performance, pressure drop, and quality factor of fabricated substrates were assessed.

According to results, optimal conditions for electrospinning of PAN/ZIF8 polymeric solution for polymer concentration (A), electrospinning voltage (B), electrospinning distance (C), and polymer injection flow rate (D) were respectively 70 w/v%, 20 kV, 18 cm, and 0.4 ml/h. Moreover, despite lower base weight of PAN/ZIF8 nanofiber mask, it displayed higher filtration performance (98.51%), lower pressure drop (31.42 Pa), and higher quality factor (0.140 Pa-1) in comparison to other studied masks.

Experimental models developed in this study provide acceptable values for filtration efficiency and quality factor for filtration applications. Additionally, they serve as a guideline for subsequent experiments to produce uniform and continuous nanofibers with desired diameter for future applications in absorbent media (intermediate absorbent layers) of respirators.

Iran has the most extensive maritime transport fleet in the Middle East, with 2700 km of water border with other countries in the region. However, the complex and hazardous marine environment has turned this advantage into a disadvantage. On the other hand, technological advancement has added to the complexity. Thus, new accident analysis tools should be developed to bring unity to marine casualty analysis and improve the analyst’s power of discovery from incident information. The current project aims to develop a specialized AcciMap-based marine accident investigation method.

The primary stages of this applied descriptive study include data collection, method development, and validation. The necessary information about the factors leading to marine accidents was initially gathered through a review of previous studies, expert interviews, and analysis of actual cases. The AcciMap technique was then partially developed, and marine experts approved the designed model.

This study’s results included an AcciMap model established on three levels: external influences (national and international), intra-organizational factors, and environmental/individual conditions and individual activities. Whereas external factors (international and national) are categorized into three main layers, two sublayers, and 13 secondary sublayers, intra-organizational factors are categorized into two main layers, 11 sublayers, and 35 secondary sublayers, and environmental/individual conditions and individual activities are organized in one main layer, three sublayers, and 11 secondary sublayers.

The developed approach can identify flawed levels and determine who is responsible for implementing corrective action. Because it includes emerging components that are effective in accidents, the method used in this study can better examine data from marine accidents.