مجتبی ذکائی

Nowadays, the statistics prove that the underground construction projects in the country are increasing, as well as the number of accidents arising from the unsafe condition of these projects. The purpose of this study was to create a framework of safety and health risk management in the construction phase of the Tehran Metro Line 7 tunnel, using IoT technology.

In the first stage, the national safety and health standards, laws and requirements related to the mentioned hazards were collected. In the second stage, the criteria and permissible limits of exposure to occupational hazards were determined. Next, sensors with optical, auditory, gas detection, and visual capabilities connected to the network were examined, and computer programming and comparing sensor information with the specified standards were carried out. Finally, intelligent warning and control systems related to the determined hazards were proposed.

In this study, a combined model of risk management utilizing IoT for controlling and monitoring safety and health hazards such as sound, light, explosive and toxic gases was proposed. According to the model, sensors for detecting the mentioned hazards were determined and coded based on the permissible limit of each of the harmful factors.

This study has shown that by employing specialized IT and safety knowledge and utilizing relevant software and hardware, the concept of the Internet of Things can be utilized in precise monitoring of the concentration levels of flammable and toxic gases, as well as monitoring of physical agents such as noise and light in various workplace, such as metro tunnel construction sites.

Noise is one of the most important environmental stressors, which, along with the prevalence of exposure in the work and living environment, has various effects. Noise exposure can create positive or negative consequences at different levels. Based on this, in the present study, brain wave changes in exposure to different levels of noise were investigated. In this experimental study, 72 student volunteers with an average age of 26.27 years old, participated in this study after meeting the exclusion criteria and receiving sufficient training regarding the implementation procedure. Before starting the test, demographic questionnaires, noise sensitivity, and audiometry were completed for the participants. For exposure, a noise level of 45 dB was chosen as the background sound, and three levels of 75, 85, and 95 dB were selected for exposure. The participants were exposed to the determined facial pressure level for half an hour and rested for half an hour after that. During exposure to the noise, the brain waves of the volunteers were used by the portable EEG device Ewave, 16 channels. And the results were analyzed by the mat lab v12 software. The results of the study show that exposure to two levels of 75 and 85 dB of absolute power alpha has increased in 14 brain channels, including CZ and O2 channels. The results showed that the noise level of 75 dB compared to the background state did not change significantly in any of the channels (P>0.05). At the level of 85 and 95 dB, the absolute power of the beta frequency band has increased. At the level of 95 dB, this increase is statistically noticeable and significant in almost all brain regions (P<0.05). Based on the results of this study, it can be said that exposure to noise causes changes in neuronal activities in the brain, and this can affect the performance of the exposed workers.

Due to the increase in the provision of electronic services to citizens in government offices, the number of computer users and the occurrence of musculoskeletal disorders have increased. Therefore, this study aimed to predict and model the complex relationships between the risk factors of musculoskeletal disorders in computer users working in government offices by an artificial neural network.

The current cross-sectional study was conducted in 2020 on 342 employees of various government offices in Saveh city. First, the researcher visited the work environment to identify the problems and measure the environmental factors. Then, ergonomic risk assessment and psychosocial factors were evaluated using the Nordic questionnaire and the ROSA method. The effect of various factors in causing musculoskeletal disorders was investigated using a logistic regression test.Then the resulting data were collected and modeled by one of the neural network algorithms. Finally, artificial neural networks presented an optimal model to predict the risk of musculoskeletal disorders.

The results showed that by increasing the level of social interactions, the level of demand, control, and leadership in the job, musculoskeletal disorders in men and women decrease. There was a significant relationship between the prevalence of musculoskeletal disorders and job demand, job control levels, social interaction levels, leadership levels, organizational climate levels, job satisfaction levels, and stress levels, in addition between reports of pain in the neck and shoulder and wrist/hand region. There was a significant relationship with the overall ROSA score. Also, there was a significant relationship between the report of pain or discomfort in the neck area with the phone screen risk score, wrist/hand with the keyboard-mouse risk score, and shoulder, upper back, elbow, and lower back with the chair risk score. The accuracy of the presented model for predicting musculoskeletal disorders was also about 88.5%, which indicates the acceptability of the results.

The results showed that several factors play a role in causing musculoskeletal disorders, which include individual, environmental, psychosocial, and workstation factors. Therefore, in the design of an ergonomic workstation, the effects of the mentioned factors should be investigated. Also, predicting the effectiveness of each of the mentioned factors using an artificial neural network showed that this type of modeling can be used to prevent musculoskeletal disorders or other multifactorial disorders.

Many industries have multiple factors harmful to health, leading to simultaneous exposure of these factors to each other. Noise is one of the most common physical parameters in the work environment. On the other hand, heat is also increasing due to various energy processes in industries. Therefore, this study was conducted with the aim of determining changes in physiological parameters and visual-auditory attention in acute exposure to heat and noise.

In this experimental study, 72 individuals (36 men and 36 women) aged between 23 and 33 years participated according to the inclusion criteria. In total, 12 different test modes were performed (3 temperature levels and 4 noise pressure levels). The test was conducted for each person in 4 steps during a specific day. The duration of exposure to each condition was half an hour, and a half-hour rest was given between each test condition. Saliva samples of each subject were collected before and immediately after exposure to noise and heat. Also, The Integrated Visual and Auditory (IVA) was recorded by the participants simultaneously.

The results of combined exposure to noise and heat on visual and auditory attention showed that only two modes of combined exposure, SPL95+WBGT34 and SPL95+WBGT29, caused a significant increase (P < 0.05) in mental workload and a significant decrease (P < 0.05) in visual and auditory attention. In addition, the results showed that independent exposure to noise at the levels of 85 and 95 dB and exposure to heat at higher temperature levels of 34 and 29 degrees Celsius cause a significant increase (P < 0.05) in salivary cortisol after exposure. The results of the effect of combined exposure to noise and heat on salivary cortisol showed that three experimental modes of combined exposure (SPL85+WBGT34, SPL95+WBGT29, and SPL95+WBGT34) caused a noticeable and significant (P<0.001) increase in salivary cortisol.

Indeed, salivary cortisol can be recommended as a physiological index to evaluate noise and heat exposure. It’s also noteworthy that salivary cortisol is more affected by noise and heat exposure than cognitive performance.

Musculoskeletal disorders are one of the main problems of industries and administrative jobs, which are caused by various factors. The study aimed to determine the role of each individual, physical, psychosocial, and environmental factors in causing musculoskeletal disorders; Identifying and controlling risk factors, is an important step in reducing and preventing these disorders.

The present study is a cross-sectional study of 342 employees working in different government offices in Saveh city in 2021. In this study, the Nordic summary questionnaire and ROSA checklist were used to investigate the prevalence of musculoskeletal disorders. Also, to investigate individual and psychosocial factors of the work environment, a personal information questionnaire and a general Nordic questionnaire were used. In addition, the evaluation of conditions of work environment was done by Hagner model E1 lux meter devices, TIS10 model thermal stress measuring device, and TES1358 sound meter. Finally, all the resulting data were entered into SPSS software and tested after coding.

The results showed that body mass index and gender have a significant effect on suffering from musculoskeletal disorders (p-value<0.05). The results of the Pearson correlation test indicated that there is a significant relationship between the report of pain or discomfort in the neck area with the screen-phone risk score, wrist/hand with the keyboard-mouse risk score, as well as shoulder, upper back, elbow and lower back with the chair risk score. p-value <0.05). In addition, there is a significant relationship between the report of pain or discomfort in the neck, shoulder, and wrist/hand areas with the overall ROSA score. Also, there is a significant difference between the prevalence of musculoskeletal disorders and levels of job demands, levels of job control, levels of social interactions, levels of leadership, levels of the organizational atmosphere, levels of job satisfaction, and levels of stress (p-value<0.05).

The results of this study showed that several factors play a role in musculoskeletal disorders, such as job requirements, social interactions, and stress in the group of psychosocial factors that had considerable importance in causing musculoskeletal disorders. Among the individual factors, gender and body mass index (BMI) is important, and among the workstation factors, the chair has played a significant role in causing musculoskeletal disorders.

Awareness of a disease can affect people's attitudes and practices, and wrong attitudes and practices directly increase the risk of infection. The aim of this study was to determine the status and relationship between knowledge, attitude and practice of industry employees about personal protection measures effective in preventing covid-19 infection in Kaveh Industrial City.

In this cross-sectional study, which was conducted to assess the knowledge, attitude and practice of individuals about effective personal protection measures to prevent COVID-19 in Iran in the summer of 2020, a researcher-made questionnaire was used. In this study, after selecting 24 factories in Saveh Industrial City, 500 questionnaires were distributed among the employees by quota sampling. After collecting and reviewing them, 461 questionnaires were fully answered and studied. Finally, the scores related to all three parameters were calculated and Pearson correlation coefficient was used to examine their relationship.

The average age of participants in this study was 36.4 ± 6 and had a work experience of 12.66± 6.6 years. It was determined that the score related to the awareness of the virus nature was greater than the awareness of personal protective measures. It was deduced that, while 88.9% of individuals are well aware of the nature of the virus, 71.8% were in the subgroup of taking protective measures. The highest level of desirable score was related to their attitude, which accounted for 92.4%. In terms of preventive practice, 80.3% of participants exhibited moderate adherence to good practices towards preventing Covid-19 infection

individuals had heightened awareness towards the nature of Covid-19 virus, however they had little awareness towards preventive health measures. consideration that majority of people have received concerned information via television, its essential to give accurate and timely information in order to increase community’s awareness as well as optimal behavior in preventing Covid-19

Investigations of accidents in industry have shown that various factors affect the occurrence of accidents. Therefore, the aim of this study was to investigate the relationship between the prevalence of occupational accidents with individual and occupational factors in the industrial work environment of Qom province.

This descriptive study was performed based on the incidents registered in the Labor Inspection Office of Qom Province in 2017. All cases were selected and 1048 cases were reviewed according to the accurate registration of incidents. Necessary parameters were extracted from accident reporting forms and their frequency and frequency percentage were analyzed by SPSS 18 software.

The highest number of accidents was in the age range of 20-30 years with less than 5 years of work experience. The lowest number of accidents was related to bachelor's degree and higher. In addition, a high number of victims (41.5%) were involved in construction activities. In the study of the working population, the highest number of accidents was related to workshops with a staff number of 10-24. In investigating the causes of accidents, 33.2% of accidents were identified as lack of safety training and 24.2% as lack of safe work procedures. In the group of equipment causes, the highest share of accidents was due to the lack of proper equipment and in relation to human causes, the main reason for the accident was the non-stopping of the device during repair.

The results of the present study showed that demographic and occupational factors, such as age, work experience, and type of industry were very important in the occurrence of industrial accidents. In addition, it was found that managerial, equipment and human causes each have an effective role in the occurrence of accidents, which can be significantly reduced using more supervision by managers and recruiting safety and health officials, and finally observing safety principles in all areas of work.

Determining methods for assessing heat stress in different work environments is one of the major challenges for researchers in this field. The purpose of this study was to validate WBGT index and heat pressure assessment (HPA) by some physiological responses in Iranian South Oil Company.

This descriptive-analytical study was carried out on 154 employees of Kharg, Asalouyeh and Mahshahr oil terminals recruited from three different working conditions including indoor, outdoor and rest environments in the summer. The amount of heat stress in the workplace was evaluated by WBGT index HPA method. To meet this purpose, the environmental parameters i.e., temperature, wet temperature, radiation temperature, relative humidity, water vapor pressure and air flow rate were determined. In addition to the direct reading method by the WBGT meter, ISO 7243 was used to calculate the WBGT index. In order to validate the heat stress indicators, physiological parameters of oral temperature, tympanic temperature and work metabolism were measured.

The results of paired sample t-test showed a significant difference between WBGT index and HPA in indoor and outdoor environment (P<0.05). Moreover, there was a significant difference between the physiological indices of oral and tympanic temperatures and work metabolism in the indoor and outdoor environment (P<0.05). Furthermore, the correlation test was significant between WBGT index as an independent variable and HPA as a dependent variable (P<0.05)  and showed a high correlation (R2=0.914) between WBGT index with oral temperature and tympanic temperature . Also, the rate of work metabolism was significantly related with the aforementioned parameters (P<0.05) and was equal to R2=0.423, R2=0.335, R2=0.552, respectively. The correlations were also significant between HPA with Oral temperature, tympanic temperature and work metabolism (P<0.05)and were equal to R2=0.632, R2=0.605, R2=0.557, respectively. The results showed also that the correlation rate between the HPA with physiological parameters is stronger than that between physiological parameters with the WBGT index.

This study showed that WBGT and HPA methods are useful for assessing the heat stress of Iranian South Oil Company. Also, the HPA method is more reliable for assessing heat stress in these regions.

Electrocardiography is one of the most useful and common tools for examining heart function. In studies in the 1960s, heart rate variability (HRV) was introduced and used as a non-invasive tool to evaluate the functions of the autonomic nervous system and other functional disorders of the heart under various conditions. In addition to the clinical applications of heart rate variability, this physiological parameter is also widely used in ergonomics and occupational health. In the study of mental workload, exposure to industrial noise, shift work, stress, and other parameters related to the workplace benefit heart rate variability. Heart rate variability is regulated by the autonomic nervous system and by the sinoatrial (SA) node. The autonomic nervous system is divided into sympathetic and parasympathetic branches, the autonomic nervous system is divided into sympathetic and parasympathetic branches, thereby affecting the heart rate and heart rate variability. Sympathetic activity tends to increase heart rate and decrease heart rate variability, while parasympathetic tend to reduce heart rate and increase heart rate variability. The most prominent component of the variable heart rate period is a respiratory arrhythmia (RSA), which is considered to be 0.15 to 0.4 Hz. The high-frequency component is only affected by parasympathetic neural activity. Another component of heart rate variability is the low-frequency (LF) component in the frequency range, 0.04 to 0.15 Hz. This component is affected by sympathetic and parasympathetic neural activity. Many computational methods have been developed for HRV analysis, each of which is associated with strengths and weaknesses. Although there may still be difficulties in interpreting this index, it provides researchers and health experts with reliable non-invasive physiological information. HRV parameters can be classified in terms of time, frequency, and nonlinear methods. The commercially available ECG equipment does not usually include HRV features due to the lack of standard diagnostic protocols. As an alternative to this commercial software, many simple, online and free, device-independent, and portable software has been developed for HRV analysis and cardiovascular research.Heart Rate Variability Quantification: Heart rate variability can be measured in long-term (24 hours), short-term (5 minutes), and very short-term periods (less than 5 minutes) and can be analyzed as time- -domain, frequency-domain, and non-linear.1. Time-domain measuresThe simplest method to analyze heart rate variability is time-domain. Analysis of heart rate variability in the time-domain is performed through both statistical and geometric analysis, both of which are based on heart rate or RR intervals between successive QRS series. Using these methods, the heart rate can be assessed at any point in time or between normal consecutive sets. Statistical parameters recommended by the European Society of Cardiology and the American Society of Pacing Electrophysiology include: 1) SDNN 2) NN50 3) SDSD 4) SDANN 5) RMSSD 6) SDSD 7) NN50 count (Table 1).Table 1: time-domain measures of HRV Variable Units Description [1]SDNN ms Standard deviation of all NN intervals SDRR[2] ms standard deviation of RR interval series SDANN ms Standard deviation of the averages of NN intervals in all 5 min segments of the entire recording SDNN index ms Mean of the standard deviations of all NN intervals for all 5 min segments of the entire recording pNN50 % NN50 count divided by the total number of all NN intervals HR Max –HR Min bmp The average difference between the highest and lowest HRs during each respiratory cycle rMSSD ms Root mean square of successive RR interval difference HRV triangular index   Integral of the density of the RR interval histogram divided by its height TINN ms Baseline width of the RR interval histogram  2. Frequency-domain measures:Time-domain measurements information about the overall change in time series or maximum variable amplitude, but no information about periodic heart rate fluctuations. Data frequency domain analysis provides information on how power distribution is a function of frequency. According to the European Society of Cardiology, the power range of a healthy person is usually divided into four main frequency bands. The range of components used is usually: high-frequency (0.4 - 0.15 Hz), low-frequency (0.15-0.04 Hz), very low frequency (0.04 - 0.003 Hz) and infinitely low frequency (<0.003 Hz).Table 2: frequency-domain measures of HRV Variable Units Description ULF power ms2 Absolute power of the ultra-low-frequency band (≤0.003 Hz) VLF power ms2 Absolute power of the very-low-frequency band(0.0033–0.04 Hz) LF peak Hz Peak frequency of the low-frequency band (0.04–0.15 Hz) LF power ms2 Absolute power of the low-frequency band (0.04–0.15 Hz) LF power nu Relative power of the low-frequency band (0.04–0.15 Hz) in normal units LF power % Relative power of the low-frequency band (0.04–0.15 Hz) HF peak Hz Peak frequency of the high-frequency band (0.15–0.4 Hz) HF power ms2 Absolute power of the high-frequency band (0.15–0.4 Hz) HF power nu Relative power of the high-frequency band (0.15–0.4 Hz) in normal units HF power % Relative power of the high-frequency band (0.15–0.4 Hz) LF/HF % Ratio of LF-to-HF power  3. Nonlinear measures:The parameters commonly used in the analysis of time and frequency domain HRV are not always suitable for analysis due to the existence of various nonlinear phenomena in physiological signal parameters. Therefore, the use of nonlinear techniques is recommended. Pincus developed Approximate Entropy (ApEn) as a nonlinear complexity index to determine the random quantity of a physiological time series. Richman and Moorman developed a sample entropy (SampEn), a new family of statistics, to measure the complexity and data of clinical and experimental time series, and compared it to ApEn.Common heart rate analysis tools: HRV analysis has led to the development of several commercial and non-commercial software. Most commercial equipment for heart monitoring and HR analysis includes software that depends on devices for HRV analysis, but there are also software-independent. In addition to commercial tools, several free non-commercial software have been developed.Kobius:This powerful software is based on MATLAB. Kobius (version 2.1) is a free and non-commercial software for researchers and physicians (http://kubios.uef.fi 7). This software can analyze HRV in time-, frequency-domine, and non-linear indicators. Kobius is compatible with Windows and Linux operating systems, and supports both ECG and RR data formats, and performs the pre-processing operations required to detect QRS and correct corrections.gHRV:gHRV is based on the Python programming language and performs heart rate variability analysis for a specified period of time. The software can be easily run on Windows, Apple OS X Linux, or GNU operating systems. Data and formats supported by gHRV include heart rate in WFDB and ASCII formats, (IBI (InterBeat Intervals ASCII files), heart rate monitoring in polar (common heart rate recording form), and Santo wristbands. The pre-processing step involves deleting and interpolate. Updated versions of gHRV are available for free at http://ghrv.milegroup.net. This website provides information on how to download, install, and use. GHRV analyzes HRV in terms of time, frequency, and nonlinear domain.KARDIA:KARDIA is based on MATLAB programming language. All functions of this software are written in a single program (kardia.m) which is available for free (at http://sourceforge.net/projects/mykardia/). Execution of m-file requires MATLAB 7 or updated version with MATLAB signal processing toolbox. KARDIA can calculate the heart rate in any method sampled by the user by interpolating using fixed, linear, or splint methods. Linear parameters of heart rate variability in time and frequency range and nonlinear parameters can be quantified by analyzing fluctuations.VARVI:VARVI is free software designed in Python programming language for HRV analysis in response to various visual stimuli. This HRV software measures the person who is watching a video. This software has wide applications in psychiatry and psychological studies. VARVI software is available at varvi.milegroup.net.RHRV:This software is based on R programming language for HRV statistical calculations. This programming language (R) is originally implemented in the S language and is compatible with Windows and MacOSX. Several advantages of this software are available. The data file containing the heart rate in WFDB and ASCII format is entered into the software. Software package is available for download and installation.ARTiiFACT :ARTiiFACT is a MATLAB-based tool with compiler 4.13 for artifact processing and HRV analysis. ARTiiFACT has options for processing a set of data, analyzing HRV by the autoregressive and nonlinear domain model, as well as correcting respiration-related distortions, which allows raw data from the ECG to be applied bypassing the filter over, and over. Set their bypass at the appropriate critical frequency. Software, tutorials and user manuals are available for free upon request (email tobias.kaufmann@uni-wuerzburg.de).LabVIEW:LabVIEW software is a design-specific operating system that provides a development environment. It can also be used to analyze heart rate variability. LabVIEW is supported by Windows, Linux GNU or Apple OSX.POLYAN:POLYAN is based on MATLAB programming language and has a computing environment with the aim of excellent performance in numerical and visual calculations. The software can be easily run on Windows operating systems, Linux GNU or Apple OS X. POLYAN is a free software specifically designed for the simultaneous analysis of multiple signals (multi-parameter approach) to evaluate the performance of an Autonomic nervous system.aHRV:aHRV is a commercial software developed by Nevrokard for heart rate variability analysis. The software supports data in the form of ASCII, binary files in European data format and many dedicated formats.

HRV plays an important role in assessing ANS fluctuations in healthy individuals and heart patients and promoting understanding of disease mechanisms and physiological phenomena. Currently, there are commercial or semi-commercial tools that possible simultaneous ECG recording, respiration, blood pressure. Commercially available recording systems are not usually separated by HRV analysis features. Software developers have not prioritized this because HRV is not yet included in standard diagnostic protocols. However, various developers and research groups are developing software tools tailored to their specific needs. [1] - Standard deviation of NN intervals[2] - Standard deviation of RR intervals

Heat Stress in Oil and Gas Industries Is Important Concern in Safety and Health fields. The Aim Of Study Was Comparison To The Heat Stress By Experimental And Analytical Index In Two Oil Terminals In The North And South Of Iran.

This Descriptive-Analytical Study Was Carried On 130 Employees Of Neka And Kharg Oil Terminals. In This Research, HSI, AET, WBGT And P4SR Indices Were Calculated. In Order To Validate These Indicators, The Oral Temperature And Tympanic Temperatures Of Employees Were Studied. Data Analysis Was Performed Using 22spss Software.

Significant Correlation Was Found between Physiological Indices and Thermal Indices in Indoor Environment Kharg and Neka .There Is Not Significant Relationship With HSI Index. In The Outdoor Environment Kharg .Significant Correlation Was Found For All of The Indices Except For HSI Index. In Neka, With The Exception Of The HSI Index, Was Significant Correlation Between Oral Temperature And Thermal Indices, But There Is Not Significant Difference Between The Tympanic Temperatures With Thermal Indices (P> 0.05). WBGT And AET Indices Had A Significant Difference In Both Terminal Environments. The HSI Index Were not Shown Any Significant Difference at Any of These Terminals. The P4SR Index Was Not Significant Different In the Indoor Environments of Two Terminals (P> 0.05).

It was found that WBGT index and AET index are reliable indices for assessing thermal stress in oil terminals. According to them, the amount of thermal stress in outdoor environment in Kharg oil terminal was higher than NEA oil terminal.

With the developing use of electricity in all aspects of human life, electricity accidents have also increased. One of the main components of the for the prevention policy, is the safety performance assessment of the organization's or industry's by using appropriate performance indicators with related operations.

This study was a descriptive-analytical of 6 steps including: analysis of work Breakdown Structure of the project, preliminary hazard analysis of the operation, the establishing of the accident causal network, determination of control measures, extraction of active performance indicators and validation of the indicators.

In this study, the probability of occurrence of electric shock was 0.053 calculated using the method of BN and 11 active performance indicators were developed. The R-square value of the incident frequency with the active indicators of the total project was 0.819 and P-value was less than 0.05. Therefore, these results indicate that the correlation between incident frequency as an associated variable and active indicators as independent variables in the whole project is significant.

As the project progresses, the nature and level of risk of the operation of construction projects is changing. Therefore, indicators of safety performance measurements in these projects should be sensitive to rapid changes. For this reason, active indicators with a short-term measurement period are more effective in measuring the safety performance of construction operations.

Throughout the world, many efforts have been made to provide suitable tools for achieving sustainable urban development and the achievement of a sustainable city. Establishing a Health, Safety and Environment Management System (HSE-MS) is one of the tools for achieving sustainable urban development. Measuring the performance of an organization in the HSE area is a precondition for continuous improvement, which is the spirit of the new HSE management systems. Therefore, the main purpose of this research was to provide a practical model for quantitative ranking of different areas of Tehran municipality in terms of HSE performance with using of multi-criteria decision-making method.   In this descriptive-applied study, after determining functional axis and performance evaluation indicators related to each of them (29 functional axis and 154 performance evaluation indicators), through designing a questionnaire and based on the views of the expert group, weight of functional axis and performance indicators were determined using a hierarchical process analysis technique.   In this study, the weighted value for functional axis of the process based HSE in comparison to the result based HSE were higher. “Commitment and Leadership” and “HSE Certificate of Occupations” for the process based HSE, “Safety” and “Health” for the result based HSE, and “Economic Sustainability” and “Architecture and Urbanism” for urban management had the higher and lowest weighted values. The results of assessment and validation of selected indicators and functional axis showed that in designing and determining the HSE performance assessment model of municipalities, in addition to the axises and indicators of the HSE domain, factors affecting urban management can have a significant impact on the performance of municipalities in the field of HSE.

Performance assessment and also performance indicators have a great importance in all aspects of life. By these indicators appropriate responses to what is happening for make some improvement, could be determined. In the past, the safety and health performance of organizations was measured with using of some indicators from the USA Occupational Health and Safety Administration (OSHA) such as the rate of recorded injuries, the rate of lost days, the rate of workers' complaints, and so on. Determining of this information were done to compare the health and safety status of contractors and industries and ranking them. However, improvement or weakening the safety and health status is cleared by the OSHA indicators, but the ways were not determined by these indicators.
The main objective of measuring safety and health performance is to provide the necessary information on the developments and current status of strategies, processes and activities that an organization is conducting to control health and safety risks. Safety performance indicators are divided into two main categories: the leading and the lagging indicators.
The leading indicators are the organization's actions for predicting and preventing incidents and accidents before they occur, while the lagging indicators are shown the organization's performance after the occurrence of the accidents to reduce its consequences. Sustainable urban development is a high-profile goal, and its realization in metropolitan areas requires the use of efficient management practices and extensive planning. The extent and complexity of urban issues and the urban ever- increasing development have made urban management a difficult task. In addition to issues such as transportation, urban planning and management is one of the important factors that has a main influence on urban constructive factors. In organizations such as the municipality, and on a wider dimension in societies, various plans and policies such as environmental plans, safety plans, crisis management, educational policies, occupational health plans, as well as some international standards for sustainable urban development were used. The Integrated Health, Safety and Environment Management System (HSE-MS), by providing the appropriate structure and model, manages all these policies and plans, and, in addition to creating a specific order in the implementation of these programs helps to centralize costs and improve the economic status of the organization and the achievement of sustainable urban development.
Performance measurement is the main issue at all levels of the organization and its improvement needs to be measured, so an organization cannot be conceived without a performance evaluation system. Measuring the performance of an organization in the HSE field is a precondition for continuous improvement. Different organizations and industries need to design performance measurement indicators to assessment and monitor the performance of the HSE management system and determine the effectiveness of themselves performance. Determining the performance assessment indicators of HSE in addition to measuring of the management system performance can lead to systematic identification of improvement points and reduction of HSE related risk factors and ultimately lead to increased organizational productivity. The research shows that the applied, comprehensive and structured model has not yet been designed and implemented to ensure the efficiency and effectiveness of the HSE management system in different metropolitan areas.
Although there are some retrospective and prospective HSE performance assessment indicators in municipalities but these indicators are purely result-oriented and the creation and institutionalization of processes related to the seven components of the health, safety and environmental management system cannot be measured by them. What matters here is to create an appropriate method with sufficient accuracy to determine the effectiveness of the system. This research, while introducing an innovative model for quantitative ranking of different municipality areas of metropolitans according to the HSE performance assessment with using of AHP technique, the final goal is the determine of key indicators of urban HSE performance assessment. This descriptive-applied study was conducted in four steps.
Step 1: Selecting HSE Performance Measurement Indicators and Urban Management:In the first step, a variety of safety and health management systems (HSE-MS, OHSAS 18001, ISO 14001, etc.), a variety of existing national and international health and safety assessment methods, guidelines, and requirements for safety and health management systems for determining the performance measurement indicators were studied. At this step, through the field visits of the different areas of the municipality and observing work processes, interviewing and organizing various meetings with HSE managers and experts, and studying documentation, the HSE performance assessment indicators in the three areas including process-oriented, result-oriented and urban management were categorized.
Step 2: Selecting the components of the performance monitoring system:The findings suggest that the use of a systematic approach in different domains, in addition to integrating activities, has improved efficiency and effectiveness and increased operational efficiency. Accordingly, many organizations have set up various health, safety and environmental management systems as the basis of themselves operations. The use of the main components of an integrated management system to identify weaknesses or strengths of system is one of the effective measures for measuring performance. At this step, after determining the assessment axes, the performance assessment components were identified for each of the performance monitoring axes.
Step 3: Development of Urban HSE Performance Assessment Indicators:At this step, the indicators for assessing the performance of the urban HSE management system were determined based on the components of each of the performance monitoring axes. According to the main components, the HSE management system was included 18 components such as commitment and leadership, policy, resources, etc. Also in the urban management part 6 components including economic sustainability, social sustainability, architecture and urbanization, demographics, political, legal, and industrial was considered. Indicators related to the result performance were also developed based on the components of the HSE performance output monitoring system in the six areas including safety, health, environment, education, culture and HSE of citizenship.
Step 4: Select Key Performance Indicators:To create an effective HSE-MS performance measurement method, it is necessary to reduce the number of LPIs to fewer or the most important KPIs. This means that among the existing indicators, the best and most important indicators are selected based on the considered criteria. At this step, key performance indicators were selected from the sum of the extracted indicators based on the elements of the HSE management system using the AHP method. All indicators were compared in pairs and each of them was prioritized as a number between 1-9, 1 as lowest priority and 9 as most preferred. Couple comparisons were conducted based on SMART criteria and expert’s opinion. In this study, the paired comparison of axes and performance indicators and determining the weight vector of the indicators was performed using Expert Choice11 software. In addition to examining the HSE management systems deployed in the municipalities, as well as using previous studies, the axes and indicators for assessing the performance of the urban HSE management system were determined. Of the 30 components and 155 indicators of performance assessment, 18 components and 98 indicators were related to monitoring of management system of HSE based on the seven elements and sub elements of the Health, Safety and Environment Management System (HSE-MS). Performance output and urban management axes with 40 and 17 indicators, respectively, have a smaller share of the total indicators developed. Between the process-oriented performance axes, the commitment and leadership axes (0.198) and the HSE records of occupations (0.016) have the highest and lowest weight, respectively. The safety components (0.247) and training (0.150) had the highest and lowest weight in the result-oriented performance axes respectively and economic sustainability (0.301) and architecture and urban planning (0.122) had the highest and lowest weight in among the urban management functional axes respectively. After weighting the indicators for measurement of performance, 70 indicators that had the highest weight than other indicators were selected as key performance indicators. Of the 70 indicators, 47, 16 and 7 indicators are related to the HSE process, the result and urban management respectively. Between the functional sub axes of the HSE process, accident management, inspection, and audit each with five key performance indicators, has the highest measurement index compared to other HSE process sub axes. In the functional axis of the HSE result, the sub axes of ecology with 4 key performance indicators and the sub-axes of safety and health, each with 3 indicators, had the highest number of indicators in this axis. In the urban management axis, sub axes including the socio-cultural and architecture and urbanism axes, each with two key performance indicators, had 4 indicators of total 70 selected key performance indicators. The results of this study indicate that the determination of HSE performance indicators in addition to the components of the HSE management system should be done based on the type of macro management structure and other influential parameters of the organization. The study of the municipals management structure shows that the extracted indicators based on the components of the HSE management system alone cannot cover the urban HSE performance because of factors such as economic sustainability, socio-cultural, demographic, architectural, urban, and industrial-industrial can significantly affect the performance status of the HSE management system of city.
Therefore, it is essential to design and codification of indicators as a tool for measuring the performance of management systems, all aspects of the management system in order to achieve the more accuracy and reliability be considered.

The safety and health performance measurement, designed to provide the necessary information on the concern to progress and the current state of the organization's strategies, processes and activities. The purpose of this study is to present a new model for the development of safety performance indicators using the probability risk assessment model and applying experts' opinions. This descriptive-analytic study was carried out in 3 steps: categorize of the construction face activities and its related hazards identification; formation of the accident causal network occurred in the oil and gas refinery construction phase using the Bayesian network and the selection of key performance indicators using AHP method. The statistical analysis of the recorded accidents showed that 21% of the incidence rate is related to the falling. Among all the construction phase activities, using the WBS analysis of the project, 27 activities with work at height risk of were identified. 18 active performance indicators were extracted the accident causal network that using SMART criteria and occurrence probability rate Calculated from the Bayesian network was selected as 5 active key performance indicators. Determining the leading performance indicators is influenced by various organizational, managerial, operational and other factors. As the project progresses, the nature and level of risk of the operation of construction projects is changing. Therefore, indicators of safety performance measurements in these projects should be sensitive to rapid changes. For this reason, active indicators with a short-term measurement period are more effective in measuring the safety performance of construction operations

Cognitive activities and the operation of tasks in the workplaces lead to the creation of a cognitive workload and specifically mental workload employee in the work environment. In order to measure these cognitive variables, physiological parameters are used. Electroencephalography is a non-invasive and relatively inexpensive method that can be used to evaluate neurophysiology and cognitive functions. Electroencephalography the electrical activity records a large number of brain neurons on the surface of the skull or the brain. The purpose of this article is to provide generalizations of imaging methods in neuroergonomic, brain wave bases, equipment and requirements for participants. It also describes the brainwave recording protocol step by step. Due to the expansion of interdisciplinary studies, the acquisition of brainwave recording skills is essential for researchers in the field of ergonomics and occupational health

One of the most important and preventable hazard related to Healthcare Workers (HCWs) are Needle Stick Injuries (NSI). Biologic outcomes of these injuries can be so hazardous and can cause to transmission of disease such as AIDS, Hepatitis B and C. The aim of this study was determination of occupational exposure to needle stick and its risk factors in one of Sabzevar’s hospital.
This is a cross sectional study on HCWs that by the help of related questionnaire, rate and characteristics of exposure of healthcare personnel was determined. Sampling method was in form of consensus and finally collected data with the help of STATA software and using descriptive and chi-square test were analyzed.
Occupational exposure to needle stick among participated HCWs with at least one injury in 12 months before study was close to 32.99%. Among the different variables that might have influenced on the needle stick injuries only training, education level and work experience had significant relationship. (p= 0.001, 0.009,0.009). About organizational factors, the result showed there is a good guideline for reporting injuries and about 79% of employees said they are familiar with how to report. In the case of cause of needle stick injuries, carelessness and high work load pressure were the most frequent respectively.(40.68, 38.98).
regarding to high rate of needle stick injurie, its a very serious threat for health care workers to suffer from infectious diseases.detailed inspection in order to achieve to hidden causes and providing control solution for hazardous factors can help managers in improving the level of health and safety in health care system.

One of the pollutants that is developing in human life day by day is Magnetic field. In modern urban transport systems, diesel motors have been replaced with electric motors, working with alternating and direct currents, and leading to occupational exposure of drivers with magnetic fields. This study aimed to determine the urban train's drivers exposure with static magnetic fields and compare it with national occupational exposure limits.
In order to measure the train's drivers exposured with static magnetic field, several samples were selected from urban AC and DC and AC intercity trains, in the 1,2,4, and 5 lines of Tehran, Iran. After determination of the sampling location, static magnetic field was measured by three axes magnetic field meter (HI-3550), according to the standard IEEE std C95.3.1 and previous studies. In order to analyze the data, SPSS software (ver. 20) was used.
The maximum exposure of drivers was in DC trains- line 2- (0.52 mT), meanwhile, average exposure of AC trains driver (0.095 mT) was higher than DC trains driver (0.081 mT). The average magnetic flux density between different lines has not have significant differences. The highest levels of time-weighted average exposure were related to line 1 AC train drivers (0.06 mT).
Exposure of train’s drivers was 10 time higher than background level, indicating a significant exposure in this job. However, in none of the assessment situation, the whole body exposure of train’s drivers was not exceeded from National Occupational Exposure Level (TWA= 0.2 and ceiling= 2 T). Of course, it does not imply that this level of exposure is completely safe, because different studies have reported health problems even at lower values of the magnetic field.

driving is such a complex cognitive task that requires a high level of vigilance and response to an emergency. Anything that leads to cognitive performance degradation in the driver's mental processing, increases crash risks. Traffic noise as one of the most destructive elements of cognitive function was examined in this study.
In this study, the sample consisted of 80 patients (40 cases and 40 controls) who were students of Tehran University of medical sciences that were selected through systematic sampling and then the average sound pressure level recorded traffic noise was played for participants in the acoustics room. To Measure reaction time and error in time movement anticipation, the RT and ZBA softwares were used ,respectively.
The results revealed that reaction time increased significantly after exposure to traffic noise. The error time movement after exposure to traffic noise has not significant difference.
Conlusions: According to the results it can be concluded that mental activities such as speed and power of information processing are affected by traffic noise and in a confrontation with traffic noise show different changes.

Extremely low frequency magnetic field is a part of electromagnetic spectrum with frequency range from 30-300 Hz, which effects on the mental and physical health. In the current conditions, some of the labor affairs authorities believe that psychological problems are the main problem among the workers. The present study was designed to assess general health and depression in workers who are exposed to these fields.

This is a case-control study. In order to evaluate the exposure of these two groups, magnetic flux density with extremely low frequency was measured with TES-1394 device in workplace and staff commuter. Beck Depression Inventory and General Health Questionnaires were used to assess general health status and depression.

There are significant differences between the case and control groups in terms of public health (p<0.003) and depression (p=0.031). 60% of the workers who were exposed to these magnetic fields were suspected to the general health problems and 68% of these were reported different degrees of depression (mild 20%, moderate 30%, severe 10%).

General health and depression among the workers who were exposed to magnetic fields had a significant difference compared with the control group. Lower general health and higher rates of depression were seen in the case group. According to the previous studies, analysis and interpreting of the effects of these magnetic fields on the outbreak of depressive symptoms were difficult and this was because of the different results from different studies.

One of the most main jobs in the automotive industries is assembly that its activities include hand motions، navigation of pieces and using controlled forces for joining of them together. Awkward posture is one of the most important risk factors in incidence of musculoskeletal disorders. There are different methods to assess those factors. This study was conducted to illustrate the correlation between the results of MFA method and RULA in the assessment of musculoskeletal disorders risk. In this cross-sectional study 37 jobs were selected as a sample by using of Cochran formula. In this study، 80 postures were assessed by using of two mentioned methods to determine the musculoskeletal risk level. The results of MFA method indicated that 17. 5%، 11. 3% and 7. 5% of jobs in shoulders، low back، wrist and fingers were sequentially in “very high” level of modified actions preference. On the other hand، the results of RULA assessment pointed out that 46. 3% of jobs were in level 3 of modified actions and 38. 8 of them were in level 3 of those actions. Analyzing of data by using of Spearman test displayed that there is significant relationship between RULA scores of shoulders، body and neck with the level of modified action in MFA method (P-value≤0. 05) and sequentially، the correlation coefficients were 0. 782، 0. 787 and 0. 8. In general view، there are many similarities between two methods in both the way of study and the final assessment; however، one of the main differences of them is that; the results of MFA method are more reliable when all parts of body involve in physical activities. In addition، in MFA method، the details of body’s limbs are assessed more than RULA method.

The term "crystalline silica", refers to crystallized form of SiO2 and quartz, as the most abundant compound on earth crust, it can causing silicosis and lung cancer at inhalation large doses in course of occupational exposure. Silica exposure is unavoidable during demolition of buildings and therefore it can result in many problems for demolition workers’ health the aim of this study was assessment of workers respiratory exposure with crystalline silica in during demolition of buildings in Tehran. In this study, in order to assessment of airborne crystalline silica exposure, four zone of Tehran (west،east،south،center) selected. Samples were collected on mixed cellulose filters, by using filter holder at flow rate of 2 l/min for a maximum volume of 800 liters. After the transferring the samples to laboratory then in order to analysis of samples, Visible absorption spectrometry (at 420-820nm) was used according to the "National Institute of Occupational Safety and Health" (NIOSH) method No. 7601 higher average of exposure crystalline silica with geometric mean of 0/185 mg/m3 was related to south area، and center area with GM 0/085 mg/m3 have lowest exposure with crystalline silica. 48 sample (80%) of total sample were above the standard for crystalline silica (ACGIH0/05mg/m3). The geometric mean of worker's exposure to crystalline silica was in the range of 0/085-0/0185 mg/m3. regarding to 80% of total of sample was above the threshold limit value (0/05mg/m3). And exposure with crystalline silica during demolition of building unavoidable, this necessitates control of emission of dust during demolition.

Repetitive tasks are common in assembly industries and the prevalence of musculoskeletal disorders is very high. Ergonomic survey should be applied to identify, assess and control related problems. There are several methods for risk assessment of repetitive tasks. This study aimed to assess the risk of repetitive tasks among assemblers in an electric industry using Assessment Repetitive Tasks (ART) tool. This tool was developed by the Health, Safety and Executive (HSE), UK in 2009. In this current study all workstations (20 workstations) were selected based on census method, after that, Hierarchical Task Analysis (HTA) method was used for task analysis and job was degraded to tasks, actions and movements. Then, ART method was implemented to identify common risk factors in repetitive tasks that can contribute to develop musculoskeletal disorders of upper limbs. In total, 20 ART worksheets were completed in 2 assembly lines. Results showed that 15% of tasks were at low level of risk, 55% of tasks were at medium level of risk and 35% of tasks were at high level of risk. The most important risk factors were hand grip and breaks that were high risk in all tasks. Monotonous of work was also the most important psychosocial factors in all tasks. the results of current study shown that the musculoskeletal disorders due to repetitive tasks are approximately high and ergonomics interventions is needed to reduce risk levels. Using ART method shown that it is a usable, easy and suitable method for assessing repetitive tasks that is recommended for ergonomics interventions and redesigns.

Hot and humid conditions are common in many parts of the world; these conditions can influence both the health and performance of individuals. Therefore to describe the environmental conditions appropriately، the amount of reliability of heat stress indices should be measured. The aim of this study was evaluating the reliability of WBGT and P4SR by comparison to core body temperature in an OilTerminal. The participants (94 persons) were two groups of acclimatized and not acclimatized employees of different units of the Oil Terminal. After identifying the units and their activities، air and wet temperatures، WBGT، and core body temperature (oral and tympanic) were measured in three situations including outdoor، indoor، and rest activities. The statistically significant correlation was found between above mentioned heat stress indices with oraland tympanictemperatures (P<0/05). The regression equations were shown that the most determinant coefficient belong to WBGT and tympanic temperature (R2=0/571). It was found that the WBGT and P4SR with core body temperature had significant correlations and WBGT had the most accuracy to predict heat stress in employees.