A risk model for occupational noise-induced hearing loss in workers.

BACKGROUND: Occupational hearing loss is one of the most common work-related diseases with various risk factors and considerable negative impacts on both physical and mental well-being of affected workers. Occupational noise-induced hearing loss (ONIHL) has a complex interaction with personal, environmental and occupational factors. OBJECTIVE: This study aimed to develop a risk model for ONIHL in workers by identifying risk factors and their interactions. METHODS: The subjects were 605 males in an industrial factory in Arak, Iran. The study took place between 2022 and 2023. The sociodemographic and occupational characteristics were collected by a health technician using questionnaires and medical records. Hearing status was assessed using audiometry by a qualified audiologist. Hearing loss was analyzed by univariate logistic analysis including age, smoking, medical history, type of occupation, and some workplace hazards. The risk model was generated by logistic regression. RESULTS: Hearing loss in the participants was 44.13% (n = 267). In univariate logistic analysis, age (OR: 2.93,95% CI: 1.848-4.656), smoking (OR: 1.80, 95% CI: 1.224-2.655), work experience (OR: 1.06, 95% CI: 1.016-1.107), previous exposure to noise (OR: 1.60, 95% CI: 1.112-2.312) or vibration (OR: 1.68, 95% CI: 1.150-2.475) and type of occupation (OR: 2.126, 95% CI: 1.055-4.285) were associated with an increased risk of ONIHL (P < 0.05). CONCLUSION: It was found that vibration exposure, work experience, previous noise exposure, type of occupation as well as age and smoking significantly affected the likelihood of developing ONIHL. This risk model could help management to prevent ONIHL and enhance application-oriented research on the condition.

In-silico computational approaches to study microbiota impacts on diseases and pharmacotherapy.

Microorganisms have been linked to a variety of critical human disease, thanks to advances in sequencing technology and microbiology. The growing recognition of human microbe-disease relationships provides crucial insights into the underlying disease process from the perspective of pathogens, which is extremely useful for pathogenesis research, early diagnosis, and precision medicine and therapy. Microbe-based analysis in terms of diseases and related drug discovery can predict new connections/mechanisms and provide new concepts. These phenomena have been studied via various in-silico computational approaches. This review aims to elaborate on the computational works conducted on the microbe-disease and microbe-drug topics, discuss the computational model approaches used for predicting associations and provide comprehensive information on the related databases. Finally, we discussed potential prospects and obstacles in this field of study, while also outlining some recommendations for further enhancing predictive capabilities.

Analysis and identification of drug similarity through drug side effects and indications data.

BACKGROUND: The measurement of drug similarity has many potential applications for assessing drug therapy similarity, patient similarity, and the success of treatment modalities. To date, a family of computational methods has been employed to predict drug-drug similarity. Here, we announce a computational method for measuring drug-drug similarity based on drug indications and side effects. METHODS: The model was applied for 2997 drugs in the side effects category and 1437 drugs in the indications category. The corresponding binary vectors were built to determine the Drug-drug similarity for each drug. Various similarity measures were conducted to discover drug-drug similarity. RESULTS: Among the examined similarity methods, the Jaccard similarity measure was the best in overall performance results. In total, 5,521,272 potential drug pair's similarities were studied in this research. The offered model was able to predict 3,948,378 potential similarities. CONCLUSION: Based on these results, we propose the current method as a robust, simple, and quick approach to identifying drug similarity.

Development and validation of assessment tool of knowledge, attitude, and practice of outdoor workers regarding heat stress.

BACKGROUND: Improving the level of knowledge, attitude and practices of workers exposed to heat stress using a suitable tool can be a cheap and effective method. This requires the consideration of personal, environmental and social factors, which, the PRECEDE model is highly applicable for. Thus, the aim of the present study is the development of a tool assessment for measuring the knowledge, attitude and practices of workers in outdoor occupations regarding heat stress exposure using the PRECEDE model. METHODS: In the present study, a tool was designed and constructed using the PRECEDE model by analyzing the relevant literature and expert opinion. The face validity of the tool was determined based on the opinion of ten experts with experience in the field of occupational weather conditions. The content validity of the tool was determined using the Content Validity Ratio (CVR) and the Content Validity Index (CVI). Cronbach's alpha reliability coefficient was used to determine the reliability of the tool's internal consistency. SPSS version 23 was used for statistical analysis. RESULTS: A PRECEDE based questionnaire was designed with a total of 55 questions consisting of predisposing factors (28 questions for knowledge and 14 questions for attitude), enabling factors (5 questions), reinforcing factors (3 questions) and preventive behaviors (5 questions). The Content Validity Index (CVI) of all questions was above 0.79. The Content Validity Ratio (CVR) of all questions was above 0.62 (Lawshe method). The Cronbach's alpha reliability coefficient of all PRECEDE domains were above the 0.7 acceptable value. Based on the results obtained, all 55 questions were approved and thus the content validity and reliability of this tool was deemed acceptable. CONCLUSION: Considering the reliability and validity of this tool, its application is recommended in all health and safety inspections within various industries for measuring the heat stress knowledge, attitude and practices of workers engaged in outdoor occupations and also for presenting suitable solutions or preventive measures.

Tinnitus characteristics at high-and low-risk occupations from occupational noise exposure standpoint.

INTRODUCTION: The aim of the present study was to compare tinnitus characteristics in high- and low-risk occupations from the occupational noise exposure standpoint, considering demographic data, hearing loss and concomitant diseases. METHODS: Demographic data, characteristics of tinnitus, hearing and concomitant diseases were recorded in the questionnaires. Their pure tone air conduction thresholds were determined using a double-channel diagnostic Audiometer and the Bone Conduction was assessed using a B-71 bone vibrator. RESULTS: Totally, 6.3% subjects (6.8% high-risk group and 5.6% low-risk group) had subjective tinnitus, mainly as whistling sound. In the high-risk group, tinnitus was mainly left-sided (41.18%) and hearing loss was mild. Bilateral tinnitus (52.63%) and slight hearing loss were observed predominantly in the low-risk group. CONCLUSIONS: The study showed higher incidence of tinnitus in high-risk professions regarding with occupational noise exposure.

The combined effect of industrial noise type, level and frequency characteristics on hand motor skills: A lab trial study.

BACKGROUND: The study aimed to assess the interactive effects of industrial noise type, level and frequency characteristics on hand motor skills using the Minnesota Manual Dexterity Test and the Hand Tool Dexterity Test. METHODS: A total of ten nonsmoking male volunteers with normal hearing and vision were selected for this study. The study followed a full 3×3×2 factorial design. Independent variables were noise type (steady, intermittent and fluctuating), noise level (75, 85 and 95 dBA) and frequency characteristics ("roar" <2000 Hz and "hiss" >2000 Hz). RESULTS: For Minnesota Manual Dexterity Test, the lowest speed is related to steady hiss noise at 75 dBA and the highest speed is related to fluctuating roar noise at 95 dBA. The speed is being significantly affected by the frequency characteristic (P = 0.041) and noise type (P = 0.025). The effect of hiss noise on speed is greater than roar noise (P = 0.038). There is a significant difference (P = 0.035) between continuous noise and fluctuating noise. For the Hand Tool Dexterity Test, the lowest speed is related to fluctuating hiss noise at 95 dBA and the highest speed is related to steady roar noise at 95 dBA. The speed is being significantly affected by the frequency characteristic (P = 0.002), noise type (P = 0.0001) and noise level (P = 0.005). The effect of hiss noise on response variable to be greater than roar noise (P = 0.008). There is a significant difference (P = 0.0001) between steady noise and the two other types of noise, and also there is a significant difference between 75 dBA and 85 dBA level (P = 0.003). CONCLUSIONS: The results showed that on hand motor skills, speed response was influenced by three characteristics: the type of noise, frequency characteristics and noise level. Also, the effect of the hiss noise was more than the roar noise.

Modeling heat stress changes based on wet-bulb globe temperature in respect to global warming.

BACKGROUND: This ecological study aims to model the trend of changes in exposure of outdoor workers to heat stress in outdoors in the coming decades with the use of the Wet-Bulb Globe Temperature (WBGT), Hadley Coupled Atmosphere- Ocean General Circulation Model, version 3 (HADCM3), and Long Ashton Research Station Weather Generator (LARS-WG) in Tehran, Iran, considering the climate change and the global warming. METHODS: The hourly values of environmental parameters including minimum and maximum air temperature, relative humidity, precipitation and radiation related to Prakash , Shahriar and Damavand cities were obtained from the Meteorological Organization of Iran. These data were recorded during 1965 to 2015. The climate modeling was done for 2011-2030, 2046-2065, and 2080-2099. RESULTS: The minimum and maximum air temperatures in the different months of the year in the three studied cities show an increasing trend. Our finding shows that the WBGT will be increased by 2099. In Pakdasht, this index will be close to the danger zone in the coming years, especially in 2080-2099. CONCLUSIONS: All the results obtained indicate an increase in risk of heat stress in outdoor workplaces, given the global warming.

Prediction of RNA- and DNA-Binding Proteins Using Various Machine Learning Classifiers.

BACKGROUND: Nucleic acid-binding proteins play major roles in different biological processes, such as transcription, splicing and translation. Therefore, the nucleic acid-binding function prediction of proteins is a step toward full functional annotation of proteins. The aim of our research was the improvement of nucleic-acid binding function prediction. METHODS: In the current study, nine machine-learning algorithms were used to predict RNA- and DNA-binding proteins and also to discriminate between RNA-binding proteins and DNA-binding proteins. The electrostatic features were utilized for prediction of each function in corresponding adapted protein datasets. The leave-one-out cross-validation process was used to measure the performance of employed classifiers. RESULTS: Radial basis function classifier gave the best results in predicting RNA- and DNA-binding proteins in comparison with other classifiers applied. In discriminating between RNA- and DNA-binding proteins, multilayer perceptron classifier was the best one. CONCLUSION: Our findings show that the prediction of nucleic acid-binding function based on these simple electrostatic features can be improved by applied classifiers. Moreover, a reasonable progress to distinguish between RNA- and DNA-binding proteins has been achieved.

Application of Universal Thermal Climate Index (UTCI) for assessment of occupational heat stress in open-pit mines.

The purpose of this article is to examine the applicability of Universal Thermal Climate Index (UTCI) index as an innovative index for evaluating of occupational heat stress in outdoor environments. 175 workers of 12 open-pit mines in Tehran, Iran were selected for this research study. First, the environmental variables such as air temperature, wet-bulb temperature, globe temperature, relative humidity and air flow rate were measured; then UTCI, wet-bulb globe temperature (WBGT) and heat stress index (HSI) indices were calculated. Simultaneously, physiological parameters including heart rate, oral temperature, tympanic temperature and skin temperature of workers were measured. UTCI and WBGT are positively significantly correlated with all environmental parameters (p<0.03), except for air velocity (r<-0.39; p>0.05). Moreover, a strong significant relationship was found between UTCI and WBGT (r=0.95; p<0.001). The significant positive correlations exist between physiological parameters including oral temperature, tympanic and skin temperatures and heart rate and both the UTCI and WBGT indices (p<0.029). The highest correlation coefficient has been found between the UTCI and physiological parameters. Due to the low humidity and air velocity (~<1 m/s) in understudied mines, UTCI index appears to be appropriate to assess the occupational heat stress in these outdoor workplaces.

Weighting Criteria and Prioritizing of Heat stress indices in surface mining using a Delphi Technique and Fuzzy AHP-TOPSIS Method.

BACKGROUND: Heat stress as a physical harmful agent can increase the risk of health and safety problems in different workplaces such as mining. Although there are different indices to assess the heat stress imposed on workers, choosing the best index for a specific workplace is so important. Since various criteria affect an index applicability, extracting the most effective ones and determining their weights help to prioritize the existing indices and select the optimal index. METHODS: In order to achieve this aim, present study compared some heat stress indices using effective methods. The viewpoints of occupational health experts and the qualitative Delphi methods were used to extract the most important criteria. Then, the weights of 11 selected criteria were determined by Fuzzy Analytic Hierarchy Process. Finally, fuzzy TOPSIS technique was applied for choosing the most suitable heat stress index. RESULTS: According to result, simplicity, reliability, being low cost, and comprehensiveness were the most determinative criteria for a heat stress index. Based on these criteria and their weights, the existing indices were prioritized. Eventually, wet bulb glob temperature appropriated the first priority and it was proposed as an applicable index for evaluating the heat stress at outdoor hot environments such as surface mines. CONCLUSIONS: The use of these strong methods allows introducing the most simple, precise, and applicable tool for evaluation the heat stress in hot environments. It seems that WBGT acts as an appropriate index for assessing the heat stress in mining activities at outdoors.

An all-solid-state, WDM silicon photonic digital link for chip-to-chip communications.

We describe a multiwavelength hybrid-integrated solid-state link on a 3 µm silicon-on-insulator (SOI) nanophotonic platform. The link spans three chips and employs germanium-silicon electroabsorption waveguide modulators, silicon transport waveguides, echelle gratings for multiplexing and demultiplexing, and pure germanium waveguide photo-detectors. The 8λ WDM Tx and Rx components are interconnected via a routing "bridge" chip using edge-coupled optical proximity communication. The packaged, retimed digital WDM link is demonstrated at 10 Gb/s and 10(-12) BER, with three wavelength channels consuming an on-chip power below 1.5 pJ/bit, excluding the external laser power.

Survey of accidents in suburban Tehran and the prediction of future events based on a time-series model.

BACKGROUND: Car accidents are currently a social issue globally because they result in the deaths of many people. The aim of this study was to examine traffic accidents in suburban Tehran and forecast the number of future accidents using a time-series model. METHODS: The sample population of this cross-sectional study was all traffic accidents that caused death and physical injuries in suburban Tehran in 2010 and 2011, as registered by the Tehran Emergency Section. In the present study, Minitab 15 software was used to provide a description of traffic accidents in suburban Tehran for the specified time period as well as those that occurred during April 2012. RESULTS: The results indicated that the average number of traffic accidents in suburban Tehran per day in 2010 was 7.91 with a standard deviation of 7.70. This figure for 2011 was 6 daily traffic accidents with a standard deviation of 5.30. A one-way analysis of variance indicated that the average of traffic accidents in suburban Tehran was different for different months of the year (P = 0.000). The study results showed that different seasons in 2010 and 2011 had significantly different numbers of traffic accidents (P < 0.05). Through an auto-regressive moving average (ARMA), it was predicted that there would be 166 traffic accidents in April 2012 with a mean of 5.53 and maximum of 6 traffic accidents/day. CONCLUSION: There has been a decreasing trend in the average number of traffic accidents per day.

Epidemiology of mental health problems in female students: a questionnaire survey.

Mental health as a state of well-being can be affected by gender. The present work aims to examine the mental health status in female students and recognize its affecting factors. A cross-sectional study on female students of Payame-Noor University in West Azerbaijan, Iran, was conducted among 1632 students. Data collection tools were the demographic data and the General Health Questionnaires (GHQ-28). The results show that 51.5% of the population under study were healthy and 48.5% have had mental disorders. Based on the social effects on the mental health of students, the correlations between age (p=0.15), location (p=0.29) and parental education (p=0.34) with general health status were assessed and there were no significant differences between them. However, birth order (p<0.002), marital status (p<0.001) and family income (p<0.000) had significant differences with regard to mental health status. This study indicates that 43.6% of students are suspected to have mental and physical disorders, and the most effective factor is the socioeconomic condition. The strong correlation between birth order, marital status, and family income and mental health disorders suggests the necessity to pay more attention to all these issues in all at-risk students.

Survey and comparison of sleep quality among fixed and changing shift staff in a steel factory in Tehran, Iran.

BACKGROUND: Given the hazardous nature of the work in steel factories and that the staff has to deal with hazardous equipment and machines, improper sleep quality and drowsiness among the works tackles performance and boosts rate of job accidents. This study is aimed to survey the quality of sleep and sleepiness status and the pertinent factors among the workers in a rolling mill and a steel production company in Tehran, Iran. METHODS: In a Cross-Sectional study 2011, 180 workers were selected randomly from a rolling mill and a steel production company in Tehran. A questionnaire was designed to collect demographic data and variables of work condition. Pitersborg's sleep quality questionnaire was used to survey quality and problems of Participants' sleep. Epworth Sleepiness questionnaire was used to deals with sleepiness during work, studying, watching TV, or during time spent in public. RESULTS: Average score of sleep quality for the fixed shift staff and changing shift staff were 7.5±2.82 and 8.49±2.95 respectively. Surveys of sleep quality for the two groups of the participants based on T-test showed a significant difference between the two groups so that the changing shift staff group suffered poorer sleep quality (p=0.03). Comparison of average drowsiness scores between the two groups of participants based on Mann-Whitney test showed no significant difference (p>0.005). Chi square test showed a significant difference between severity of drowsiness and type of working shift (p =0.028 and 0.009). CONCLUSION: Staff in revolving shifts suffers poor sleep quality comparing with staff with fixed working shift. Moreover, type of working shift greatly affects severity of drowsiness as staff at different work shift experienced different level of sleepiness. It is essential to survey sleep disorder of the staff in the industry and pay more emphasis on sleep disorder epidemic in other fields of industry.

Assessment of patient safety culture among personnel in the hospitals associated with Islamic Azad University in Tehran in 2013.

BACKGROUND: Patient safety is an essential element in the quality of healthcare, and a clear knowledge of its culture in healthcare organizations will lead to both improved healthcare and patient safety. The aim of this study was to assess the patient safety culture at Islamic Azad University hospitals in Tehran, Iran, in 2013. METHODS: This cross-sectional study was conducted on clinical and diagnostic staff in all Islamic Azad University hospitals in Tehran in June 2013. The international "Hospital Survey on Patient Safety Culture" questionnaire was used as the measurement tool. RESULTS: In these hospitals, the overall positive score of patient safety culture was 35%. "Teamwork within units" (48% positive) was evaluated as reflecting the most knowledge of the aspects of patient safety culture, and "non-punitive response to error" (12% positive) was evaluated as reflecting the least knowledge of the aspects of patient safety culture. CONCLUSION: The patient safety culture in the hospitals that were studied should be improved. This goal could be achieved by reinforcing the basics of patient safety culture by teaching the staff members about the aspects of a positive patient safety culture and encouraging them to incorporate these aspects in their day-to-day activities.

The effect of the use of NP305 masks in improving respiratory symptoms in workers exposed to sulfuric acid mists in plating and pickling units.

BACKGROUND: Plating and pickling processes are the most effective ways for increasing the strength of metal structures, and workers in these units are exposed to various contaminants, including acid mists. The aim of this study was to investigate the effect of protective masks in decreasing the respiratory symptoms and the aerobic capacity of workers that are exposed sulfuric acid mist. METHODS: This interventional study was based on National Institute for Occupational Safety and Health (NIOSH) standard 7903 in which silica gel tubes are used for sampling the air in plating and pickling units for eight hours. After the samples were acquired and prepared, they were analyzed by ion chromatography and were compared with the American Conference of Governmental Industrial Hygienists (ACGIH) exposure limits. Respiratory symptoms were evaluated among two sets of test subjects, i.e., those who used NP305 masks in the workplace and those who did not use the mask. RESULTS: The results showed that the concentration of sulfuric acid mist in the plating units was greater than the exposure limits, and concentrations at this level can cause an increase in symptoms related to irritation of the airway and a slight decrease in respiratory capacity. In this study, smoking had no significant effect on the severity of pulmonary dysfunction. CONCLUSION: The results indicated that the use of an NP305 mask is effective for decreasing symptoms resulting from exposure to sulfuric acid mist and improving respiratory capacity.

Review the number of accidents in Tehran over a two-year period and prediction of the number of events based on a time-series model.

BACKGROUND: One of the significant dangers that threaten people's lives is the increased risk of accidents. Annually, more than 1.3 million people die around the world as a result of accidents, and it has been estimated that approximately 300 deaths occur daily due to traffic accidents in the world with more than 50% of that number being people who were not even passengers in the cars. The aim of this study was to examine traffic accidents in Tehran and forecast the number of future accidents using a time-series model. METHODS: The study was a cross-sectional study that was conducted in 2011. The sample population was all traffic accidents that caused death and physical injuries in Tehran in 2010 and 2011, as registered in the Tehran Emergency ward. The present study used Minitab 15 software to provide a description of accidents in Tehran for the specified time period as well as those that occurred during April 2012. RESULTS: The results indicated that the average number of daily traffic accidents in Tehran in 2010 was 187 with a standard deviation of 83.6. In 2011, there was an average of 180 daily traffic accidents with a standard deviation of 39.5. One-way analysis of variance indicated that the average number of accidents in the city was different for different months of the year (P < 0.05). Most of the accidents occurred in March, July, August, and September. Thus, more accidents occurred in the summer than in the other seasons. The number of accidents was predicted based on an auto-regressive, moving average (ARMA) for April 2012. The number of accidents displayed a seasonal trend. The prediction of the number of accidents in the city during April of 2012 indicated that a total of 4,459 accidents would occur with mean of 149 accidents per day during these three months. CONCLUSION: The number of accidents in Tehran displayed a seasonal trend, and the number of accidents was different for different seasons of the year.

High speed GeSi electro-absorption modulator at 1550 nm wavelength on SOI waveguide.

We demonstrate a high speed GeSi electro-absorption (EA) modulator monolithically integrated on 3 µm silicon-on-insulator (SOI) waveguide. The demonstrated device has a compact active region of 1.0 × 55 µm(2), an insertion loss of 5 dB and an extinction ratio of 6 dB at wavelength of 1550 nm. The modulator has a broad operating wavelength range of 35 nm and a 3 dB bandwidth of 40.7 GHz at 2.8 V reverse bias. This compact and energy efficient modulator is a key building block for optical interconnection applications.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

From both the structural and functional points of view, ß-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify ß-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of ß-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a ß-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other ß-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying ß-turns in proteins.

Design and fabrication of 3µm silicon-on-insulator waveguide integrated Ge electro-absorption modulator.

We present the design and fabrication of a waveguide-based Ge electro-absorption (EA) modulator integrated with a 3 µm silicon-on-isolator (SOI) waveguide. The proposed Ge EA modulator employs a butt-coupled horizontally-oriented p-i-n structure. The optical design achieves a low-loss transition from Ge to Si waveguides. The interaction between the optical mode of the waveguide and the bias induced electric field in the p-i-n structure was maximized to achieve high modulation efficiency. By balancing the trade-offs between the extinction ratio and the insertion loss of the device, an optimal working regime was identified. The measurement results from a fabricated device were used to verify the design. Under a -4Vpp reverse bias, the device demonstrates a total insertion loss (including the transition loss) of 2.7-5.2 dB and an extinction ratio of 4.9-8.2 dB over the wavelength range of 1610-1640 nm. Subtracting the contribution of the transition loss, the Δα/α value for the fabricated device was estimated to be between 2.2 and 3.2 with an electric field around 55 kV/cm.