Analysis of Asymmetric Stress Ratio in Shallow Buried Tunnels

Qingyang Yu,Zeyu Song,Chao Du,Zhenxue Dai,Shangxian Yin,Mohamad Reza Soltanian,Mojtaba Soltanian,Wei Liu 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.6

Asymmetric stress occurs in shallow buried highways and railway tunnels. Due to asymmetricalloading, the design process of the tunnel is different from a regular tunnel. Chinese code for designing railway tunnel contains empirical values for different grounding rock to facilitate engineering judgement of asymmetrical loading tunnels based on the slope angle of surface and the burial depth of the tunnel. However, when calculating the asymmetric stress, there seem to be no quantitative criteria for estimating the asymmetric stress. Thus, in this work we create a numerical model to better evaluate the asymmetric stress ratios in different rock types. Our results demonstrate for surrounding rocks of grade V with poor stability, an asymmetrical loading conditions should be considered specifically when the stress ratio at the spandrel is higher than unity. For surrounding rock with grade IV in which stability slightly increases we found that the tunnel is asymmetrical once the stress ratio at the spandrel reaches to above 2 − 3. For the grade IV with a higher stability, an asymmetrical loading should be considered in the design when the stress ratio reaches to 3 − 4. For rock with grade III with the maximum stability only when the stress ratio is higher than 7 − 8, the asymmetrical loading conditions should be considered. We found that for grades III, IV, and V, the stress ratio of sidewall is about unity under various slope angles and burial depth. Importantly, we show that the stress ratio at the sidewall cannot be used to make judgements on whether the shallow buried tunnels are asymmetrical loading conditions. Our results have practical implications in design, safety, and risk analyses of tunnels.

Comparison of the Performance of Log-logistic Regression and Artificial Neural Networks for Predicting Breast Cancer Relapse

Faradmal, Javad,Soltanian, Ali Reza,Roshanaei, Ghodratollah,Khodabakhshi, Reza,Kasaeian, Amir Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.14

Background: Breast cancer is the most common cancers in female populations. The exact cause is not known, but is most likely to be a combination of genetic and environmental factors. Log-logistic model (LLM) is applied as a statistical method for predicting survival and it influencing factors. In recent decades, artificial neural network (ANN) models have been increasingly applied to predict survival data. The present research was conducted to compare log-logistic regression and artificial neural network models in prediction of breast cancer (BC) survival. Materials and Methods: A historical cohort study was established with 104 patients suffering from BC from 1997 to 2005. To compare the ANN and LLM in our setting, we used the estimated areas under the receiver-operating characteristic (ROC) curve (AUC) and integrated AUC (iAUC). The data were analyzed using R statistical software. Results: The AUC for the first, second and third years after diagnosis are 0.918, 0.780 and 0.800 in ANN, and 0.834, 0.733 and 0.616 in LLM, respectively. The mean AUC for ANN was statistically higher than that of the LLM (0.845 vs. 0.744). Hence, this study showed a significant difference between the performance in terms of prediction by ANN and LLM. Conclusions: This study demonstrated that the ability of prediction with ANN was higher than with the LLM model. Thus, the use of ANN method for prediction of survival in field of breast cancer is suggested.

Surprising Incentive: An Instrument for Promoting Safety Performance of Construction Employees

Ghasemi, Fakhradin,Mohammadfam, Iraj,Soltanian, Ali Reza,Mahmoudi, Shahram,Zarei, Esmaeil Occupational Safety and Health Research Institute 2015 Safety and health at work Vol.6 No.3

Background: In comparison with other industries, the construction industry still has a higher rate of fatal injuries, and thus, there is a need to apply new and innovative approaches for preventing accidents and promoting safe conditions at construction sites. Methods: In this study, the effectiveness of a new incentive system-the surprising incentive system-was assessed. One year after the implementation of this new incentive system, behavioral changes of employees with respect to seven types of activities were observed. Results: The results of this study showed that there is a significant relationship between the new incentive system and the safety performance of frontline employees. The new incentive system had a greater positive impact in the first 6 months since its implementation. In the long term, however, safety performance experienced a gradual reduction. Based on previous studies, all activities selected in this study are important indicators of the safety conditions at workplaces. However, there is a need for a comprehensive and simple-to-apply tool for assessing frontline employees' safety performance. Shortening the intervals between incentives is more effective in promoting safety performance. Conclusion: The results of this study proved that the surprising incentive would improve the employees' safety performance just in the short term because the surprising value of the incentives dwindle over time. For this reason and to maintain the surprising value of the incentive system, the amount and types of incentives need to be evaluated and modified annually or biannually.

Association between polycystic ovary syndrome and risk of attention-deficit/hyperactivity disorder in offspring: a meta-analysis

Maleki Azam,Bashirian Saeid,Soltanian Ali Reza,Jenabi Ensiyeh,Farhadinasab Abdollah 대한소아청소년과학회 2022 Clinical and Experimental Pediatrics (CEP) Vol.65 No.2

Background: There is evidence of a relationship between prenatal excess androgen exposure and central nervous developmental problems and attention-deficit/hyperactivity disorder (ADHD) in the offspring of mothers with polycystic ovary syndrome (PCOS).Purpose: Here we aimed to use a meta-analysis to investigate whether the offspring of mothers with PCOS are at an increased chance of developing ADHD.Methods: Three main English databases were searched for articles published through December 2020. The NewcastleOttawa Scale was used to assess study quality. Study heterogeneity was determined using I2 statistics and publication bias was assessed using Begg and Egger tests. The results are presented as odds ratio (OR) and relative ratio (RR) estimates with 95% confidence intervals (CIs) using a random-effects model.Results: Six articles (3 cohort and 3 case-control studies; 401,413 total ADHD cases) met the study criteria. Maternal PCOS was associated with an increased risk of ADHD in the offspring based on OR and RR (OR, 1.42; 95% CI, 1.27–1.57) and (RR, 1.43; 95% CI, 1.35–1.51), respectively. There was no heterogeneity among the included articles based on OR (I2=0.0%, P=0.588) and RR (I2=0.0%, P=0.878).Conclusion: Our study showed that maternal PCOS is a risk factor for ADHD. Therefore, screening their offspring for ADHD should be considered part of the comprehensive clinical care of women with PCOS.

Prevalence of burnout and related factors in nursing faculty members: a systematic review

Marziyeh Hosseini,Mitra Soltanian,Camellia Torabizadeh,Zahra Hadian Shirazi 한국보건의료인국가시험원 2022 보건의료교육평가 Vol.19 No.-

Purpose The current study aimed to identify the prevalence of burnout and related factors in nursing faculty members through a systematic review of the literature. Methods A comprehensive search of electronic databases, including Scopus, PubMed, Web of Science, Iranmedex, and Scientific Information Database was conducted via keywords extracted from Medical Subject Headings, including burnout and nursing faculty, for studies published from database inception to April 1, 2022. The quality of the included studies in this review was assessed using the appraisal tool for cross-sectional studies. Results A total of 2,551 nursing faculty members were enrolled in 11 studies. The mean score of burnout in nursing faculty members based on the Maslach Burnout Inventory (MBI) was 59.28 out of 132. The burnout score in this study was presented in 3 MBI subscales: emotional exhaustion, 21.24 (standard deviation [SD]=9.70) out of 54; depersonalization, 5.88 (SD=4.20) out of 30; and personal accomplishment, 32.16 (SD=6.45) out of 48. Several factors had significant relationships with burnout in nursing faculty members, including gender, level of education, hours of work, number of classroom, students taught, full-time work, job pressure, perceived stress, subjective well-being, marital status, job satisfaction, work setting satisfaction, workplace empowerment, collegial support, management style, fulfillment of self-expectation, communication style, humor, and academic position. Conclusion Overall, the mean burnout scores in nursing faculty members were moderate. Therefore, health policymakers and managers can reduce the likelihood of burnout in nursing faculty members by using psychosocial interventions and support.

Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors

Shiva Borzouei,Ali Reza Soltanian 한국역학회 2018 Epidemiology and Health Vol.40 No.-

OBJECTIVES: To identify the most important demographic risk factors for a diagnosis of type 2 diabetes mellitus (T2DM) using a neural network model. METHODS: This study was conducted on a sample of 234 individuals, in whom T2DM was diagnosed using hemoglobin A1c levels. A multilayer perceptron artificial neural network was used to identify demographic risk factors for T2DM and their importance. The DeLong method was used to compare the models by fitting in sequential steps. RESULTS: Variables found to be significant at a level of p<0.2 in a univariate logistic regression analysis (age, hypertension, waist circumference, body mass index [BMI], sedentary lifestyle, smoking, vegetable consumption, family history of T2DM, stress, walking, fruit consumption, and sex) were entered into the model. After 7 stages of neural network modeling, only waist circumference (100.0%), age (78.5%), BMI (78.2%), hypertension (69.4%), stress (54.2%), smoking (49.3%), and a family history of T2DM (37.2%) were identified as predictors of the diagnosis of T2DM. CONCLUSIONS: In this study, waist circumference and age were the most important predictors of T2DM. Due to the sensitivity, specificity, and accuracy of the final model, it is suggested that these variables should be used for T2DM risk assessment in screening tests

Effects of fresh mineralized dentin and cementum on socket healing: a preliminary study in dogs

Mahdi Kadkhodazadeh,Majid Ghasemianpour,Negar Soltanian,Gholam Reza Sultanian,Shahriar Ahmadpour,Reza Amid 대한구강악안면외과학회 2015 대한구강악안면외과학회지 Vol.41 No.3

Objectives: Dentin is composed of many minerals and growth factors. Based on this composition, we studied its effect as a possible regenerative material for alveolar healing. Materials and Methods: This study was conducted using four 2.5-year-old mongrel dogs (male; weight, 25 to 30 kg). The third mandibular premolars were carefully mobilized with a dental elevator and then removed using forceps. The crown portions of the extracted teeth were removed with cutters, and the root portions of the remaining teeth were collectively trimmed as closely as possible to 350 to 500 μm. Dentin and cementum (DC) chips harvested from the extracted teeth were soaked in blood and packed into the fresh sockets (autograft). Biopsies were performed at the ends of day 14 and day 56 following implantation. Data were expressed as mean±standard deviation and compared with t-test results. Results: The ratio of S A (bone) to total area of each probe was determined and was 170±16 μm 2 for the control group and 71±14 μm 2 for the DC group, a significant difference (P<0.05). Conclusion: DC particulate grafts offered no improvement in bone regeneration in alveolar extraction sockets.

Surprising Incentive: An Instrument for Promoting Safety Performance of Construction Employees

Fakhradin Ghasemi,Iraj Mohammadfam,Alireza Soltanian,Shahram Mahmoudi,Esmaeil Zarei 한국산업안전보건공단 산업안전보건연구원 2015 Safety and health at work Vol.6 No.3

Background: In comparison with other industries, the construction industry still has a higher rate of fatal injuries, and thus, there is a need to apply new and innovative approaches for preventing accidents and promoting safe conditions at construction sites. Methods: In this study, the effectiveness of a new incentive systemdthe surprising incentive systemdwas assessed. One year after the implementation of this new incentive system, behavioral changes of employees with respect to seven types of activities were observed. Results: The results of this study showed that there is a significant relationship between the new incentive system and the safety performance of frontline employees. The new incentive system had a greater positive impact in the first 6 months since its implementation. In the long term, however, safety performance experienced a gradual reduction. Based on previous studies, all activities selected in this study are important indicators of the safety conditions at workplaces. However, there is a need for a comprehensive and simple-to-apply tool for assessing frontline employees’ safety performance. Shortening the intervals between incentives is more effective in promoting safety performance. Conclusion: The results of this study proved that the surprising incentive would improve the employees’ safety performance just in the short term because the surprising value of the incentives dwindle over time. For this reason and to maintain the surprising value of the incentive system, the amount and types of incentives need to be evaluated and modified annually or biannually.

Human Error Probability Determination in Blasting Process of Ore Mine Using a Hybrid of HEART and Best-Worst Methods

Aliabadi, Mostafa Mirzaei,Mohammadfam, Iraj,Soltanian, Ali Reza,Najafi, Kamran Occupational Safety and Health Research Institute 2022 Safety and health at work Vol.13 No.3

Background: One of the important actions for enhancing human reliability in any industry is assessing human error probability (HEP). The HEART technique is a robust tool for calculating HEP in various industries. The traditional HEART has some weaknesses due to expert judgment. For these reasons, a hybrid model is presented in this study to integrate HEART with Best-Worst Method. Materials Method: In this study, the blasting process in an iron ore mine was investigated as a case study. The proposed HEART-BWM was used to increase the sensitivity of APOA calculation. Then the HEP was calculated using conventional HEART formula. A consistency ratio was calculated using BWM. Finally, for verification of the HEART-BWM, HEP calculation was done by traditional HEART and HEART-BWM. Results: In the view of determined HEPs, the results showed that the mean of HEP in the blasting of the iron ore process was 2.57E-01. Checking the full blast of all the holes after the blasting sub-task was the most dangerous task due to the highest HEP value, and it was found 9.646E-01. On the other side, obtaining a permit to receive and transport materials was the most reliable task, and the HEP was 8.54E-04. Conclusion: The results showed a good consistency for the proposed technique. Comparing the two techniques confirmed that the BWM makes the traditional HEART faster and more reliable by performing the basic comparisons.

Analysis of the severity of occupational injuries in the mining industry using a Bayesian network

Mostafa Mirzaei Aliabadi,Hamed Aghaei,Omid Kalatpuor,Ali Reza Soltanian,Asghar Nikravesh 한국역학회 2019 Epidemiology and Health Vol.41 No.-

OBJECTIVES: Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis. METHODS: The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents. RESULTS: Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers’ experience had the strongest influence on the severity of accidents. CONCLUSIONS: Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.