monireh dehghani arani

The steel industry is known as the most important consumer of energy and fuel. In doing so, ensuring safety of energy sources of a country needs to expect the risks analysis in order to select a comprehensive approach. This study aimed to identify the energy consumption and control measures available in the Hot Rolling Kavir Steel Complex and to conduct risk assessment by Energy Tracking and Barrier Analysis method (ETBA).

In this study, initially a team of experts identified mobilized energies and risks of the system and control measures using ETBA sheet that result of a standard MILSTD-882B. Then, the initial risk assessment was carried out using ETBA method. Finally, the control strategies were proposed and the secondary risk level was calculated.

Using ETBA, in total 19 energy types and 74 risk types were successfully identified so that in the first stage, 19 risks were unacceptable, 50 risks were unfavorable and 5 risks were acceptable for which the corrective strategies were required Then, the corrective revisions were proposed to reduce the risk level and calculate RAC2.

Corrective controlling measures including safety, health and environmental training, continual monitoring and ongoing visit are effective using the safety equipment and personal protective equipment for reducing the unacceptable risks.

Studies indicate that Muscularskeletal Disorders (MSD) are among the first ranks in terms of economic and healthcare cost of which back pain is in the first place.
Methods and Materials: This study was a cross-sectional study. The study participants were 100 students who were studying at the Tarbiat Modares University in the year of 2016. Data on back pain was collected via the standardized Quebec questionnaire. Quebec questionnaire contains 20 questions with 6 options by which pain intensity is ranked between 0 and 100. Collected data was analyzed using SPSS software version 16. In order to determine the status of musculoskeletal disorders and associated factors, descriptive statistics and chi-square test were used.
Totally 100 students who living in Tarbiat Modares University with mean age of 26.1 ± 3.1 were participated in the study. According to the results, 84% of the students (N = 84) were single, 15% (N = 15) were married, and 1% of the students (N = 1) was divorced. Eighty seven percent of the students (N = 87) were studying in Master degree and 10% of the students (N = 10) were studying in PhD degree. The majority of the students (60%, N = 60) did not report any musculoskeletal pain. However, forty students (40%) suffering from MSD.
This study was designed to investigate the musculoskeletal disorders among the students. As this study revealed a high percentage of the students were suffering from a kind of MSD, designing more researches to confirm these findings and also to design proper preventive intervention are strongly recommended.

In competing risks data، when a person experiences an event other than the one of interest in the study، usually the probability of experiencing the event of interest is altered. Therefore، it is necessary to analyze the competing risk data. The aim of this study was to analyze the breast cancer risk factors using the competing risk model in patients with breast cancer. In this cohort study، 6206 cancerous patients included all women diagnosed with breast cancer were identified during 1990-1999 by the British Columbia Cancer Center and followed until 2010. To compare the competing risk models، the stratified Cox and proportional sub-distribution hazards models were fitted. Findings showed that for breast cancer death، the hazard ratio increased for age (29%، 40%)، radiotherapy (71%، 55%) and hormone therapy (76%، 84%) in the stratified Cox and proportional sub-distribution hazards models، respectively. Surgery decreased the hazard ratio in both models (89%، 80%). For deaths not due to breast cancer، the hazard ratio for age (81%، 91%) and chemotherapy (67%، 61%) decreased in both models، respectively. The Cox model، which ignores the competing risks، presents the different estimates and results than the proportional sub-distribution hazards model. Thus، in the analysis of competing risks data، the sub-distribution proportion hazards model is more appropriate than the Cox model.