A method for cancer elemental risk assessments in hookah: An example in two common types of traditional and flavored tobaccos in Iran

Aim: This study aimed to compare the elemental composition of traditional and flavored hookah tobacco, with a focus on heavy metals. Methods: We used inductively coupled plasma mass spectrometry (ICP-MS) to analyze the concentrations of 29 elements in the raw tobacco, tobacco ash, hookah water after smoking, and tobacco smoke. Results: The results showed that the traditional tobacco had significantly higher metal concentrations than the flavored tobacco in all samples. Most of the toxic metals (more than 98 %) remained in the smoke of both types of tobacco. The tobacco and hookah smoke contained high levels of harmful metals that can pose health risks to hookah users. • ICP-MS provides a comprehensive analysis of multiple elements simultaneously and it allows for precise quantification of metal concentrations in different samples. • ICP-MS requires specialized equipment and trained personnel and it may not detect elements present in extremely low concentrations

Comparing Awareness about Occupational Exposure Management among Nursing, Midwifery, and Surgical Technology Students

Introduction: Occupational exposure with polluted sharp equipment usually occurs during procedures such as transfusion of blood and blood products, blood sampling, disposal of needles, and collection of polluted sharp materials. Considering the fact that students have less work experience and lower practical skills, they are more vulnerable to work-related infections. The present study was conducted to determine and compare the awareness of nursing, midwifery, and surgical technology students about occupational exposure management. Methods: This descriptive-analytical cross-sectional study was conducted on 221 students of nursing, midwifery, and surgical technology selected using the stratified random sampling in 2016. Data gathering tool was a researcher-made questionnaire including the students' demographic characteristics and awareness about occupational exposure management. Data were analyzed by SPSS18 using descriptive and analytical statistical tests. Results: Our findings showed that the mean scores of awareness about occupational exposure management were not significantly different among the nursing, midwifery, and surgical technology students (p value = 0.435). We observed that the students' age and educational level were significantly correlated with their scores of awareness about occupational exposure management (p value < 0.001). Conclusions: Results of the present study indicated poor awareness of the students about in-time management of occupational exposure. Measures such as educational workshops on preventive aspects in occupational exposure, observance of safety principles and comprehensive standards for accurate measurement of viral markers should be taken. Individual health profiles should be designed for each student to improve the occupational exposure management. &nbsp

Jet grouting column diameter prediction based on a data-driven approach

This study takes advantage of the high learning capabilities of data mining (DM) techniques towards to the development of a novel approach for jet grouting (JG) column diameter prediction. The high number of variables involved in JG technology as well as the complex phenomena related with the injection process make JG column diameter (D) prediction a difficult task. Therefore, in order to overcome it, the flexible learning capabilities of DM techniques were applied as an alternative approach of the traditional tools. The achieved results show that both artificial neural network and support vector machine algorithms can be trained to accurately predict D built in different soil types of clayey nature and using different JG systems. In both cases a coefficient of correlation () very close to the unity was achieved. For models training, a set of eight input variables were considered. Among them, the rod withdrawal speed, flow rate of the grout slurry and the JG system were identified as the most relevant ones, although the grout pressure and the dynamic impact of the grout also revealed an important influence on D prediction. Moreover, additionally to the identification of the key model variables, it was also measured their effects on D prediction based on a data-based sensitivity analysis. These achievements represent a novel contribution for JG technology, mainly at the design level. Furthermore, the obtained results also underline the potential and contribution of DM to solving complex problem in geotechnical engineering.The authors wish to thank to “Fundação para a Ciência e a Tecnologia” (FCT) for the financial support under the strategic project PEst-OE/ECI/UI4047/2011 as well as the Pos-Doc grant SFRH/BPD/94792/2013. Also, the authors would like to thank the interest of Tecnasol-FGE that supplied all data used in this study.info:eu-repo/semantics/publishedVersio