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All issues Volume 201 (2020) E3S Web Conf., 201 (2020) 01021 References
Open Access
Issue
E3S Web Conf.
Volume 201, 2020
Ukrainian School of Mining Engineering - 2020
Article Number 01021
Number of page(s) 11
DOI https://doi.org/10.1051/e3sconf/202020101021
Published online 23 October 2020
  1. ISO/IEC31010:2009 .(2009). Risk management - Risk assessment techniques. Geneva: International Organization for Standardization. [Google Scholar]
  2. ISO45001:2018.( 2018). Occupational health and safety management systems — Requirements with guidance for use. Geneva: International Organization for Standardization. [Google Scholar]
  3. Respiratory Protection Equipment Market worth 7.28 Billion USD by 2022 Markets and Markets. Respiratory Protection Equipment Market by Product Type (Air-purifying Respirators, 5upplied Air Respirators), End-use Industry (Healthcare & pharmaceuticals, Defense & Public Safety Services, Oil & Gas, Manufacturing, Mining) - Global Forecast to 2022 (2017). [Google Scholar]
  4. Han, S., Chen, H., Harvey, M-A., Stemp, E., & Cliff, D. (2018). Focusing on Coal Workers’ Lung Diseases: A Comparative Analysis of China, Australia, and the United States. International Journal of Environmental Research and Public Health, 15(11), 2565.https://doi.org/10.3390/ijerph15112565 [CrossRef] [Google Scholar]
  5. Blackley Blackley, D. J., Halldin, C. N., & Laney, A. S. (2018). Continued Increase in Prevalence of Coal Workers’ Pneumoconiosis in the United States, 1970-2017. American Journal of Public Health, 108(9),1220-1222. https://doi.org/10.2105/ajph.2018.304517 [CrossRef] [PubMed] [Google Scholar]
  6. Occupational safety and health in the mining industry in Ukraine. (2018). International Labour Organization. DWT and Country Office for Central and Eastern Europe. Kyiv, Ukraine. [Google Scholar]
  7. Aneziris, O.N., Papazoglou, I.A., Konstantinidou, M., & Nivolianitou, Z. (2014). Integrated risk assessment for LNG terminals. Journal of Loss Prevention in the Process Industries, (28), 23-35. https://doi.org/10.1016/j.jlp.2013.07.014 [CrossRef] [Google Scholar]
  8. Ramesh, R., Prabu, M., Magibalan, S., & Senthilkumar, P. (2017). Hazard Identification and Risk Assessment in Automotive Industry. International Journal of ChemTech Research, 10(4),352-358. [Google Scholar]
  9. Directive 89/391/EEC - OSH “Framework Directive”. (2018). On the introduction of measures to encourage improvements in the safety and health of workers at work - “Framework Directive ”. Brussels: European Agency for Safety and Health at Work. [Google Scholar]
  10. Lachapelle, E., & Voca, N. (2014). OHSAS 18001. Occupational health and safety management systems - Requirements. Canada: PECB Headquarters. [Google Scholar]
  11. Di Noia, A., Martino, A., Montanari, P., & Rizzi, A. (2019). Supervised machine learning techniques and genetic optimization for occupational diseases risk prediction. Soft Computing, 24(6),4393-4406. https://doi.org/10.1007/s00500-019-04200-2 [CrossRef] [Google Scholar]
  12. Benavides, F., Ramada, J., Ubalde-Lopez, M., Delclos, G., & Serra, C. (2019). A Hospital Occupational Diseases Unit: An Experience to Increase the Recognition of Occupational Disease. La Medicina delLavoro, 110(4),278-284. https://doi.org/10.23749/mdl.v110i4.8138 [Google Scholar]
  13. Van der Molen, & Frings-Dresen. (2019). Occupational Diseases: From Cure to Prevention. Journal of Clinical Medicine, 8(10), 1681. https://doi.org/10.3390/jcm8101681 [CrossRef] [Google Scholar]
  14. Shafiei, M., Ghasemian, A., Eslami, M., Nojoomi, F., & Rajabi-Vardanjani, H. (2019). Risk factors and control strategies for silicotuberculosis as an occupational disease. New Microbes and New Infections, (27), 75-77. https://doi.org/10.1016/j.nmni.2018.11.002 [CrossRef] [PubMed] [Google Scholar]
  15. Rezapour, M., Khorrami, Z., Tabe, R., & Khanjani, N. (2019). The Prevalence of Occupational Risk Factors and Occupational Diseases in Kerman, Iran. International Journal of Epidemiologic Research, 6(2),65-69. https://doi.org/10.15171/iier.2019.12 [CrossRef] [Google Scholar]
  16. Di Piazza, A., Argo, A., Scalici, E., Guajana, A., Picone, D., & Lo Re, G. (2019). Occupational Diseases: Asbestosis and Mesothelioma in Forensic Practice. Radiology in Forensic Medicine, 189-195. https://doi.org/10.1007/978-3-319-96737-017 [Google Scholar]
  17. Carrico, R.M., Coty, M.B., Goss, L.K., & LaJoie, A.S. (2007). Changing health care worker behavior in relation to respiratory disease transmission with a novel training approach that uses biosimulation. American Journal of Infection Control, 35(1),14-19.https://doi.org/10.1016/i.aiic.2005.12.013 [CrossRef] [PubMed] [Google Scholar]
  18. Bergman, M.S., Zhuang, Z., Hanson, D., Heimbuch, B.K., McDonald, M.J., Palmiero, A.J., … Wander, J.D. (2013). Development of an Advanced Respirator Fit-Test Headform. Journal of Occupational and Environmental Hygiene, 11(2),117-125.https://doi.org/10.1080/15459624.2013.816434 [Google Scholar]
  19. Nicas, M. (2001). Modeling Turbulent Diffusion and Advection of Indoor Air Contaminants by Markov Chains. American Industrial Hygiene Association Journal, 62(2),149-158.https://doi.org/10.1080/15298660108984617 [CrossRef] [PubMed] [Google Scholar]
  20. Nelson, T.J. (1995). The Assigned Protection Factor of 10 for Half-mask Respirators. American Industrial Hygiene Association Journal, 56(7),717-724.https://doi.org/10.1080/15428119591016755 [CrossRef] [PubMed] [Google Scholar]
  21. Colton, C.E., & Bidwell, J.O. (1995). A Comparison of the Workplace Performance of Two Different Types of High-Efficiency CE Filters on Half-Facepiece Respirators. In American Industrial Hygiene Conference and Exposition (pp. 34-45). Kansas City, Missouri,USA . [Google Scholar]
  22. Tannahill, S.N., Willey, R.J., & Jackson, M.H. (1990). Workplace protection factors of hse approved negative pressure full-facepiece dust respirators during asbestos stripping: preliminary findings. The Annals of Occupational Hygiene, 34(6),547-552.https://doi.org/10.1093/annhyg/34.6.547 [PubMed] [Google Scholar]
  23. Johnston, A.R., & Mullins, H.E. (1987). Workplace Protection Factor Study for Airborne Meal Dusts. In American Industrial Hygiene Conference and Exposition (pp. 64-75). Kansas City, Missouri, USA. [Google Scholar]
  24. Golinko, V. I., Yavorskaya, E. A., Cheberyachko, Y. I., Cheberyachko, S. I. (2015). Analysis of protective value of dust-fighting respirators and its effect on dust burden of miners. Gornyi Zhurnal, 76-80. https://doi.org/10.17580/gzh.2016.03.16 [CrossRef] [Google Scholar]
  25. Franna, R., & Gaspar, R.M. (2011). Expectation Hypothesis Bias: Risk Aversion versus Stochastic Adjustments. SSRN Electronic Journal. ADVANCE working paper Series, n. 1/2011. https://doi.org/10.2139/ssrn.2417268 [Google Scholar]
  26. Bansal, R., & Yaron, A. (2004). Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles. The Journal of Finance, 59(4), 1481-1509. https://doi.org/10.1111/j.1540-6261.2004.00670.x [Google Scholar]
  27. Golinko, V.I., Cheberyachko, S.I., Yavorskaya, E.A., & Cheberyachko, Y.I. (2016). Analysis of protective value of dust-fighting respirators and its effect on dust burden of miners. Gornyi Zhurnal, (3), 76-80. [Google Scholar]
  28. Cheberyachko, S., Yavors’ka, O., & Morozova, T. (2013). Study of mechanical half-mask pressure along obturation bar. Annual Scientific-Technical Colletion - Mining of Mineral Deposits 2013, 317-322. https://doi.org/10.1201/b16354-58 [Google Scholar]
  29. Cheberiachko, S., Yavors’ka, O., Radchuk, D., & Yavorskyi, A. (2018). Respiratory Protection Provided by Negative Pressure Half Mask Filtering Respirators in Coal Mines. Solid State Phenomena, (277), 232-240. https://doi.org/10.4028/www.scientific.net/ssp.277.232 [CrossRef] [Google Scholar]
  30. Graveling, R., Sanchez-Jimenez, A., Lewis, C., & Groat, S. (2011). Protecting Respiratory Health: What Should be the Constituents of an Effective RPE programme? The Annals of Occupational Hygiene, 55(3),230-238. https://doi.org/10.1093/annhyg/meq098 [PubMed] [Google Scholar]

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