Thesis (M.S.)--Boston University

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Several factors affect the activities of the mining industry. For example, accident rates are critical because they affect company ratings in the stock market (Standard & Poors). Considering that the corporate image is directly related to its stakeholders, this study conducts an accident analysis using quantitative and qualitative methods. In this way, the contingency rate is controlled, mitigated, and prevented while serving the needs) of the stakeholders. The Bayesian network method contributes to decision-making through a set of variables and the dependency relationships between them, establishing an earlier probability of unknown variables. Bayesian models have different applications, such as diagnosis, classification, and decision, and establish relationships among variables and cause–effect links. This study uses Bayesian inference to identify the various patterns that influence operator accident rates at a contractor mining company, and therefore, study and assess the possible differences in its future operations.

Cerebrovascular accidents (CVAs) are a leading cause of morbidity and mortality in the United States. Metabolic derangements such as hypoglycemia, infections, brain masses or lesions, neurodegenerative disorders, neuropathies, myelopathies, seizures, syncope, types of migraines, and many other disorders may mimic CVA. Our case presents a 38-year-old female who was evaluated in the emergency department with a three- hour history of headache, lethargy, left- sided upper extremity weakness, facial droop, and dysarthria. A CVA workup was initiated and she immediately underwent a computed tomography (CT) scan of the head which revealed no intracranial hemorrhage. She was unable to provide a thorough medical history due to lethargy, however she was able to answer yes/no questions to screen for tissue plasminogen activator (tPA) qualification. She qualified based on her screening results and was administered tPA for her presumed ischemic CVA. She was then monitored in the intensive care unit for twenty-four hours. Due to reoccurrence of headache and left-sided weakness, as well as recent administration of tPA increasing risk of hemorrhage, she underwent two subsequent negative non- contrast head CT scans to rule out bleeding during that time. On hospital day two, magnetic resonance imaging (MRI) of the head, neck, and spine were performed which were also negative for infarct or hemorrhage. A more detailed history from our patient revealed previous migraine headaches, but her left sided weakness and dysarthria were new symptoms. With this information, it was suspected that she was suffering from a hemiplegic migraine, a rare mimic of CVA. Prochlorperazine, diphenhydramine, valproic acid, and corticosteroids were administered for migraine treatment, which aborted her symptoms entirely. Topiramate was then started for migraine prophylaxis. Daily low-dose aspirin was also initiated due to inability to fully rule out CVA/transient ischemic attack (TIA). An outpatient neurology follow up was scheduled on discharge. In clinical practice, hemiplegic migraines and CVA/TIA may be difficult to differentiate as symptoms often overlap. A detailed history and physical exam with careful attention to associated symptoms and timing of symptom onset is essential to formulating a correct diagnosis. This must be done quickly, as tPA is a high-risk medication with a narrow time window for administration. In conclusion, not all disease processes have an available “gold standard” diagnostic test to differentiate similar diagnoses. MRI of the brain is usually performed to differentiate ischemic CVA from TIA; however, imaging is not useful to differentiate hemiplegic migraine from TIA. Therefore, performing a thorough history, physical exam, and chart review is paramount to provide patients with the correct treatment as well as prevent adverse outcomes. It is the responsibility of the clinician to make difficult decisions weighing the risks and benefits of providing various treatments or interventions, and to know the complications of those treatments. Disease processes mimicking CVA must be considered in all patients, as treating an incorrect diagnosis can have devastating effects.

No description available.

No description available.

Thesis (M.S.)--Boston University

No description available.

Yes / Job stress and safety climate have been recognized as two crucial factors that can increase the risk of occupational accidents. This study was performed to determine the relationship between job stress and safety climate factors in the occurrence of accidents using the Bayesian network model. This cross-sectional study was performed on 1530 male workers of Asaluyeh petrochemical company in Iran. The participants were asked to complete the questionnaires, including demographical information and accident history questionnaire, NIOSH generic job stress questionnaire, and Nordic safety climate questionnaire. Also, work experience and the accident history data were inquired from the petrochemical health unit. Finally, the relationships between the variables were investigated using the Bayesian network model. A high job stress condition could decrease the high safety climate from 53 to 37% and increase the accident occurrence from 72 to 94%. Moreover, a low safety climate condition could increase the accident occurrence from 72 to 93%. Also, the concurrent high job stress and low safety climate could raise the accident occurrence from 72 to 93%. Among the associations between the job stress factor and safety climate dimensions, the job stress and worker's safety priority and risk non-acceptance (0.19) had the highest mean influence value. The adverse effect of high job stress conditions on accident occurrence is twofold. It can directly increase the accident occurrence probability and in another way, it can indirectly increase the accident occurrence probability by causing the safety climate to go to a lower level.

Existing containment models for a loss of coolant accident at many nuclear power plants were created in the 1970s using older computer technology and thermal hydraulic models which were available at that time. While conservative, these models may not present the detail necessary to identify conditions which may be used to produce additional design margin for the plant. After exploring containment and critical flow modeling, the basis for the use of GOTHIC in this analysis was established. A GOTHIC model was then created to simulate the loss of coolant accident results shown in an Updated Final Safety Analysis Report analysis for the North Anna Power Station. This model was used to examine the effects of increased nodalization in a subcompartment on the existing containment model. It is shown that adding multidimensional sub-nodes to areas of interest can provide valuable detail which was absent in the UFSAR model. Simulations are able to show the localized pressure spike around a LOCA pipe break that quickly dissipates, leaving significantly lower pressures in what was once an averaged, single, lumped-parameter node. This suggests that additional design margin may exist depending on where the pipe break is assumed to occur. / Master of Science

No / To investigate the cross-cultural validity of international Dutch-English comparisons when using the Dutch Rivermead Mobility Index (RMI), and the intra-test reliability and construct validity of the Dutch RMI. METHODS: Cross-cultural validity was studied in a combined data-set of Dutch and English patients undergoing rehabilitation after stroke, who were assessed with the Dutch version of the RMI and the original English RMI, respectively. Mokken scale analysis was used to investigate unidimensionality, monotone homogeneity model fit, and differential item functioning between the Dutch and the English RMI. Intra-test reliability and construct validity were studied in the Dutch patients by calculating the reliability coefficient and correlating the Dutch RMI and the Dutch Barthel Index. RESULTS: The RMI was completed for Dutch (n = 200) and English (n = 420) patients after stroke. The unidimensionality and monotone homogeneity model fit of the RMI were excellent: combined Dutch-English data-set (coefficient H = 0.91); Dutch data-set (coefficient H = 0.93); English data-set (coefficient H = 0.89). No differential item functioning was found between the Dutch and the English RMI. The intra-test reliability of the Dutch RMI was excellent (coefficient rho = 0.97). In a sub-sample of patients (n = 91), the Dutch RMI correlated strongly with the Dutch Barthel Index (Spearman's correlation coefficient rho = 0.84). CONCLUSION: The Dutch RMI allows valid international Dutch-English comparisons, and has excellent intra-test reliability and construct validity.