970 resultados para fatal accidents


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BACKGROUND: Pseudomonas aeruginosa is the major pathogen associated with chronic and ultimately fatal lung infections in patients with cystic fibrosis (CF). To investigate how P. aeruginosa-derived vesicles may contribute to lung disease, we explored their ability to associate with human lung cells. RESULTS: Purified vesicles associated with lung cells and were internalized in a time- and dose-dependent manner. Vesicles from a CF isolate exhibited a 3- to 4-fold greater association with lung cells than vesicles from the lab strain PAO1. Vesicle internalization was temperature-dependent and was inhibited by hypertonic sucrose and cyclodextrins. Surface-bound vesicles rarely colocalized with clathrin. Internalized vesicles colocalized with the endoplasmic reticulum (ER) marker, TRAPalpha, as well as with ER-localized pools of cholera toxin and transferrin. CF isolates of P. aeruginosa abundantly secrete PaAP (PA2939), an aminopeptidase that associates with the surface of vesicles. Vesicles from a PaAP knockout strain exhibited a 40% decrease in cell association. Likewise, vesicles from PAO1 overexpressing PaAP displayed a significant increase in cell association. CONCLUSION: These data reveal that PaAP promotes the association of vesicles with lung cells. Taken together, these results suggest that P. aeruginosa vesicles can interact with and be internalized by lung epithelial cells and contribute to the inflammatory response during infection.

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BACKGROUND: Road traffic injuries (RTIs) are a growing but neglected global health crisis, requiring effective prevention to promote sustainable safety. Low- and middle-income countries (LMICs) share a disproportionately high burden with 90% of the world's road traffic deaths, and where RTIs are escalating due to rapid urbanization and motorization. Although several studies have assessed the effectiveness of a specific intervention, no systematic reviews have been conducted summarizing the effectiveness of RTI prevention initiatives specifically performed in LMIC settings; this study will help fill this gap. METHODS: In accordance with PRISMA guidelines we searched the electronic databases MEDLINE, EMBASE, Scopus, Web of Science, TRID, Lilacs, Scielo and Global Health. Articles were eligible if they considered RTI prevention in LMICs by evaluating a prevention-related intervention with outcome measures of crash, RTI, or death. In addition, a reference and citation analysis was conducted as well as a data quality assessment. A qualitative metasummary approach was used for data analysis and effect sizes were calculated to quantify the magnitude of emerging themes. RESULTS: Of the 8560 articles from the literature search, 18 articles from 11 LMICs fit the eligibility and inclusion criteria. Of these studies, four were from Sub-Saharan Africa, ten from Latin America and the Caribbean, one from the Middle East, and three from Asia. Half of the studies focused specifically on legislation, while the others focused on speed control measures, educational interventions, enforcement, road improvement, community programs, or a multifaceted intervention. CONCLUSION: Legislation was the most common intervention evaluated with the best outcomes when combined with strong enforcement initiatives or as part of a multifaceted approach. Because speed control is crucial to crash and injury prevention, road improvement interventions in LMIC settings should carefully consider how the impact of improvements will affect speed and traffic flow. Further road traffic injury prevention interventions should be performed in LMICs with patient-centered outcomes in order to guide injury prevention in these complex settings.

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p.67-76

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The interactions between water curtain protective barriers and impinging cold gas clouds released during industrial accidents are simulated by a 2D finite difference code using a PSI-cell of the heat, mass and momentum transfer processes between the phases. A consistent derivation of the continuous phase source terms is presented. The results of early simulations of an existing 1:10 experimental model of a water curtain impacted by a cold gas cloud are presented for two typical curtain configurations.

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The purpose of this paper is to demonstrate the potential of the EXODUS evacuation model in building environments. The latest PC/workstation version of EXODUS is described and is also applied to a large hypothetical supermarket/restaurant complex measuring 50 m x 40 m. A range of scenarios is presented where population characteristics (such as size, individual travel speeds, and individual response times), and enclosure configuration characteristics (such as number of exits, size of exits, and opening times of exits) are varied. The results demonstrate a wide range of occupant behavior including overtaking, queuing, redirection, and conflict avoidance. Evacuation performance is measured by a number of model predicted parameters including individual exit flow rates, overall evacuation flow rates, total evacuation time, average evacuation time per occupant, average travel distance, and average wait time. The simulations highlight the profound impact that variations in individual travel speeds and occupant response times have in determining the overall evacuation performance. 1. Jin, T., and Yamada T., "Experimental Study of Human Behavior in Smoke Filled Corridors," Proceedings of The Second International Symposium on Fire Safety Science, 1988, pp. 511-519. 2. Galea, E.R., and Galparsoro, J.M.P., "EXODUS: An Evacuation Model for Mass Transport Vehicles," UK CAA Paper 93006 ISBN 086039 543X, CAA London, 1993. 3. Galea, E.R., and Galparsoro, J.M.P., "A Computer Based Simulation Model for the Prediction of Evacuation from Mass Transport Vehicles," Fire Safety Journal, Vol. 22, 1994, pp. 341-366. 4. Galea, E.R., Owen, M., and Lawrence, P., "Computer Modeling of Human Be havior in Aircraft Fire Accidents," to appear in the Proceedings of Combus tion Toxicology Symposium, CAMI, Oklahoma City, OK, 1995. 5. Kisko, T.M. and Francis, R.L., "EVACNET+: A Computer Program to Determine Optimal Building Evacuation Plans," Fire Safety Journal, Vol. 9, 1985, pp. 211-220. 6. Levin, B., "EXITT, A Simulation Model of Occupant Decisions and Actions in Residential Fires," Proceedings of The Second International Symposium on Fire Safety Science, 1988, pp. 561-570. 7. Fahy, R.F., "EXIT89: An Evacuation Model for High-Rise Buildings," Pro ceedings of The Third International Sym posium on Fire Safety Science, 1991, pp. 815-823. 8. Thompson, P.A., and Marchant, E.W., "A Computer Model for the Evacuation of Large Building Populations," Fire Safety Journal, Vol. 24, 1995, pp. 131-148. 9. Still, K., "New Computer System Can Predict Human Behavior Response to Building Fires," FIRE 84, 1993, pp. 40-41. 10. Ketchell, N., Cole, S.S., Webber, D.M., et.al., "The Egress Code for Human Move ment and Behavior in Emergency Evacu ations," Engineering for Crowd Safety (Smith, R.A., and Dickie, J.F., Eds.), Elsevier, 1993, pp. 361-370. 11. Takahashi, K., Tanaka, T. and Kose, S., "An Evacuation Model for Use in Fire Safety Design of Buildings," Proceedings of The Second International Symposium on Fire Safety Science, 1988, pp. 551- 560. 12. G2 Reference Manual, Version 3.0, Gensym Corporation, Cambridge, MA. 13. XVT Reference Manual, Version 3.0 XVT Software Inc., Boulder, CO. 14. Galea, E.R., "On the Field Modeling Approach to the Simulation of Enclosure Fires, Journal of Fire Protection Engineering, Vol. 1, No. 1, 1989, pp. 11-22. 15. Purser, D.A., "Toxicity Assessment of Combustion Products," SFPE Handbook of Fire Protection Engineering, National Fire Protection Association, Quincy, MA, pp. 1-200 - 1-245, 1988. 16. Hankin, B.D., and Wright, R.A., "Pas senger Flows in Subways," Operational Research Quarterly, Vol. 9, 1958, pp. 81-88. 17. HMSO, The Building Regulations 1991 - Approved Document B, section B 1 (1992 edition), HMSO publications, London, pp. 9-40. 18. Polus A., Schofer, J.L., and Ushpiz, A., "Pedestrian Flow and Level of Service," Journal of Transportation Engineering, Vol. 109, 1983, pp. 46-47. 19. Muir, H., Marrison, C., and Evans, A., "Aircraft Evacuations: the Effect of Passenger Motivation and Cabin Con figuration Adjacent to the Exit," CAA Paper 89019, ISBN 0 86039 406 9, 1989. 20. Muir, H., Private communication to appear as a CAA report, 1996.

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Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

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Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

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While incidents requiring the rapid egress of passengers from trains are infrequent, perhaps the most challenging scenario for passengers involves the evacuation from an overturned carriage subjected to fire. In this paper we attempt to estimate the flow rate capacity of an overturned rail carriage end exit. This was achieved through two full-scale evacuation experiments, in one of which the participants were subjected to non-toxic smoke. The experiments were conducted as part of a pilot study into evacuation from rail carriages. In reviewing the experimental results, it should be noted that only a single run of each trial was undertaken with a limited — though varied — population. As a result it is not possible to test the statistical significance of the evacuation times quoted and so the results should be treated as indicative rather than definitive. The carriage used in the experiments was a standard class Mark IID which, while an old carriage design, shares many features with those carriages commonly found on the British rail network. In the evacuation involving smoke, the carriage end exit was found to achieve an average flow rate capacity of approximately 5.0 persons/min. The average flow rate capacity of the exit without smoke was found to be approximately 9.2 persons/min. It was noted that the presence of smoke tended to reduce significantly the exit flow rate. Due to the nature of the experimental conditions, these flow rates are considered optimistic. Finally, the authors make several recommendations for improving survivability in rail accidents. Copyright © 2000 John Wiley & Sons, Ltd.

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The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.

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This paper describes recent developments with the Aircraft Accident Statistics and Knowledge (AASK) database. The AASK database is a repository of survivor accounts from aviation accidents developed by the Fire Safety Engineering Group of the University of Greenwich with support from the UK CAA. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. Access to the latest version of the database (AASK V3.0) is available over the Internet. AASK consists of information derived from both passenger and cabin crew interviews, information concerning fatalities and basic accident details. Also provided with AASK is the Seat Plan Viewer that graphically displays the starting locations of all the passengers - both survivors and fatalities - as well as the exits used by the survivors. Data entered into the AASK database is extracted from the transcripts supplied by the National Transportation Safety Board in the US and the Air Accident Investigation Branch in the UK. The quality and quantity of the data was very variable ranging from short summary reports of the accidents to boxes of individual accounts from passengers, crew and investigators. Data imported into AASK V3.0 includes information from 55 accidents and individual accounts from 1295 passengers and 110 crew.