PURPOSE: The purpose of this in vitro study was to evaluate the SR, tensile strength (TS), and percentage elongation (% E) of different SEs subjected to outdoor weathering in the Malaysian climate.
MATERIAL AND METHODS: Type-II dumbbell-shaped specimens (N-120) (nonweathered=15, weathered=15) were made from 3 room-temperature vulcanized (A-2000, A-2006, and A-103) and 1 heat-temperature vulcanized (M-511) silicone (Factor II). For 6 months, weathered specimens were subjected to outdoor weathering inside a custom exposure rack. Simultaneously, the nonweathered specimens were kept in a dehumidifier. Subsequently, the SR was measured with a profilometer; TS and % E were measured by using a universal testing machine. Two-way ANOVA was used to compare the means of the tested properties of the nonweathered and weathered specimens, and pairwise comparison was carried out between the silicones (α=.05).
RESULTS: After outdoor weathering, the SR, TS, and % E were adversely affected by weathering in the Malaysian environment. Among the silicone materials, A-2000 showed the least TS changes (2.51 MPa), while A-2006 demonstrated significant changes in percentage elongation after outdoor weathering (266.5%). M-511 exhibited the highest mean value (2.50 μm) for SR changes. In addition, A-103 SE showed statistically significant differences in most pairwise comparisons for all 3 dependent variables.
CONCLUSIONS: Based on the evaluation of mechanical properties, A-103 can be suggested as a suitable silicone for maxillofacial prostheses fabricated for tropical climates. However, A-2000 can be a suitable alternative, although significant changes to surface roughness were detected after outdoor weathering.
METHOD: This study proposes a combination of decision tree and logistic regression techniques to model crash severity (injury vs. noninjury), because the combined approach allows the specification of nonlinearities and interactions in addition to main effects. Both a scobit model and a random parameters logit model, respectively accounting for an imbalance response variable and unobserved heterogeneities, are tested and compared. The study data set contains a total of 5 years of crash data (2008-2012) on selected mountainous highways in Malaysia. To enrich the data quality, an extensive field survey was conducted to collect detailed information on horizontal alignment, longitudinal grades, cross-section elements, and roadside features. In addition, weather condition data from the meteorology department were merged using the time stamp and proximity measures in AutoCAD-Geolocation.
RESULTS: The random parameters logit model is found to outperform both the standard logit and scobit models, suggesting the importance of accounting for unobserved heterogeneity in crash severity models. Results suggest that proportion of segment lengths with simple curves, presence of horizontal curves along steep gradients, highway segments with unsealed shoulders, and highway segments with cliffs along both sides are positively associated with injury-producing crashes along rural mountainous highways. Interestingly, crashes during rainy conditions are associated with crashes that are less likely to involve injury. It is also found that the likelihood of injury-producing crashes decreases for rear-end collisions but increases for head-on collisions and crashes involving heavy vehicles. A higher order interaction suggests that single-vehicle crashes involving light and medium-sized vehicles are less severe along straight sections compared to road sections with horizontal curves. One the other hand, crash severity is higher when heavy vehicles are involved in crashes as single vehicles traveling along straight segments of rural mountainous highways.
CONCLUSION: In addition to unobserved heterogeneity, it is important to account for higher order interactions to have a better understanding of factors that influence crash severity. A proper understanding of these factors will help develop targeted countermeasures to improve road safety along rural mountainous highways.
RESULTS: Sea surface temperatures (SSTs) in the equatorial east Pacific ocean have anomalously increased significantly during July - October 2006 indicating the typical development of El Niño conditions. The persistence of these conditions will lead to extremes in global-scale climate anomalies as has been observed during similar conditions in the past. Positive Outgoing Longwave Radiation (OLR) anomalies, indicative of severe drought conditions, have been observed across all of Indonesia, Malaysia and most of the Philippines, which are usually the first areas to experience ENSO-related impacts. This dryness can be expected to continue, on average, for the remainder of 2006 continuing into the early part of 2007. During the period November 2006 - January 2007 climate forecasts indicate that there is a high probability for above normal rainfall in the central and eastern equatorial Pacific Islands, the Korean Peninsula, the U.S. Gulf Coast and Florida, northern South America and equatorial east Africa. Taking into consideration current observations and climate forecast information, indications are that the following regions are at increased risk for disease outbreaks: Indonesia, Malaysia, Thailand and most of the southeast Asia Islands for increased dengue fever transmission and increased respiratory illness; Coastal Peru, Ecuador, Venezuela, and Colombia for increased risk of malaria; Bangladesh and coastal India for elevated risk of cholera; East Africa for increased risk of a Rift Valley fever outbreak and elevated malaria; southwest USA for increased risk for hantavirus pulmonary syndrome and plague; southern California for increased West Nile virus transmission; and northeast Brazil for increased dengue fever and respiratory illness.
CONCLUSION: The current development of El Niño conditions has significant implications for global public health. Extremes in climate events with above normal rainfall and flooding in some regions and extended drought periods in other regions will occur. Forecasting disease is critical for timely and efficient planning of operational control programs. In this paper we describe developing global climate anomalies that suggest potential disease risks that will give decision makers additional tools to make rational judgments concerning implementation of disease prevention and mitigation strategies.