METHODS: In this study, a time series analysis was used to determine the variation of variables over time. All series were seasonally adjusted and Poisson regression analysis was performed. In the analysis of meteorological data and emotional distress due to religious mourning events, the best results were obtained by autoregressive moving average (ARMA) (5,5) model.
RESULTS: It was determined that average temperature, sunshine, and rain variables had a significant effect on death. A total of 2375 AMI's were enrolled. Average temperate (°C) and sunshine hours a day (h/day) had a statistically significant relationship with the number of AMI's (β = 0.011, P = 0.014). For every extra degree of temperature increase, the risk of AMI rose [OR = 1.011 (95%CI 1.00, 1.02)]. For every extra hour of sunshine, a day a statistically significant increase [OR = 1.02 (95% CI 1.01, 1.04)] in AMI risk occurred (β = 0.025, P = 0.001). Religious mourning events increase the risk of AMI 1.05 times more. The other independent variables have no significant effects on AMI's (P > 0.05).
CONCLUSION: Results demonstrate that sunshine hours and the average temperature had a significant effect on the risk of AMI. Moreover, emotional distress due to religious morning events increases AMI. More specific research on this topic is recommended.
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.
METHODS: We used the Autoregressive Moving Average Models (ARIMA) to forecast the number of cases in the upcoming 14 days and the Spearman correlation analysis to analyze the relationship between B.1.1.7 cases and meteorological variables such as temperature, humidity, rainfall, sunshine, and wind speed.
RESULTS: The results of the study showed the fitted ARIMA models forecasted there was an increase in the daily cases in three provinces. The total cases in three provinces would increase by 36% (West Java), 13.5% (South Sumatra), and 30% (East Kalimantan) as compared with actual cases until the end of 14 days later. The temperature, rainfall and sunshine factors were the main contributors for B.1.1.7 cases with each correlation coefficients; r = -0.230; p < 0.05, r = 0.211; p < 0.05 and r = -0.418; p < 0.01, respectively.
CONCLUSIONS: We recapitulated that this investigation was the first preliminary study to analyze a short-term forecast regarding COVID-19 and B.1.1.7 cases as well as to determine the associated meteorological factors that become primary contributors to the virus spread.
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.
METHODS: 12-year observational study of a UK Fracture Liaison Service (outpatient secondary care setting). Database analyses of the records of adult outpatients aged 50 years and older with fragility fractures. Weather data were obtained from the UK's national Meteorological Office. In the seasonality analyses, we tested for the association between months and seasons (determinants), respectively, and outpatient attendances, by analysis of variance (ANOVA) and Tukey's test. In the meteorological analyses, the determinants were mean temperature, mean daily maximum and minimum temperature, number of days of rain, total rainfall and number of days of frost, per month, respectively. We explored the association of each meteorological variable with outpatient attendances, by regression models.
RESULTS: The Fracture Liaison Service recorded 25,454 fragility fractures. We found significant monthly and seasonal variation in attendances for fractures of the: radius or ulna; humerus; ankle, foot, tibia or fibula (ANOVA, all p-values <0.05). Fractures of the radius or ulna and humerus peaked in December and winter. Fractures of the ankle, foot, tibia or fibula peaked in July, August and summer. U-shaped associations were showed between each temperature parameter and fractures. Days of frost were directly associated with fractures of the radius or ulna (p-value <0.001) and humerus (p-value 0.002).
CONCLUSION: Different types of fragility fractures present different seasonal patterns. Weather may modulate their seasonality and consequent healthcare utilisation.