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.
MATERIALS AND METHODS: Eighty test specimens were fabricated according to the manufacturer's instructions into rectangular test specimens. The hardness and surface roughness were tested, after 6 months of exposure to natural hot and dry weather. The hardness was measured through the International Rubber Hardness Degree (IRHD) scale using an automated hardness tester. The surface roughness was measured using a novel 3D optical noncontact technique using a combination of a light sectioning microscope and a computer vision system. Statistical Package for Social Sciences software SPSS/version 24 was used for analysis and a comparison between two independent variables was done using an independent t test, while more than two variables were analyzed, F test (ANOVA) to be used followed by a post hoc test to determine the level of significance between every two groups.
RESULTS: The hot and dry weather statistically influenced the hardness and surface roughness of MFSEM. Cosmesil M-511 showed the least hardness in test groups while A-2000 showed the hardest material (p < 0.05). A-2000 showed significant changes from rough in case of nonweathered to become smoother in weather followed by A-2186 (p < 0.05). Cosmesil M-511 showed the roughest material.
CONCLUSION: Cosmesil M-511 showed the least hard MFSEM after outdoor weathering while A-2000, the highest and least material showed hardness and surface roughness, respectively.
CLINICAL IMPLICATION: A-2000 had a high IRHD scale hardness. This makes this material more suitable for the replacement of ear and nose defects. Cosmesil M-511 is soft and easily adaptable material that makes the material more appropriate for the replacement of small facial defect with undercut area to be easily inserted and removed. Whilst A-2000 is smoother and finer in test specimens after weathering, Cosmesil M-511 became rougher after weathering.