Despite the favourable result of Willems' method in comparison with Demirjian's method, this study demonstrated a high correlation coefficient between both chronological and obtained dental age, thus confirming their potential applicability in clinical practice and forensic dentistry.

Objective: To assess the prevalence of malocclusion and deleterious oral habits among 12 and 15-year-old school children in Shimla city, India and to find, if any correlation exists between the two. Design: Correlational study design. Setting: Twelve schools in Shimla city, India. Materials and Methods: Prevalence of malocclusion and orthodontic treatment need was assessed using the Dental Aesthetic Index (DAI) among a sample of 961, 12 and 15-year-old school children in Shimla city, who received no orthodontic treatment before or during the study. Subjects were also assessed for deleterious oral habits. Statistical Analysis: Chi-square and Mann-Whitney U tests were used. Multivariate regression analysis was used to test the correlation of habits with mean DAI score and malocclusion traits. Results: Mean DAI score was 26.81±5.25. Nearly 53% of the study sample presented with malocclusion, ranging from 'definite' to 'handicapping' based on the DAI scores. The prevalence of various deleterious oral habits was 25.9%. About 29% of children with any oral habit developed malocclusion as compared to those without any habit (P value=0.023). Tongue thrusting, mouth breathing and thumb sucking habits had a significant impact on malocclusion. Conclusion: There was high prevalence of malocclusion (52.7%). Abnormal oral habits, particularly mouth breathing and tongue thrusting had a significant impact on malocclusion, resulting in higher frequency of crowding in anterior teeth, open bite, and spacing.

The caries experience of 12- and 15- year-old children was low compared to WHO - 'recommended' values. Effective oral health promotion strategies need to be implemented to further improve the dental health of school children in Shimla city.

Objectives:To assess the dental caries, periodontal health, and malocclusion of school children aged 12 and 15 years in Shimla city and to compare them in government and private schools.Materials and Methods:A cross-sectional study of 12- and 15-year-old children in government and private schools was conducted in Shimla city, Himachal Pradesh, India. A sample of 1011 school children (both males and females) was selected by a two-stage cluster sampling method. Clinical recordings of dental caries and malocclusion were done according to World Health Organization diagnostic criteria 1997. Periodontal health was assessed by Community Periodontal Index of Treatment Needs index. The data collected was analyzed by SPSS package 13. The statistical tests used were t-test and Chi-square tests.Results:The prevalence of dental caries was 32.6% and 42.2% at 12 and 15 years, respectively. At the12 years of age, the mean decayed, missing, filled teeth was 0.62 ± 1.42 and it was 1.06 ± 2.93 at 15 years of age. Females had higher level of caries than males at both the ages. At both ages, mean of decayed teeth was statistically higher in government schools as compared with private schools. Children in government schools had significantly less number of mean filled teeth at both ages as compared with private schools. The healthy component of gingiva was present in higher percentage of children in private schools as compared with government schools at both the age groups. The prevalence of malocclusion among the 12- year-old (58.1%) was more as compared with that among the 15-year-old (53.5%).Conclusion:The caries experience of 12- and 15-year-old children was low but the prevalence of gingivitis and malocclusion was quite high. Effective oral health promotion strategies need to be implemented to improve the oral health of school children further in Shimla city.

Artificial intelligence (AI) is a domain of computer science that emphasizes the creation of intelligent and smart machines that work and reacts like humans. Artificial Intelligence is a trendy field in computer science and it has been a boon to humans in many areas. A major contribution of AI is in the field of astronomy. With a vast range of data sets in astronomy, it becomes difficult for humans to have correct calculations and predictions. How these vast data sets can be effectively processed and analyzed is a challenging task. Here, Artificial Intelligence promises to deal with this vast data in an efficient and effective manner and provide with the accurate predictions. This paper summarizes the developments of artificial intelligence (AI) techniques, and examines their application to astronomy.