Patterns of psychiatric morbidity were studied retrospectively in children who attended the psychiatric outpatient clinic of a general hospital over a period of two years (January 1991-December 1992). Three hundred and eighty six children attended the clinic during this period. Twenty three percent of the children were diagnosed as mental retardation, whereas epilepsy was the diagnosis in 21% cases. A formal psychiatric diagnosis could be made only in less than half of the cases. The findings are discussed in terms of public awareness about child psychiatric disorders.

While higher anxiety during antenatal period cause several maternal and foetal health related complications, lower anxiety levels are found to be associated with lesser “precautionary behaviours” and consequently greater risk of infection, during the COVID-19 pandemic. In this study, we aimed to assess rates and determinants of generalized anxiety at the time of the pandemic as well as anxiety that was specific to the context of being pregnant during the COVID-19 pandemic. (COVID-19-antenatal anxiety) in Indian women. This hospital-based, cross-sectional study using face-to-face interviews was conducted at antenatal clinics of five medical college hospitals in India. The Generalized Anxiety Disorder-7 scale (GAD −7) and a customized scale to assess antenatal COVID-19 anxiety along with other tools that assessed social support and COVID-19-risk perception were administered to 620 pregnant women. We found that the percentage of women with moderate or severe anxiety based on GAD −7 was 11.1%. Multivariate analysis showed that higher COVID-19-risk perception, greater antenatal COVID-19 anxiety and lower perceived support significantly predicted moderate and severe generalized anxiety. Greater number of weeks of gestation, lower education, semiurban habitat and lower perceived social support were significant predictors of antenatal COVID-19 anxiety. We conclude that the rates of anxiety in pregnant women though not very high, still warrant attention and specific interventions.

A new and simple optimization algorithm known as Varna-based Optimization (VBO) is introduced in this paper for solving optimization problems. It is inspired by the human-society structure and human behavior. Varna (a Sanskrit word, which means Class) is decided by people's Karma (a Sanskrit word, which means Action), not by their birth. The performance of the proposed method is examined by experimenting it on six unconstrained, and five constrained benchmark functions having different characteristics. Its results are compared with other well-known optimization methods (PSO, TLBO, and Jaya) for multi-dimensional numeric problems. Our experimental results show that the VBO outperforms other optimization algorithms and have proved the better effectiveness of the proposed algorithm. IndexTerms-VBO, optimization, constrained benchmark, unconstrained benchmark.

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