Factors Influencing Infant Morbidity in the Urban Field Practice Area of a Medical College in Bangalore

Background: Infants constitute 2.92% of the total population in India. Health of infants is considered as a sensitive indicator of health status and level of socio-economic development of a country. In India, the infant morbidity and mortality are in decline, but the pace of decline is not sufficient to attain the target goals of National Health Mission. Objective: To assess the factors influencing infant morbidity in the urban field practice area of a medical college in Bangalore. Methods and Material: This was a population based cross sectional study done at an urban poor locality in Bangalore. The study was conducted between April 2018 to September 2019 with a sample size of 300 after obtaining the approval from Institutional ethics committee. Population proportion to size was used to ensure equal representation. Data was collected using pre tested semi structured questionnaire & analysed using open epi like descriptive statistics with univariate & multi variate logistic regression were used. Results: Total of 165(55%) subjects were females, with majority 206(68.7%) Muslim by religion and 161(53.7%) lived in the nuclear family. The prevalence of morbidities among infants was 209(69.7%). The most common infant morbidities reported were 121(40.3%) ARI, 85(28.3%) fever and 45(15%) diarrhea. Infants with perinatal complications, faulty feeding practices like delayed initiation of breast feeding, bottle feeding and immunization had significant association with infant morbidities. Conclusions: To conclude there is a statistically significant association between perinatal complications, bottle feeding & partial immunization with infant morbidity. Keywords: Infant, Immunization, Breast feeding, Morbidit

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 2,700 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai