Relationship between Body Mass Index and Physical Fitness among Medical Students of Gujarat, India

Introduction: Body Mass Index (BMI) is commonly used as a marker for adiposity. Physical fitness refers to a series of physical characteristics that are directly related to the ability of an individual to perform physical activity or exercise. Physical fitness tests measure the efficiency of muscular and cardiovascular systems. Aim: To assess the relationship between BMI and physical fitness in college students of a medical university at Gujarat, India. Materials and Methods: This was an observational study, conducted in the Department of Physiotherapy at Sumandeep Vidyapeeth, India. The study was conducted from September 2019 to January 2020 and included 180 participants of which 105 were females and 75 were males aged between 18 to 30 years. Height and weight were measured and physical fitness tests i.e. push-up test for upper body strength, sit-up test for abdominal strength, queens college step test for cardiorespiratory endurance were performed. Kolmogorov-Smirnov test of normality showed the data to be normally distributed. Association between variables was seen using Chi-square test and correlation was found using Pearson’s coefficient. A p-value <0.05 was considered statistically significant. Results: Out of total 180 students, 26.1% people were underweight and 32.2% were of normal weight. The mean age of the participants was 19.7±1.99 years and mean BMI was 21.9±5.14 kg/m2. There was no statistically significant association between BMI and abdominal strength (p-value=0.64), BMI and upper body strength (p-value=0.75) and BMI and cardiorespiratory endurance (p-value=0.47). Males performed better than females in all the tests although it was statistically significant (p-value=0.001) only for the sit-up test and not for push-up test (p-value=0.16) and queens college step test (p-value=0.47). Conclusion: Performances on fitness tests varied with weight status. Higher BMI was generally associated with lower physical fitness. There is a great need to organise fitness programme in colleges on large scale to overcome the health problems in young age

Object Detection in Indian Food Platters using Transfer Learning with YOLOv4

Object detection is a well-known problem in computer vision. Despite this, its usage and pervasiveness in the traditional Indian food dishes has been limited. Particularly, recognizing Indian food dishes present in a single photo is challenging due to three reasons: 1. Lack of annotated Indian food datasets 2. Non-distinct boundaries between the dishes 3. High intra-class variation. We solve these issues by providing a comprehensively labelled Indian food dataset- IndianFood10, which contains 10 food classes that appear frequently in a staple Indian meal and using transfer learning with YOLOv4 object detector model. Our model is able to achieve an overall mAP score of 91.8% and f1-score of 0.90 for our 10 class dataset. We also provide an extension of our 10 class dataset- IndianFood20, which contains 10 more traditional Indian food classes.Comment: 6 pages, 7 figures, 38th IEEE International Conference on Data Engineering, 2022, DECOR Worksho

International Nosocomial Infection Control Consortiu (INICC) report, data summary of 43 countries for 2007-2012. Device-associated module

We report the results of an International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2007-December 2012 in 503 intensive care units (ICUs) in Latin America, Asia, Africa, and Europe. During the 6-year study using the Centers for Disease Control and Prevention's (CDC) U.S. National Healthcare Safety Network (NHSN) definitions for device-associated health care–associated infection (DA-HAI), we collected prospective data from 605,310 patients hospitalized in the INICC's ICUs for an aggregate of 3,338,396 days. Although device utilization in the INICC's ICUs was similar to that reported from ICUs in the U.S. in the CDC's NHSN, rates of device-associated nosocomial infection were higher in the ICUs of the INICC hospitals: the pooled rate of central line–associated bloodstream infection in the INICC's ICUs, 4.9 per 1,000 central line days, is nearly 5-fold higher than the 0.9 per 1,000 central line days reported from comparable U.S. ICUs. The overall rate of ventilator-associated pneumonia was also higher (16.8 vs 1.1 per 1,000 ventilator days) as was the rate of catheter-associated urinary tract infection (5.5 vs 1.3 per 1,000 catheter days). Frequencies of resistance of Pseudomonas isolates to amikacin (42.8% vs 10%) and imipenem (42.4% vs 26.1%) and Klebsiella pneumoniae isolates to ceftazidime (71.2% vs 28.8%) and imipenem (19.6% vs 12.8%) were also higher in the INICC's ICUs compared with the ICUs of the CDC's NHSN