Fabrication of a Resonant Photoacoustic Cell for Samples Study

Nondestructive treatment of a sample in photoacoustic spectroscopy is helpful in the study of thermal and optical properties of ice and snow. In the present study, a  low-temperature resonant photoacoustic cell, based on Helmholtz resonator model, has been designed and fabricated for the study of samples like ice or snow. Its performance has also been studied using carbon black as a standard sample and various other samples like water, ice, glass, plexi-glass, polycarbonate, etc. Thermal diffusivity of ice, water, and many other transparent materials has been determined by varying chopping frequency and recording corresponding phase changes in the photoacoustic signal. The results obtained are in good agreement with those predicted by Rosencwaig-Gersho (R-G)' theory

Visual proof of the two-variable am-gm inequality

The algebraic proof of (1) consists of recognizing that a b ab 2 2 + − 2 is a perfect square, namely, (a – b)2 which is always non-negative as a and b are real numbers. This is probably the simplest and the most direct proof

Triangle equalizers - a probabilistic approach, part 1

An equalizer of a triangle is a line which divides it into two regions having equal areas as well as equal perimeters. Every triangle has at least one and at most three equalizers. In, triangles of all three types are identified and it is remarked that triangles with two equalizers are quite rare

The power triangle

In is described for finding a formula for the sum of the powers of the first the companion article by Prof V G Tikekar, a method n positive integers, for any positive k-th integer k, using a triangular array of numbers—the Power Triangle. This article shows why the method works. The proof makes use of a family of combinatorial numbers called the Stirling set numbers (also called Stirling numbers of the second kind; they are dwelt upon in the other companion article by Dr Shailesh Shirali). By exploiting a relation between these numbers and the power functions, we are led to the formulas we seek

SD-Measure: A Social Distancing Detector

The practice of social distancing is imperative to curbing the spread of contagious diseases and has been globally adopted as a non-pharmaceutical prevention measure during the COVID-19 pandemic. This work proposes a novel framework named SD-Measure for detecting social distancing from video footages. The proposed framework leverages the Mask R-CNN deep neural network to detect people in a video frame. To consistently identify whether social distancing is practiced during the interaction between people, a centroid tracking algorithm is utilised to track the subjects over the course of the footage. With the aid of authentic algorithms for approximating the distance of people from the camera and between themselves, we determine whether the social distancing guidelines are being adhered to. The framework attained a high accuracy value in conjunction with a low false alarm rate when tested on Custom Video Footage Dataset (CVFD) and Custom Personal Images Dataset (CPID), where it manifested its effectiveness in determining whether social distancing guidelines were practiced.Comment: Contains 6 pages & 7 figures. Published in 12th CICN 202

Deep Learning Framework to Detect Face Masks from Video Footage

The use of facial masks in public spaces has become a social obligation since the wake of the COVID-19 global pandemic and the identification of facial masks can be imperative to ensure public safety. Detection of facial masks in video footages is a challenging task primarily due to the fact that the masks themselves behave as occlusions to face detection algorithms due to the absence of facial landmarks in the masked regions. In this work, we propose an approach for detecting facial masks in videos using deep learning. The proposed framework capitalizes on the MTCNN face detection model to identify the faces and their corresponding facial landmarks present in the video frame. These facial images and cues are then processed by a neoteric classifier that utilises the MobileNetV2 architecture as an object detector for identifying masked regions. The proposed framework was tested on a dataset which is a collection of videos capturing the movement of people in public spaces while complying with COVID-19 safety protocols. The proposed methodology demonstrated its effectiveness in detecting facial masks by achieving high precision, recall, and accuracy.Comment: Contains 6 pages and 6 figures. Published in 12th CICN 202

Iodine status during pregnancy in India and related neonatal and infant outcomes

Objective: To document iodine status in Indian pregnancies, associations with maternal diet and demographics, and offspring developmental measures. Design: Longitudinal study following mothers through pregnancy and offspring up to 24 months. Setting: Rural health-care centre (Vadu) and urban antenatal clinic (Pune) in the Maharashtra region of India. Subjects: Pregnant mothers at 17 (n 132) and 34 weeks’ (n 151) gestation and their infants from birth to the age of 24 months. Results: Median urinary iodine concentration (UIC) was 203 and 211 μg/l at 17 and 34 weeks of pregnancy, respectively (range 26–800 μg/l). Using the UIC distribution adjusted for within-person variation, extreme UIC quartiles were compared for predictors and outcomes. There was no correlation between UIC at 17 and 34 weeks, but 24 % of those with UIC in the lowest quartile at 17 weeks had UIC in the same lowest quartile at 34 weeks. Maternal educational, socio-economic status and milk products consumption (frequency) were different between the lowest and highest quartile of UIC at 34 weeks. Selected offspring developmental outcomes differed between the lowest and highest UIC quartiles (abdominal circumference at 24 months, subscapular and triceps skinfolds at 12 and 24 months). However, UIC was only a weak predictor of subscapular skinfold at 12 months and of triceps skinfold at 24 months. Conclusions: Median UIC in this pregnant population suggested adequate dietary provision at both gestational stages studied. Occasional high results found in spot samples may indicate intermittent consumption of iodine-rich foods. Maternal UIC had limited influence on offspring developmental outcomes

Estimation of Epiphytic Macrolichen Biomass in Binsar Wildlife Sanctuary (BWS), Almora, Uttarakhand, India

The lichen litter fallen on the forest floor from canopy and main branches between elevations of 900-2500 m was estimated for the Binsar Wildlife Sanctuary (BWS) of Almora district in Uttarakhand, India. The forest of the sanctuary was divided in 5 major forest stands, viz., Quercus, Alnus, Pinus, Rhododendron and Mixed. At each stand ten, 1-m2 quadrats were randomly placed and the lichen litter was collected in April 2013. Lichen biomass was highest in Quercus stand (2.55 g m-2) followed by Alnus (2.33 g m-2), Mixed stand (2.00 g m-2), Rhododendron (0.82 g m-2), and Pinus with the lowest lichen litter biomass (0.21 g m-2). The highest biomass was recorded for Matrix lichens (0.8944 g m-2), followed by Forage lichens (0.6976 g m-2) and Cyanolichens (0.0064 g m-2)