Mask Use pattern, Public Perception and Barriers to Effective Mask Usage-A battle far from over

Background & Objective: Proper mask wearing reduces the transmissibility and risk of Covid-19 infection still compliance to mask use is low. This study was conducted to observe the mask usage pattern, perception and barriers to effective mask usage (EMU). Settings and Design: This cross-sectional study was conducted in collaboration with district police administration to observe mask usage pattern in various crowded places. Methods and Material: Participants from general public (n=6995) in 10 preselected areas of city were observed and then interviewed about their perceptions about EMU. Indirect observation of EMU was also done by screening CCTV footage, followed by another set of observation at same places after conducting a health education campaign. Data was entered in Microsoft excel and analyzed using SPSS. P value <0.05 was considered significant. Results: EMU was seen in nearly 62% participants. Younger age, native population, education above matric, persons driving two & four wheelers, had significantly higher compliance. During CCTV observation, EMU was 57.5%, and was highest near public places, roads and intersections while lowest near bus stand and religious places. Some improvement in compliance was seen after health education at these places. Breathing difficulty, no use of wearing mask and feeling uncomfortable were the most common reasons given by participants for non-compliance.Conclusions: EMU was lower in elderly, migrants, less educated, unemployed, daily wage workers, so these groups should be especially sensitized about preventive measures. There is need for extensive public education to bring out behavioral change regarding proper mask wearing to control this pandemic and prevent further waves

BDD Ordering and Minimization Using Various Crossover Operators in Genetic Algorithm

Abstract: Binary Decision Diagram (BDD) is a data structure which is extensively used for compact representation of Boolean functions. On a more abstract level, BDDs can be considered as a compressed representation of sets or relations. BDDs are extensively used in CAD software to synthesize circuits (logic synthesis) and in formal verification. Ordering of BDDs play a major role in reduction of nodes and hence the area. In this paper, genetic algorithm with three crossover operators namely order, cycle and partially mapped has been proposed for minimization of shared ordered BDDs.The results have been compared using these three operators for Multi-input Adder Benchmark Circuits

Analysis and Comparison of Brain Tumor Detection and Extraction Techniques from MRI Images

ABSTRACT: Magnetic Resonance Imaging (MRI) is the procedure used in hospitals to scan patients and determine the severity of certain injuries. It produces high quality images of the human body part. Tumors in various body parts are also scanned using MRI. Brain tumor is an abnormal cell formation within the brain leading to brain cancer. Thus it is very important to detect and extract brain tumor. The main thing behind the brain tumor detection and extraction from an MRI image is the image segmentation. Segmenting an image means dividing an image into regions based on some specific criteria. Various algorithms have been proposed for this purpose. This is a knowledge based review paper presenting a brief study of such algorithms highlighting their methodology and advantages and disadvantages if any. KEYWORDS: Image processing, MRI, segmentation, watershed segmentation, CNN, k-Means clustering, I. RELATED WORK Rajesh C. Patil and Dr. A. S. Bhalchandra have analysed that processing of MRI images is the most challenging and emerging field. Magnetic Resonance Imaging (MRI) is an advanced medical imaging technique used to produce high quality images of the parts contained in the human body. The paper brings out the methodology, which includes preprocessing of the given MRI image, its segmentation and lastly morphological operations on it, for the detection and extraction of brain tumour of real time patient's MRI scan images. Azian Azamimi Abdullah, Bu Sze Chize and Yoshifumi Nishio developed an automated detection method for brain tumor using Cellular Neural Network (CNN). For this purpose they combined many templates to obtain the accurate results. Simulation results using the new algorithm prove that brain tumor can be detected in shorter time. Ishita Maiti and Dr. Monisha Chakraborty have used the technique of Watershed algorithm in combination with Edge Detection operation for the Brain Tumor segmentation of an MRI image. The paper includes Marker based Watershed algorithm. And the Edge detection is carried out by the Canny Edge Detector. The two methods are performed on the HSV Color model of an image. The results have been shown to be very accurate through the paper. J.Vijay and J.Subhashini have concluded that k-Means Clustering is a recognized as a powerful tool for the detection and extraction of Brain tumor from MRI images. The paper uses pixel-based k-Means clustering technique to achieve the aim. The paper has deduced that unsupervised segmentation methods are better than the supervised methods. This technique is proved to be lesser time consuming and achieves maximum lossless compression. The paper proves this technique to be very efficient. Anam Mustaqeem, Ali Javed, Tehseen Fatima have concluded that Watershed based segmentation and thresholding based segmentation is a powerful tool for the detection of Brain tumour in MRI images. The paper further contains th

Genetic Variation and Structure of the People of Uttarakhand, Central Himalayas, India

The Indian Himalayas, being semi-isolated geographically, provide ideal conditions for population genetics investigations. The main aim of this study is to genetically characterize and analyze the genetic structure of the people of Uttarakhand, a newly created North Indian hill state in the Central Himalayas, using original phenotype and allele-frequency data on a battery of seven red cell enzyme polymorphisms. For this analysis, blood samples were collected from 3,222 unrelated subjects belonging to various endogamous caste populations (Brahmin, Rajput, and Shilpkar) and tribal Bhotia inhabiting seven different districts in the Garhwal (northern) and Kumaon (southern) regions of Uttarakhand. Hemolysates were typed for isozymes of ESD, PGM1, ADA, AK1, GLO1, ACP1, and GPI using standard electrophoretic techniques. The genetic structure of these regional caste and tribal population groups was investigated with the help of different statistical measures. The present biochemical marker results show that the overall genetic constitution of the different populations of Uttarakhand is rather heterogeneous but similar to that of various caste and tribal populations of the neighboring hill state of Himachal Pradesh, situated on Uttarakhand’s western border. The extent of genic differentiation observed in different contemporary populations of Garhwal was twice as high as that of Kumaon. Interestingly, in genetic distance dendrograms of both the regions and of all of Uttarakhand, all the Shilpkar groups are differentiated from the remaining groups of Brahmin, Rajput, and Bhotia. The genetic constitution of the Shilpkar (a scheduled caste population of Uttarakhand) and to a lesser extent that of the Bhotia (a scheduled tribe population of Uttarakhand) are rather different from both the Brahmin and Rajput high-caste populations, which tend to show genetic similarities between them. These observations are corroborated by the known ethnohistory of different populations of Uttarakhand

Ultrasound-guided subarachnoid block in kyphoscoliotic parturient posted for urgent caesarean section

Parturient with kyphoscoliosis poses a major challenge in the administration of spinal anaesthesia owing to changes in the anatomy of the spine and physiological changes associated with pregnancy. Recently, ultrasound guidance has proved to be a boon for regional anaesthesia techniques. We report the successful anaesthetic management of a 43 year-old primigravida with kyphoscoliosis who was posted for emergency caesarean section using an ultrasound-guided subarachnoid block

A NOVEL STRAIN OF Aspergillus niger PRODUCING A COCKTAIL OF HYDROLYTIC DEPOLYMERISING ENZYMES FOR THE PRODUCTION OF SECOND GENERATION BIOFUELS

The screening and isolation of fungi producing a cocktail of hydrolytic enzymes was studied. Among the various isolates obtained from different soil samples, a strain NS-2 was selected. The phylogenetic analysis of this strain showed highest homology (99%) with Aspergillus niger. It was capable of producing cellulolytic, hemicellulolytic, amylolytic, and pectinolytic enzymes in appreciable titers on wheat bran based liquid and solid state media. The mixture of enzymes produced by this organism could effectively hydrolyze various domestic waste residues, revealing conversion efficiencies of 89 to 92% and produced high reducing sugar yields of 0.48 to 0.66 g/g of dry residue. This enzyme cocktail could potentially find a significant application in the conversion of agricultural and other waste residues having cellulose, hemicellulose, starch, and pectin as carbohydrates to produce simpler sugars which can be fermented for the production of second generation biofuels