Studies on some Heterocyclic Compounds

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Lockdown-2020 and Livelihood of Migrant Women Workers in Jharkhand

The entire globe faces a very precarious situation during pandemic Covid-19. During national lockdown in India, it was hazardous for the migrant labourers and more unsafe for women migrant workers. They came across many livelihood challenges like: employment, nutrition, government support, societal security, health facility, etc. which were repeatedly underlined in numerous mass medianews. Therefore, to know the actual problems encountered by the women migrant returnees, this particular study was undertaken in Jharkhand state where most of women workers go on migration for earning. For the purpose, 41 women migrant returnees were randomly selected as respondents from 18 villages covering five blocks of the state. By the use of a survey schedule, data was collected in the arena of socio-economic outline, place of migration, reason of migration, sector of engagement, income, difficulties confronted and support need from government for livelihood enhancement which are pronounced in this study. View Article DOI: 10.47856/ijaast.2021.v08i7.00

A study on correlation between depression, fear of fall and quality of life in elderly individuals

Background: Fear of falling in elderly is a major cause of loss of independence, which has an effect on the physical function in elderly individuals. Depression is another important public health problem for older adults, because late life depression might have devastating consequences, such as an increase in mortality. QOL of older adults has become an important issue, because of demographic changes resulting from the ageing of the population. The goal of the study was to assess the depression and fear of fall which will provide further insights into the relationship between QOL, depression and fear of fall among elderly individuals in India.Methods: The sample consisted of 62 elderly people of age between 65 years to 75 years (mean=71.96, SD±5.92) were taken in the study. Depression was assessed using the 30-item geriatric depression scale (GDS), fear of falling was measured using falls efficacy scale (FES), QOL was assessed using the 26-item, World Health Organization Quality of Life, brief version (WHOQOL-BREF).Results: The data was analysed using Pearson co-efficient of correlation to examine the relationship between GDS, FES, and WHOQOL-BREF. The correlation co-efficient between GDS and FES was 0.5257 (p<0.05) and correlation coefficient between GDS and WHOQOL was 0.4372 (p<0.05).Conclusions: This study concluded that there was a significant association between the depression, fall efficacy, and QOL in the elderly people. This relationship has an important implication for the development of the rehabilitation programs that aim to improve the balance confidence and motivation will diminish its impact on QOL in elderly people

Nanoparticles in the soil environment and their behaviour : An overview

The increasing use of nanoparticles (NPs) in industries, soil and water remediation technologies, potential agricultural uses (e.g. fertilizers) and unintentional releases via air, water and sewage sludge application to the land likely leads to the release of such materials into the environment. The unique properties of NPs, such as high specific surface area, abundant reactive sites on the surface as a consequence of a large fraction of atoms located on the exterior rather than in the interior of NPs, as well as their mobility, could cause environmental hazards orpotentially harm soil health.It could be assumed that NPs may not have a direct influence on plant growth but may be responsible for the influence through indirect mechanisms. Light microscopy of root sections showed that the ZnO particles adsorbed into root tissues and cells and damaged the root tissues. Results from ecotoxicological studies show that certain NPs have effects on organisms under environmental conditions, though mostly at elevated concentrations. Nanominerals and mineral NPs in the environment have been present throughout the evolutionary development of hominids, and our exposure to these through inhalation, ingestion are important foci of nanotoxicology and environmental sciences. The more research on occurrence, characteristics of NPs and their behaviour in environment is needed towards a logical conclusion of the effects of NPs on environment

Mapping of the multifoliate pinna (mfp) leaf-blade morphology mutation in grain pea Pisum sativum

The multifoliate pinna (mfp) mutation alters the leaf-blade architecture of pea, such that simple tendril pinnae of distal domain are replaced by compound pinna blades of tendrilled leaflets in mfp homozygotes. The MFP locus was mapped with reference to DNA markers using F2 and F2:5 RIL as mapping populations. Among 205 RAPD, 27 ISSR and 35 SSR markers that demonstrated polymorphism between the parents of mapping populations, three RAPD markers were found linked to the MFP locus by bulk segregant analyses on mfp/mfp and MFP/MFP bulks assembled from the F2:5 population. The segregational analysis of mfp and 267 DNA markers on 96 F2 plants allowed placement of 26 DNA markers with reference to MFP on a linkage group. The existence of common markers on reference genetic maps and MFP linkage group developed here showed that MFP is located on linkage group IV of the consensus genetic map of pea

Solution of Travelling Salesman Problem based on Metaheuristic Techniques

The traveling salesman problem is a classic problem in combinatorial optimization. This problem is to find the shortest path that a salesman should take to traverse through a list of cities and return to the origin city. The list of cities and the distance between each pair are provided. It is an NP-complete problem i.e., class of computational problem for which no efficient solution algorithm has been found, presently there is no polynomial solution available. In this paper, we try to solve this very hard problem using various heuristics such as Simulated Annealing, Genetic Algorithm to find a near-optimal solu-tion as fast as possible. We try to escape the local optimum, using these advanced heu-ristic techniques

Prevalence of ocular morbidity in rural population of eastern Uttar Pradesh, India

Background: Ocular morbidity is a significant problem in rural areas of India as it remains undiagnosed and neglected.&nbsp;Aims &amp; Objectives:&nbsp; To determine the prevalence of ocular morbidity in the rural population of Barabanki, Uttar Pradesh.&nbsp;Material &amp; Methods: A community based cross-sectional study was conducted in the villages around RHTC Satrikh of HIMS Barabanki. Ocular examination and vision testing was done among 812 people using ophthalmoscopic instruments. Information was collected using pre-tested questionnaire. Analysis was done using SPSS and appropriate Statistical tests.&nbsp;Results: Of the total 812 individuals interviewed, the prevalence of ocular morbidity was 41.3% (335 subjects had one or more ocular morbidity); with 88.8% elderly affected (age &gt;65 years).&nbsp;&nbsp; Myopia was the most common ocular morbidity 14.8%, followed by cataract (14.3%) and hypermetropia (12.8%).&nbsp; Allergic and infective conjunctivitis affected 5.8% and 3.9%, respectively.&nbsp; The prevalence of Vitamin A deficiency disorder (including night blindness and bitot spots) was 1.3%.&nbsp; Higher ocular morbidity was present in houses with higher SES. Environmental conditions had no significant relation to ocular morbidity.&nbsp;&nbsp;Conclusion: The prevalence of ocular diseases among the elderly was highest and requires prompt attention.&nbsp; Myopia was the most common ocular morbidity having a prevalence of 14.8%, followed by cataract (14.3%) and hypermetropia (12.8%)

Deep 3D Convolutional Neural Network for Automated Lung Cancer Diagnosis

Computer Aided Diagnosis has emerged as an indispensible technique for validating the opinion of radiologists in CT interpretation. This paper presents a deep 3D Convolutional Neural Network (CNN) architecture for automated CT scan-based lung cancer detection system. It utilizes three dimensional spatial information to learn highly discriminative 3 dimensional features instead of 2D features like texture or geometric shape whick need to be generated manually. The proposed deep learning method automatically extracts the 3D features on the basis of spatio-temporal statistics.The developed model is end-to-end and is able to predict malignancy of each voxel for given input scan. Simulation results demonstrate the effectiveness of proposed 3D CNN network for classification of lung nodule in-spite of limited computational capabilities.Comment: Initial draft of PAPER Presented at IRSCNS 2018 , Goa , India final version available at Mishra S., Chaudhary N.K., Asthana P., Kumar A. (2019) Deep 3D Convolutional Neural Network for Automated Lung Cancer Diagnosis. In: Peng SL., Dey N., Bundele M. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 75. Springer, Singapor