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The study gives new evidence on the effects of public debt on economic growth in India with key macroeconomic indicators from 1980 to 2019. In the past decade, and after the COVID-19 pandemic, there is a substantial rise in public debt, which reached 90% of the GDP in April 2021. Therefore, it is imperative to study the impact of different public debt sources on the Indian economy to help policymakers frame informed debt management policies. The long-run equilibrium relationship and cointegrating coefficients are calculated using Johansen cointegration and fully modified ordinary least square techniques. Toda and Yamamoto's (1995) Granger causality test is used as a short-run diagnostic test for the long-run equilibrium relationship. The study's major findings suggest that domestic debt, total factor productivity (TFP) and exports are the major determinants of economic development in the long run. In contrast, economic prosperity determines the growth of external debt, debt service payments and TFP in the short run. It is recommended that the government should control and channel public debt productively for favourable growth effects.
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Background: School age is the foundation of human life. A healthy and balanced diet plays a major role in the proper growth development of the body as well as the mind. Only a balanced diet can provide all the macro and micronutrients. Covid 19 has impacted each and every human being in some or another manner. School-going children had to cope with new encounters involving online teaching-learning methodology and social distancing. As a result, these children have undergone mental and psychological trauma. This led them to follow faulty dietary habits, which would have long time impact on their health. Aim and Objectives: In the present survey, an attempt has been made to compile a report on the dietary intake of school-going children in the Roopnagar district of Punjab, India. Methodology: For the purpose sample of 100 students (7 to 12 years) was selected from four development blocks of district Roopnagar, and the cluster sampling method was adopted for data collection. A detailed pretested questionnaire on the dietary habits of children was used. Results: 59% of children were vegetarian, 32% were non-vegetarian, and 9% were eggetarian. Study findings showed that children preferred some of the items such as wheat, rice, sugar, rajma, black gram, green gram, potato, tomato, onion, apple, banana, and grapes over other food items in the same food group. Conclusion: Results showed that children do not consume a variety of food items, and some selected food items only resulting low dietary diversity and food variety. © 2022 Lifescience Global.
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The COVID-19 pandemic that emerged in Wuhan city of China in December 2019 has adversely impacted the health and the economy, society, and other significant spheres of the human environment. The pandemic has severely impacted economic activities, especially the industrial production, transportation, tourism, and hoteling industries. The present study analyses the impact of varying severity of lockdowns of economic activities during various phases of the pandemic on the water quality of the Yamuna river on parameters like pH values, biological oxygen demand, chemical oxygen demand, dissolved oxygen, total suspended solids, and electrical conductivity. The study has found a significant improvement in water quality parameters with closing economic activities during lockdowns. The average levels of concentration of these parameters of water quality were quite low during the lockdown period at 7.26 (pH value), 31.32, 136.07, 7.93, 30.33 mg/L, and 1500.24 mu S/cm compared to pre lockdown periods levels at 7.53 (pH), 39.62, 116.52, 6.1, 57.2 mg/L and 1743.01 mu S/cm for biological oxygen demand, chemical oxygen demand, dissolved oxygen, total suspended solids, and electrical conductivity, respectively. In addition, the study has found a strong significant positive correlation between COD with BOD and TSS during the lockdown period. The major findings from the present study could be instrumental in making environmentally sustainable policies for the country's economic development. There is also a huge scope of scaling up of the study at the national level to analyze the health of the rivers in the backdrop of lockdowns.
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Covid-19 has disrupted lives throughout the world. It has spread all over the world and detection of the virus is an imperative step in beating the virus. Methods such as the RTPCR and Rapid antigen tests are not only time consuming but also complex and expensive. Since the virus attacks the lungs, the Xray images of the chest can be used for the detection of coronavirus. This paper summarizes as well as gives a detailed study of the research and various techniques used for this subject. Methods used for COVID-19 detection using medical imaging using Chest X-Ray (CXR) and CT scan images as well as role and usage of GANs in tackling this problem have been summarized. © 2022 IEEE.
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The COVID-19 epidemic continues to have a devastating influence on the global population's well-being and economy. One of the most important advances in the fight against COVID-19 is thorough screening of infected individuals, with radiological imaging using chest radiography being one of the most important screening methods. Early studies revealed that patients with abnormalities in chest radiography images were infected with COVID-19. Persuaded by this, a variety of computerized reasoning and simulated intelligence frameworks based on profound learning have been suggested, with promising results in terms of precision in differentiating COVID-infected individuals. COVID-Net, a neural system configuration custom-fit for the recognition of COVID-19 instances from chest radiography photographs that is open source and accessible to the general public, is presented in this study. Many techniques have been used for the detection of COVID-19, but here we are going to focus on the chest radiography technique with the application of machine learning and image processing concepts. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Green nanotechnology produces nanomaterials and nanoproducts without impairing the environment and living organisms and also provides a way to deal with environmental problems. Green-synthesized nanomaterials from biological systems are a superior biomimetic engineered methodology for the synthesis of nanostructured materials, and are reflected as secure, cost-effective, realistic, and environmentally friendly methodology without toxic ingredients, and renewable inputs. Currently, green nanotechnology is an incredible and interdisciplinary field that has come out as a safe and rapidly emergent research area of many disciplines of research and development. Various kinds of natural biological sources such as plants, phototrophic eukaryotes, namely, algae, microbes, biopolymers, bacteria, actinomycetes, fungi, yeasts, virus, and many biocompatible agents are capable of reducing metal ions to metal nanoparticles. These are also utilized as efficient and environmentally friendly green nanofactories for the production of different metal and metal oxide nanoparticles.The use of green nanomaterial-based technology in various coating industries is a current interest of many researchers. The integration of nanostructured materials in preferred coatings enhances product qualities in terms of chemical and corrosion resistance, antireflection, wear resistance, permeability with state-of-art electrical, mechanical, and surface properties. The green nanotechnology involves coatings including the use of nanoparticles as resource materials, in situ, of nanostructure coatings comprised of nanostructured thin films.Green nanomaterials for application in various coatings, such as anticorrosion coatings, ultraviolet (UV) protective coatings, coatings for making buildings and homes cleaner and stronger, sensors, self-cleaning coatings, depolluting coatings, antifogging coatings, anti-COVID coating, antifouling coatings, antigraffiti coatings, carbon nanotube (CNT)-based coatings, paint coatings, fabric nanocoatings to thwart certain chemical weapons, textile coatings, antibacterial and antifungal coatings, hydrophobic and hydrophilic coatings, are currently commercially available and an immense interest area of research for materials scientists and technologist.This chapter mainly highlights and reviews the fabrication of green nanomaterials in brief with wide-scale state-of-the-art applications of green nanomaterials in coatings for using in various fields such as medical, buildings, energy storage, sensing, agriculture, textiles and allied industrial segments, etc. © 2022 Elsevier Inc. All rights reserved.
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Novel Coronavirus disease (COVID-19), after being identified in late December 2019 in Wuhan city of China, spread very fast and has affected all the countries in the world. The impact of lockdowns on particulate matter during the lockdown period needs attention to explore the correlation between anthropogenic and natural emissions. The current study has demonstrated the changes in fine particulate matter PM2.5, PM10 and their effect on air quality during the lockdown. The air quality before the lockdown was low in New Delhi (India) and Riyadh (Saudi Arabia), among major cities worldwide. The air quality of India is influenced by dust and sand from the desert and surrounding areas. Thus, the current study becomes important to analyse changes in the air quality of the Indian sub-continent as impacted by dust storms from long distances. The result indicated a significant reduction of PM2.5 and PM10 from 93.24 to 37.89 mu g/m(3) and from 176.55 to 98.87 mu g/m(3) during the lockdown period as compared to pre lockdown period, respectively. The study shows that average concentrations of PM10 and PM2.5 have declined by -44% and -59% during the lockdown period in Delhi. The average value of median PM10 was calculated at 33.71 mu g/m(3) for Riyadh, which was lower than that value for New Delhi during the same period. The values of PM10 were different for pre and during the lockdown periods in Riyadh, indicating the considerable influence on air quality, especially the concentration of PM10, from both the natural (sand and dust storms) and the anthropogenic sources during the lockdown periods. However, relatively smaller gains in the improvement of air quality in Riyadh were correlated to the imposition of milder lockdown and the predominance of natural factors over the anthropogenic factors there. The Air Quality Index (AQI) data for Delhi showed the air quality to be 'satisfactory' and in the green category during the lockdown period. This study attempts to better understand the impact of particulate matter on the short- and long-term air quality in Delhi during the lockdown. This study has the scope of being scaled up nationwide, and this might be helpful in formulation air pollution reduction and sustainable management policies in the future.
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Background: COVID-19 is a disasterous pandemic that the world has ever faced. It is affecting the global health system irrespective of race, ethnicity, environment, and economic status. This study is conducted with the aim of assessing the progression of the COVID-19 pandemic in India. Methods: This article uses the functional concurrent regression analysis approach to describe the pattern of daily reported confirmed cases of COVID-19 in India. The approach provides an excellent fit to the daily reported confirmed cases of the disease. The data used in this study have been taken from covid19india.org. Results: Estimated value of the parameter k b of the model is highly volatile. During the first phase of the pandemic which last up to 31st March 2020, value was very high. During 31st March to 19th July 2020 except for a few exceptions. Its value again increased rapidly from 17th February 2021 to 16th April 2021 and started decreasing after mid- March, 2021 and continued decreasing till present. Conclusion: The data-driven approach used in this study is purely empirical and does not make any assumption about the progression of the pandemic or about the data. The article suggests that based on the parameter of the model, an early warning system may be developed and institutionalised to undertake the necessary measures to control the spread of the disease, thereby controlling the pandemic. © 2021 Indian Society for Malaria and Communicable Diseases. All rights reserved.
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COVID-19 has devasted many sectors of Indian economy including livestock sector which got more turmoil during the lockdown period. With an intuition to find out the appraisal of livestock management and health services accessed by the farmers and delivered by the private veterinary practitioners, the present study was conducted in Uttar Pradesh. The production parameters, viz. milk production, sell, consumption and utility pattern of milk similarly the pattern of milk supply chain was studied and compared before and during lockdown period. The results revealed that except milk consumption remaining parameters showed negative trend as compared to before lockdown, and dairy co-operative has played a major role in maintaining the milk supply chain during lockdown. The major constraints perceived by the farmers during lockdown were accessed and it was observed that increase in price of feed and fodder followed by fear of corona were major problems. The delivery of livestock services viz. AI, treatment, livestock extension and vaccination by the private veterinary practitioners was accessed and compared before lockdown and during lockdown period. The results revealed that less number of cases attended during lockdown due to low response from farmers for availing the service from them, and fear of corona virus.
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AIM: Studies on the changes in the presentation and management of acute myocardial infarction (AMI) during the COVID-19 pandemic from low- and middle-income countries are limited. We sought to determine the changes in the number of admissions, management practices, and outcomes of AMI during the pandemic period in India. METHODS & RESULTS: In this two-timepoint cross-sectional study involving 187 hospitals across India, patients admitted with AMI between 15th March to 15th June in 2020 were compared with those admitted during the corresponding period of 2019. We included 41,832 consecutive adults with AMI. Admissions during the pandemic period (n = 16414) decreased by 35·4% as compared to the corresponding period in 2019 (n = 25418). We observed significant heterogeneity in this decline across India. The weekly average decrease in AMI admissions in 2020 correlated negatively with the number of COVID cases (r = -0·48; r2 = 0·2), but strongly correlated with the stringency of lockdown index (r = 0·95; r2 = 0·90). On a multi-level logistic regression, admissions were lower in 2020 with older age categories, tier 1 cities, and centers with high patient volume. Adjusted utilization rate of coronary angiography, and percutaneous coronary intervention decreased by 11·3%, and 5·9% respectively. CONCLUSIONS: The magnitude of reduction in AMI admissions across India was not uniform. The nature, time course, and the patient demographics were different compared to reports from other countries, suggesting a significant impact due to the lockdown. These findings have important implications in managing AMI during the pandemic.
Subject(s)
COVID-19 , Myocardial Infarction , Non-ST Elevated Myocardial Infarction , Percutaneous Coronary Intervention , ST Elevation Myocardial Infarction , Aged , COVID-19/epidemiology , Communicable Disease Control , Cross-Sectional Studies , Female , Humans , India/epidemiology , Male , Middle Aged , Myocardial Infarction/diagnosis , Myocardial Infarction/epidemiology , Myocardial Infarction/therapy , Pandemics , Stroke Volume , Ventricular Function, LeftABSTRACT
This paper analyses the trend in daily reported confirmed cases of COVID19 in India using joinpoint regression analysis. The analysis reveals that there has been little impact of the nation-wide lockdown and subsequent extension on the progress of the COVID-19 pandemic in the country and there is no empirical evidence to suggest that relaxations under the third and the fourth phase of the lockdown have resulted in a spike in the reported confirmed cases. The analysis calls for a population-wide testing approach to check the increase in the reported confirmed cases of COVID-19.
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The unprecedented and rapidly spreading Coronavirus Disease-19 (COVID-19) pandemic has challenged public health care systems globally. Based on worldwide experience, India has initiated a nationwide lockdown to prevent the exponential surge of cases. During COVID-19, management of cardiovascular emergencies like acute Myocardial Infarction (MI) may be compromised. Cardiological Society of India (CSI) has ventured in this moment of crisis to evolve a consensus document for care of acute MI. However, this care should be individualized, based on local expertise and governmental advisories.