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The effectiveness and cost implications are always top factors for policy makers while deciding upon the appropriate air pollution abatement measures. The present study aimed to understand the actual particulate matter (PM2.5 and PM10) patterns during different phases of COVID-19 lockdown periods and depict their spatial distributions covering the 36 major areas in Delhi, India. Drastic visible reduction in both the pollutants was found during lockdown phase 1 and 2. Average PM2.5 reductions of 41.97%, 39.24%, 56.04%, and 56.77% were recorded comparing lockdown and/or study period with the years 2018, 2019, 2021, and 2022, respectively. Similar average reduction of PM10 to the magnitude of 51.72%, 48.95%, 48.24%, and 49.00% was found for the referred years. However, the reduction during the before-lockdown period of 2018 and 2019 and the year 2020 did not follow such radical reduction returning the values for PM2.5 as 7.66-14.88% and that for PM10 as 12.86-20.67%. The geospatial maps generated for Delhi city followed the similar findings at macro level depicting huge reduction in PM distribution classes for the study period. For instance, the percent surface area under "moderately high"polluted due to PM2.5 came down to 0.61 during lockdown phase 2 from 13.96 during January 2020. Further, about 15 of the 36 locations reported compliance to the National Ambient Air Quality Standards (NAAQS) for either of the pollutants during the study period. Nevertheless, such reductions are short-lived because the levels went up again in the years 2021 and 2022 (except similar lockdowns) as the situation got back to normal daily life activities postlockdown. Although, lockdown may be imposed in case of severe ambient air quality in a densely populated megacity like Delhi, it remains a temporary or quick-fix solution, to be looked as a last line of defense. © 2023 Mary Ann Liebert, Inc., publishers.
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Background: Cryptococcus lives in the environment all over the globe. Although it spreads via inhalation route still most of the exposed individuals never get sick as the majority of cases are seen in immunocompromised. Objective of this clinical case report is to highlight the rare fungal etiology associated with iliac bone abscess to avoid incorrect diagnosis and prompt management of case. Case Presentation: A 70-year-old elderly female presented with hip pain for a month duration, not relieved with analgesics in September, 2021. In MRI a well-defined irregularly marginated hyperintense focal lesion was found in left iliac bone with joint effusion suggestive of infective etiology, tubercular, or less likely metastasis. CT-guided biopsy reported occasional hyphae-like fragments giving an impression of acute on chronic osteomyelitis with suspicion of fungalinfection.Culture reported Cryptococcus ne oformans.Fungal markers and Beta-dglucan were indeterminate and Galactomannan was found negative for the sample. Extrapulmonary TB was ruled out by AFB staining, MGIT Culture, and GeneXpert MTB. Bone scan, tumor markers, and PET scan ruled out osteolytic lesion secondary to metastasis. Though PET Scan and HRCT thorax confirm pulmonary involvement giving a picture of bilateral interstitial lung disease along with multiple enlarged lymph nodes. Patient serum was found negative for HIV, HBV, and HCV. Liver and renal function tests were within normal range and in hematology, ESR was raised (50;normal range:0-20). Patient is hypertensive with HbA1c of 5.3. There was no history of travel, avian exposure, weight loss, and COVID-19 infection. Patient was started on voriconazole and considering generalized lymphadenopathy, a therapeutic trial of anti-tubercular therapy was started which was stopped within a week on patient non-compliance. Abscess resolved with voriconazole and patient was discharged. In February 2022, Patient presented with similar complaints. CT scan of this fluctuant nodule depicted hypoechoic lesion which was ultrasound-guided drained.Sections show many rounds of oval fungal organism which were found PASpositive with mucicarmine and alcian blue positive capsule.Budding yeast cells were seen on KOH mount and India ink preparation demon-strated capsule which was confirmed by Cryptococcal Antigen test giving an overall impression in favor of Cryptococcosis. Patient was started on oral fluconazole and Injection liposomal amphotericin B 250 mg for 14 days. Discussion and Conclusion(s): This is the first case of skeletal Cryptococcosis at our institution which was managed by antifungals without surgical debridement resulting in resolution of abscess. Isolated focal iliac bone cryptococcosis is unusual but may occur in immunocompetent with everyday exposure to the organism. Herein, Patient had bilateral lung involvement along with multiple lymphadenopathies with no evidence of TB bacilli which inferences that the isolate most likely originated from environmental bird droppings and has disseminated from pulmonary lesion to the iliac bone. The radiological findings of iliac cryptococcosis abscess were nonspecific.A definitive diagnosis was made on histopathological and fungal examinations of ultrasound-guided drained abscess. Patient will be followed in the near future for relapse or any other medical issues related to the case.
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Background Patients with coronavirus disease 2019 (COVID-19) presenting for neurosurgery are not rare. Considering the lack of literature informing the outcomes in this subset, present study was conducted to compare perioperative management and postoperative outcomes between COVID-19 and non-COVID-19 neurosurgical patients. Methods After ethics committee approval, data of all patients with COVID-19 along with an equal number of age and diagnosis matched non-COVID-19 patients undergoing neurosurgery between April 2020 and January 2021 was analyzed retrospectively. Predictors of poor outcome were identified using multivariate logistic regression analysis. Results During the study period, 50 COVID-19 patients (28 laboratory confirmed (group-C) and 22 clinicoradiological diagnosed [group-CR]) underwent neurosurgery and were compared with 50 matched non-COVID-19 patients. Preoperatively, clinicoradiological diagnosed COVID-19 patients had higher American Society of Anesthesiologists (ASA) grade ( p = 0.01), lower Glasgow Coma Scale (GCS) score ( p < 0.001), and more pulmonary involvement ( p = 0.004). The duration of intensive care unit stay was significantly longer in laboratory confirmed patients ( p = 0.03). Poor clinical outcome (in-hospital mortality or discharge motor-GCS <= 5) did not differ significantly between the groups ( p = 0.28). On univariate analysis, younger age, higher ASA grade, lower preoperative GCS, and motor-GCS, higher intraoperative blood and fluid administration and traumatic brain injury diagnosis were associated with poor outcome. On multivariable logistic regression. only lower preoperative motor-GCS remained the predictor of poor outcome. Conclusions The concomitant presence of COVID-19 infection did not translate into poor outcome in patients undergoing neurosurgery. Preoperative motor-GCS predicted neurological outcome in both COVID-19 and non-COVID-19 neurosurgical patients.
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The World Health Organization estimated that there are 1.5 billion people globally living with some degree of hearing loss. It is estimated that the number of affected people is going to rise to 2.5 billion by 2050. One of the primary reasons behind hearing impairment is exposure to high noise levels. The Worldwide Hearing Index reveals that India has the highest hearing loss (−12.85 years). During the lockdown due to COVID-19, environmental pollution reached baseline levels. The present study investigates the effect of lockdown on noise levels and assesses the current level of noise pollution in Delhi and Mumbai, two metropolitan cities of India. The data for Leq (A), L10 (A), and L90 (A) was recorded through 20 noise monitoring stations (10 in each city) across India. The recorded noise levels during lockdown (25th March 2020–31st May 2020) were compared with pre-lockdown noise levels for both BL2020 (1st February to 24th March 2020) and AL2019 (25th March to 31st May 2019). The highest drop in noise levels in both cities compared to AL2019 levels was recorded in the commercial zones (5%), while the lowest was recorded in silence zones (1%). The highest drop in noise levels compared to BL2020 was recorded in Anand Vihar, Delhi (16%) and Vashi Hosp. Navi Mumbai (20%). The present study may help policymakers, and governing bodies devise a national action plan for redressal noise pollution in India’s urban cities. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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We are very pleased to present the conference proceedings of ICIAST-2021. The conference has been organized in virtual mode due to worldwide COVID Protocol and safety measures by Department of Applied Sciences, Galgotias College of Engineering and Technology, Greater Noida, Uttar Pradesh, India during December, 21-23, 2021, in Greater Noida, Uttar Pradesh, India.In this conference approx. 300 young researchers, engineers, scientists, academicians and industrial delegates participated from more than 20 countries of the globe on common virtual platform of zoom to share and exchange their research findings including theoretical results, novel scientific models and work in progress in the different areas of Science & Technology. During virtual conversations participants from remote areas faced sometime network issues but overall communication was good throughout the even. More than 30 international resource persons from different fields share their expertise with the young academicians and researcher with case studies and concrete examples within allowed time span. The scientific & technical program of the three days international conference have review talks, invited lectures, contributed oral presentations.This proceeding includes papers from Physics, Mathematics and their applications. A sound understanding of the same shall help emergence of new ideas that can be helpful in building trained professionals who can serve in the knowledge-based industries. We are pleased to appreciate our dynamic reviewers who took time and effort for providing their valuable comments in time and help towards the improvement of quality of papers through rigours review process.List of Organizing Committee, image, ICIAST-2021 Proceeding Editorial Team are available in this pdf.
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The pandemic of Corona Virus Disease (COVID-19) is triggering a public health emergency. Wearing a face mask is one of the most important ways to combat the infection. Face mask identification is discussed in the article, and it can be used by authorities to enable COVID-19 avoidance, assessment, prevention, and action plans. In this project, we developed a deep learning model to detect the presence of a mask on a person. We have trained it using Keras and OpenCV. The image classification method: MobilenetV2 is used to speed up the training time and we use approx. 2000 images to train the model. © 2021 IEEE.
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The importance of social media has seen a huge growth in last few years as it lets folks from any part of the world remain in contact. Due to COVID-19 epidemic, social media is used extensively and has turned to be more pertinent than the past years. Alongside, fake news dissemination has revived and also dissemination of tweets has taken the attention. For the present study, we used various machine learning models to detect the fake news on COVID-19 related tweets. Due to millions of active social media users, identifying the fake news has become a crucial task. The models we applied are Gradient Boosting Classifier (GBC), Logistic Regression (LR), Random Forest Classifier (RFC), Decision Tree Classification (DT). All these models detect if the tweet relating to COVID-19 is “Fake News” or “Not a Fake News”. Hence we conclude that Logistic Regression is best among all other models. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The Covid-19 pandemic has disrupted the world economy and significantly influenced the tourism industry. Millions of people have shared their emotions, views, facts, and circumstances on numerous social media platforms, which has resulted in a massive flow of information. The high-density social media data has drawn many researchers to extract valuable information and understand the user's emotions during the pandemic time. The research looks at the data collected from the micro-blogging site Twitter for the tourism sector, emphasizing sub-domains hospitality and healthcare. The sentiment of approximately 20,000 tweets have been calculated using Valence Aware Dictionary for Sentiment Reasoning (VADER) model. Furthermore, topic modeling was used to reveal certain hidden themes and determine the narrative and direction of the topics related to tourism healthcare, and hospitality. Topic modeling also helped us to identify inter-cluster similar terms and analyzing the flow of information from a group of a similar opinion. Finally, a cutting-edge deep learning classification model was used with different epoch sizes of the dataset to anticipate and classify the people's feelings. The deep learning model has been tested with multiple parameters such as training set accuracy, test set accuracy, validation loss, validation accuracy, etc., and resulted in more than a 90% in training set accuracy tourism hospitality and healthcare reported 80.9 and 78.7% respectively on test set accuracy.
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The present article dealt with the impact of COVID-19 outbreak on the world economy. The study has covered the outbreak of corona virus along with its impact on agriculture, energy sector, space science and overall economy. Coronavirus posing serious, challenging and troublesome effects on the economy is believed to create sudden economic recession which will burst the estimated budget of the world in the very first quarter. The global economic recession is expected to make a loss of trillion dollars of global income. Due to this pandemic spread over all the world wide webinars and conferences across technology along with sports and fashions are being postponed or being cancelled and it also led to shutdown of shops and companies except pharmaceuticals and groceries etc. which shows that there will be negative impact on the economies of the countries. It has made numerous impacts in agricultural sector affecting income and profit of farmers as well as distributors and consumers. Hence, there is a urgent need of government action and advanced research labs so that the world with all its major affected countries could turn the situation over and make the economic growth could reach little far towards the target.
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The novel coronavirus, also known as COVID-19, is the newest strain of coronavirus that causes respiratory infections in humans. This virus is affecting the entire world and has impacted many important sectors, such as travel, economy, education, and hospitality. Many researchers are trying to find effective methods in an attempt to limit the spread of the virus and find a cure for infected people. The study assesses the impact of the virus in 212 countries using advanced data visualization techniques. The research analyzes multiple factors impacting the spread of the virus;Population, Population Density, Median Age, Human Development Index (LIDO, Number of COVID-19 Cases, and Number of COVID-19 Deaths. The research incorporates R-Values and Linear Regression to highlight trends and patterns observed.
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Most of the countries in the world are facing the problem of disease caused by Novel coronavirus (covid-19) with symptoms of higher grade flu like symptoms or with no symptom. The infection spreads through contact with the person suffering/suffered from coronavirus symptoms like sneezing, high fever, cough and ultimately blockade of respiratory system. Sometimes symptoms of diarrhea and dysentery were also detected at advanced stage of the disease. Till now any effective medicine or vaccine could not be developed for its prevention and getting relief. Only trial and error by applying some antimalarial drugs chloroquine hydroxide along with some other antiviral infections is used and up to 38% are being recovered in India as well as other countries. Under such circumstances strengthening immune system becomes only option for preventing from this viral disease and our traditional medicines are playing vital role for immunity strengthening. Accordingly, some herbs either singly or in combination form have been suggested as preventive measure for coronavirus through this communication.
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The present article dealt with the impact of COVID-19 outbreak on the world economy. The study has covered the outbreak of corona virus along with its impact on agriculture, energy sector, space science and overall economy. Coronavirus posing serious, challenging and troublesome effects on the economy is believed to create sudden economic recession which will burst the estimated budget of the world in the very first quarter. The global economic recession is expected to make a loss of trillion dollars of global income. Due to this pandemic spread over all the world wide webinars and conferences across technology along with sports and fashions are being postponed or being cancelled and it also led to shutdown of shops and companies except pharmaceuticals and groceries etc. which shows that there will be negative impact on the economies of the countries. It has made numerous impacts in agricultural sector affecting income and profit of farmers as well as distributors and consumers. Hence, there is a urgent need of government action and advanced research labs so that the world with all its major affected countries could turn the situation over and make the economic growth could reach little far towards the target.