A Novel Cnn Based Smart Mask Detection System

The Coronavirus made a new normalization of life where communal distancing and use of masks for covering their face perform an essential part in monitoring the effects of spreading of the corona virus, still the majority of population are found not using face shields or masks in public areas that accelerates the spreading of the corona virus. This might lead to the serious issue of rise in scattering of the disease. Therefore, to neglect any kind of circumstances we are in need to explore and alert the public for wearing masks. Persons can't be deployed for this procedure, as the risk of getting affected by corona virus increases. Henceforth, the presented model for mask detection is surrounded along the theories of artificial intelligence (AI), deep learning, object detection technologies and convolutional neural networks (CNN) which are the key subject of this project. The project performs by recognizing the people are wearing their face shields or masks or not in public areas via utilizing image processing and deep learning practices and transmitting data to the governing authorities. These algorithms for abject detection have been optimized for recognition of people with face masks or not. This paper is attempting for development of a model for real-time monitoring which will turn out to be pretty effective and simple. This model magnificently recognizes whether an individual is wearing a mask or not up to 98% of accuracy as achieved till date and observed that it has yielded outstanding outcomes for the detection. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Acnn Basedsmartmask Detectionsystem

The Coronavirus made a new normalization of life where communal distancing and use ofmasks for covering their face perform an essential part in monitoring the effects of spreading of thecorona virus, still the majority of population are found not using face shields or masks in public areasthat accelerates the spreading of the corona virus. This might lead to the serious issue of rise inscattering of the disease. Therefore, to neglect any kind of circumstances we are in need to exploreand alert the public for wearing masks. Persons can't be deployed for this procedure, as the risk ofgetting affected by corona virus increases. Henceforth, the presented model for mask detection is surroundedalongthetheoriesofartificialintelligence(AI), deep learning, object detection technologies andconvolutionalneuralnetworks(CNN)whicharethekeysubjectofthisproject.Theprojectperformsbyrecognizing the people are wearing their face shields or masks or not in public areas via utilizingimage processing and deep learning practices and transmitting data to the governing authorities.These algorithms for abject detection have been optimized for recognition of people with face masksor not. This paper is attempting for development of a model for real-time monitoring which will turnout to be pretty effective and simple. This model magnificently recognizes whether an individual iswearing amask or not up to 98% of accuracy as achieved till date and observed that it has yieldedoutstandingoutcomesforthedetection. Copyright © 2022, Anka Publishers. All rights reserved.

Intensive care unit delirium in patients with severe COVID-19: A prospective observational cohort study.

Background: Delirium is common in patients with severe coronavirus disease-19 (COVID-19). The purpose of our study was to determine whether severe COVID-19 is an independent risk factor for the development of delirium in patients treated in the intensive care unit (ICU). Methods: This prospective observational cohort study involved 162 critically ill patients admitted to a multidisciplinary ICU during 2019 and 2020. A validated screening tool was used to diagnose delirium. Multiple delirium risk factors were collected daily including clinical characteristics, hospital course, lab values, vital signs, surgical exposure, drug exposure, and COVID-19 characteristics. After univariate analysis, a multivariate logistic regression analysis was performed to determine independent risk factors associated with the development of delirium. Results: In our study population, 50 (31%) patients developed delirium. A total of 39 (24.1%) tested positive for COVID-19. Initial analysis showed COVID-19 to be more prevalent in those patients that developed delirium (40% vs. 17%; P = 0.003). Multivariate analysis showed opioid use (odds ratio [OR]: 24 [95% confidence intervals (CI): 16-27]; P ≤ 0.001), benzodiazepine use (OR: 23 [95% CI: 16-63] P = 0.001), and estimated mortality based on acute physiology and chronic health evaluation IV score (OR: 1.04 [95% CI: 1.01-1.07] P = 0.002) to be independently associated with delirium development. COVID-19 (OR: 1.44 [95% CI: 0.13-10.6]; P = 0.7) was not found to be associated with delirium. Conclusion: Delirium is prevalent in critically ill patients admitted to the ICU, including those with COVID-19. However, after adjustment for important covariates, we found in this cohort that COVID-19 was not an independent risk factor for delirium.

Cytokine profiles in intensive care unit delirium.

BACKGROUND: Neuroinflammation causing disruption of the blood-brain barrier and immune cell extravasation into the brain parenchyma may cause delirium; however, knowledge of the exact pathophysiologic mechanism remains incomplete. The purpose of our study was to determine whether cytokine profiles differ depending on whether delirium occurs in the setting of sepsis, coronavirus disease 2019 (COVID-19), or recent surgery. METHODS: This prospective observational cohort study involved 119 critically ill patients admitted to a multidisciplinary intensive care unit (ICU) during 2019 and 2020. Delirium was identified using the validated confusion assessment method for the ICU. Multiple delirium risk factors were collected daily including clinical characteristics, hospital course, lab values, vital signs, surgical exposure, drug exposure, and COVID-19 characteristics. Serums samples were collected within 12 hours of ICU admission and cytokine levels were measured. RESULTS: The following proinflammatory cytokines were elevated in our delirium population: tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-18, C-C motif ligand (CCL) 2, CCL3, C-X-C motif chemokine ligand (CXCL)1, CXCL10, IL-8, IL-1 receptor antagonist, and IL-10. Analysis of relative cytokine levels in those patients that developed delirium in the setting of sepsis, COVID-19, and recent surgery showed elevations of CCL2, CXCL10, and TNF-α in both the sepsis and COVID-19 group in comparison to the postsurgical population. In the postsurgical group, granulocyte colony-stimulating factor was elevated and CXCL10 was decreased relative to the opposing groups. CONCLUSIONS: We identify several cytokines and precipitating factors known to be associated with delirium. However, our study suggests that the cytokine profile associated with delirium is variable and contingent upon delirium precipitating factors.

Evidence showing lipotoxicity worsens outcomes in covid-19 patients and insights about the underlying mechanisms.

We compared three hospitalized patient cohorts and conducted mechanistic studies to determine if lipotoxicity worsens COVID-19. Cohort-1 (n = 30) compared COVID-19 patients dismissed home to those requiring intensive-care unit (ICU) transfer. Cohort-2 (n = 116) compared critically ill ICU patients with and without COVID-19. Cohort-3 (n = 3969) studied hypoalbuminemia and hypocalcemia's impact on COVID-19 mortality. Patients requiring ICU transfer had higher serum albumin unbound linoleic acid (LA). Unbound fatty acids and LA were elevated in ICU transfers, COVID-19 ICU patients and ICU non-survivors. COVID-19 ICU patients (cohort-2) had greater serum lipase, damage-associated molecular patterns (DAMPs), cytokines, hypocalcemia, hypoalbuminemia, organ failure and thrombotic events. Hypocalcemia and hypoalbuminemia independently associated with COVID-19 mortality in cohort-3. Experimentally, LA reacted with albumin, calcium and induced hypocalcemia, hypoalbuminemia in mice. Endothelial cells took up unbound LA, which depolarized their mitochondria. In mice, unbound LA increased DAMPs, cytokines, causing endothelial injury, organ failure and thrombosis. Therefore, excessive unbound LA in the circulation may worsen COVID-19 outcomes.

Uplifting the Grassroots Through Community Entrepreneurship Development: A Case Study of Sualkuchi Handloom Town of Assam, India

A strong foundation of the economy lies in strengthening the grassroots. A robust rural economy and sound financial health at the grassroots is imperative for a balanced economic growth of any region. This Covid-19 pandemic and resultant lockdown showed the helplessness of industrialization with 10 million immigrant workers in India rushing back to their native places in search of food and shelter. A sustainable income that provides adequate stability to not just one but future generations is the need of the hour. After agriculture, the largest labour intensive sector in India is handloom. It employs around 4.3 million people, contributes 2.3 % to the country's GDP and 12% to earnings from exports. Total handloom export stood at US$ 176.97 million (April 2020 to January 2021) as per Ministry of Textiles, Government of India. So this sector has potential for an increased GDP and per capita rural income. Some facts about India's rich history of trade and commerce give an insight into the high demand of Indian textiles all across the globe. Apart from spices, herbs and minerals, India exported silk and cotton textiles to Central Asia, Southeast Asia and even Europe as early as in the 3rd - 4th centuries. Silk rearing and weaving are skills that are passed on from one generation to the other in rural areas of our country. Investments in terms of infrastructure and skill training would be extremely minimal if this tradition is taken up as an entrepreneurial venture within a geographical community. This paper attempts to study the handloom weavers of Sualkuchi town of Assam, their problems and future growth plans. This paper would also try to understand the possibilities of developing a community entrepreneurial programme for these weavers. This would be an initiative to motivate the younger generation to take up this tradition and enjoy a healthy sustainable living within their geographical boundaries rather than contributing towards growing urban slums.

A Survey of Self-perceived Physical Discomforts and Health Behaviors Related to Personal Protective Equipment of Indian Dental Professionals during COVID-19 Pandemic.

AIM: In the current situation of COVID-19 pandemic, personal protective equipment has to be mandatorily worn by dental professionals all times in the dental clinical settings. The aim of this study was to assess the physical discomforts and related health issues faced by dental professionals while wearing personal protective equipment in dental clinical settings during the pandemic. METHODS: This was an online cross-sectional survey conducted in November to December 2020 among dental professionals of various regions of country. A prevalidated questionnaire was sent through email/WhatsApp groups to 650 dental professionals. Informed consent was taken from all the participants. Information was collected about the demographics, type of dental set-up, average daily working hours, types of PPE worn, physical discomforts related to the various procedures in dentistry. Association was analyzed between demographics and the discomforts using Chi-square test. RESULTS: A total of 309 dental professionals (163 females, 146 males) from all parts of the country responded to the online questionnaire. Maximum respondents were postgraduates or pursuing MDS (79%), majority (42.1%) were pediatric dentists followed by general dentists. Sweating, difficulty in vision, difficulty in breathing, and headache were the common discomforts reported by majority of the respondents. Headache and difficult breathing were more significantly associated with female dental professionals (p < 0.05). N95 wear was associated with breathing difficulty (56%) while use of faceshield led to the discomforts in visual acuity in 46% respondents. CONCLUSION: The survey has depicted several challenges and various physical discomforts being experienced by the dental professionals during this pandemic. Although wearing PPE is associated with difficulties to dentists but it is extremely essential to wear PPEs for self-protection during the ongoing pandemic. HOW TO CITE THIS ARTICLE: Bansal K, Saji S, Mathur VP, et al. A Survey of Self-perceived Physical Discomforts and Health Behaviors Related to Personal Protective Equipment of Indian Dental Professionals during COVID-19 Pandemic. Int J Clin Pediatr Dent 2021;14(6):784-789.

What is the impact of COVID-19 pandemic on global carbon emissions?

The coronavirus 2019 (COVID 19, or SARS-CoV-2) pandemic that started in December 2019 has caused an unprecedented impact in most countries globally and continues to threaten human lives worldwide. The COVID-19 and strict lockdown measures have had adverse effects on human health and national economies. These lockdown measures have played a critical role in improving air quality, water quality, and the ozone layer and reducing greenhouse gas emissions. Using Soil Moisture Active Passive (SMAP) Level 4 carbon (SMAP LC4) satellite products, this study investigated the impacts of COVID-19 lockdown measures on annual carbon emissions globally, focusing on 47 greatly affected countries and their 105 cities by December 2020. It is shown that while the lockdown measures significantly reduced carbon emissions globally, several countries and cities observed this reduction as temporary because strict lockdown measures were not imposed for extended periods in 2020. Overall, the total carbon emissions of select 184 countries reduced by 438 Mt in 2020 than in 2019. Since the global economic activities are slowly expected to return to the non-COVID-19 state, the reduction in carbon emissions during the pandemic will not be sustainable in the long run. For sustainability, concerned authorities have to put significant efforts to change transportation, climate, and environmental policies globally that fuel carbon emissions. Overall, the presented results provide directions to the stakeholders and policymakers to develop and implement measures to control carbon emissions for a sustainable environment.

Effect of COVID-19 shutdown on aerosol direct radiative forcing over the Indo-Gangetic Plain outflow region of the Bay of Bengal

The Indo Gangetic Plain (IGP), one of the most densely populated regions of the world, is a global hotspot of anthropogenic aerosol emissions. In the pre-monsoon season (March-May), the strong westerlies carry transported dust aerosols along with anthropogenic aerosols onto the Bay of Bengal (BoB). The outflow from IGP modulates the aerosol loading and the aerosol direct radiative forcing (ADRF) over the BoB. The quantification of the anthropogenic aerosol impact on the radiative forcing over the outflow region remains inadequate. The enforced shutdown amid the COVID-19 pandemic eased the anthropogenic activities across the country, which helped to examine the magnitude and variability of aerosol loading and subsequent changes in ADRF over IGP and the outflow region of the BoB. Wind trajectory analysis illustrates that the ADRF over the BoB is greater during the days when the winds originated from the IGP region (at the surface -54.2±6.4 W m-2, at the top of the atmosphere, -26.9±3.4 W m-2 and on the atmosphere, 27.0±3.1 W m-2 ) compared to the seasonal average (-46.3±7.1 W m-2, -24.9±4.0 W m-2 and 20.6±3.2 W m-2, respectively). This indicates that anthropogenic aerosols emission in IGP can contribute an additional 31% of the atmospheric ADRF over the IGP outflow region of the BoB. The reduced aerosol loading during the shutdown period resulted in a reduction of ADRF at the surface, at the top of the atmosphere, and on the atmosphere over the IGP outflow region of the BoB by 22.0±3.1%, 20.9±3.4% and 23.2±3.3%, respectively. This resultant 20-25% reduction in ADRF over the IGP outflow region of BOB matches well with 10-25% reduction in aerosol optical depth (AOD) over the IGP during the shutdown period showing a robust coupling between IGP aerosol emissions and ADRF over the BoB.

Cytomegalovirus haemorrhagic enterocolitis associated with severe infection with COVID-19.

We present a case of haemorrhagic enterocolitis in a patient with SARS-CoV-2 who recovered from respiratory failure after support with venovenous extracorporeal membrane oxygenation. We describe clinicopathological features consistent with the systemic coinfection/reactivation of cytomegalovirus (CMV) concurrent with COVID-19 infection and the protracted clinical course of resolution of gastrointestinal inflammation after the treatment of CMV infection. Stool PCR, abdominal CT perfusion scan and histological examination of ileal and colonic tissues excluded enterocolitis secondary to other causes of infection (common viral, bacterial and protozoal gastrointestinal pathogens), macrovascularand microvascular ischaemia and classic inflammatory bowel disease, respectively. We propose possible synergistic pathophysiologic mechanisms for enterocolitis complicating severe COVID-19 infection: (1) T lymphocyte depletion and immune response dysregulation, (2) use of immunomodulators in the management of severe COVID-19 infection and (3) high concentration of ACE-2 receptors for COVID-19 virus in the gastrointestinal tract.

Improved air quality during COVID-19 at an urban megacity over the Indo-Gangetic Basin: From stringent to relaxed lockdown phases.

The enforced lockdown amid COVID-19 pandemic eased anthropogenic activities across India. The satellite-derived aerosol optical depth (AOD) and absorption AOD showed a significant reduction of ~30% over the Indo-Gangetic Basin (IGB) in north India during the lockdown period in 2020 with respect to the previous year 2019, when no such lockdown was in effect. Further, near-surface air pollutants were investigated at an urban megacity Delhi during 01 March to 31 May 2020. Except O3, a drastic reduction in PM10, PM2.5, NO, NO2 and CO concentrations were observed by ~58%, 47%, 76%, 68% and 58%, respectively during the lockdown period of 2020 as compared to 2019. While, O3 was low in the initial phase and gradually increased with progression of lockdown phases, the mean O3 during the entire lockdown period was nearly similar in both the years. Though, all the measured pollutants showed significant reduction during the entire lockdown, a phase-wise enhancement, associated with the conditional relaxations was observed in their concentrations. Thus, the present results may help, not only to assess the impact of outbreak on air quality, but also in designing the mitigation policies in urban megacities in more efficient ways to combat the air pollution problems.

Apparent scaling of virus surface roughness-An example from the pandemic SARS-nCoV.

This paper investigates the scaling of the surface roughness of coronavirus, including the SARS-nCoV based on fractal and spectral analyses of their published electron microscopy images. The box-counting fractal dimensions obtained are subjected to ANOVA tests for statistical significance. Results show that the SARS-nCoV particles could not statistically be resolved by their shape on the basis of the fractal dimension values, but they could be distinguished from the earlier SARS-CoV particles. MANOVA test results require interaction of factors used for classifying virions into different types. The topological entropies, a measure of randomness in a system, measured for the images of varying size show correlation with the fractal dimensions. Spectral analyses of our data show a departure from power-law self-similarity, suggesting an apparent scaling of surface roughness over a band of maximum an order of magnitude. The spectral crossover that corresponds to characteristic length scale may represent average viral size. Our results may be useful in inferring the nature of surface-contact between the viral and human cell, causing infection and also in providing clues for new drugs, although it is too early to say. In addition, limitations of this study, including possible ways to avoid the bias in scaling exponents due to the use of different techniques are discussed.