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The design of a Covid-19 testing kit is proposed in this research using a photonic crystal structure (PhC) and a violet laser beam. The basic principle of this structure relies on the phenomenon of absorbance reflectance and transmission at the signal of a 412 nm laser beam. Finally, the transmitted light energy through the PhC structure is the conclusive factor to detect the types of virus which is the function of the reflectance and absorbance. The reflected light energy is computed by plane wave expansion (PWE) whereas the absorbance of light energy is obtained through numerical computation. The notable advantages of this technique are that the virus related to Covid-19 can be recognized by observing the colour of transmitted energy through a photo energy meter. Finally, the outcomes of the research affirm that the sample could be Covid-19 if the output energy would be infrared (IR). Similarly, the sample could be a normal coronavirus, if the output energy would lie within the visible regime.
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The current work employs a Si-based one-dimensional (1-D) photonic struc-ture which delivers 20 different types of monochromatic laser beam via the filtering action. The I/P signals are essentially varying from visible to near infrared (NIR) range to justify the work. Though similar types of work related to filtering application are found in the literature, the present research deals with an output laser beam which could be deployed in different pur-poses vis-a-vis dentistry, dermatology, spectroscopy, printing, holography, barcode scanning, etc. The mechanism of this work incorporates 68 layers of SiO and Si-based 1-D optical waveguide along with their configuration where the plane wave expansion (PWE) method does fulfil the basics of the required mathematics to solve out electromagnetic wave equations. Reflec-tance and transmittance characteristics along with the absorbance are the critical parameters that substantiate the said application.
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The COVID-19 pandemic has left scars on the Indian public transportation system. In order to regain its original momentum, policymakers will need to assess the barriers hindering the effectiveness of the public transportation sector. In this regard, this article analyzes the various factors affecting the public transportation sector in India and determines their interrelationships. The research is presented in three steps. First, we review the literature to identify the factors that affect the public transportation system in India. Next, we propose an integrated model of grey-DEMATEL and ANP, grey-DANP, to calculate the priority ranking and weight of the factors. The grey-DEMATEL method is used to find the interrelationships among the factors, while ANP determines the local and global weights of the factors to form a priority order. Then, we present the interrelationships in the form of influential relation maps. Furthermore, we provide a sensitivity analysis to enhance the credibility of our study. The paper reveals that governmental regulations are the most influential factors in India's public transportation system. The transportation authorities and policymakers must also focus on improving the financial stability and enhancing the customer's trust in the public transportation system. The framework provided in this paper can be applied to other countries where similar hindrances in the public transportation system have been caused by COVID-19. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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Coronavirus disease-2019 (COVID-19) is a contagious infection caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), leading to a pandemic and traumatizing the world. To prevent the spread of virus, infected people were isolated as per the strict protocols. Due to the genome sequence of the virus being strikingly similar to that of SARS-CoV, many antiviral medicines previously approved to treat SARS and MERS are now being repurposed for the plausible treatment COVID-19. To combat SARS-CoV-2, a slew of experimental and clinical medicine and vaccine trials are currently underway worldwide. In the fight against COVID-19 infection, a variety of natural substances are also being searched extensively. Coumarins and chalcones are two important natural chemical classes. They can be found in a wide range of natural products and have many pharmacological effects. SARS-CoV-2 and other coronaviruses were successfully treated with these drugs, which showed significant antiviral activity. This chapter discusses the possible role of coumarins and chalcones in SARS-CoV-2 infection treatment. © 2023 Elsevier Inc. All rights reserved.
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Genetic lineages of severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) have continued to emerge and circulate around the world since the onset of the COVID-19 pandemic. There are numerous variants of SARS-CoV-2, the virus that causes corona virus disease 2019 (COVID-19). Like other viruses, SARS-CoV-2 evolves over time. Most mutations in the SARS-CoV-2 genome have no impact on viral function, but certain variants have gained worldwide attention because of their rapid emergence within populations, evidence of transmission, and clinical implications. During the pandemic, most parts of India were affected, including Odisha, leading to high rates of morbidity and mortality. For the present study, 368,303 samples were received by the COVID-19 lab i.e., medical college level (Virus Research Diagnostic Laboratory) VRDL from six districts of western Odisha, including approximately 25,000 COVID-19-positive samples. The diagnostic method of the quantitative RT-PCR cannot be used to distinguish among the variants created by mutation of the genes initially, therefore selected positive clinical samples were sent in cold chain for whole genome sequencing (WGS), using the Illumina Seq. at ILS, BBSR for variant detection. The reported observation from the next generation sequencing (NGS) based sequenced samples of western Odisha updated in the INSACOG-WGS portal confirms the presence of Delta (B.1.617.2) and Delta sublineages, Omicron (BA.2), and Omicron (B.1.1.529). Maximum infection was caused by Delta sublineages (83.5%) irrespective of age, sex, and geographic area followed by Delta and Omicron. Molecular diagnosis and WGS based study reveal the widespread transmission of the fatal virus, significantly affecting every corner of the globe. Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.
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Genetic lineages of severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) have continued to emerge and circulate around the world since the onset of the COVID-19 pandemic. There are numerous variants of SARS-CoV-2, the virus that causes corona virus disease 2019 (COVID-19). Like other viruses, SARS-CoV-2 evolves over time. Most mutations in the SARS-CoV-2 genome have no impact on viral function, but certain variants have gained worldwide attention because of their rapid emergence within populations, evidence of transmission, and clinical implications. During the pandemic, most parts of India were affected, including Odisha, leading to high rates of morbidity and mortality. For the present study, 368,303 samples were received by the COVID-19 lab i.e., medical (Virus Research Diagnostic Laboratory) VRDL from six districts of western Odisha, including approximately 25,000 COVID-19-positive samples. The diagnostic method of the quantitative RT-PCR cannot be used to distinguish among the variants created by mutation of the genes initially. Therefore, selected positive clinical samples were sent in cold chain for whole genome sequencing (WGS), and disease severity was sequenced using the Illumina Seq at ILS, BBSR for variant detection. The reported observation from the next generation sequencing (NGS) based sequenced samples of western Odisha updated in the INSACOG-WGS portal confirms the presence of Delta (B.1.617.2) and Delta sub lineages, Omicron (BA.2), and Omicron (B.1.1.529). Maximum infection was caused by Delta sub lineages 83.5%) irrespective of age, sex, and geographic area followed by Delta and Omicron. Molecular diagnosis and WGS based study reveal the widespread transmission of the fatal virus, significantly affecting every corner of the globe. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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Children with prior coronavirus disease 2019 (COVID-19) infection display an increased systemic inflammation causing multiorgan dysfunctions in the cardiovascular, respiratory, central nervous system, and gastrointestinal (GI) systems, known as MIS-C, that is, multisystem inflammatory syndrome in children. Most of the MIS-C cases have GI manifestations like pain abdomen, loose motion, vomiting or nausea, elevated liver enzymes, ileus, and bleeding. Angiotensin-converting enzyme 2 (ACE2) receptors in the terminal ileum and colon are responsible for the majority of ACE2-induced damage to these tissues. In the pandemic's second wave, a significant number of MIS-C patients with predominantly GI symptoms (around 80%) were reported. Although different molecular inflammatory mechanisms are involved, there is a significant overlap of the children's GI symptoms with those of MIS-C and other conditions of the abdomen caused by infection or inflammation, thus resulting in a diagnostic dilemma. Here, we report two cases of MIS-C with acute appendicular perforation and ileal perforation needing both medical management and surgical intervention. © 2022 Medical Journal of Dr. D.Y. Patil Vidyapeeth ;Published by Wolters Kluwer - Medknow.
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Background. Two years into the pandemic, clinicians do not have access to a standardized measurement of SARS-CoV-2 viral load (VL) that allows for VL comparison across clinical specimens and different assays. Reliable VL measurement in diverse respiratory specimens, over time, and in response to treatments such as remdesivir (RDV), could better inform treatment and prevention. Methods. To investigate the use of a standardized VL assay in respiratory specimens, we enrolled patients hospitalized with COVID-19 in Providence, RI, with/ without RDV exposure;collected serial samples from 4 compartments (nasopharyngeal-NP, nasal-NA, oropharyngeal-OP, saliva-SA) in 3 visits during the 1st week of hospitalization;and characterized SARS-CoV-2 VL using a ChromaCode HDPCRTM quantitative research use only assay, calibrated to the first World Health Organization (WHO) International Standard (IS). Linear mixed effects models and associated regression coefficients were used to analyze intercompartmental VL differences at enrollment, over time, and with/without RDV. Results. Of 35 participants (60% male;70% White, 14% Hispanic/Latino, 49% RDV exposure), all had visit 1 samples (median hospital day 1, IQR 0-2;pre-RDV for those exposed);80% visit 2 samples (median hospital day 2, IQR 1-8);and 37% visit 3 samples (median hospital day 4, IQR 3-7). Overall, 38 NP, 67 NA, 57 OP, and 67 SA samples were collected. Mean log VLs (Log10IU/mL) differed by compartment at visit 1 (NP 6.3, NA 4.9, OP 4.1, SA 5.6, p=0.0001) and significantly decreased over time in all compartments (p< 0.04 for all comparisons). Log VL change over time was not significantly different between compartments or between people treated/not treated with RDV. Conclusion. We successfully measured respiratory intercompartmental SARS-CoV-2 VL differences among hospitalized patients using a standardized assay calibrated to the WHO IS. Dissemination of standardized VL measurement methods will allow accurate VL comparisons across assay types quantified in IU/mL and improve assessment of the impact of COVID-19 treatments. Inter-compartmental VL differences at baseline may indicate sampling variability or different viral burden. RDV did not appear to accelerate viral decay.
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Introduction: Chronic lymphocytic leukemia (CLL) is a lymphoproliferative disorder with clonal proliferation of functionally incompetent mature B lymphocytes, defined by an absolute lymphocyte count>5 9 109/ml malignant cells in the blood. The disorder is more common in men. In most of the cases, it is asymptomatic and diagnosed during routine blood investigations while getting evaluated for some other disease. However, patients need treatment once they are symptomatic with painless enlarged, bulky lymphnodes, anemia or thrombocytopenia. Case report: We report a case of 67 year female, with Type-2DMand HTN, who presented with difficulty in breathing to the emergency during the first wave of Covid -19 pandemic. Chest X-ray revealed left mid zone opacity suggestive of a lung mass. CT Thorax done showed multiple mildly enlarged mediastinal lymph nodes, with lobulated heterogeneously enhancing mass in the prevascular compartment of anterior mediastinum compressing left upper lobar bronchus. USG guided core needle biopsy of left upper lobe mass was done and pleural fluid was analysed, which was suggestive of a lymphoproliferative neoplasm. Then CBC was advised which demonstrated lymphocytosis. Flow cytometry and IHC confirmed the diagnosis mature B-cell neoplasm Chronic Lymphocytic Leukemia (CLL). Discussion(s): Pulmonary manifestation of CLL include, hilar and mediastinal lymphadenopathy. Lung masses are a rare presentation. Richter's transformation is a unique complication of CLL. However, patients with CLL also have an increased risk of secondary malignancy most commonly Kaposi sarcoma, malignant melanoma and carcinoma lung. Our case is unique,as there were no features of Richter transformation that is weight loss, fever, night sweats, muscle wasting and increased hepatosplenomegaly or lymphadenopathy. She was evaluated for respiratory distress and diagnosed on Lung mass biopsy as atypical lymphoid cell infiltration and not as lung carcinoma or transformation to high grade lymphoma. Conclusion(s): Clinicians should be aware that though chronic lymphocytic leukemia is diagnosed incidentally on routine blood investigations, atypical presentation must be kept in mind. A simple CBC and a peripheral smear examination gives a clue to the diagnosis at the earliest.
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Covid 19, a deadly virus is spreading exponentially across the globe that leads to loss of precious life. Recent data suggests that more than 4.6 million people have been died due to this, so it is requiring an ample precaution to stop it. Development of good vaccine along with rapid testing could reduce the mortality rate. Though recently few good vaccines have developed but adequate numbers of doses are not available for every individual due to lack of mass production. Not only are the production issues but also their prob-lems lie in transportation and distribution to huge population. In this sce-nario testing will play a vital role so that affected people could get a dose in priority basis. To meet the nitty-gritty of such problem. A violet laser beam interacted with a photonic crystal (PhC) structure having dimension of 600 x 600 nm2 to identify the novel coronavirus (n-CoV) know as SARS CoV-2. The device finds 16 squares which hold the samples of the swab collected from a patient where the signal of 412 nm (728 THz) incident to it. The principle of mechanism deals with the analysis of scattering parameters (S11 and S12) of the signals which is obtained through the finite element method (FEM). The S11 and S12 parameters deal with the transmittance and reflec-tance of the signal pertaining to the chosen structure. Further, the investiga-tion of transmittance identifies the nature of the virus;for example, the present research claims that blue and violet colours are two possible implica-tions at the output when the structure containing sample excited with a violet laser beam. The output with blue colour indicating the presence of just ordi-nary coronaviruses. On the other hand, if we receive violet colour then it is novel corona viruses (n-CoV)
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COVID-19 (novel coronavirus disease) is a deadly illness, has infected and killed a very large number of people worldwide. The widely followed lab testing (RT-PCR Test) for the detection of this disease has various limitations with high cost and take long time to provide the outcome. As a result, diverse technologies that permit for the quick and accurate finding of the infection can provide much required assistance to medical management. In recent studies, gained radiological imaging techniques, such images convey important information about this virus. Advanced Deep learning (DL) techniques combined with the radiology images can aid in the correct diagnosis of the virus, as well as defeat the problem of insufficient expert physicians in rural areas. In this work, aimed at presenting a DL based-Convolutional neural network (CNN) model for the automatic detection of the coronavirus from X-ray images of chest. The Kaggle dataset available publicly of total 42330 images from 4-categories are used. The experiment produced the accuracy of 88.53% and 86.19% for training and validation, which is better result for the highest number of radiographic images in comparison to existing work. © 2022 IEEE.
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Nanoparticle (NP)-based colorimetric methods are extensively used for the rapid detection of environmental contaminants, different substances and SARS-CoV-2 in various fields such as environmental science, virology, pollution research, and the food industry, as well as biomedicine. Colorimetric sensors exhibit high sensitivity and selectivity, are easy to handle, portable, safe for screening purposes and can be visualized by the naked eye. Herein, the colorimetric sensing approaches of the two most commonly used metallic NPs, i.e., gold (Au) and silver (Ag), and their physicochemical methods are discussed, as metallic NPs show good efficiency due to their unique optical and chemical properties. This review summarizes the progress on colorimetric sensors based on metallic NPs as sensors and their applications, elucidating the utility and superior features of metallic-NP-based colorimetric assay for the detection of different environmental contaminants, biomolecules and SARS-CoV-2 in the environmental as well as human biological samples. An outlook with respect to the trends and future development of the proposed sensors is also provided.
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Since December 2019, the world has entered a new phase, where the health sector and lifestyle of people has threatened worldwide due to global pandemic COVID-19. Because of this infectious disease, approximately 6 million people have died worldwide, and still, it is increasing. RT-PCR (Reverse Transcription-Polymerase Chain Reaction) is the prime method of testing covid- 19 now, but its pricey cost, lengthy testing result, and several other factors reduce the quality of prediction accurately within the time. In this paper, a deep learning approach is used to detect the Covid-19 disease using a dataset of chest X-ray images. A total 21165 chest X-ray images of 4-categories are taken and applied on the deep learning model ResNet50. The experiments show that it has better accuracy of 97.17% as compared to the existing models. In addition, the data set is also applied to Convolutional Neural Network model which has given the accuracy of 96.68%. © 2022 IEEE.
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The pandemic COVID-19, caused by the organism severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) belongs to the family Coronoviridae has become a serious global healthcare crisis. The biggest demand of the present time is to develop efficacious medication for the treatment of SARS-CoV-2. In the present study, we performed the interaction of 50 flavonoids selected from the Pubchem database, with five efficacious protein targets for SARS-CoV-2: main protease (Mpro), spike glycoprotein-receptor binding domain (SGp-RBD), RNA-dependent RNA polymerase (RdRp), angiotensin converting enzyme-2 (ACE-2) and non-structural protein15 (NSP15, an endonuclease). All the work involve in the present study was accomplished by using Maestro 12.4 (Schrodinger Suite) to obtain the docking scores and ADME-T study result of selected ligands with the five effective target proteins of SARS-CoV-2. Molecular docking-based results indicated that diosmin has the most favorable docking scores-10.16,-11.52,-9.75,-11.25 and-10.25 kcal/mol for the Mpro, SGp-RBD, ACE-2, RdRp and NSP-15 protein targets and had acceptable drug suitability as a therapeutic agent against COVID-19. The structure of this compound can be further useful to medicinal chemists, pharmacologists, and clinicians for efficiently discovering or developing effective drugs to cure COVID-19.
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Introduction: The novel coronavirus (2019-nCoV) is a contagious virus that causes respiratory infection and has shown evidence of human-to-human transmission. In this infection the immunity of the patient is decreased;making them susceptible to various secondary infections. This leads to increased morbidity and mortality in these patients. Aim: To estimate the profile of secondary infections in hospitalised Coronavirus Disease-2019 (COVID-19) patients and analyse their antimicrobial susceptibility pattern. Materials and Methods: A cross-sectional study was conducted for a period of five months from June to October 2021, which included COVID-19 positive patients with secondary infection admitted in the dedicated COVID hospital, Maharaja Krishna Chandra Gajapati Medical College and Hospital (MKCG MCH), Berhampur, Odisha, India. Clinical samples like blood, urine, sputum, tissue biopsy and Bronchoalveolar Lavage (BAL) were collected aseptically from patients with COVID-19 and were processed in microbiology laboratory as per standard operating procedures. All the necessary information like demographic features (age, gender), associated co-morbidities and oxygen saturation levels of COVID-19 positive patients at the time of admission were collected and entered in a Microsoft Excel sheet for further analysis. Results of continuous variables were described by mean and range while categorical variables were described by frequency. All the generated data was analysed by Statistical Package for the Social Sciences (SPSS) 16.0. Results: A total of 438 patients suspected of COVID-19 were admitted during the study period, out of which 138 patients were positive for COVID-19 by Reverse Transcriptase Polymerase Chain Reaction (RT-PCR). Out of 138 COVID-19 positive patients, 105 patients were willing to give samples and their samples were processed for bacterial and fungal culture and sensitivity. Total 18/105 (17.1%) samples were positive for bacterial and fungal growth. Blood Stream Infection (BSI) were seen in 14/18 (77.8%) and was predominantly associated with Staphylococcus aureus 5/14 (35.7%), followed by Enterococcus spp. 3/14 (21.4%). Out of total culture positive cases, 2/18 (11.1%) showed Urinary Tract Infection (UTI). Of the UTI cases Escherichia coli was isolated from 1/2 (50%) of cases. Out of total culture positive cases, 2/18 (11.1%) were identified having mucormycosis. All gram positive bacteria had shown maximum resistant to ampicillin and gram negative bacteria were resistant to ampicillin-sulbactam, levofloxacin, cotrimoxazole. Conclusion: In COVID-19 positive patients with secondary infection, early diagnosis and prompt treatment will lead to improved patient care and better outcome.
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This study estimates the potential source regions contributing to PM2.5 in the capital city of Thimphu, Bhutan, during the years 2018-2020 using the ground-based data, followed by the HYSPLIT back trajectory analysis. The average PM2.5 concentration in the entire study period was 32.47 µg/m3 which is three times of the World Health Organization recommended limit of 10 µg/m3. Less than half of the days in pre-monsoon (43.47%) and post-monsoon (46.41%), and no days in winter were within the 24-h average WHO guideline of 25 µg/m3. During the COVID-19 lockdown imposed from August 11 to September 21 in Bhutan, only a marginal reduction of 4% in the PM2.5 concentrations was observed, indicating that nonlocal emissions dominate the PM2.5 concentrations in Thimphu, Bhutan. Most back trajectories in the analysis period were allocated to south or south-west sector. India was the major contributor (~ 44%), followed by Bangladesh (~ 19%), Bhutan itself (~ 19%) and China (~ 16%). This study confirms that there are significant contributions from transboundary sources to PM2.5 concentrations in Thimphu, Bhutan, and the elevated PM2.5 concentrations need to be tackled with appropriate action plans and interventions.
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COVID-19 has significant influence on the financial market. This paper aimed to explore the COVID-19 scenario analysis for stock market of beauty industry. Stock data of Estée Lauder Companies (EL), Revlon Inc. (REV) and Coty Inc. (COTY) is considered for this purpose. Deep learning models (LSTM and CNN) are utilized for the stock price prediction of beauty companies during COVID-19 era. LSTM and CNN, both the model worked well for the stock price prediction;however, LSTM performed better in all cases. Lockdown scenario along with the stock data is taken for the analysis purpose. Study shows that beauty industries got affected during initial spread of the virus, but now recovering. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The world is in distress because of the COVID-19 pandemic;the best remedy is isolation from this infection. Wearing a face mask is vital to protect ourselves from the virus. A person wearing a face mask can be detected by Computer Vision and notify the authorities if the protocol is not followed. Since it is very labor-intensive to check if a person is wearing a face mask in public places, Computer Vision makes it easy for real-time monitoring. This method uses MobileNet and OpenCV to classify people into two categories, wearing the face mask or not, with 99.41% and 100% testing accuracy for face mask detection and without face mask detection, respectively. It requires low computing power and is compatible with mobile devices, which can help the concerned authorities enforce the rule of wearing face masks in public places. © 2021 IEEE.
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COVID 19, a furious virus, exploded across the globe in 2020. Treatment, tracing and testing are the only way to retain a normal life. But the biggest obstacle is the shortage of proper testing kits which makes life horrendous. As a consequence it demands time to ramp up the development of a suitable test kit. In this scenario we propose a kit that is made up of a two-dimensional (2-D) Si-based photonic crystal structure (PCS) that could distinguish the novel coronaviruses (n-CoV) from ordinary coronaviruses. The principle of identification relies on the reflectance, absorbance and transmittance characteristics at the signal of 412 nm wavelength obtained from a laser diode (LD);moreover, the operational mechanism deals with the manipulation of the signal with the proposed PCS structure which contains the virus solution. Finally, the output transmitted energy differentiates the viruses pertaining to their nature;for example, an output with visible light energy gives an indication of normal flu;on the other hand, output energy within the infrared (IR) range confirms the case of novel coronavirus infection.