An impact study of <scp>COVID</scp>‐19 on six different industries: Automobile, energy and power, agriculture, education, travel and tourism and consumer electronics

Nayak, Janmenjoy; Mishra, Manohar; Naik, Bighnaraj; Swapnarekha, H.; Cengiz, Korhan; Shanmuganathan, Vimal

doi:10.1111/exsy.12677

Cited by 111 publications

(67 citation statements)

References 26 publications

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“…The current pandemic, known as coronavirus disease 2019 (COVID-19) triggered by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is provoking devastating health, psychological and financial consequences worldwide. [1][2][3] Although several vaccines have been developed, due to limitation in their manufacturing and distribution capacities, the desired globally "herd immunity" still appears to be a distant mirage. In addition, the constant mutations in SARS-CoV-2 put the effectiveness of these vaccination campaigns at serious risk regardless of its speed.…”

Section: Introductionmentioning

confidence: 99%

Possible Therapeutic Effects of Adjuvant Quercetin Supplementation Against Early-Stage COVID-19 Infection: A Prospective, Randomized, Controlled, and Open-Label Study

Pierro¹,

Derosa²,

Maffioli³

et al. 2021

IJGM

136

104

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Background: Quercetin, a well-known naturally occurring polyphenol, has recently been shown by molecular docking, in vitro and in vivo studies to be a possible anti-COVID-19 candidate. Quercetin has strong antioxidant, anti-inflammatory, immunomodulatory, and antiviral properties, and it is characterized by a very high safety profile, exerted in animals and in humans. Like most other polyphenols, quercetin shows a very low rate of oral absorption and its clinical use is considered by most of modest utility. Quercetin in a delivery-food grade system with sunflower phospholipids (Quercetin Phytosome ® , QP) increases its oral absorption up to 20-fold. Methods: In the present prospective, randomized, controlled, and open-label study, a daily dose of 1000 mg of QP was investigated for 30 days in 152 COVID-19 outpatients to disclose its adjuvant effect in treating the early symptoms and in preventing the severe outcomes of the disease. Results:The results revealed a reduction in frequency and length of hospitalization, in need of non-invasive oxygen therapy, in progression to intensive care units and in number of deaths. The results also confirmed the very high safety profile of quercetin and suggested possible anti-fatigue and pro-appetite properties. Conclusion: QP is a safe agent and in combination with standard care, when used in early stage of viral infection, could aid in improving the early symptoms and help in preventing the severity of COVID-19 disease. It is suggested that a double-blind, placebo-controlled study should be urgently carried out to confirm the results of our study.

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Section: Introductionmentioning

confidence: 99%

Possible Therapeutic Effects of Adjuvant Quercetin Supplementation Against Early-Stage COVID-19 Infection: A Prospective, Randomized, Controlled, and Open-Label Study

Pierro¹,

Derosa²,

Maffioli³

et al. 2021

IJGM

136

104

View full text Add to dashboard Cite

show abstract

“…Besides this, it helps in making a suitable compromise between the above-explained models so that an effective implementation can be made of IoT devices. It is because it will help in tracking down the COVID-19 result along with monitoring it in an effective way that will enhance the feasibility and flexibility rate of the whole process [28].…”

mentioning

confidence: 99%

RETRACTED ARTICLE: A Measurement Approach Using Smart-IoT Based Architecture for Detecting the COVID-19

Poongodi

Nguyen

Hamdi

et al. 2021

Neural Process Lett

Self Cite

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The corona virus has infected the entire world in the most severe ways. Many countries found the situation is very difficult to deal with and their health support infrastructure is not sufficient to manage the spread. People are locked in their homes and the whole world economy is in danger. That final vaccine has not yet reached the masses to deal with the epidemic. The corona virus, also known as COVID-19, can be spread by touching or coming close contact with an affected person, which is why the risk becomes so significant. However, the emergence of new emerging innovative technology such as blockchain and the Internet of Things (IoT) has changed the healthcare sector, especially in preventive measures. Different devices have ushered in a new era in the field of symptom-based diagnosis where doctors can most easily identify a person with a corona infection. This article presents a robust health-based IoT systems that can strengthen full COVID-19 administration and achieve greater results with available resources. The simulation results confirm the effectiveness of the proposed infection detection system.

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“…The virus causing this disease is known as the SARS-CoV2 virus with the first recorded cases in 2019 [2]. In addition to the burden on healthcare resources, other impacts were also observed in other industries including education, economy, and travel [3, 4]. Countries all around the world tried to curb the infections by employing a series of mitigation measures in the form of lockdowns, face coverings, social distancing, frequent sanitizing, limits on gatherings, etc [5].…”

Section: Covid-19 and Genetic Datamentioning

confidence: 99%

Classifying COVID-19 variants based on genetic sequences using deep learning models

Basu

Campbell

2021

Preprint

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The COrona VIrus Disease (COVID-19) pandemic led to the occurrence of several variants with time. This has led to an increased importance of understanding sequence data related to COVID-19. In this chapter, we propose an alignment-free k-mer based LSTM (Long Short-Term Memory) deep learning model that can classify 20 different variants of COVID-19. We handle the class imbalance problem by sampling a fixed number of sequences for each class label. We handle the vanishing gradient problem in LSTMs arising from long sequences by dividing the sequence into fixed lengths and obtaining results on individual runs. Our results show that one- vs-all classifiers have test accuracies as high as 92.5% with tuned hyperparameters compared to the multi-class classifier model. Our experiments show higher overall accuracies for B.1.1.214, B.1.177.21, B.1.1.7, B.1.526, and P.1 on the one-vs-all classifiers, suggesting the presence of distinct mutations in these variants. Our results show that embedding vector size and batch sizes have insignificant improvement in accuracies, but changing from 2-mers to 3-mers mostly improves accuracies. We also studied individual runs which show that most accuracies improved after the 20th run, indicating that these sequence positions may have more contributions to distinguishing among different COVID-19 variants.

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An impact study of COVID‐19 on six different industries: Automobile, energy and power, agriculture, education, travel and tourism and consumer electronics

Cited by 111 publications

References 26 publications

Possible Therapeutic Effects of Adjuvant Quercetin Supplementation Against Early-Stage COVID-19 Infection: A Prospective, Randomized, Controlled, and Open-Label Study

Possible Therapeutic Effects of Adjuvant Quercetin Supplementation Against Early-Stage COVID-19 Infection: A Prospective, Randomized, Controlled, and Open-Label Study

RETRACTED ARTICLE: A Measurement Approach Using Smart-IoT Based Architecture for Detecting the COVID-19

Classifying COVID-19 variants based on genetic sequences using deep learning models

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