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1.
Innov Syst Softw Eng ; : 1-12, 2022.
Article in English | Web of Science | ID: covidwho-2174811

ABSTRACT

Coronavirus disease 2019 (Covid-19) is a contiguous disease which affected a large volume of population with a high mortality rate across the globe. For dealing with the recent spread of COVID-19, one of the prime measures was to vaccinate people in full extent. People across the globe have diverse opinion regarding the vaccination process, its side effect and effectiveness. Such opinions get located into different micro-blogging sites including twitter. Opinion mining through analyzing public sentiments of such micro-blogs is a common method for detection of public responses. This paper focuses on classifying the public opinions expressed related to COVID-19 vaccination at sub topic level. The procedure tries to find out different keywords regarding positive, negative and neutral sentences. From those keywords, different related query set was constructed using Rocchio query expansion algorithm for positive, negative and neutral sentiments. Later Extended query set is used to form subtopic using LDA algorithm to identify the nature of the tweets. The proposed LDA model came across with 0.56 coherence score with twenty subtopics, which is fair enough to classify the tweets in different classes. This trained model is finally used to classify the tweets in real time with Apache Kafka framework regarding different subtopic based on positive, negative or neutral sentiment.

2.
Innovation in Small-Farm Agriculture: Improving Livelihoods and Sustainability ; : 53-62, 2022.
Article in English | Scopus | ID: covidwho-2154181

ABSTRACT

The vulnerability of the highly contagious coronavirus pandemic has bushwhacked the entire world and crippled the global development to a state of tremendous medical emergency. All the vital sectors of society such as the agriculture, industry, trade, and economics, education have perceived serious blows. The medical research for suitable medications is underway;however, patient history reveals that a highly immune body can bear the infection without any morbidity or mortality. This phenomenon brings forward the necessity of research and policy enactment for ensuring a nutrition-sensitive agricultural system. Soil serving as the medium of crop growth, also inculcates several researchable issues like carbon sequestration, balanced fertilization, bio-fortification, composting and rearing beneficial microbes, wastewater treatment, soil pollution remediation, and remote-sensing-based land capability studies. The post COVID-19 period soil research should integrate other agricultural disciplines to strive for the coveted sustainable goal of a hunger-free world where food and nutrition security persists for disease resilience. © 2022 selection and editorial matter, Amitava Rakshit, Somsubhra Chakraborty, Manoj Parihar, Vijay Singh Meena, P.K. Mishra, H.B. Singh;individual chapters, the contributors.

3.
4th International Conference on Computational Intelligence, Communications and Business Analytics, CICBA 2022 ; 1579 CCIS:298-310, 2022.
Article in English | Scopus | ID: covidwho-1971565

ABSTRACT

Health monitoring by government in rural and Urban areas become very much challenging task as they require huge amount of technicians, doctors and funds to complete. In the time of COVID-19 pandemic, it is difficult to allow doctors to visit rural areas for monitoring the health of public, rather than allocate their duties in COVID-19 hospitals to save critical patients. But, it is also necessary to monitor health of public to vaccinate them priority wise in the scarcity of COVID-19 vaccines. In this paper we have proposed a novel UAV (Unmanned Aerial Vehicle) assisted health monitoring system which can be operated in any remote location to get required data about the health condition of the people. After collecting the desired data from the user, system saves them in memory. In the control room, UAV uploads the collected data to the server for analysis. From the analysed data the system can decide whom need to be vaccinated immediately. UAV system will analyse the data with respect to different parameters like age, co-morbidity, blood pressure and other attributes. From this analysed data using machine learning algorithm, system also predicts how many days might be taken to complete the whole vaccination process. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

4.
2022 International Conference on Interdisciplinary Research in Technology and Management, IRTM 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1932119

ABSTRACT

With time, Science has proved to be the Best Solution for solving problems and making our work easier and effective. In the last year and a half, COVID-19 has completely transformed our lives. Technology has become more important and necessary than ever in order for us to lead a quality life and help us adjust to the new normal. If one thing that COVID-19 has shown us profoundly, then it is how machines and technology can perform certain tasks efficiently, sometimes better than humans. Be it delivering food and medicine or predicting the number of cases or telling us the probability of spread of the virus, technology has proven to be very efficient in these testing times. Especially with a virus-like COVID-19 which is highly contagious and spreads through human contact, humans were highly dependent on technology even for the simplest of tasks. Through this paper, we review and research how exactly important technological domains Robotics, Data Science, Data Analytics, Computer Vision, VR, and others have played a major role or can play a major role in the management of and study of COVID-19. We have done a thorough study on the various technologies used to combat COVID 19. © 2022 IEEE.

5.
Bioprospecting of Microbial Diversity: Challenges and Applications in Biochemical Industry, Agriculture and Environment Protection ; : 455-469, 2022.
Article in English | Scopus | ID: covidwho-1872879

ABSTRACT

The scientific community is still in search of compounds that can be most effective to fight against COVID-19. A thorough evaluation of natural therapeutic compounds in relation to combat COVID-19 disease is the call of the hour. Out of many resources, seaweeds, available in the marine environment, offer immense potential, containing various therapeutic molecules and possess antimicrobial, anti-inflammatory, and antioxidant properties. Seaweeds contain various polysaccharides including sulfated galactan, sulfated rhamnans or mannans, carrageenans, and agars, etc. These compounds are known to inhibit the growth, transformation, and settlement of many viruses. Various seaweed species are sources for steroids, flavonoids, glycosides, alkaloids, and other related bioactive compounds with great medicinal values. Seaweeds and their products can be used to aid in the treatment of many diseases without any side effects. This review summarizes the medicinal use of seaweeds with special reference to the COVID-19 situation and human health. © 2022 Elsevier Inc.

6.
Biomedical and Pharmacology Journal ; 15(1):321-325, 2022.
Article in English | EMBASE | ID: covidwho-1822619

ABSTRACT

Corona Virus Disease -2019 (COVID-19) has jeopardised human life globally for last more than one year due to its high infectivity and tendency to develop sudden deterioration of cases by complicated pathophysiology. Some cost effective markers are necessary to predict severity so that timely appropriate management can be given. Neutrophil to lymphocyte ratio (NLR) in blood is such a common parameter that has been previously used to predict severity in various conditions like cardiovascular diseases and sepsis. Our objective was to estimate total White blood cell count (TC) and NLR in hospitalised COVID-19 patients and to find out their role to predict severity. This observational cross sectional study was done on hospitalized COVID-19 adult patients where patients were categorized into moderate and severe cases as per guideline of Govt. of India. TC and Differential count were estimated by automated cell counter and NLR was compared in these two groups by unpaired t test to find out their significance. Out of total 175 cases, 49(28%) were categorized as severe while rest 126 (72%) patients were in moderate category of disease. The mean ± standard deviations of TC (X103/μl) and NLR for moderate disease were 8.85±4.60 and 5.57±6.80 respectively while those for severe disease were 12.78±6.54 and 12.99±12.21 respectively. Both the parameters have statistically significant difference between two groups (p <0.001). TC and NLR were significantly higher in severe cases compared to moderate cases and hence they can be utilised to triage COVID-19 cases at an early stage.

7.
2021 IEEE International Conference on Big Data, Big Data 2021 ; : 4411-4420, 2021.
Article in English | Scopus | ID: covidwho-1730859

ABSTRACT

A key takeaway from the COVID-19 crisis is the need for scalable methods and systems for ingestion of big data related to the disease, such as models of the virus, health surveys, and social data, and the ability to integrate and analyze the ingested data rapidly. One specific example is the use of the Internet of Things and wearables (i.e., the Oura ring) to collect large-scale individualized data (e.g., temperature and heart rate) continuously and to create personalized baselines for detection of disease symptoms. Individualized data, when collected, has great potential to be linked with other datasets making it possible to combine individual and societal scale models for further understanding the disease. However, the volume and variability of such data require novel big data approaches to be developed as infrastructure for scalable use. This paper presents the data pipeline and big data infrastructure for the TemPredict project, which, to the best of our knowledge, is the largest public effort to gather continuous physiological data for time-series analysis. This effort unifies data ingestion with the development of a novel end-to-end cyberinfrastructure to enable the curation, cleaning, alignment, sketching, and passing of the data, in a secure manner, by the researchers making use of the ingested data for their COVID-19 detection algorithm development efforts. We present the challenges, the closed-loop data pipelines, and the secure infrastructure to support the development of time-sensitive algorithms for alerting individuals based on physiological predictors illness, enabling early intervention. © 2021 IEEE.

9.
9th International Conference on Culture and Computing, C and C 2021, Held as Part of the 23rd HCI International Conference, HCII 2021 ; 12794 LNCS:357-373, 2021.
Article in English | Scopus | ID: covidwho-1359831

ABSTRACT

The COVID-19 pandemic has greatly accelerated the digitization of services. As physical spaces become harder to access, there is a growing shift towards the use of virtual spaces for remote work, education and entertainment. In 2020, brick-and-mortar spaces like museums, art exhibits and galleries were especially affected by a lack of visitors. Shifting to a virtual medium would allow these entities to reach out and retain visitors more effectively. However, the use of virtual spaces to support these kinds of services is still quite under-explored. Presence, engagement and a real connection are difficult to establish through virtual exhibits. To explore these challenges, we partnered with the Liberation War Museum in Bangladesh and created a web-based 3D virtual museum to represent three of their historical galleries. Each virtual gallery has a different presentation modality - “self-guided”, “avatar-guided” and “game-based”. We sought to explain which of these artifact presentation modes led to the best performance in learnability, usability and engagement by conducting a user study. Our findings and user feedback are presented in this paper. We hope that these findings will be useful for designing virtual experiences that can allow users to learn and engage with virtual artifacts as effectively as they would with real-world ones. © 2021, Springer Nature Switzerland AG.

10.
Journal of the Indian Medical Association ; 119(4):50-54, 2021.
Article in English | EMBASE | ID: covidwho-1357945

ABSTRACT

The COVID-19 pandemic which started in late 2019 is still continuing unabated, rather with resurgence of cases in certain areas globally. Even with the emergency use authorization of several vaccines and extensive vaccination programs, we are yet to bring the pandemic to its knees. The present scenario has more than ever highlighted the importance of face masks in controlling the infection and transmission of the SARS CoV2 virus. In this review article, we discuss the evidence available to date to support the use of masks as a protective barrier to limitvirus entry. We also discuss how masks indirectly help stimulate protective immune responses and provide a comparative glimpse on the characteristics of various masks.

11.
44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021 ; : 2303-2307, 2021.
Article in English | Scopus | ID: covidwho-1350050

ABSTRACT

We propose VADEC, a multi-task framework that exploits the correlation between the categorical and dimensional models of emotion representation for better subjectivity analysis. Focusing primarily on the effective detection of emotions from tweets, we jointly train multi-label emotion classification and multi-dimensional emotion regression, thereby utilizing the inter-relatedness between the tasks. Co-training especially helps in improving the performance of the classification task as we outperform the strongest baselines with 3.4%, 11%, and 3.9% gains in Jaccard Accuracy, Macro-F1, and Micro-F1 scores respectively on the AIT dataset [17]. We also achieve state-of-the-art results with 11.3% gains averaged over six different metrics on the SenWave dataset [27]. For the regression task, VADEC, when trained with SenWave, achieves 7.6% and 16.5% gains in Pearson Correlation scores over the current state-of-the-art on the EMOBANK dataset [5] for the Valence (V) and Dominance (D) affect dimensions respectively. We conclude our work with a case study on COVID-19 tweets posted by Indians that further helps in establishing the efficacy of our proposed solution. © 2021 ACM.

12.
Journal of Nuclear Medicine ; 62(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1312155

ABSTRACT

Objectives: COVID-19 pneumonia is documented to produce pulmonary thromboembolism. Despite achievingCOVID negative status, few patients continue to be symptomatic, especially with respiratory distress. This has beennoted particularly in those patients who had severe pulmonary involvement requiring high flow oxygenadministration at the time of admission. It often becomes challenging to correlate the clinical findings, D-dimervalues and ultrasonographic evaluation to rule out deep vein thrombosis related acute pulmonary embolism in thesepatients. Computed tomography pulmonary angiography has many limitations in assessing pulmonary embolism inthese patients as there are several other lung findings which can be seen in this cohort. Lung perfusion scintigraphywith SPECT/CT is a valuable tool in evaluation of pulmonary embolism. Lung perfusion scintigraphy in thesepatients, as a part of evaluation of pulmonary thromboembolism after recovering from COVID-19 pneumonia shows a multitude of findings. The aim of this exhibit is to acquaint the imaging physicians with these findings and henceimprove the diagnostic accuracy of pulmonary embolism in these patients. Methods: Records of lung perfusion scintigraphy with SPECT/CT done in patients with post COVID-19 pneumoniawere reviewed. Those patients who had severe symptoms clinically were reviewed for the imaging findings. Typicalperfusion finding of a wedge shaped perfusion defect in the planar imaging along with no lung parenchymal changesshould be easy to identify as well as strongly suggests the diagnosis of pulmonary embolism. However, somepatients might show difficult to interpret images in the planar and SPECT/CT imaging which requires careful analysisof both the perfusion and corresponding CT images. Results: Different possible findings of lung perfusion scintigraphy with SPECT/CT are presented. These includesclassical wedge shaped segmental defects in the planar as well as SPECT/CT imaging with (matched defects) orwithout (mismatched defects) corresponding various lung parenchymal findings (diffuse ground glassing, subpleuralground glassing, subsegmental cystic areas, parenchymal consolidation, fibrosis, interlobular reticulation) in the CTimages. Apart from the classical segmental defects, a good number of subsegmental perfusion defects are alsonoted in many cases, which poses a challenge in diagnosing the pulmonary embolism in these patients. Conclusions: In the wake of COVID-19 pandemic, ventilation scintigraphy carries an inherent risk of COVID-19exposure to the imaging personnel. However, the lung perfusion scintigraphy with added SPECT/CT imaging servesto overcome the deficiency of ventilation imaging. This exhibit illustrates the common and uncommon perfusion andcomputed tomography lung findings in those patients who recovered from COVID-19 infection and continue to besymptomatic, requiring supportive therapy. The knowledge of these findings will help the readers in interpreting theclinical and laboratory findings and correlate it with the lung perfusion imaging in any patient who have recoveredfrom COVID-19 infection. (Figure Presented).

15.
Asian Journal of Pharmaceutical and Clinical Research ; 14(4):49-50, 2021.
Article in English | EMBASE | ID: covidwho-1200455

ABSTRACT

This article gives a contemplative viewpoint on the lenses in dentistry.

16.
International Journal of Current Research and Review ; 13(6 special Issue):S-86-S-96, 2021.
Article in English | Scopus | ID: covidwho-1196189

ABSTRACT

Current pandemic COVID-19 has severely affected the world, having a mortality rate ranging from 1 to 10% which is different for many countries. The time interval from symptoms to clinical recovery is 6–8 weeks and to death is 2 to 8 weeks. The increase in severity and fatality in COVID 19 is primarily due to the presence of comorbidities like cardiovascular disease, pre-existing lungs disease, hypertension, diabetes, obesity and cancer. As we already know that humans show the difference in drug responses because of their varied genetic make-up. Therefore, Population genomics gives an insight into the genetic characteristic of a population and it is critical in determining susceptibility, severity and natural protection against infectious diseases. Hence, this study was done to evaluate the population genetic makeup which is necessary to identify those who are at risk or protection from disease and develop genomics information, that would be useful in providing insight about COVID-19 disease severity or outcomes. Some of the proposed genetic gateways in COVID 19 pathogenesis are mentioned in this review that includes roles of ACE2 gene, HLA gene, Chromosome 3P21.31, ABO locus, genes responsible for cytokine storm, TLR-pathway, Family Mediterranean fever and G6PD deficiency. This review also emphasises the current treatment available in COVID-19 like hydroxychloroquine, azithromycin, RNA polymerase inhibitors, interleukin inhibitors, antivirals, ivermectin, doxycycline and their pharmacogenomics viewpoint. Such Pharmacogenomic studies are very helpful for physicians to choose and give accurate first-line therapy for COVID 19 patients. © IJCRR.

17.
Methods ; 2020.
Article in English | PubMed | ID: covidwho-850892

ABSTRACT

COVID-19 pandemic posed an unprecedented threat to global public health and economies. There is no effective treatment of the disease, hence, scaling up testing for rapid diagnosis of SARS-CoV-2 infected patients and quarantine them from healthy individuals is one the best strategies to curb the pandemic. Establishing globally accepted easy-to-access diagnostic tests is extremely important to understanding the epidemiology of the present pandemic. While nucleic acid based tests are considered to be more sensitive with respect to serological tests but present gold standard qRT-PCR-based assays possess limitations such as low sample throughput, requirement for sophisticated reagents and instrumentation. To overcome these shortcomings, recent efforts of incorporating LAMP-based isothermal detection, and minimizing the number of reagents required are on rise. CRISPR based novel techniques, when merge with isothermal and allied technologies, promises to provide sensitive and rapid detection of SARS-CoV-2 nucleic acids. Here, we discuss and present compilation of state-of-the-art detection techniques for COVID-19 using CRISPR technology which has tremendous potential to transform diagnostics and epidemiology.

18.
Curr Treat Options Neurol ; 22(10): 36, 2020.
Article in English | MEDLINE | ID: covidwho-739679

ABSTRACT

PURPOSE OF REVIEW: To investigate the association between the olfactory dysfunction and the more typical symptoms (fever, cough, dyspnoea) within the Sars-CoV-2 infection (COVID-19) in hospitalized and non-hospitalized patients. RECENT FINDINGS: PubMed, Scopus and Web of Science databases were reviewed from May 5, 2020, to June 1, 2020. Inclusion criteria included English, French, German, Spanish or Italian language studies containing original data related to COVID19, anosmia, fever, cough, and dyspnoea, in both hospital and non-hospital settings. Two investigators independently reviewed all manuscripts and performed quality assessment and quantitative meta-analysis using validated tools. A third author arbitrated full-text disagreements. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 11 of 135 studies fulfilled eligibility. Anosmia was estimated less prevalent than fever and cough (respectively rate difference = - 0.316, 95% CI: - 0.574 to - 0.058, Z = - 2.404, p < 0.016, k = 11 and rate difference = - 0.249, 95% CI: - 0.402 to - 0.096, Z = - 3.185, p < 0.001, k = 11); the analysis between anosmia and dyspnoea was not significant (rate difference = - 0.008, 95% CI: - 0.166 to 0.150, Z = - 0.099, p < 0.921, k = 8). The typical symptoms were significantly more frequent than anosmia in hospitalized more critical patients than in non-hospitalized ones (respectively [Q(1) = 50.638 p < 0.000, Q(1) = 52.520 p < 0.000, Q(1) = 100.734 p < 0.000). SUMMARY: Patient with new onset olfactory dysfunction should be investigated for COVID-19. Anosmia is more frequent in non-hospitalized COVID-19 patients than in hospitalized ones.

19.
J Laryngol Otol ; 134(7): 577-581, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-639738

ABSTRACT

BACKGROUND: Coronavirus disease 2019 personal protective equipment has been reported to affect communication in healthcare settings. This study sought to identify those challenges experimentally. METHOD: Bamford-Kowal-Bench speech discrimination in noise performance of healthcare workers was tested under simulated background noise conditions from a variety of hospital environments. Candidates were assessed for ability to interpret speech with and without personal protective equipment, with both normal speech and raised voice. RESULTS: There was a significant difference in speech discrimination scores between normal and personal protective equipment wearing subjects in operating theatre simulated background noise levels (70 dB). CONCLUSION: Wearing personal protective equipment can impact communication in healthcare environments. Efforts should be made to remind staff about this burden and to seek alternative communication paradigms, particularly in operating theatre environments.


Subject(s)
Communication , Coronavirus Infections/therapy , Personal Protective Equipment/adverse effects , Pneumonia, Viral/therapy , Adult , COVID-19 , Female , Humans , Intensive Care Units , Male , Middle Aged , Operating Rooms , Pandemics , Personnel, Hospital/psychology , Speech , Speech Intelligibility
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