A Genomic Signal Processing-Based Coronavirus Classification Model Using Deep Learning with Web-Based Console

Various strains of Coronavirus have led to numerous deaths worldwide with CoViD-19 being the most recent. Hence, the need for various research studies to determine and develop technologies that would reduce the spread of this virus as well as aid in the early diagnosis of the disease. The Severe Acute Respiratory Syndrome CoV (SARS-CoV), which emerged in 2003, Middle East Respiratory Syndrome CoV (MERS-CoV) in 2012 and Severe Acute Respiratory Syndrome CoV 2 (SARS-CoV-2) which is generally regarded as CoViD-19, in 2019 have very similar symptoms and genetics. Without proper diagnosis of these strains, they may be mistaken for one another. Therefore, there is a need to distinguish CoViD-19 from the other two Coronaviruses to enhance prompt and specific treatment. In this study, we developed a deep learning model with a web console for the classification of genomic sequences of the three Coronavirus strains using genomic signal processing. The DNA sequences harvested from the Virus Pathogen Database and Analysis Resource (ViPR) was used as dataset and these sequences were transformed to RGB images using Voss and Z-curve encodings. A convolutional neural network (CNN) model was consequently used for classification and incorporated in a web application platform developed with the Django framework. The results of the transformation of the images highlights the similarities of the three coronaviruses in terms of visual and genetic characteristics with the CNN model distinctly classifying SARS-CoV-2, SARS-CoV and MERS-CoV with a training and validation accuracies of 95.58% and 85% respectively which compares favourably with other results in the literature. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Literature review of data analytics utilization in Supply Chain Management

With an exponential increase in transition of various business to technical platforms there has been a huge data transfer between various platforms occurring every second. In 2020, there was a significant increase in the number of businesses shifting to online platforms during COVID, which not only increased the data traffic but also led both academic and IT industry to think of various techniques to improve data quality and data transformations in order to achieve optimal solutions from their captured data. The current review paper provides insight about how data analytics has been used by various phases within Supply chain management and also addresses the usage of data analytics in creation of various SCM models. The paper also addresses a number of research gaps while creating these SCM models, which leads to future research directions. © 2023 IEEE.

Varied presentations of complicated rhinosinusitis in COVID era: a rational approach to management

Aim: To study the various presentations and manifestations of complicated rhinosinusitis in COVID era- ranging from bacterial rhino sinusitis to invasive fungal rhino sinusitis. Methods: Design-A retrospective observational study was carried out from March 2020 to May 2021. Setting-Tertiary care hospital subjects—all COVID-positive patients who had paranasal sinus involvement. Methods-Patients were evaluated based on their symptomatology profile. Fungal stains and culture were carried out for all. They underwent Magnetic resonance Imaging and Computed Tomography scan on case-to-case basis, apart from routine nasal endoscopy. All were managed both medically and surgically depending upon their diagnosis. The natural course including outcomes, was studied, documented and analyzed. Results: Out of 496 patients presenting with sinonasal disease, 126 were COVID-positive, 16 patients had complicated rhino sinusitis, of which 4 patients had complicated rhinosinusitis with intraorbital, intracranial or combined complications. All patients were managed successfully with combined medical and surgical approach. Twelve patients had invasive mucormycosis with overall mortality rate of 37%. Conclusion: Complicated sinusitis was encountered in COVID-positive patients either when they were being actively treated for COVID-19 or as part of post-COVID sequalae. Though rhino-orbito-cerebral mucormycosis constituted the major disease burden in such patients but the possibility of bacterial rhino sinusitis with or without complications must also be kept in mind while evaluating such patients. We must remember every complicated rhinosinusitis in COVID-positive patient may not be mucor and manage appropriately. © 2023, The Author(s).

Smart Face Masks for COVID-19 Pandemic Management: A Concise Review of Emerging Architectures, Challenges and Future Research Directions

Smart sensing technology has been playing tremendous roles in digital healthcare management over time with great impacts. Lately, smart sensing has awoken the world by the advent of smart face masks (SFMs) in the global fight against the deadly Coronavirus (Covid-19) pandemic. In turn, a number of research studies on innovative SFM architectures and designs are emerging. However, there is currently no study that has systematically been conducted to identify and comparatively analyze the emerging architectures and designs of SFMs, their contributions, socio-technological implications, and current challenges. In this article, we investigate the emerging SFMs in response to Covid-19 pandemic and provide a concise review of their key features and characteristics, design, smart technologies, and architectures. We also highlight and discuss the socio-technological opportunities posed by the use of SFMs and finally present directions for future research. Our findings reveal four key features that can be used to evaluate SFMs to include reusability, self-power generation ability, energy awareness and aerosol filtration efficiency. We discover that SFM has potential for effective use in human tracking, contact tracing, disease detection and diagnosis or in monitoring asymptotic populations in future pandemics. Some SFMs have also been carefully designed to provide comfort and safety when used by patients with other respiratory diseases or comorbidities. However, some identified challenges include standards and quality control, ethical, security and privacy concerns. © 2001-2012 IEEE.

Genomic sequencing profile of SARS-CoV-2 in different parts of western Odisha, India

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.

Molecular Medical Diagnosis of COVID-19 and Omicron Variant

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.

Smart Face Masks for Covid-19 Pandemic Management: A Concise Review of Emerging Architectures, Challenges and Future Research Directions

Smart sensing technology has been playing tremendous roles in digital healthcare management over time with great impacts. Lately, smart sensing has awoken the world by the advent of Smart Face Masks (SFM) in the global fight against the deadly Coronavirus (Covid-19) pandemic. In turn, a number of research studies on innovative SFM architectures and designs are emerging. However, there is currently no study that has systematically been conducted to identify and comparatively analyze the emerging architectures and designs of SFMs, their contributions, socio-technological implications, and current challenges. In this paper, we investigate the emerging SFMs in response to Covid-19 pandemic and provide a concise review of their key features and characteristics, design, smart technologies, and architectures. We also highlight and discuss the socio-technological opportunities posed by the use of SFMs and finally present directions for future research. Our findings reveal four key features that can be used to evaluate SFMs to include reusability, self-power generation ability, energy awareness and aerosol filtration efficiency. We discover that SFM has potential for effective use in human tracking, contact tracing, disease detection and diagnosis or in monitoring asymptotic populations in future pandemics. Some SFMs have also been carefully designed to provide comfort and safety when used by patients with other respiratory diseases or comorbidities. However, some identified challenges include standards and quality control, ethical, security and privacy concerns. IEEE

MOODY: A Natural Language Processing-Based Chatbot for Mental Health Care

A chatbot is a software that establishes a human–machine interaction by using natural language processing (NLP) and natural language understanding (NLU). One of the essential tasks in machine learning and artificial intelligence is the mechanism through which conversation between a bot and a human is built and modelled. On the other hand, mental health issues have emerged up as one of the most rising diseases affecting millions around the world and are still one of the most untreated ones. People suffering from mental health disorders and issues have to live with it every single day, and the cases rose prominently during the COVID-19 pandemic. In this paper, a machine learning and natural language processing-based chatbot has been implemented to hold conversations with the purpose of mental healthcare assistance. It has been named MOODY;an intelligent conversational agent built with Dialogflow integration on NLP, NLU and its sentiment analysis feature. Dialogflow's architecture has been taken from the end-to-end neural network machine translation domain. There are plenty of variations and features that have been introduced resulting in remarkably enhancing the conversational capabilities of chatbots. MOODY's dependency, quick response generation and privacy provide a unique opportunity to assist those in need of adequate information and resources at one place. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The Ubiquitous Role of Mobile Technology Application in the Australian Open

Australia is one of the largest global sport tourist destinations. This industry employs a significant number of Australia’s total employment with contributions to the national economy. There is no shortage of exciting sporting events in Australia. Sporting activities in Australia are as much about having a good time and getting some fresh air as they are about fierce competition and amazing athleticism. It is no surprise that Australia hosts world-renowned tournaments like the Australian Open, attracting sports fans from all over the world to enjoy the adrenaline-pumping atmosphere and world-class competitors. Considering the increasing rate of emerging technologies, tour operators can use them to remain competitive in the market. Adopting the content analysis method, this study explores how the technology applications are impacting events in Australia. The study identified that the use of sharing of content via social media, use of sharing platforms like Airbnb and Uber, use of payment platforms like PayPal and Apple Pay, use of apps to provide visitor information on nearby offerings and the use of virtual reality are providing virtual tours of hotels and hotel rooms are increasing the attractiveness of this popular sports event. Though currently, the country is struggling to overcome the challenges of COVID-19 to regain the losses of revenue in the last year, it is expected that this sport event will demonstrate resilience and continue to succeed in the coming years using technology applications. Further research can be conducted to measure the impact of technology application in other sports events in Australia. © 2022 selection and editorial matter, Azizul Hassan;individual chapters, the contributors.

The utility of telemedicine for postoperative follow-up care in head and neck cancer patients during the COVID-19 pandemic

Introduction: Follow-up care and monitoring of survivorship are key aspects of head and neck cancer management. The unprecedented COVID-19 pandemic has posed an unforeseen challenge before head and neck surgeons and has created an urgent need for deploying processes for triaging patients. This study evaluates the effectiveness of a 3-tiered protocol incorporating principles of 'mhealth' proposed by WHO and telemedicine to monitor recurrence, maintain compliance, and address pressing issues in follow-up head and neck cancer patients. Materials and Methods: One hundred and one head and neck cancer patients who have undergone surgery and/or completed chemoradiation between the years 2015 and 2020 were selected. Details of patients who were on regular follow-up until March 2020 were obtained. A 3-tier screening protocol including a telephonic questionnaire, video consultation, and visit to primary care center was utilized to triage patients. Results: Fifty-seven percent of the patients did not require any intervention and were managed through video consultation with specialists. 38% of the patients needed a visit to a nearby health care worker or primary physician along with rehabilitation services. Only 5% of them needed a visit to a tertiary healthcare center for specialist care. The overall dropout from follow-up in this study was 19.8%. There was no significant difference of scores noted between oral cavity and nonoral cavity cancer groups (z = 1.17, P = 0.24, Mann-Whitney Test). Conclusion: The proposed 3-tier screening protocol using telemedicine is a feasible, cost-effective, and time-efficient tool to overcome the negative impact of COVID-19 on follow-up care. © 2022 Journal of Head and Neck Physicians and Surgeons Published by Wolters Kluwer-Medknow.

Fake News Detection of South African COVID-19 Related Tweets using Machine Learning

Social Media has grown in popularity in recent years comprising of billions of users who in turn exchange and communicate content at a volume and rate impractical to examine manually. Fake News are now being used on these platforms to manipulate and affect societies across the world as was the case in the 2016 United States of America (USA) elections and of recent during the 2019 coronavirus disease (COVID-19) pandemic. South Africa is not immune to the spread of Fake News, particularly, through Social Media platforms such as Twitter, Facebook and TikTok. It is, therefore, important to detect the presence of Fake News computationally in order assist the mitigation of its spread and prevent perceivable negative effects. This study addresses the issue by developing a Machine Learning (ML) model to analyze large amounts of data associated with Social Media. Curated annotated datasets from CONSTRAINT AAAI 2021;COVID-19 Rumour, FNIR and Zenodo's COVID-19 datasets;Google and Polifact Fact Checked websites;were utilized to develop the ML model. Specifically, the model was trained on 36254 data points and applied on a South African related COVID-19 Twitter dataset collected for cursory analysis. In total, 27 ML models were experimented with and the collected South African COVID-19 related Twitter dataset comprised of 976087 tweets from 8 November 2020 until 19 July 2021. The results detected 329107 tweets as being 'Fake' based on the LightGBM Classifier which was chosen as the most feasible model in terms of speed and a balanced accuracy score of 0.82. The proposed model is unique as it is trained on a larger combined dataset and supplements existing efforts to combat misinformation, disinformation and malinformation spread on Twitter. © 2022 IEEE.

TRANSFORMATION OF INDIAN ECONOMY THROUGH ATAMANIRBHAR BHARAT

The whole of the worlds' economies is undergoing a great change. The nations are worried about the ease of doing business and are aptly to compete with the changing climate and weather conditions and environment flexibility and situations. There is a great pollution fear all around which we see every year in the winter season, and we see there is smoke and fog everywhere. The visibility comes to one feet distance or so at the roads, on the railway track and even at airways. The roadways, railways and airways route plans are being changed and suspended due to the smog and the smoky atmosphere all around in the sky and on land. We are hardly able to breathe fresh air as there is no fresh air all around. There is highly polluted air which we breathe under compulsion. Under such conditions we keep on finding the ease of doing business for the betterment of the economy and the people residing therein. It seems pertinent and viable to shift the investment criteria the agriculture sector and giving topmost priorities to MSMEs sector so that the common man may be benefited with bread and butter at their doorstep and at the native place. In a way we need to strengthen and launch the rural development schemes which seems a prelude to the Ghandhi vision and dream making it true and to strengthen the three-tier system of the panchayat raj which was first implemented on 2nd October 1959 in Nagore by the then prime minister Jawaharlal Nehru. With the advent of strong panchayat raj system based on Balwant G Mehta committee's report of 24 November 1957, the vicious circle of poverty will break and split, and the income, output and employment will grow in the economy simultaneously. This will present a unique model of growth with respect to the developing rural sectors of the economy with special and specific emphasis laying on the agriculture sector making true the model of Prof..Ragnar Nurkse," disguised unemployment as a saving potential in the agriculture sector of the rural economy." This will also strengthen the idea of Gram Swaraj as laid down by Gandhi ji making panchayat raj strong and ensuring Gram swaraj. Undoubtedly, this will enhance, mobilize, and ensure the ease of living as well as ease of doing with ease of earning. Like this manner we can make Bapu's dream to come true

ADVANTAGES AND DISDVANTAGES OF ONLINE TEACHING LEARNING IN INDIA DURING COVID-19

The purpose of this paper is to find out the advantages and disadvantages associated with online teaching learning during COVID-19. This research is based on systematic literature review of past studies, articles published in newspapers and websites. The study also provides suggestion how to make the online teaching learning better and how to overcome with the challenges of online teaching learning in future. The study suggest that government and educational institutions should provide better internet services to students and appropriate environment to teachers such as Laptop and Pen-tabs to faculty members of educational institute. Insights from this study provides various recommendations and suggestions to government and educational institutes for betterment of online teaching-learning environment in educational institutes. This paper highlights the advantages and disadvantages associated with online teaching-learning.

Economic and financial challenges after COVID-19

This paper highlights the economic and financial challenges after COVID-19. For this study, a systematic literature review was conducted on the COVID-19. For this study, several databases such as Google scholar, Scopus and Science direct was used. 150 research papers were downloaded from the research databases. After screening, 24 studies were used for this systematic literature review.

Impact of Covid 19 on Work Integrated Learning for Computing Education

Work Integrated Learning (WIL) for university graduates allows students to gain employability skills through relevant employment experience and make them work-ready. However, the disruptions caused by COVID-19 pandemic has changed how universities deliver WIL programs for students in higher education. Students faced multiple challenges to be workplace ready during COVID-19. Enforced social distancing has impacted the delivery of WIL education in many ways, which requires the attention of all the stakeholders so that students are not missing out on the opportunities provided by WIL education and hence their career in the future. To deliver WIL in computing is different to delivering WIL in other disciplines. Consequently, there is a need to summarise the current practices adopted by higher education in delivering WIL education for computing students and how COVID19 has impacted it. This paper aims to briefly review WIL practices in computing education due to COVID-19, its impact on supervisors/academics, students, and student-industry relationships, and the challenges for developing student's professional capabilities to make them employable in computing field.

Food safety knowledge and changes in practices and concerns of Indian families during the COVID-19 pandemic

Purpose: Unsafe food can lead to various foodborne diseases and even death, especially among children. This paper aims to assess food safety knowledge and changes in practices and concerns among adults ≥ 18 years during the coronavirus disease 2019 (COVID-19) pandemic. Design/methodology/approach: A cross-sectional, web-based survey was conducted among 325 adults living in Northern India. Demographic data and information regarding their knowledge, practices and concerns about various food safety issues were collected to see if there were any changes due to the COVID-19 pandemic. Findings: The results showed that the participants had slightly higher than average knowledge and good food safety practices with mean scores of 9.75 ± 2.23 and 24.87 ± 2.28, respectively. Contracting COVID-19 from food and food packaging materials was of high concern for more than 70% of the participants. Majority (> 80%) of them reported an increase in the frequency of handwashing. About 16% of the participants used chemical disinfectants for washing fruits and vegetables. An increase (57.5%) in the frequency of food label reading was also noted during the pandemic. Freshness and the general quality of food items (49.5%), safety of food (30.8%) and cost (18.2%) were the top drivers that influenced the purchase decision. Originality/value: This study highlighted the need to send out clear messages on safe food handling practices and keeping the tempo up for sustaining good hygienic practices. This will help in reducing the risk of foodborne diseases. © 2022, Emerald Publishing Limited.

A Study on How Indian Brands Connected with Customers During Coronavirus Lockdown in India

Every year, new companies and brands come into existence in India;and in this race standing a chance to be the best is endless. Hence to position itself to be the best, companies always aim at increasing their brand reach through various platforms. The most proven way to improvise the brand reach had always been through advertising. It had been evident that the most companies' highly preferred mediums to advertise their products are television and the internet. In the past more than a decade the research reports have shown that the maximum number of viewership medium had been television and digital media. Keeping the desired results in consideration, most brands choose to spend millions on advertisements over these mediums. Even when the whole country came to a standstill due to the COVID pandemic, brands continued to advertise and promote their products. Some brands even changed their approach after considering COVID-19 and the lockdown, while others continued with their old advertisement sources and mediums. This study has analysed how brands in India have promoted their products on television and the social media platform such as Instagram, facebook, and so on. The brands that have been selected in this study are Indian and international brands that have majority of their buyers in India. © The Electrochemical Society

CLINICAL PROFILE AND OUTCOME OF COVID-19 PATIENTS: A RETROSPECTIVE OBSERVATIONAL STUDY FROM TERTIARY CARE CENTER IN NORTH INDIA

Objective: An acute respiratory infection of unknown origin was first detected in Wuhan, China, and reported to the WHO on December 31, 2019, and within a month, this outbreak was declared as a Public Health Emergency of International Concern. This study was carried out with an objective to assess the spectrum of clinical presentations and host-related factors in outcome of COVID-19 during the first wave. Methods: This study was a retrospective observational study on 427 laboratory conformed COVID-19 cases at tertiary care center in North India during 6 months of the first wave. The demographic data, clinical profiles, comorbid conditions, treatment given, duration of hospital stay, and outcome were collected on a predesigned pro forma by the investigator himself and entered a Microsoft Excel sheet and analyzed using SPSS version 17.0 software. Results: Mean age of the study participants was 48.70 years. Majority (34.89%) belonged to above 60 years. About 74% were male. Mean duration of symptoms before detection was 1.30 and mean duration of hospital stay was 11.98 days. Majority had fever (73.54%) followed by myalgia (49.88%). About 85.48% had more than 3 symptoms and 69.32 had symptoms for less than 3 days before getting detected. About 40.52% had comorbidities and only 14.05% had history of contact with COVID confirmed case. Only 8.2% were asymptomatic while 23.19% had severe symptoms. Majority 91.57% were admitted to hospital while only 8.43% were put under home isolation. About 74% were positive on rapid antigen test (RAT) while 29.51% needed RT PCR test to turn positive. About 28.1% had bilateral pneumonia on chest X-ray findings. About 6.3% of were pregnant ladies. The overall mortality rate of our hospital during that 6-month period was 4.69%. Out of all parameters, only age category was statistically significant associated with outcome on discharge while other variables such as comorbidity, symptom duration, and severity of disease during admission did not show any statistically significant association. Conclusion: This single-center study provided the spectrum of clinical presentations and host-related factors in outcome of COVID-19 during the first wave which may help in decrease the burden of disease, minimize social disruption, and reduce the economic impact associated with a pandemic. Early detection, admission, and treatment of individuals with comorbidities and elderly would increase the recovery from the disease, thereby reduce mortality.

Terpenoids from Centella asiatica, a novel inhibitor against RNA-dependent-RNA polymerase activity of NSP12 of the SARS CoV-2 (COVID-19)

Covid-19, the first case of which was reported in Wuhan (China) in December 2019 was found to be a strain of coronaviruses like SARS and MERS reported earlier. These viruses are positive strain RNA viruses composed of both structural as well as non-structural proteins. The enzyme RdRp (RNA dependent RNA polymerase) stands responsible for catalyzing the replication of this virus within the host cell. A disruption in the core catalytic subunit composed of nsp12, nsp7, and nsp8 may inhibit the replication of the same. Different drugs targeting different sites on the virus have been developed. In this context, some of the natural products of the plant Centella asiatica was lead for further drug development against the target proteins of RdRp protein (PDB ID: 6NUR) through molecular docking. These compounds are 2,3-dihydroxyurs-12-en-28-oic acid, corosolic acid and pomolic acid which are triterpenoids and have highest binding affinity against RdRp protein thereby arresting the viral replication. Several previous studies showed triterpenoids as pertinent mediators implicated in the in vitro immune response.