Diabetes and Fungal Infection- A Didactic Relationship

Oral fungal infections are frequently encountered in clinical practice, and with the advent of the Coronavirus disease 2019 (COVID-19) pandemic, their incidence has quite increased. Increased emergence of oral candidal and non candidal infections is evident in patients with uncontrolled diabetes, patients on steroids or antibiotic therapies, and immunocompromised and immunosuppressed individuals. Also, habits of smoking and alcohol consumption, intake of carbohydrate-rich food, and salivary dysfunction have many times influenced the colonisation of fungal infections in the oral cavity. Aspergillosis once considered exotic is now more prevalent than before and presents itself in two forms: non invasive or invasive form, which has led to the rapid dissemination of the disease. Hence, a timely diagnosis of such lesions is important to prevent their invasion into other parts of the body. This article discusses a rare case report of Aspergillosis occurring in the oral cavity at the site of the extraction socket in a 50-year-old woman, who is a known diabetic without any history of COVID-19 infection. Aspergillosis unlike other fungal infections of the oral cavity has been reported more in immunocompetent individuals. Here, we report a unique case limited to the oral cavity in an immunocompromised patient.

Adoption of food delivery apps during a crisis: exploring an extended technology adoption model

Purpose: This study aims to provide insight into consumer behavior regarding the use of food delivery apps when making purchases. To investigate the primary elements affecting users' intentions to use meal delivery applications, this study suggests an extension to the technology acceptance model through some contextual variable such as "various food choices (VFC),” "trust (TRR),” "perception of COVID-19-related risks (PCR)” and "convenience (CONV)” during the pandemic. Design/methodology/approach: A cross-sectional data of 407 was collected in the Indian context. This research adopts the covariance-based structural modeling approach to test the hypotheses along with hierarchical regression to predict the efficiency of constructs. Findings: Considering the outcomes, "perceived usefulness (PU)” was positively influenced by "perceived ease of use (PEOU),” "VFC” and "CONV.” In addition, the attitude (ATT) was positively impacted by "PU,” "TRR” and "PEOU.” Nevertheless, "PCR” negatively influenced ATT. In additional, this research illustrates the positive impact of ATT and PU on behavioral intention to use. Originality/value: By confirming the technology acceptance model's capacity for explanation in relation to food delivery apps, this study adds to the body of knowledge. The primary focus of this study is on determining the direct impact of the identified determinants on the adoption of food delivery applications within the context of a pandemic situation in developing countries. © 2023, Emerald Publishing Limited.

Application of AI techniques for Face Mask Detection

Covid-19 is a completely new problem, and we have seen it move to a brand new level. After the 3rd wave of Covid-19 in India and predictions of another wave this year it is a major concern and still many people are not following basic precautionary measures like wearing a mask in public locations this can be solved by our face mask detection program we want to be short a good way to respond to new facts, which they are all around us. Growing a secure environment can be paramount the human to make lifestyles as smooth as ever. Alternatives have to be taken to protect all who go back and to maintain them our loved ones who have no troubles. New era packages are being made each day to satisfy regulations and regulations but, the face mask becomes a new well known used for regular existence, but, to create a more secure surroundings that contributes to public protection, a want to be diagnosed at some stage in date and motion towards people who do not put on masks in public locations or offices. Many sections of the general public appear to simply accept Covid adherence protection gear. A face masks detector is among the most crucial equipment. This software allows one to find out who does not have the desired face masks. Those applications with them current tracking systems and neural network algorithm to see if an individual has put on a mask or not. About this, we'll do discussion in short the synthetic intelligence and its small additives specifically device gaining knowledge of and in-intensity analysing, in-intensity reading frameworks followed with the aid of the usage of simplicity implementation of face masks detection machine. © 2022 IEEE.

Omicron Case Prediction using Machine Learning

It's been over two years that the world has been dealing with the novel Coronavirus Disease 2019 (COVID-19). It has rocked the world in the face of another major outbreak. Countries have undergone various lockdowns curfews in their own ways, which certainly has impacted our daily lives. COVID-19 has undergone various mutations till now. It is responsible for the spikes in COVID-19 cases across the world. The latest variant 'Omicron'., labeled as B.1.1.529, has been marked as a Variant of Concern by the World Health Organization (WHO). It has been proven to be the most infectious, but less deadly as of now. This paper attempts to propose an analysis and prediction of Omicron daily cases in India using SARIMA Exponential Smoothing Machine Learning models. Both of these machine learning models are based on the time series forecasting concept and rely on previous data to predict future outcomes. © 2022 IEEE.

Personality Effects on Financial Responses Caused by the Perceived Financial Threat during the COVID-19 Pandemic

The link between the uncertainty of stock markets and the emotional stress of the COVID-19 pandemic has been studied by numerous researchers. For example, a few studies have provided mixed evidence about the behavioral responses of individual retail investors and their financial risk tolerance and stock trading. To the best of the authors' knowledge, however, this study is the first to analyze the influence of the psychological aspects of the pandemic on these investors' financial responses. A total of 396 investors from India participated in the study, and a mediational analysis was performed using AMOS to explore whether the perceived financial threat (PFT) was a linkage between personality traits (PTs), trading preferences, and risk tolerance during the pandemic. The results show that the PFT was a mediator between PTs and stock trading and between PTs and risk tolerance. Additionally, investors with various PTs had varying intensities of the PFT, which eventually impacted financial behavior in the form of trading and risk aversion. © 2022 Journal of Structured Finance. All right reserved.

Coalescing skills of gig players and fervor of entrepreneurial leaders to provide resilience strategies during global economic crises

The COVID-19 pandemic has caused diverse sorts of disruption across the globe. The pandemic has drastically impacted the economies of almost every country of the world. The international economic scenario is full of despair as the entrepreneurs and business leaders find it hard to come to terms with the extent of damage caused by the pandemic. In view of largely prevalent gloom and despair, it is imperative that certain resilience strategies are worked out so that global economic crisis can be stemmed from further escalation. The gig economy has been viewed as a powerful resilience mechanism to tide over the economic crisis caused the world over by COVID-19. Entrepreneurial leadership can also make significant difference in providing a paddle-push to the pandemic-struck world by reactivating the engines of economic growth. The nature of this chapter is qualitative, and it seeks to theoretically work out certain strategies that can help various economies of the world to stand up and be resilient in the face of complex challenges that the pandemic has thrown before us. © 2021, IGI Global.

Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses

Purpose: The purpose of this paper is to see how critical and vital artificial intelligence (AI) and big data are in today’s world. Besides this, this paper also seeks to explore qualitative and theoretical perspectives to underscore the importance of AI and big data applications in multi-sectoral scenarios of businesses across the world. Moreover, this paper also aims at working out the scope of ontological communicative perspectives based on AI alongside emphasizing their relevance in business organizations that need to survive and sustain with a view to achieve their strategic goals. Design/methodology/approach: This paper attempts to explore the qualitative perspectives to build a direction for strategic management via addressing the following research questions concerned with assessing the scope of ontological communicative perspectives in AI relevant to business organizations;exploring benefits of big data combined with AI in modern businesses;and underscoring the importance of AI and big data applications in multi-sectoral scenarios of businesses in today’s world. Employing bibliometric analysis along with NVivo software to do sentiment analysis, this paper attempts to develop an understanding of what happens when AI and big data are combined in businesses. Findings: AI and big data have tremendous bearing on modern businesses. Because big data comprises enormous information of diverse sorts, AI-assisted machines, tools and devices help modern businesses process it quickly, efficiently and meaningfully. Therefore, business leaders and entrepreneurs need to focus heavily on ontological and communicative perspectives to deal with diverse range of challenges and problems particularly in the context of recent crises caused by COVID-19 pandemic. Research limitations/implications: There is hardly any arena of human activity wherein AI and big data are not relevant. The implication of this paper is that of combining both well so that we may find answers to the difficult and challenging multi-sectoral scenarios concerning not just businesses but life at large. Moreover, automated tools based on AI such as natural language processing and speech to text also facilitate meaningful communication at various levels not just in business organizations but other fields of human activities as well. Social implications: This paper has layered social implications, as it conceptually works out as to how strategically we may combine AI and big data to benefit modern business scenarios dealing with service providers, manufacturers, entrepreneurs, business leaders, customers and consumers. All the stakeholders are socio-culturally and contextually rooted/situated, and that is how this study becomes socially relevant. Originality/value: This paper is an original piece of research and has been envisioned in view of the challenging business scenarios across the world today. This paper underscores the importance of strategically combining AI and big data, as they have enormous bearing on modern businesses. The insights arrived at in this paper have implications for business leaders and entrepreneurs across the globe who could focus more on ontological and communicative perspectives of AI combined with Big Data to deal with diverse range of challenges and problems that modern businesses have been facing particularly in recent times. © 2022, Emerald Publishing Limited.

The Emergence of Sustainability Adoption in the Healthcare Sector During COVID-19

The world is struggling to get rid of a coronavirus pandemic that has captured the whole world. It has not only changed the overall picture of the world but also the overall economy is in the toss. The whole economy was affected due to this pandemic. The various healthcare informatics have played an important role in the fight against COVID-19. There are various digital tools for pandemic preparedness and response such as screening of infection, quarantine and self-isolation, contact tracking, medical supplies, planning and tracking, clinical management, etc. Also, the APPS with the update, Civil Society’s with the COVID response, contact tracing, identity and COVID-19, immunity passport, location (GPS) data, migration ants, quarantine administration, telecommunication data, temperature scanning, and social media updates are the concern in the digitalization used for fighting COVID-19. Technological advancements have given a new direction to the healthcare industry. Sustainability in health care not only leads to economic but also social and environmental equality. The government has started thinking in that line so that all can be benefited from these technological advancements in the healthcare industry. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Revisiting the Inner Self in Times of Debilitating Distress: Gateways for Wellness Through Spiritual Tourism

The COVID-19 pandemic has had devastating effects on our bodies, minds and souls. Having suffered it for more than a year now we know how crucial it is to tackle the pandemic at physical, psychological and spiritual levels. We have well-established Standard Operating Procedures alongside vaccines to deal with it at physical level, but equally crucial are mental and spiritual problems caused by COVID-19 (Chopra, 2020). This paper seeks to explore certain gateways and possibilities of dealing with distress, despair, anxiety, angst, trauma and disruption caused by the COVID-19 pandemic in diverse arenas of human activities to ascertain how crucial a role spiritual tourism plays in coping with the challenges we face today. It will also take into account mystical, sufic, yogic, ayurvedic and other meditational practices that represent the richly diverse cultural and spiritual heritage of India. These practices have substantial bearing on the tourism industry by connecting tourists with their deeper, inner selves and thus providing much required spiritual solace. The inclusive and integrative aspect of spiritual and other meditational practices in India will also be underscored to demonstrate how these have been influencing and benefiting the tourism industry in India. Besides enriching the lives of tourists from different countries of the world by providing inner peace and harmony, the tourism industry also equips them with coping strategies to effectively negotiate despair and inner conflicts. © 2021 Dublin Institute of Technology. All rights reserved.

Detection of COVID-19 from CT scan images using deep neural networks

The coronavirus pandemic brought the world to a standstill of historic significance. Countries over the world have imposed lockdowns, quarantines and travel bans in an effort to stop the further spread of the disease. Healthcare systems worldwide are under extreme pressure due to the influx of a large amount of patients suffering from COVID-19. Moreover, there is a dearth of doctors, nurses, and support staff in hospitals of many countries. In such a predicament, it is imperative to leverage the advances made in computer vision and deep learning technologies to create a system that attempts to ease the burden on worldwide healthcare. In this research, ten state-of-the-art pre-trained convolutional neural networks were used to identify COVID-19 in chest Computed Tomography (CT) scan images. After extensive experimental testing and tuning, comprehensive comparative analysis was done and very promising results were obtained in this classification task. © 2021 IEEE

A panoramic perspective of travel and tourism in India during COVID-19

It has always been seen that the cuisine of a respective place has always been considered by a vacationer. Local food has always been considered as an important & a distinct element for a destination. The study focusses on different factors taken into consideration by a vacationer during the local cuisine experimentation. The literature also indicates the different factors like flavour, money value etc. which actually directs the consume of cuisine of the respective place. An impact of COVID has also been analysed to get an insight into the effect on an international perspective. At the same time, various policies have also been discussed with respect to various secondary resources. © 2021. Transnational Press London. All Rights Reserved.

In silico screening of phytochemicals as potential inhibitors of sars-cov-2 mpro and human ace-2

Background and Objective: An enzyme that inhibits the receptor could make it more difficult for coronavirus to reach cells. The key protease necessary for coronavirus proteolytic maturation is the recognized coronavirus 3-chymotrypsin-like protease 3CLpro, also known as Mpro. This Mpro is needed for immune control and the cleavage of the polyproteins pp1a and pp1ab, making it a promising target for anti-COVID-19 drugs. As a result, inhibiting the Mpro enzyme inhibits viral maturation. Bioactive constituents obtained from some selected indigenous plants of India, which have been reported to have antiviral potential, were subjected to virtual screening against ACE-2 and Mpro in the current study. Materials and Methods: Cresset's Flare 4.0 was used to establish the 3-D structure of all the compounds. Complete optimizations of these constructed structures were carried out. While performing the minimization, the spin state of the wave function was set to the singlet and standard SCF convergence was used for optimization, all other parameters were left at their default values. The Protein Data Bank (https://www.rcsb.org) was used to download the 3-D structures of Mpro from COVID-19 (PDB ID 6LU7) and ACE-2 receptor from Human (PDB ID 1R4L). Results: The findings show that these phytochemicals can bind to ACE-2 and Mpro more effectively as compared to reference compounds and act as inhibitors. Conclusion: The findings of virtual screening of these bioactive constituents revealed that most of them are more active than the reference compounds. Therefore, they could be used to produce antiviral drugs against Coronavirus in the future.

COVID-19 infection in a child following liver transplantation.

COVID-19 infection immediately after liver transplantation presents a unique and challenging situation. In this report, we present the case of an 11-year-old girl who underwent emergency living donor liver transplantation for acute liver failure. After an uneventful intra-operative course, the patient was transferred to the intensive care unit. On the second postoperative day, the patient developed unexplained severe hypoxia. A polymerase chain reaction test was positive for SARS-CoV-2 virus and a hypercoagulable state was indicated by laboratory investigations. Despite therapies such as mechanical ventilation and therapeutic anticoagulation, further clinical deterioration occurred. On the seventh postoperative day, the patient's pupils were fully dilated bilaterally and unreactive to light, and brain death was later confirmed. This report highlights unique challenges pertaining to oxygenation, coagulation and immunosuppression after liver transplantation in a child with COVID-19. Hypoxia of unknown origin in the postoperative period should prompt consideration of COVID-19 as a possible cause.

COVID-19 and tobacco cessation: lessons from India.

OBJECTIVES: The Government of India prohibited the sale of tobacco products during the COVID-19 lockdown to prevent the spread of the SARS-CoV-2 virus. This study assessed the tobacco cessation behaviour and its predictors among adult tobacco users during the initial COVID-19 lockdown period in India. METHODS: A cross-sectional study was conducted with 801 adult tobacco users (both smoking and smokeless tobacco) in two urban metropolitan cities of India over a 2-month period (July to August 2020). The study assessed complete tobacco cessation and quit attempts during the lockdown period. Logistic and negative binomial regression models were used to study the correlates of tobacco cessation and quit attempts, respectively. RESULTS: In total, 90 (11.3%) tobacco users reported that they had quit using tobacco after the COVID-19 lockdown period. Overall, a median of two quit attempts (interquartile range 0-6) was made by tobacco users. Participants with good knowledge on the harmful effects of tobacco use and COVID-19 were significantly more likely to quit tobacco use (odds ratio [OR] 2.2; 95% confidence interval [CI] 1.2-4.0) and reported more quit attempts (incidence risk ratio 5.7; 95% CI 2.8-11.8) compared to those with poor knowledge. Participants who had access to tobacco products were less likely to quit tobacco use compared to those who had no access (OR 0.3; 95% CI 0.2-0.5]. CONCLUSIONS: Access restrictions and correct knowledge on the harmful effects of tobacco use and COVID-19 can play an important role in creating a conducive environment for tobacco cessation among users.

Transfer Learning-Based Detection of Covid-19 Using Chest CT Scan Images

The global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has had historical impact on the world. The virus causes severe respiratory problems and with an R0 of 5.7, spreads at a rapid rate. At the time of writing, there were over 85 million cases and 1.8 million deaths caused by COVID-19. In the proposed methodology, Deep Convolutional Neural Networks (DCNNs) have been trained, with the help of transfer learning, to learn to identify whether a suspected patient is suffering from this disease using their chest CT scan image. Transfer learning technique enables the transfer of knowledge from pre-trained models which have been previously trained on extremely large datasets. Various DCNN models have been applied such as AlexNet, ResNet-18, ResNet-34, ResNet-50, VGG-16, and VGG-19. The DCNNs were evaluated on a set of 2,481 chest CT scan images. Various performance metrics (Accuracy, MCC, Kappa, F1 score, etc.) were calculated for all DCNN models to enable their comparative evaluation. After extensive testing, ResNet50 was found to give the best results in this binary classification task. The highest accuracy achieved was 97.37% and highest kappa was 0.947. Identification of presence of COVID-19 using this method would provide great benefit to society and mankind. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Severe acute respiratory syndrome coronavirus-2-associated perceived stress and anxiety among indian medical students: A cross-sectional study

Introduction: The spread of coronavirus disease (COVID-19) is a new public health concern that has shaken the whole world and possesses a challenge to the mental health of the public. This study aimed to investigate the impact of COVID-19 pandemic on the perceived stress, anxiety level, and mental health of medical students as well as to explore the knowledge of COVID-19 among Indian medical students. Methods: A web-based cross-sectional survey was conducted among the undergraduate medical interns and postgraduate medical residents using the online data collection form. The form consisted of five domains (sociodemographic details, knowledge assessment, perceived stress assessment, generalized anxiety disorder-7 assessment, and assessment of the perceived level of change in social habits and personal hygiene related to COVID-19 outbreak). The statistical analysis of the responses was carried out by the Mann-Whitney U-test and Kruskal-Wallis tests. Results: Two hundred participants filled the distributed survey, 61% (n = 122) were males. The mean knowledge score of 200 participants was 4.27 ± 1.45. The participant had a mean perceived stress score of 18.35 ± 6.28, and the females had a significantly higher perceived stress level than the male (P = 0.037). About 10% (n = 20) of the participants reported high perceived stress level (27-40), and moderate stress (score 14-26) was reported in 69% (n = 138) of the participants. However, only 21% (n = 42) of the participants reported low stress (0-13). While only moderate anxiety (score 10-14) was reported in 16% (n = 32) of the participant and 4% (n = 8) of the participants reported severe anxiety (score >14). Conclusion: There is an increased stress and anxiety in Indian medical students due to overburdened responsibilities and lack of adequate resources. © 2021 Medknow. All rights reserved.

Saliva as a Potential Diagnostic Tool for SARS-CoV-2

BACKGROUND COVID 19 has been labelled as a global pandemic by the World Health Organization (WHO). The sudden rise in death toll and devastation associated with it has put the entire infrastructure, economy and health sector to test. The only way for the prevention and control of this infectious disease is rapid and accurate screening of masses. Public Health Authorities mainly use antibody testing in hot spots using a mix of RT-PCR and antibody testing nasopharyngeal and orpharyngeal swabs. Considering the potential risk factors, constraints of time, cost and manpower, mass screening for COVID is not possible through nasopharyngeal and oropharyngeal swabs alone. Hence, to search an alternate method to diagnose for the initial screening of patients is the need of the hour globally. Saliva can also be used as one of the diagnostic modalities for coronavirus, helping in the rapid testing of individuals at home or at hospital. The article intends to explain the evidence regarding the reliability of saliva as a diagnostic specimen in COVID-19 patients and demonstrates the association and potential of detecting novel coronavirus in saliva of patients and how its implication in future can aid in diagnosis as a non - invasive diagnostic modality.