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Lung segmentation algorithms play a significant role in segmenting theinfected regions in the lungs. This work aims to develop a computationally efficient and robust deep learning model for lung segmentation using chest computed tomography (CT) images with DeepLabV3 + networks for two-class (background and lung field) and four-class (ground-glass opacities, background, consolidation, and lung field). In this work, we investigate the performance of the DeepLabV3 + network with five pretrained networks: Xception, ResNet-18, Inception-ResNet-v2, MobileNet-v2 and ResNet-50. A publicly available database for COVID-19 that contains 750 chest CT images and corresponding pixel-labeled images are used to develop the deep learning model. The segmentation performance has been assessed using five performance measures: Intersection of Union (IoU), Weighted IoU, Balance F1 score, pixel accu-racy, and global accuracy. The experimental results of this work confirm that the DeepLabV3 + network with ResNet-18 and a batch size of 8 have a higher performance for two-class segmentation. DeepLabV3 + network coupled with ResNet-50 and a batch size of 16 yielded better results for four-class segmentation compared to other pretrained networks. Besides, the ResNet with a fewer number of layers is highly adequate for developing a more robust lung segmentation network with lesser computational complexity compared to the conventional DeepLabV3 + network with Xception. This present work proposes a unified DeepLabV3 + network to delineate the two and four different regions automatically using CT images for CoVID-19 patients. Our developed automated segmented model can be further developed to be used as a clinical diagnosis system for CoVID-19 as well as assist clinicians in providing an accurate second opinion CoVID-19 diagnosis.
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Purpose: Capital structure is an important corporate financing decision, particularly for companies in emerging economies. This paper attempts to understand whether the pandemic had any significant impact on the capital structure of companies in emerging economies. India being a prominent emerging economy is an ideal candidate for the analysis. Design/methodology/approach: The study utilizes three leverage ratios in an extended market index, BSE500, for the period 2015–2021. The ratios considered are short-term leverage ratio (STLR), long-term leverage ratio (LTLR) and total leverage ratio (TLR). A dummy variable differentiates the pre-epidemic (2015–2019) and pandemic (2020–2021) period. Control variables are used to represent firm characteristics such as growth, tangibility, profit, size and liquidity. Dynamic panel data regression is employed to address endogeneity. Findings: The findings point out that Covid-19 has had a significant, negative effect on LTLR, while the impact on STLR and TLR was insignificant. The findings indicate that companies based in a culturally risk-averse environment, such as India, would reduce the long-term debt to avoid bankruptcy in times of uncertainty. Research limitations/implications: The study covers the impact of the pandemic on Indian companies. Hence, generalization of the findings to global context might not be valid. Practical implications: To maintain economic growth in the post-crisis period, Indian policymakers should ensure accessibility to low-cost capital. The findings provide impetus to deepen the insignificant corporate bond market in India for future economic revival. Originality/value: Developing countries are struggling to revive the economies postpandemic. This is particularly true for Asian economies which are heavily reliant on banks for survival. This research finds evidence to utilize bond market as a source of raising capital for economic revival. © 2022, Nisha Prakash, Aditya Maheshwari and Aparna Hawaldar.
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The ongoing COVID-19 pandemic has considerably promoted the usage of Digital Financial Services (DFS) in India. Therefore, exploring the various determinants influencing the DFS users is crucial for the DFS providers to understand their customers better. This study aims to identify, measure, and validate the determinants of Digital Financial Literacy (DFL) from the Indian adults who use Digital Financial Services. A sample of 384 adult DFS users from India was surveyed using a self-administered questionnaire in 2021. A multidimensional scale was developed to measure the Digital Financial Literacy in this study. The results exhibit that Digital Knowledge, Financial Knowledge, Knowledge of DFS, Awareness of Digital Finance Risk, Digital Finance Risk Control, Knowledge of Customer Right, Product Suitability, Product Quality, Gendered Social Norm, Practical Application of Knowledge and Skill, Self-determination to use the Knowledge and Skill and Decision Making are the determinants of DFL among the adults in India. Further, the users of DFS without DFL will face numerous challenges such as inability to complete the transaction, financial loss and privacy breach, etc. Hence, the study concludes that DFL is prerequisite to use DFS effectively.
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The expectations were soaring amongst the general public just before the 2022 budget with hopes in respect of reduced Income Tax rates or increased exemption limits etc. One of the biggest expectations was in respect of upward revision in Section 80 D limits which refers to health insurance premium paid and the same has not been revised for long time. Over the years, the health insurance premium has increased substantially and more so due to huge claims from Covid in last two years. But, much to shock of all Income Tax Payers, the, Section 80 D limits remains untouched. There are also other policies which comes under the broad category of Health Insurance that does not qualify for Income Tax exemption but merits serious consideration. Health Insurance policies are subject to GST of 18% which is certainly too high especially when the Government should have looked at initiating major step to boost the health insurance penetration and make feel people more secured. For an individual to manage one’s health risk properly, he/she need to have more than one type of health insurance policies for adequate amount with all applicable riders or add-on covers which matters and all dependents like spouse, children and parents being completely covered. © 2022, Indian Association of Preventive and Social Medicine. All rights reserved.
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Dengue fever has become one of the deadliest infectious diseases and requires the development of effective antiviral therapies. It is caused by members of the Flaviviridae family, which also cause various infections in humans, including dengue fever, tick-borne encephalitis, West Nile fever, and yellow fever. In addition, since 2019, dengue-endemic regions have been grappling with the public health and socio-economic impact of the ongoing coronavirus disease 19. Co-infections of coronavirus and dengue fever cause serious health complications for people who also have difficulty managing them. To identify the potentials of mangiferin, a molecular docking with various dengue virus proteins was performed. In addition, to understand the gene interactions between human and dengue genes, Cytoscape was used in this research. The Kyoto Encyclopedia of Genes and Genomes software was used to find the paths of Flaviviridae. The Kyoto Encyclopedia of Genes and Genomes and the Reactome Pathway Library were used to understand the biochemical processes involved. The present results show that mangiferin shows efficient docking scores and that it has good binding affinities with all docked proteins. The exact biological functions of type I interferon, such as interferon-α and interferon-ß, were also shown in detail through the enrichment analysis of the signaling pathway. According to the docking results, it was concluded that mangiferin could be an effective drug against the complications of dengue virus 1, dengue virus 3, and non-structural protein 5. In addition, computational biological studies lead to the discovery of a new antiviral bioactive molecule and also to a deeper understanding of viral replication in the human body. Ultimately, the current research will be an important resource for those looking to use mangiferin as an anti-dengue drug. Supplementary Information: The online version contains supplementary material available at 10.1007/s43450-022-00258-6.
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The 2019 corona virus pandemic (COVID-19) has expanded worldwide. Medical imaging, such as X-rays and CT, plays a crucial part in the worldwide fight of COVID-19, whilst new technologies of artificial intelligence (AI) further increase the imagery tools and assist medical professionals. We examine the quick reactions to COVID-19 in the medical imaging community, propelled by AI. For example, AI-enhanced picture collection may greatly assist to automate the process of scanning and also restructure the workflow with little patient interaction, giving the imagery professionals the greatest protection. In this review, the methods of extracting the features for lung CT images and for segmentation and classification we searched many data source like IEEE, Elsevier, Springer, the correct delineation of infectious X-ray and CT images by AI may further increase the job efficiency, making quantification afterwards more efficient. In addition, radiographers make clinical judgments, for example for diagnosis, tracking and prognosis of the disease, with their computer assist platforms. This review study thus covers the complete medical imagers' pipeline, including the capture of images, segmentation, diagnosis, and follow-up approaches including COVID-19. The implementation of Smart into X-ray and CT, both frequently employed in frontline hospitals, is particularly important to show the newest advances in the fight against COVID-19 in diagnostic imaging and radiology. X-rays and CT in chests are commonly employed in the COVID-19 testing and diagnosis. In order to minimise the high danger of infection during the COVID-19 pandemic, contactless and automated image capture workflows are needed. The usual process of imagery however, entails inescapable interaction between technicians and patients. In particular, the technicians assist in the positioning of the patient first in posing the patient according to a certain protocol, such as first-head versus first-foot, and supine versus prone at CT, then visually identify the target part of the patient's body location, and manually adjust the relative position and position between the patient and the x- ray tube. This procedure enables personnel to touch patients closely, which leads to significant risk of virus exposure. A contactless and automated picture process is therefore necessary to reduce interaction.
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Background: No activity in any Life Insurance Company is of more importance than the settlement of Claims to the satisfaction of the beneficiary, in case of premature death of the life Assured. It is the ultimate moment of Truth in the contract of Life insurance. The Life Insurance Companies must be conscientious enough to understand that claim settlement is the very purpose of their existence in the society in fulfillment of the promise made to policyholders. The process of claim settlement from the perspective of policyholders or the beneficiaries revolves round a. Time taken to settle the claim and b. Ease of claim settlement in terms of number as well as type of documents called for. The companies tries to achieve this objective without compromising on basic checks encompassing over things such as genuineness of the claim etc. Accordingly, the companies have established standard processes and checklist of documents that is called for at the time of claim. The claim management process consists of claim initiation by the nominee or the policyholderas the case may be under the policy, claim process or enquiry by the insurer to check the genuineness of the claim and Claim settlement within the Regulations as indicated by the Death Claim settlement Ratio (DCSR), Solvency Ratio (SR) etc., The Covid19 pandemic caused severe health disorders that resulted in more deaths, impacting the above claims process adversely warranting companies to have relook at the entire process and the checklist of documents so thatTurn around Time is maintained whatever be the number of claims intimated without giving room for entertaining any fraudulent claims By collecting the relevant claim statistics from credible sources such as Insurance Regulatory and Development of India (IRDAI) etc, this paper analyses the current practice and brings out how various components of claims management process of an Insurance Company were affected especially in the background of unprecedented Covidl9 pandemic. This paper also suggests the ways and means to address these challenges through a 6-step strategy quoting the expert's suggestions as well. Challenges thrown by Covidl9 pandemic on various components of the Claim management process ofan insurance company are listed and categorized as: I. Related to Claim intimation by customers II. Regulatory Issues related III. Claim management process related IV. Product pricing related V. Legal aspects related VI. Technology related Traditionally, in any insurance course or internal training, the impact of epidemics on Sales, Underwriting and Claims are not focused at all. The unprecedented covid has made all the departments totally to revisit their approach right from scratch afresh. It has also made all the Insurance Institutes, Colleges and the internal training of insurance companies to includethe impact of pandemics or epidemics henceforth in their books. Research Methods: The impact of Covid19 is evaluated by calculating the variation between pre-Covid19 data and post-Covid19 dataandanalyzing the reasons for the variation with supporting information. Data is extracted from authorized websites of various Life Insurance Companies and IRDAI. The data considered for analysis is also validated through information gathered through various interview articles of Senior Management People of different Insurance Companies. Results: The study brings out theimmediate need forrevisiting the process followed in respect of all the above sixcomponents of the claim management to address the challenges posed by Covid19 pandemic. It also brings out the need for amending some existing laws related to life insurance. It emphasizes the urgency of the above reforms to 1) facilitate smooth settlement of death claims to the satisfaction of the customers, 2) improve the profitability of the insurance companies within the guidelines of the regulator and Acts of Government of India.3. To reorient the training and training materials with change in focus to take care of learnings from Covid
ABSTRACT
Dengue fever has become one of the deadliest infectious diseases and requires the development of effective antiviral therapies. It is caused by members of the Flaviviridae family, which also cause various infections in humans, including dengue fever, tick-borne encephalitis, West Nile fever, and yellow fever. In addition, since 2019, dengue-endemic regions have been grappling with the public health and socio-economic impact of the ongoing coronavirus disease 19. Co-infections of coronavirus and dengue fever cause serious health complications for people who also have difficulty managing them. To identify the potentials of mangiferin, a molecular docking with various dengue virus proteins was performed. In addition, to understand the gene interactions between human and dengue genes, Cytoscape was used in this research. The Kyoto Encyclopedia of Genes and Genomes software was used to find the paths of Flaviviridae. The Kyoto Encyclopedia of Genes and Genomes and the Reactome Pathway Library were used to understand the biochemical processes involved. The present results show that mangiferin shows efficient docking scores and that it has good binding affinities with all docked proteins. The exact biological functions of type I interferon, such as interferon-α and interferon-β, were also shown in detail through the enrichment analysis of the signaling pathway. According to the docking results, it was concluded that mangiferin could be an effective drug against the complications of dengue virus 1, dengue virus 3, and non-structural protein 5. In addition, computational biological studies lead to the discovery of a new antiviral bioactive molecule and also to a deeper understanding of viral replication in the human body. Ultimately, the current research will be an important resource for those looking to use mangiferin as an anti-dengue drug. Graphical Supplementary Information The online version contains supplementary material available at 10.1007/s43450-022-00258-6.
ABSTRACT
The sudden change in the daily routine caused by the impact of Covid-19 has been given a new name called 'The New Normal'. This new normal has affected many lives in various ways. Usage of mask has become one among the other usual thing which we do as in our daily part of life. The mask helps in reducing the spread to a certain level, but it can never completely stop the spread. We must follow various measure to break the chain of virus. Only usage of mask or social distancing will not help to control the spread. The proposed automatic hand sanitizing glove will be one of the best ways to stop the spread. As most of the virus transmission takes place through hand, we are proposing an automatic hand sanitizing glove. The automatic hand sanitizing glove consists of a dc motor which could pump the sanitizer all over the outer surface of glove which is made of porous material. This glove is made of a quick dry material hence it won't remain wet for long period of time. This pumps continuously in regular intervals of time. In this way, we can sanitize our hands without applying sanitizer directly on our skin. The comprehensive study regarding the glove is discussed in the following headings. © 2021 IEEE.
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Purpose: Against the backdrop of an Indian banking sector that finds itself entangled in the triple deadlock of increasing competition, technological changes and strict regulatory compliance, the study aims to examine the need for reinforcing stringent corporate and risk governance mechanisms as an instrument for improving efficiency and productivity levels. Design/methodology/approach: The authors construct three separate indices, namely, supervisory board index, audit index and risk governance index to measure the governance practices of commercial banks. A slacks-based data envelopment analysis technical efficiency (TE) measure, a variable returns to scale cost efficiency model and Malmquist productivity index are employed to determine TE, cost efficiency and productivity change, respectively. A two-step system-generalized method of moments estimation accounts for the dynamic relationship between governance and efficiency. Findings: The authors show that strict audit and risk governance mechanisms are associated with better efficiency and productivity levels. However, consistent with the free-rider hypothesis, large, independent and diverse boards lead to cost inefficiencies. Strict risk governance structures circumvent the negative effects of high regulatory capital and improve efficiency and total factor productivity. However, friendly boards do not perform efficiently in the presence of regulatory capital, implying that incentives arising from maintaining high levels of equity capital make them more susceptible to risk-taking, and board composition is unable to sidestep this behaviour. Originality/value: The paper contributes to the literature that explores the linkages between governance, efficiency and productivity. The inferences hold relevance in the post-COVID world, as regulators try to circumvent the additional stress on the banking system by adopting sound corporate and risk governance mechanisms. © 2021, Emerald Publishing Limited.
ABSTRACT
The evolution the novel corona virus disease (COVID-19) as a pandemic has inflicted several thousand deaths per day endangering the lives of millions of people across the globe. In addition to thermal scanning mechanisms, chest imaging examinations provide valuable insights to the detection of this virus, diagnosis and prognosis of the infections. Though Chest CT and Chest X-ray imaging are common in the clinical protocols of COVID-19 management, the latter is highly preferred, attributed to its simple image acquisition procedure and mobility of the imaging mechanism. However, Chest X-ray images are found to be less sensitive compared to Chest CT images in detecting infections in the early stages. In this paper, we propose a deep learning based framework to enhance the diagnostic values of these images for improved clinical outcomes. It is realized as a variant of the conventional SqueezeNet classifier with segmentation capabilities, which is trained with deep features extracted from the Chest X-ray images of a standard dataset for binary and multi class classification. The binary classifier achieves an accuracy of 99.53% in the discrimination of COVID-19 and Non COVID-19 images. Similarly, the multi class classifier performs classification of COVID-19, Viral Pneumonia and Normal cases with an accuracy of 99.79%. This model called the COVID-19 Super pixel SqueezNet (COVID-SSNet) performs super pixel segmentation of the activation maps to extract the regions of interest which carry perceptual image features and constructs an overlay of the Chest X-ray images with these regions. The proposed classifier model adds significant value to the Chest X-rays for an integral examination of the image features and the image regions influencing the classifier decisions to expedite the COVID-19 treatment regimen.
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Background: Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has affected over 100 million individuals during the current pandemic. Cancer is a reported risk factor for worse outcomes from SARS-CoV-2 infection and its clinical syndrome COVID-19. However, risk associated with specific cancer subtypes, extent of disease, and treatment history remains unclear. Breast cancer is the most common cancer in women and is treated with multiple modalities that may affect COVID-19 severity and outcomes, including surgery, radiation (RT), hormone therapy (HT), and chemotherapy (CT). Methods: We conducted a retrospective cohort study of patients with SARS-CoV-2 and history of breast cancer at two academic centers in Los Angeles, CA between January - September, 2020. Demographic information, cancer diagnosis, treatment history, comorbid conditions, and clinical outcomes of COVID-19 were reviewed. The primary outcome was rate of hospitalization for COVID-19. Associations were evaluated for significance by chi-square test or Student's T test, with a = 0.05. Results: Our cohort included 61 patients with history of breast cancer. 19 (31.1%) required hospitalization and 3 (4.9%) died from COVID19. Median age was 61 years. 44% of patients were White/Caucasian, 37.7% Hispanic/Latinx, 8% Black/African American, 5% Asian, and 5% were of another race. 87% of patients had local or regional disease and 13% had distant metastases. 53% of patients had ever received CT historically, 66% HT, and 53% RT. 25% of patients received cancer treatment (surgery, CT, or RT) within 90 days of COVID-19 diagnosis. 38% were on HT at time of COVID-19 diagnosis. Patients with prior RT were more likely to be hospitalized from COVID-19 than those with no prior RT (44% vs 14%, p = 0.02), as were patients with 2 or more comorbidities (p = 0.01). In addition, there was a trend toward lower hospitalization rates for patients on HT [24% vs. 42% (p = 0.17)] and a trend toward higher hospitalization rate for non-white ethnicity [35% vs. 25% (p = ns)]. Extent of disease, history of CT, or receipt of any cancer treatment (e.g. surgery, RT, CT) within 90 days of COVID-19 diagnosis were not associated with hospitalization rate. Conclusions: In our diverse cohort of breast cancer patients with COVID-19 a history of RT and presence of multiple comorbidities were both associated with increased risk of hospitalization, while a history of HT was not. Further investigation is needed to validate these findings in larger cohorts. These findings may inform recommendations for breast cancer patients during the ongoing SARS-CoV-2 pandemic.
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This paper presents a study of various AI-powered ICT applications to numerous challenges related to the agriculture life cycle and its positive impact on the well-being of Indian farmers. Technology-driven solutions to various problems, such as soil fertility, inadequate irrigation, pest control, weed management and yield prediction have been discussed, along with, affirmative actions taken by the Indian government to promote smart agriculture. The agricultural life cycle faces many impediments, such as disease, weeds, pest infestation, improper soil conditions, outdated irrigation methods, unpredictable weather conditions, etc. These lead to severe crop failure, food shortage and increasing environmental hazards, driving the farmers to poverty. Extensive research has been done to address these problems in the past few decades. Further, due to the outbreak of pandemic COVID 19, certain restrictions have been imposed by the Indian Government in the farming sector to ensure the safety of farmers from getting infected with the deadly virus. This has resulted in an acute shortage of farmworkers. The use of ICT in agriculture becomes even more important at this crucial time, when, the pandemic has spread across the globe. The ICT based solutions reduce the dependence of farmers on farm-workers and enable them to maintain stable income levels and farm yield, despite the shortage of farm labourers. Various agro-intelligent practices adopted in the last 15 years, worldwide, have also been surveyed, in this paper. Some of the tools and platforms developed by Indian Start-ups to implement smart agriculture and to deal with the shortage of manpower and supply chain disruption due to lockdown during pandemic, have also been discussed. © Proceedings of the 13th IADIS International Conference ICT, Society and Human Beings 2020, ICT 2020 and Proceedings of the 6th IADIS International Conference Connected Smart Cities 2020, CSC 2020 and Proceedings of the 17th IADIS International Conference Web Based Communities and Social Media 2020, WBC 2020 - Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.
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COVID-19 is a viral pandemic disease affecting more than 215 countries worldwide. Understanding the nature of the disease is a challenge not only for the scientists but also for general public. In this study, the authors have evaluated the perception of general public about the disease COVID-19 using a questionnaire survey. Questionnaire was designed using Google Forms and circulated through the social media like WhatsApp and Facebook. The questions related to the personal details on age, sex and education were received from the respondents. Further, the general understanding about COVID-19, causal organism and symptoms, airborne nature of COVID-19, their spread and containment were also received. The opinion of the respondents towards controlling the disease by State and Central Government, implementation of policy for containment of COVID-19 for Buildings with Air conditioning system were also received using the questionnaire. A total of 463 people responded to the questions. Among the respondents 70.9% are female and the remaining 29 % male. The age of the respondents ranges from 18 to 57. Maximum number of respondents provided correct answer related to the nature, size, shape and the spread of the causal organism. However, confusion prevailed among the respondents related to the medicinal system to practice and the distance of the viral spread. Maximum respondents are satisfied with the steps taken by the Government in controlling the disease and supports bringing a bill for clearance and certification for COVID-19 in A/c Buildings and other public Buildings. The study can be used as an insight by both Central and State Government and the policy makers of India in creating further awareness towards the disease among general public.
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In present scenario respiratory diseases are major challenge in healthcare sector and many individuals suffer from respiratory diseases like asthma, lung cancer, throat cancer etc., due to air pollution, smoking and infections in respiratory system. Sometimes the respiratory diseases will become pandemic diseases such as SARS and COVID-19. In order to protect people from these pandemic diseases, detecting the diseases at earlier stage is much essential by proper diagnosis. The two diagnostic techniques are the invasive and non-invasive techniques. Diagnostic equipment like Computed Tomography (CT), Biomarkers and Artificial Electronic Nose are generally used in hospitals, however these methods are not affordable for common people. This paper reviews various invasive and non-invasive techniques and also tries to analyze cost effective device for diagnosing respiratory diseases. © 2019 SERSC.