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Individuals with comorbidities (i.e., Diabetes Mellitus, hypertension, heart diseases) are more likely to develop a more severe form of coronavirus disease 2019 (COVID-19), thus, they should take necessary precautions to avoid infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its emerging variants and subvariants by getting COVID-19 vaccination and booster doses. In this regard, we used text analytics techniques, specifically Natural Language Processing (NLP), to understand the perception of Twitter users having comorbidities (diabetes, hypertension, and heart diseases) towards the COVID-19 vaccine booster doses. Understanding and identifying Twitter users' perceptions and perspectives will help the members of medical fraternities, governments, and policymakers to frame and implement a suitable public health policy for promoting the uptake of booster shots by such vulnerable people. A total of 176,540 tweets were identified through the scrapping process to understand the perception of individuals with the mentioned comorbidities regarding the COVID-19 booster dose. From sentiment analysis, it was revealed that 57.6% out of 176,540 tweets expressed negative sentiments about the COVID-19 vaccine booster doses. The reasons for negative expressions have been found using the topic modeling approach (i.e., risk factors, fear of myocardial fibrosis, stroke, or death, and using vaccines as bio-weapons). Of note, enhancing the COVID-19 vaccination drive by administering its booster doses to more and more people is of paramount importance for rendering higher protective immunity under the current threats of recently emerging newer Omicron subvariants which are presently causing a rise in cases in a few countries, such as China and others, and might lead to a feasible new wave of the pandemic with the surge in cases at the global level. Copyright © The Author(s) 2023.
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Introduction: For over 50 years mediastinoscopy was considered the gold-standard to sample the mediastinum. The introduction of EBUS-TBNA (endobronchial ultrasound - transbronchial needle aspiration) revolutionised the diagnosis and staging of lung cancer and the diagnosis of metastases and investigation of isolated mediastinal and hilar lymphadenopathy. Objective(s): We aim to examine the relation between the number of EBUS and mediastinoscopy procedures performed in a large regional Cancer Alliance. Methodology A retrospective observational study of the number of EBUS and Mediastinoscopy procedures performed in the Greater Manchester Cancer Alliance between 2011-2020. Result(s): The number of EBUS procedures performed increased annually, from 362 in 2013 to a peak of 1,660 in 2019. There was a decline in in 2020 owing to the COVID-19 pandemic but this has recovered again in 2021 (n=1565). The number of mediastinoscopies was inversely proportional and declined on an annual basis with 179 performed in 2011, reducing to 21 in 2020 Conclusion(s): EBUS is now a widely available and highly adopted procedure for sampling the mediastinum. The number of procedures performed has increased on an annual basis and led to a reduction in the need for undertaking mediastinoscopies. The less invasive nature of EBUS has likely lowered the threshold for sampling the mediastinum to investigate benign conditions such as tuberculosis and sarcoidosis.
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Background: Cancer patients are at high risk of severe COVID infection and recommended at least three doses of SARS-CoV2 mRNA vaccines. Various anti-neoplastic treatments may affect long-term vaccine immunogenicity. Methods: Patients with solid or haematological cancer were recruited from two Singapore hospitals between July 2021 and March 2022. GenScript cPASS surrogate virus neutralisation assays measured antibody responses, which were correlated with clinical outcomes obtained from medical records and national mandatory-reporting databases. Results: In total, 273 patients were recruited (40 with haematological malignancies and the rest solid tumours). Two-hundred and four patients (74.7%) were receiving active cancer therapy: 98 (35.9%) receiving systemic chemotherapy and the rest targeted or immunotherapy. All patients were seronegative at baseline. After receiving one, two and three doses of SARS-CoV-2-mRNA vaccination, seroconversion rate was 35.2%, 79.4% and 92.4% respectively. After three doses, patients on active treatment for haematological malignancies had lower antibodies (57.3%±46.2) as compared to patients on immunotherapy (94.1%±9.56, p<0.05) and chemotherapy (92.8%±18.1, p<0.05). SARS-CoV-2 infection was reported in 77 (28.2%) patients of which 18 were severe. Conclusion: This study demonstrates high immunogenicity of three doses of vaccines and protection against severe infection in cancer patients.
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Keeping up the attendance record with everyday exercises is a difficult task. The conventional method of marking staff attendance is by tapping their ID card and then using fingerprint scanner. But due to COVID-19 pandemic the attendance system of using fingerprint scanner is stalled and currently not in use. The following system depends on face recognition and intranet connectivity to keep up attendance record of facilities and staff. The paper discusses the attendance marking system that is passive (no direct contact with the scanner or sensor) and restricting the users within certain network. The main goal of this system is divided in two steps, in initial step face is snare from the front camera of the smart phone and it is then recognized in the picture and in the second step these distinguished appearances and features are contrasted with stored information in data set for confirmation. © 2021 The authors and IOS Press.
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Corona pandemic has affected the daily routine of life disturbing the trade and economic globally. Wearing a mask has become compulsory and a new tradition. within the close to future, several suppliers can raise the shoppers to wear masks properly. Therefore, detection of face mask has become one of the important tasks to assist the international society. This paper provides a easy and simplified approach to detect the face masks using some of the important Machine Learning packages like TensorFlow, Keras, OpenCV and Scikit-Learn. The projected methodology detects the face from the image properly and so identifies if it's a mask thereon or not. As a police work task performing artist, it may detect a face together with a mask in motion. the tactic gives an accurate output with an accuracy of 96.77% on dataset. The model tendency to find the optimized values of parameters are employed using Convolutional Neural Network (CNN) model to identify whether the masks are worn properly or not while not inflicting over-fitting. © 2021 IEEE.
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One of the major issues faced by the financial sector today is the loan delinquencies and loan defaults specifically for NBFC's in Rural areas. The study conducted with a sample NBFC Mahindra & Mahindra Financial services also struggles with the same issue. The Researcher in this study has tried to find out the methods used by the NBFC for pre loan assessment and the impact of it in controlling the loan defaults at later stages of loan. Mostly these methods help the credit manager identify the suitability of the applicant for loan disbursement, but if these methods have any impact in controlling loan defaults at later stages of loans is an area for study. The data required for this analysis is not available as a published data. Thus it has been collected as Opinion based data from Credit Managers. One sample T test has been applied to statistically analyse the data.
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The moored buoy network in Indian Ocean revolutionized the observational programs with systematic time series measurement of in-situ data sets from remote marine locations. The real time meteorological and oceanographic data sets significantly improved the weather forecast and warning services particularly during extreme events since its inception in 1997. The sustenance of the network requires persistent efforts to overcome the multitude of challenges such as vandalism, bio-fouling, rough weather, corrosion, ship time availability, telemetry issues etc. Besides these, the COVID-19 pandemic constrained the normal functioning of activities, mainly by delaying the maintenance of the network that resulted in losing a few expensive buoy system components and precious data sets. However, the improvements in the buoy system, in-house developed data acquisition system and efforts in ensuring the quality of measurements together with ‘best practice methods’ enabled 73 % of the buoy network to be functional even when the cruises were reduced to 33 % during the Covid lockdown in 2020. The moored buoys equipped with Indian buoy data acquisition system triggered high frequency transmission during the Super cyclone Amphan in May 2020, which greatly helped the cyclone early warning services during the Covid pandemic. The Covid lockdown point towards the reliability and enhanced utility of moored buoy observations particularly when other modes of measurements are limited and also necessitates more such platforms to better predict the weather systems. The present study analyses the enhancement of the buoy program and improvisation of the buoy system that extended the lifetime beyond the stipulated duration and enabled the high frequency data transmission during cyclones amid the Covid lockdown. The recommendations to better manage the remote platforms specifically in the event of a pandemic based on the operational experience of more than two decades is also presented.
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In response to the coronavirus (COVID-19) pandemic, Government and public health authorities around the world are developing contact tracing apps as a way to trace and slow the unfold of the virus. There is major divergence among nations, however, between a "privacy-first" approach that protects citizens' information at the price of very restricted access for public health authorities and a "data-first" approach that stores massive amounts of knowledge that, whereas of immeasurable price to epidemiologists. Contact tracing apps work by gathering information from people who have tested positive for the virus and so locating and notifying individuals with whom those people are in shut contact, oftentimes by use of GPS, Bluetooth, or wireless technology. All of the user's information is employed and picked up, the study found that users' information would be created anonymous, encrypted, secured, and can be transmitted on-line and stored solely in an aggregated format. Contact tracing apps use either a centralized or a decentralized approach to work the user's information. Apps that use a centralized approach have high privacy risks. In this paper, the researcher's contributions related to the security and privacy of Contact tracing apps have been discussed and, later research gaps have been identified with proposed solutions.
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The emergence of cryptocurrency has sparked an interesting debate on the future of financial transactions. Post-COVID, there will be unbelievable advancements in the most popular and promising technology, cryptocurrency particularly bitcoins, as it is more valuable than any form of cryptocurrencies. Our work is about bitcoin price alert system using bolt Internet of Things (IOT) and Blockchain. In this research paper, we will be writing a python program that checks the current price of the bitcoin and sends an alert if the current price of the bitcoin is higher than the set selling price. The program checks the current price of bitcoins whenever the price of bitcoins is updated. And at that same time it compares the current price with the bitcoin price that has been set as selling price. It alerts through buzzer, email and message. For this we use Bolt Internet of Things (IOT) module and ubuntu software for writing program in python. © 2020 IEEE.
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In light of the multiple legal issues, compliance and disruptions caused by the pandemic, organisations searching for new solutions need to know what smart contracts are and how they would function under the legal doctrine of force majeure in light of COVID-19. The Blockchains which use Bitcoin type of scripts have been popular as payment solutions, but it is less used as smart contracts. In the case of multi-level games and incremental project payments, there is a high potential to use Bitcoin type of scripts, but it is not being used currently. Interestingly, there have been attempts to associate smart contract mainly using Ethereum Blockchain but not with Bitcoin type of scripts. This article intends to demonstrate the novelty of designing smart contracts using Bitcoin type of scripts for hierarchical execution of smart contracts. An attempt is done to show its application in two use cases (multi-level reward games payment and incremental project payment). An evaluation is done with three methods each having a combination of pros and cons based on the requirements which aids in understanding for transparency and control over funds through Blockchain. © 2020 IEEE.