Digital Banking through the Uncertain COVID Period: A Panel Data Study

This research investigates how the uncertainty caused by the COVID-19 pandemic has affected digital banking usage in India. The study is made by utilizing a panel of data consisting of 108 firm-month observations during covid period from 2020 to 2022, with data mainly collected to analyze the impact of COVID-19 uncertainty. Most of the determinants were collected from the RBI data website. The main emphasis of this study is on the utilization of digital banking services in the context of the pandemic, and the research assesses the factors that have influenced this trend, including the number of physical bank branches, the utilization of debit and credit cards at automated teller machines (ATMs) and points of sale (PoS), as well as the level of economic policy uncertainty (EPU). The analysis was conducted using panel regression analysis, a suitable method for handling the error components in the model that are either fixed or random. The findings indicate that the uncertainty caused by the pandemic has had a negative impact on the use of digital banking services. Additionally, the study highlights that the usage of debit and credit cards at PoS has significantly contributed to promoting the progress of digital banking services during the pandemic. Overall, this study provides valuable insights into how digital banking services have evolved during a period of significant uncertainty and disruption. © 2023 by the authors.

Use of metolazone as an adjunct therapy to loop diuretics in diuretic resistant acute decompensation of heart failure: A systematic review and meta-analysis: Metolazone in diuretic resistant AHF: A Meta-Analysis

Introduction: Loop diuretics are the first-line treatment for volume overload in acute decompensation of congestive heart failure (AHF). Loop diuretic resistance is common due to pharmacologic tachyphylaxis. Therefore, thiazide and thiazide-like diuretics are often used as add-on therapy to combine two different pharmacologic mechanisms. This systemic review and meta-analysis aimed to synthesize the current evidence on the efficacy and safety of metolazone and other thiazide-like diuretics in AHF. Method(s): PRISMA guidelines were followed in conducting this systematic review. PubMed, Scopus, PubMed Central, and Embase databases were searched using relevant keywords for studies published before 5 Jan 2022. and title screening was performed, followed by full-text screening using the Covidence software. Data were extracted, and analysis was done using Cochrane Review Manager (RevMan v5.1). The results were reported in odds ratio and mean difference with 95% confidence intervals. Result(s): Out of 2999 studies identified by database search, eight studies met the inclusion criteria (2 RCTs and 6 cohort studies). Pooled analysis using a random-effects model showed no difference in mean difference among the metolazone group and control group for 24 hours total urine output (MD 69.32, 95% CI -638.29 to 776.94;n = 551;I2 = 84%), change in urine output in 24 hours (MD -284.09, 95% CI -583.99 to 15.81;n = 345;I2 = 0%), 48 hours total urine output (MD -465.62, 95% CI -1302.22 to 370.99;n = 242;I2 = 0%) and urine output at 72 hours (MD -13.24, 95% CI -90.88 to 64.40;n = 205;I2 = 0%). However, studies with furosemide only in the comparator arm, 24 hours of total urine outcome favored metolazone (MD 692.70, 95% CI 386.59 to 998.82;n = 334;I2 = 0%). There was no difference between the two groups in the rate of adverse events, loss of weight, mortality, or readmission rates. Conclusion(s): Metolazone therapy in diuretic resistant AHF may improves urine output and facilitates achieving a net negative balance. Thus, metolazone and thiazide-like diuretics can be used as add-on therapy in acute decompensation of heart failure, especially in diuretic resistance.Copyright © 2023 The Author(s)

Abdominal Aortic Occlusion in Setting of Covid-19

Introduction: The incidence of arterial thrombosis among critically ill patients with COVID-19 is 4.4%, acute aortic obstruction alone having a mortality rate of 31%. We present a review of the literature regarding isolated abdominal aortic thrombosis (IAAT) in the setting of COVID-19 infection, as well as a case presentation. Method(s): A literature review was performed using Pubmed with the keywords, aorta, aortic, thrombus, and Covid-19. Within these articles, the scope was narrowed to articles that related to IAAT in the setting of Covid-19 infection. Result(s): Our literature review found 9 articles detailing a total of 11 cases of IAAT in the setting of COVID-19 infection. IAAT had a mortality 22% (2 out of 9 patients). Approximately, 55% (6 out of 11) of the patients were treated with surgery and 27% (3 out of 11) received anticoagulation. 73%, (8 out of 11) of the patients in our literature review presented with symptoms of acute limb ischemia. Ages ranged from neonate to 85 years old, though 82% (9 out of 11) were over the age of 50. Conclusion(s): Our literature review suggests that IAAT is a serious complication of COVID-19 infection. IAAT is more common in males and people over the age of 50, which aligns with the 52 year- old male patient who presented to our clinic with lower extremity claudication and bilateral 1st & 5th toe cyanosis after COVID-19 infection. To prevent devastating limb ischemia, we emphasize early evaluation of claudication symptoms in patients with COVID-19 or recent COVID-19 infection.

Long-Term Neurologic Sequelae Among Patients with Varying COVID-19 Severity: An Administrative Claims Database Analysis

Objectives: Examine the long-term incident neurologic sequelae post COVID recovery and assess relationship with COVID severity using real-world data. Method(s): This retrospective cohort study was conducted using Optum Research Database between 01July2019 to 30Sep2022. Patients included were >=18 years with COVID diagnosis (index date) between 01Jan2020 and 31Oct2020, with continuous enrollment 6 months before and >=12 months after index date, known demographics, not pregnant, and with no baseline neurologic conditions. Patients were stratified into COVID severity cohorts as mild (index diagnosis), moderate (inpatient visit within 15 days of index), or severe (evidence of acute respiratory distress) and followed for a minimum of 12-months post-index. Neurologic sequelae examined were persistent headache, migraine, anosmia, sleep disturbance, cognitive dysfunction, post-traumatic stress disorder, suicidality, anxiety, depression, attention deficit hyperactivity disorder, cerebrovascular disease (CVD), fatigue/myalgia and tremors. Descriptive statistics and incidence rate ratios (IRR) were calculated to assess outcomes. Result(s): Of 534,843 patients, 107,656 (Mild 96,637;Moderate 3,371;Severe 7,648) met the study inclusion criteria. Median follow up time was 750, 774 and 768 days in the mild, moderate and severe cohorts, respectively. About 20% of patients in the mild, 32% in moderate and 35% in the severe cohort experienced >=3 neurologic sequelae during the follow-up period. A significantly higher incidence of any neurologic sequelae was observed in moderate and severe cohorts compared with the mild cohort (IRR 3.1 and 3.0, respectively;p<0.001). Cognitive dysfunction (moderate IRR 5.4, severe IRR 5.7;p<0.001), and CVD (moderate IRR 4.8, severe IRR 4.0;p<0.001) were the most commonly occurring manifestations in moderate and severe cohorts compared with the mild cohort. Conclusion(s): These results highlight the need for long-term monitoring and preventative strategies for neurologic conditions post COVID recovery that might impair quality of life and increase overall healthcare burden in the U.S.Copyright © 2023

Nanobiosensors Potentialities for Monitoring SARS-CoV-2 in the Environment

The worldwide pandemic of coronavirus disease-2019 (COVID-19) is a devastating and distressing scenario that highlights humanity's inability to build fast diagnostic tools for emerging infectious diseases. However, the majority of existing approaches have a significant probability of false negatives, leading in patient diag-nostic errors and prolonging therapy. Nanoparticles have shown significant improve-ment and have the potential to be used as a platform for quickly and accurately identifying viral infection. The relevance of nanoparticles is potential platforms for COVID-19 diagnostics was emphasized in this research. In addition, nanomaterials have surface chemistry, which may be beneficial for the bioconjugation of molecules, large surface potential, and a significant amplification impact on signals. Due to various potential benefits, metallic nanomaterials like gold, silver nanoparticles, and carbon-based nanomaterials (carbon nanotube and graphene), nanogels, and photonic crystals are utilized for biosensing applications. In compared to traditional techniques for identifying severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), this study covers the most relevant aspects of nanobiosensor-based diagnostics tech-niques. Additionally, major potential challenges and prospects associated with the advancement of these distinct sensors for SARS-CoV-2 detection are discussed in detail. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Extracorporeal membrane oxygenation for airway emergencies

Objectives: Extracorporeal membrane oxygenation (ECMO) is well established in cardiorespiratory failure. Here we report the use of ECMO in an airway emergency to provide respiratory support. Method(s): Informed consent was obtained from patient at the time of admission. Result(s): A 48-year-old with COVID-19 requiring venovenous ECMO (VVECMO) for 32 days and tracheostomy for 47 days had developed tracheal stenosis three months after tracheostomy removal, and undergone tracheal resection and reconstruction. He presented two weeks later with acute dyspnea, bloody drainage and a bulge in his neck with coughing. A computerized tomography (CT) of the cervical spine and chest showed dehiscence of the tracheal wound and a gap in the trachea. He was managed with High Flow Nasal Canula and supported on VVECMO support using 25 Fr. right femoral drainage cannula and 23 Fr. left IJ return cannula. A covered stent was placed, neck wound was irrigated and debrided. Patient was decannulated after 10 days on ECMO. Future therapeutic considerations include mediastinal tracheostomy, aortic homograft interposition of the disrupted segment of trachea with stent placement and permanent self-expandable stent with internal silicone stent. Conclusion(s): ECMO is increasingly used in complex thoracic surgery as well as in the perioperative period as salvage support. One of the areas where it has shown promising results is traumatic main bronchial rupture, airway tumor leading to severe airway stenosis, and other complex airway problems. The ease of cannulation, the technological advances and growing confidence in the management of ECMO patients are the main reasons for the expansion of ECMO use beyond conventional indications. The case described above is an example of the use of ECMO in the perioperative management of impending respiratory failure due to airway obstruction or disconnection. (Figure Presented).

Auditing during a pandemic - can continuous controls monitoring (CCM) address challenges facing internal audit departments?

PurposeDuring a pandemic, with businesses implementing social distancing protocols and work-from-home strategies, the use of continuous controls monitoring (CCM) may add value to the internal audit function. This study aims to examine the use of CCM technologies and the impact on the internal audit function during a pandemic. Design/methodology/approachThis study adopted a case study approach for this study because it focuses on questions of "how" and "what." Case studies provided an opportunity for an in-depth analysis of the phenomena being investigated. Semi-structured interviews were used to collect data. This study did not use sampling. Instead, multiple case studies were used for data collection. FindingsBased on the findings, this study makes several contributions to the literature, for example, in health-care evidence suggests the pandemic has caused internal audit to focus on risk areas. Other industries, such as retail, have invested in CCM. However, in all cases, education and preparedness (or the lack thereof) appeared to significantly influence uptake of CCM. Organizations that made prior investments in CCM technologies experienced greater acceptance in the face of changing demands. Training in emerging technologies is a key competency in supporting audit operations in changing environments. Research limitations/implicationsAs the study was conducted with a small sample of cases, findings cannot be extrapolated nor generalized beyond the case study organizations. Practical implicationsThis study found that several factors limit adoption, exploitation and further development of CCM technologies, such as lack of top management support, acceptance of CCM technologies and suitable education and training of internal audit staff. Originality/valueThis study addresses the issue of the value that CCM offers organizations and whether it is a silver bullet that the internal audit profession needs, particularly when physical access to organizations may be restricted. The COVID-19 pandemic placed considerable focus on digital access. Better IT systems and more data will allow organizations to better support employees, inform strategic and financial decisions and engage stakeholders. During the recovery phase, leveraging investments in CCM technologies will contribute to internal audits' ability to help clients to manage organizational risk.

Clinical characteristics and outcome of older patients with severe COVID-19: a retrospective observational study

Introduction: The objective of the study was to assess the relevant laboratory and clinical factors that may affect the prognosis of patients with severe COVID-19 in older population. Very few studies have specifically investigated the age-specific factors that affect the outcome of the patient in elderly patients [1,2]. Method(s): The study population was adults (>= 60 years) with severe COVID-19 admitted to the intensive care unit of a tertiary care hospital between March 2021 and June 2021. Binomial logistic regression analysis was used to analyze all variables as potential predictors for the death of older patients. Result(s): In total, 113 older patients with severe COVID-19, with a median age of 68 years (interquartile range (IQR) 63-74), mortality rate was 61.9%. At admission, the median PO2/FiO2 ratio of the patients was 100 (IQR 90-150) and 33.6% were on mechanical ventilation. Binomial logistic regression showed that total leucocyte counts (TLC), platelet counts (PC), lactate dehydrogenase (LDH), D-dimer, and interleukin- 6 levels were all significantly associated with death. Patients with poor outcomes had significantly lower PO2/ FiO2 ratios at admission, higher TLC, lower PC, higher serum creatinine, and higher LDH as compared to survivals. Patients with poor outcomes had a significantly higher percentage of chronic kidney disease patients (20% vs 4%), and patients who didn't receive remdesivir (27% vs 2.3%). Conclusion(s): Increased TLC, LDH, D-Dimer, IL-6, and decreased PC are associated with poor outcomes. The use of remdesivir may increase the chance of survival in older patients.

Biomarkers of renal injury as early predictors of COVID-19 associated AKI: a prospective observational trial (BRICOAKI-trial)

Introduction: Early prediction by the use of serum and urinary biomarkers for the detection of acute kidney injury (AKI) may be very valuable to optimize the management and helps in improving the outcomes. This study aims to investigate whether daily measurement of urinary and plasma renal biomarkers have a role in earlier predicting COVID-19 associated AKI. Method(s): The study was conducted as a single-center, prospective, observational cohort study between August 2020 and December 2020 in hospitalized COVID-19 patients. A total of 65 moderate and severe COVID-19 positive adult (>= 18 years) patients were enrolled for this study. We measured serum creatinine, cystatin C, NGAL, KIM-1, Urine-Klotho, TIMP-2, IL-6 level, and urinary microalbumin/urinary creatinine on various days. The receiver operating characteristic curve (ROC) analysis was used to find the sensitivity and specificity of various markers to predict the incidence of AKI. Result(s): A total of 24 moderate and 41 severe COVID-19 patients were included. Out of which 47 patients developed (72.3%) acute kidney injury (AKI) over the course of COVID-19. Among these subjects, 18/47 (38.2%) developed severe AKI (KDIGO 2 + 3), and 5/47 (10.6%) required RRT. NGAL was found to be the best marker to predict the probability of AKI (Area under curve AUC of 0.713-0.786) with a sensitivity of 76-90% and specificity of 56-79% on different days of assessment from Day 1 to Day 7. IL-6 had moderate accuracy of prediction and cystatin C, KIM-1, Urine-Klotho, TIMP-2, IL-6 had poor accuracy for predicting the incidence of AKI. Conclusion(s): Urinary biomarkers like NGAL have good predictability for AKI.

An Enhanced Multipath TCP: E-Adoption of Emerging Technology for Better Internet Bandwidth

Since 2020, the coronavirus disease 2019 (COVID-19) pandemic and lockdown policy have changed our life drastically. Due to this, companies, offices, schools, etc. are running in online mode. Therefore, the demand for internet bandwidth is very popular nowadays. Due to an increase in demand for internet bandwidth and the availability of multihomed devices, multipath TCP (MPTCP), and e-adoption of emerging technology enhanced bandwidth by utilizing the bandwidth of all available networks simultaneously. This paper analyzes the working principle of the MPTCP so that each internet device can easily use MPTCP to achieve high bandwidth. Load distribution and its performance mainly depend on the congestion control algorithm and the packet scheduler. MPTCP has various existing packet scheduling algorithms and congestion control algorithms. Here, the authors compare the performance of MPTCP with each congestion control algorithm and packet scheduler one by one and try to find out the best-performing MPTCP. This paper also shows that the MPTCP helps COVID-19 patients in various aspects.

Divergence between economic growth and stock market performance in India: implications for investor education and financial well-being

Amidst declining trends of Indian macroeconomic indicators during COVID-19 period, certain indicators, which can be takes as proxies of investors' behaviour, sentiments and biases, were discerned in Indian securities markets. The study provides significant insight into sentiments and biases of a particular segment of retail investors trading in uncertain times of COVID-19, whose investment behaviour may have serious impact on their financial well-being in the long-term. This exploratory-descriptive study uses data collected by various regulators and government sources in India and abroad to evaluate the behaviour of investors in the backdrop of macroeconomic trends during COVID-19. After analysing the trends of investor participation, trading behaviour and general sentiment in the Indian capital markets and evaluating the implications of these investor-related behaviours on the financial well-being of individual investors, a comprehensive and segmented approach of financial literacy has been recommended to safeguard financial well-being of investors.

Machine Learning-Based COVID-19 Classification Using E-Adopted CT Scans

In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.

Machine Learning-Based COVID-19 Classification Using E-Adopted CT Scans

In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.

COVID-19 Data Clustering Using K-means and Fuzzy c-means Algorithm

Corona Virus Disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory symptoms. It has been declared a global pandemic since 2019 by the World Health Organization. Countries are in an authoritarian state of preventing and controlling this pandemic, and the USA is the central hub. The COVID-19 virus has also shown variance. As an outcome of the genetic recombination of genes that arise from coronavirus, their short life span results in mutations that promote new strains. However, the number of individuals who passed their lives is still counted. Additionally, it is crucial to analyze the spread of the virus before it is deferred in the lungs. In this research, the effort has been taken to predict the proliferation of the virus through various chest radiography images by data clustering. In this study, two clustering algorithms, i.e., the K-means algorithm and the Fuzzy c-means algorithm, have been used better to analyze the spread of the virus in the lungs. These algorithms are further being compared and evaluated for the precise result of both models. This study helps to recognize the most suitable clustering model for the COVID-19 prediction and spread of the virus in the lung. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Labour welfare and industrial hygiene during COVID-19

This .study aims to define essential principles that the organization must follow in labour welfare during COVID-19. It is a vital facet of industrial relations, the extra dimension that provides satisfaction to workers in a way that no amount of money can do so. The government initiates statutory laws from time to time to bring about some uniformity in the basic facilities provided to industrial workers since it is not confident that all employers are progressive and provide basic welfare measures. Industrial hygiene has been defined as science and art devoted to the anticipation, recognition, evaluation, and control of those environmental factors or stress arising in or from the workplace, which may cause sickness, impaired health, and significant stress among workers or the citizens of the community. Because it is a labor-intensive sector, it has a greater emphasis on employee welfare. The authors choose a bakery industry personnel's stress analysis during COVID-19 for this research work. © 2023 by IGI Global. All rights reserved.

A review on synthetic methods for 2-Deoxy-D-glucose

2-Deoxy-D-glucose (2-DG) is a non-metabolizable glucose analog that has shown promising pharmacological activities and has been used to study the role of glucose in cancer cells. 2-DG is an inhibitor of glycolysis, potential Energy Restriction Mimetic agent and inhibits pathogen-associated molecular patterns. Its radioisotope derivatives have application as tracers. Recently, 2-DG has been used as an anti-COVID-19 drug lowering the need for supplemental oxygen. In this review, different synthetic strategies for preparation of 2-DG including enzymatic synthesis have been discussed. The understanding of these methods would help in developing therapeutics or diagnostic agents aimed at exploring therapeutic targets related with energy metabolism. © AUTHOR(S).

Structure property relationship in two thiazole derivatives: Insights of crystal structure, Hirshfeld surface, DFT, QTAIM, NBO and molecular docking studies

Detailed structural and noncovalent interactions in two thiazole derivatives (N-(4-Bromophenyl)-2-(methylthio)thiazole-5-carboxamide and Ethyl-5-((4-bromophenyl)carbamoyl)thiazole-4-carboxylate) are investigated by single crystal X-ray diffraction study and computational approaches. The structure investigation revealed that various interactions like C-H…O, N-H…O, and N-H…N hydrogen bonds and Br…Br interactions are involved in constructing ring motifs to stabilize the crystal packing. Hirshfeld surface analysis and fingerprint plots were carried out to study the differences and similarities in the relative contribution of noncovalent interactions in both the molecules. The FMOs and other global reactive parameters are analyzed for thiazole derivatives. The strength and nature of weak interactions present in the molecule were characterized by RDG-based NCI and QTAIM analyses. Natural bond orbital (NBO) analysis unravels the importance of non-covalent and hyperconjugative interactions for the stability of the molecules in their solid state. Further, molecular docking of N-(4-Bromophenyl)-2-(methylthio)thiazole-5-carboxamide and Ethyl-5-((4-bromophenyl)carbamoyl)thiazole-4-carboxylate with SARS-Covid-19 have been carried out. © 2023 Taylor & Francis Group, LLC.

Investigation of seroprevalence of SARS-CoV-2 IgG antibodies among healthcare workers in a tertiary care centre in district Amritsar

Background: SARS-CoV-2 infection poses tremendous challenge to the healthcare system of nations across the globe. Healthcare workers (HCWs) are crucial to the ongoing response to the SARS-CoV-2 pandemic. During the course of their work, they are exposed to hazards that place them at the risk of infection. Serological testing for SARS-CoV2 among healthcare workers, which form a high risk group helps in identifying the burden of hidden infection in an institutional setting. The present study aims to investigate the seroprevalence of IgG antibodies against SARS-CoV-2 among HCWs during 1st and 2nd wave. Material & Methods: A prospective study was conducted at Viral Research and Diagnostic Laboratory, Government Medical College, Amritsar during June July 2020 (1st wave)and April May 2021(2nd wave). During this period, 184 blood samples were collected from healthcare workers from Government Medical College and Hospital, Amritsar. Serum was separated and used for detection of Anti-SARS-CoV-2 IgG antibodies by ELISA technique. Results: Out of the 184 samples, 79 (42.9%) were found to be seropositive. Higher seropositivity was seen i.e 60.8% during the 2nd wave (April-May 2021) as compared to 25% during 1st wave. The increase in seroprevalence was observed in almost all categories of HCWs, Doctors 44.4% vz 13.04%, nurses 54.8% vz 34.7%, lab technicians 72% vz 30.4% and housekeeping staff 72.2% vz 21.7%. Also the unvaccinated HCWs showed higher seroprevalence during the second wave and 87.5% of vaccinated HCWs had demonstrable IgG antibodies. Conclusions: High seropositivity was observed among healthcare workers due to their nature of work. Rise of seropositivity among unvaccinated HCWs during 2nd wave concludes that increase in seroprevalence was attributable to natural infection. The vaccine's immunological response was also highlighted in the study.

Digital Platforms and Craft Workers in India in the Time of COVID

The COVID-19 lockdown situation has raised important socio-economic issues within the craft industry in India. This paper specifically proposes to discuss to what extent the pandemic has strengthened the use of digital platforms and accelerated certain reconfiguration processes within the craft industry. E-commerce platforms have been recently investing in this sector, from local entrepreneurs' initiatives and governmental interventions to large e-commerce platforms (Amazon, Flipkart etc.). The idea is to examine the adaptation of work dynamics in a largely informal and precarious sector, the changes in terms of platform strategies, and the way in which the pandemic may have reinforced processes of dependency on certain digital players. Based on the case of the craft industry in India's North-East region, this paper will rely on qualitative methodology associating document analysis and fieldwork conducted before the lockdown in February 2020 in Assam, and followed by online interviews conducted after several months of lockdown. © OpenEditions Journals. All Rights Reserved.