The impact of female dominance on business resilience: A technology adoption perspective

This study explores the relationship between women entrepreneurship and business resilience, the moderation of pre-crisis and during-crisis technology adoption, and female representation in top management in the aforementioned relationship. Building on the "mom-cession” theory, the authors propose an integrated multiple-moderation model to understand the boundary conditions that can reduce the negative effect of female dominance on business resilience. Using a sample of 9035 firms across 24 countries and employing a structural equation modeling technique for model testing, this study found a negative relationship between female dominance and business resilience. Female-dominated firms led by female top managers exhibited lower business resilience. The results showed that firms' pre- and post-COVID-19 technology adoption moderated the negative relationship between female dominance and business resilience such that this relationship was weaker for firms that had already adopted technology before COVID-19 and stronger for firms that adopted technology only during COVID-19. © 2023 Elsevier Inc.

Impact of geo-political risk on stocks, oil, and gold returns during GFC, COVID-19, and Russian–Ukraine War

The study uses wavelet power spectrum and wavelet coherence transformation methodologies to examine how geopolitical risk affected the returns on stocks, oil, and gold during the GFC, COVID-19, and Russia-Ukraine war-three disruptive events that affected the world's financial markets. For better diversification benefits during the turbulent times, we further investigate the degree of co-movement in frequency and time domains. We observe that GPR has high variations during Russia-Ukraine war period compared to COVID-19 period and is shown to have least variation during the GFC period. WTI crude oil and DJGI indexes are observed to have high variations during GFC, and COVID-19 periods followed by Russia-Ukraine war. We further observe that GOLD offers better diversification opportunity as well as leading movement against WTI and DJGI during disruptive events in financial markets. The results provide new understanding of how geopolitical risk affects financial assets for international investors, fund managers, and regulators, which would further aid to find risky and safer haven possibilities during the turmoil periods. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Deranged Liver Enzymes in COVID-19 Patients;and its Impacts on Prognosis

Objectives: The objective of this study was to investigate derangement of liver enzymes in COVID-19 patients. The prevalence of deranged hepatic enzymes with COVID-19 infection, its association with other co-morbidities and any changes in its prognosis were investigated. Methodology: This study was conducted in Mayo hospital from 1st June 2021 till 31st September 2021. A number of 224 patients were included in this study. Both male and female patients of varying age groups were included in the study. Laboratory tests were conducted to collect data related to liver enzyme values of each patient. Liver function test (LFT) was performed twice, first on day 1 and then on day 7 to observe any further changes in liver enzymes values in COVID-19 patients. The LFTs of the patients told us Bilirubin, Alanine aminotransferase (ALT), Alkaline Phosphatase (ALP), C-reactive protein (CRP), Ferritin and D-dimer levels in the body. The data were analyzed by SPSS analysis. The t-test used was for the comparison of standard features in both groups. The P value less than 0.05 was regarded significant. Data about co-morbidities, autoimmune disease and its treatment, and outcome was also collected. Gender, autoimmune disease and COVID-19 PCR data was analyzed using descriptive analysis. Prevalence of deranged liver enzymes in COVID-19 patients was analyzed using paired sample test. Association with co-morbidities and prognosis was also analyzed by frequency analysis. Result(s): Sample consists of 224 individuals among them the ratio of male and female was 50:50 with age ranging 17-90 years. There were 220 COVID-19 PCR positive patients, 1 negative and 3 suspected patients with about 89.7 per cent patients having no autoimmune disease. The results showed that bilirubin, ALT and D-dimer show significant derangement in COVID-19 patients while ALP, CRP and Ferritin did not. The patients with both diabetes mellitus and hypertension showed the highest percentage of association with the value being 25 percent. Other co-morbidities like asthma, chronic liver disease and hepatitis C among many other also showed association with corona virus disease. And the results of prognosis showed that 33 percent, of the patients were shifted to the ICU. 18.8 percent of the patients were admitted in the hospital. 20.5 percent of the patients died. 18.8 percent were discharged and 6.3 percent shifted to the HDU. Conclusion(s): As the results show liver enzyme ALT, D-dimer and bilirubin show significant derangement in COVID-19 patients. This concludes that some, but not all, of the liver enzyme derangement is prevalent in COVID-19 patients. The patients with both diabetes mellitus and hypertension showed highest association with COVID-19. The patients being shifted to the ICU was the highest prognosis of disease. Other than that a large number of patients died, some were admitted to the hospital due to worsening condition, some discharged and others shifted to the HDU. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.

Role of adenosine receptors in cardiovascular disorders and novel corona virus infection

Objective: To assess the importance of adenosine signaling in cardiovascular disorders (thrombosis, ischemia) and novel corona virus infection. Methodology: A specified web search was done to gather the relevant information using different scientific research forums and databases like WHO database, Pubmed and Google Scholar etc. Results: Adenosine receptors are P1 type of purinergic receptors and belong to G protein-coupled receptors (GPCRs), which is the largest family of integral membrane bound proteins receptors. Adenosine receptors are further classified into four subclasses known as A1, A2A, A2B, and A3. All four subclasses are being mediated by extracellular adenosine and perform a key role in a wide range of physiological functions such as immune system modulation, angiogenesis and sleep regulation. Adenosine receptors are thought to play a significant role in many pathophysiological conditions including cardiovascular disorders such as ischemia and thrombosis and novel corona virus infection making it a key target against these disorders. Conclusion: We suggest that modulation of adenosine receptor activity could increase the regenerative phase in these disorders by increasing the proliferation and differentiation rates of damaged tissue.

Time Varying Impact of Oil Prices on Stock Returns: Evidence from Developing Markets

In this study, we provide new evidence on the relationship between crude oil, exchange rate and stock returns before and after the official announcement of COVID-19 as a pandemic by WHO. Data for the present study consists of the major stock indices of ten emerging markets (Brazil, China, India, Indonesia, Mexico, Russia, Saudi Arabia, South Africa, Taiwan and Thailand), their exchange rates, and prices of Brent crude oil. We employ panel vector autoregression and provide evidence based on panel granger causality, impulse response function and forecast error variance decomposition. Panel granger causality reveals that after the declaration of COVID-19 as pandemic, interdependence between oil price changes and stock returns has increased. We find positive (negative) impact of oil market (exchange rate) shocks on stock returns. Analysis of impulse response suggests that during pandemic shocks to crude oil, exchange rate and stock market have larger and longer own and cross-market impact. Thus, there is a need for sharing timely and adequate information to minimize uncertainties in financial and commodity markets. This would benefit investors by lessening the transmission of shocks during the times of crisis. © 2022 WITPress. All rights reserved.

COVID-Beat: a low-cost breath monitoring approach for people in quarantine during the pandemic

Due to COVID-19, people have to adapt to the new lifestyle until scientists develop a permanent solution for this pandemic. Monitoring the respiration rate is very important for a COVID-infected person because the Coronavirus infects the pulmonary system of the person. Two problems that arise while monitoring the breath rate are: sensors are contact based and expensive for mass deployment. A conventional wearable breath rate monitoring system burdens the COVID-affected patient and exposes the caregivers to possible transmission. A contactless low-cost breath monitoring system is required, which monitors and records the breath rate continuously. This paper proposes a breath rate monitoring system called COVID-Beat, a wireless, low-cost, and contactless Wi-Fi-based continuous breath monitoring system. This sensor is developed using off-the-shelf commonly available embedded Internet of Thing device ESP32, and the performance is validated by conducting extensive experimentation. The breath rate is estimated by extracting the channel state information of the subcarriers. The system estimates the breath rate with a maximum accuracy of 99% and a minimum accuracy of 91%, achieved by advanced subcarrier selection and fusion method. The experimental results show superior performance over the existing breath rate monitoring technologies.

Oral Health Issues During Pregnancy

Objective: To find out what oral health issues women face during pregnancy. Study Design: A cross-sectional observational study Place and Duration of Study: This study was conducted at the Chiniot General Hospital Korangi Karachi's Dental OPD from November 2019 to July 2020. Materials and Methods: This study was originally intended to involve 150 pregnant women, however owing to the COVID-19 crisis and the closing of dental OPDs, many pregnant women are unable to get dental check-ups and appointments. Thus, 90 individuals' data was gathered, encompassing all phases of pregnancy, and the outcomes of 90 people were analyzed. Each participant gave their informed consent prior to the start of data collection. Results: Seven components were examined during the oral examination. The first was the oral hygiene status, which revealed that 24 women (26.7 percent) had good oral hygiene, whereas 66 women had terrible oral hygiene (73.3 percent). Second, 74 (82.2%) pregnant women had gingival bleeding on probing, which was followed by visible plaque in 77 (85.6%) women, caries activity in 83 (92.2%) women, and extra oral edoema in 14 (15.6%) women. Finally, 78 (86.7%) of the women showed gingival edoema, with 35 (38.9) having localized swelling. Conclusion: The significance of dental care throughout pregnancy, as well as sociodemographic differences in clinical OH during pregnancy, are highlighted in this study, which provides important results for customizing treatments for pregnant women. © 2022 Medical Forum Monthly. All rights reserved.

Prevalence of Dental Pain During Pregnancy

Objective: The purpose of this study was to find out how often oral pain is during pregnancy. Study Design: Cross-sectional observational study Place and Duration of Study: This study was conducted at the Dental OPD of Chiniot General Hospital Korangi Karachi from Nov 2019 to July 2020 for a period of nine months. Materials and Methods: This study was initially designed to include 150 pregnant females but due to COVID-19 situation and OPDs closure restrict many pregnant females for their dental check-ups and appointments in Dental OPDs. Thus, the data collected of 90 participants including all stages of pregnancy and the analysis was done on the results of 90 participants. Before the commencement of data collection, each participant was given an informed consent. Results: Among the study participants (n=90) who sought dental care, 64 (71.1%) presented with dental pain while 26(28.9%) presented with periodontal symptoms. Conclusion: A high prevalence of dental pain was observed among pregnant women and dental caries was the most specific determinant of the dental pain. © 2021 Medical Forum Monthly. All rights reserved.

IMPACT OF SARS-COV-2 INFECTION IN WAITING LIST FOR LIVER TRANSPLANTATION

Background and aim: Infections in cirrhotic patients are associated with an increased risk of liver-related complications (LRC) and mortality. Limited data regarding the prevalence of Coronavirus disease (COVID-19) in cirrhotic patients’ awaiting liver transplantation (LT) are available. The aim of this study was to evaluate the prevalence of SARS-CoV2 in a cohort of cirrhotic patients and its impact on LRC rate and on LT.Materials and methods: We retrospectively included 187 waitlist patients for LT from 24-January-2020 (2020-cohort) and 123 patients from 24-January-2019 (2019-cohort). All 2020-cohort patients were screened for COVID-19 symptoms with a survey. COVID-19 infection was defined by a positive PCR assay for SARS-CoV-2 on nasopharyngeal swab or the positivity for specific antibodies or typical lung lesions on CT scan. We also assessed the indirect impact of SARSCoV2 infection on LRC and LT rate, estimated by competitive risk survival analyses in 2020-cohort vs. 2019-cohort (Fine and Gray method).Results: In 2020-cohort, 72.7% (n=136) of patients were male with mean age of 55.5±12, 47.2% (n=85) patients have alcohol and/or NASH related cirrhosis, with a median MELD score of 14.1±7.4. 45.5% (n=71), 38.5% (n=60) and 14.8% (n=23) of patients were A, B and C for Child-Pugh-score, respectively. 172 patients responded to survey and 22% (n= 38) had symptoms. 20/38 patients were tested for SARS-CoV2 and 4 patients were positive. 3/4 patients with COVID-19 disease needed hospitalization and 1 intensive care support. No death was reported and 1 patient was LT. The 2020-cohort and 2019-cohort were comparable for sex (p=0,6), age (p=0.7), comorbidities (p=0.2) and Child-Pugh-score (p=0.2). The cumulative incidence of LRC was not significantly higher in the 2020-cohort vs. 2019-cohort (SHR 0.65, 95% CI 0.36-1.15, p=0.138). The cumulative incidence of LT was significantly lower in the 2020-cohort than in the 2019-cohort (SHR0.21, 95% CI 0.13-0.33, p<0.001). Conclusions: Our study reported a low prevalence rate of SARSCoV2 infection in a cohort of cirrhotic patients waiting for LT. No SARS-CoV2 infection direct or indirect impact on mortality and LRC rate was reported. However, a significant shortage of LT was found in 2020 cohort.

Impact of sars-cov-2 infection in waiting list for liver transplantation: A cohort study on clinical outcomes

Purpose: Infections in cirrhotic patients are associated with an increased risk of liverrelated complications (LRC) and mortality. Limited data regarding the prevalence of Coronavirus disease (COVID-19) in cirrhotic patients' awaiting liver transplantation (LT) are available. The aim of this study was to evaluate the prevalence of Sars-cov2 in a cohort of cirrhotic patients and its impact on LRC rate and on LT. Methods: We retrospectively included 187 waitlist patients for LT from 24-January-2020 (2020-cohort) and 123 patients from 24-January-2019 (2019-cohort). All 2020-cohort patients were screened for COVID-19 symptoms with a survey. COVID-19 infection was defined by a positive PCR assay for SARS-CoV-2 on nasopharyngeal swab or the positivity for specific antibodies or typical lung lesions on CT scan. We also assessed the indirect impact of Sars-Cov2 infection on LRC and LT rate, estimated by competitive risk survival analyses in 2020-cohort vs. 2019-cohort (Fine and Gray method). Results: In 2020-cohort, 72.7% (n=136) of patients were male with mean age of 55.5±12, 47.2% (n=85) patients have alcohol and/or NASH related cirrhosis, with a median MELD score of 14.1±7.4. 45.5% (n=71), 38.5% (n=60) and 14.8% (n=23) of patients were A, B and C for Child-Pugh-score, respectively. 172 patients responded to survey and 22% (n= 38) had symptoms. 20/38 patients were tested for Sars-Cov2 and 4 patients were positive. 3/4 patients with COVID-19 disease needed hospitalization and 1 intensive care support. No death was reported and 1 patient was LT. The 2020-cohort and 2019-cohort were comparable for sex (p=0,6), age (p=0.7), comorbidities (p=0.2) and Child-Pugh-score (p=0.2). The cumulative incidence of LRC was not significantly higher in the 2020-cohort vs. 2019-cohort (SHR 0.65, 95% CI 0.36-1.15, p=0.138). The cumulative incidence of LT was significantly lower in the 2020-cohort than in the 2019-cohort (SHR0.21, 95% CI 0.13-0.33, p<0.001). Conclusions: Our study reported a low prevalence rate of Sars-Cov2 infection in a cohort of cirrhotic patients waiting for LT. No Sars-Cov2 infection direct or indirect impact on mortality and LRC rate was reported. However, a significant shortage of LT was found in 2020 cohort.

Lies Kill, Facts Save: Detecting COVID-19 Misinformation in Twitter.

Online social networks (ONSs) such as Twitter have grown to be very useful tools for the dissemination of information. However, they have also become a fertile ground for the spread of false information, particularly regarding the ongoing coronavirus disease 2019 (COVID-19) pandemic. Best described as an infodemic, there is a great need, now more than ever, for scientific fact-checking and misinformation detection regarding the dangers posed by these tools with regards to COVID-19. In this article, we analyze the credibility of information shared on Twitter pertaining the COVID-19 pandemic. For our analysis, we propose an ensemble-learning-based framework for verifying the credibility of a vast number of tweets. In particular, we carry out analyses of a large dataset of tweets conveying information regarding COVID-19. In our approach, we classify the information into two categories: credible or non-credible. Our classifications of tweet credibility are based on various features, including tweet- and user-level features. We conduct multiple experiments on the collected and labeled dataset. The results obtained with the proposed framework reveal high accuracy in detecting credible and non-credible tweets containing COVID-19 information.

Effectiveness of Noninvasive Positive Pressure Ventilation in COVID-19 Patients with Severe Acute Respiratory Distress Syndrome

Results of invasive positive pressure ventilation (IPPV) in COVID-19 patients with Severe Acute Respiratory Distress Syndrome are discouraging despite its prompt use. However noninvasive positive pressure ventilation (NIPPV) is yet not a common practice internationally because of lack of global evidence advocating its effective use in severe cases of ARDS as well as dreadful concern about aerosol generation especially in patients having COVID-19 infection. Objective: To determine whether, NIPPV application is effective and safe in COVID-19 Patients. Methods: One hundred and thirty hemodynamically stable patients with severe CARDS as per Berlin definition (PaO2/FiO2 ratio <= 100mm Hg), having GCS > 13, respiratory breathing index (RBI) < 105, and without any systemic complication were selected. They were managed with NIPPV in Corona Intensive Care Unit of Mayo Hospital/King Edward Medical University Lahore. A little innovation was done with the application of a specific orofacial interface, fitted with heat and moist exchanger (HME) at the interface and viral/bacterial filters at the expiratory limb of ventilatory circuit. Favorable outcome has been observed in 64% of treated cases in terms of improvement in PaO2/FiO2 ratio, thus abating severity of ARDS from severe to mild category, in an average time span of 6 days. Remaining 36% of patients progressed to IPPV with definitive airway. During study period, 4.2% of healthcare workers (HCW) got infected with COVID-19. Associated complications of NIPPV application were claustrophobia (13.8%), nasal crusting (6.9%), aspiration (6.1%) and barotrauma (0.7%). Conclusion: In carefully selected patients, use of noninvasive positive pressure ventilation with the application of HME and viral/bacterial filters is an effective, preferable and safe modality of choice to provide respiratory support, thus obviating the need for IPPV. However further larger studies are needed to confirm our recommendations.

Automated image classification of chest X-rays of COVID-19 using deep transfer learning.

INTRODUCTION: In December 2019, the city of Wuhan, located in the Hubei province of China became the epicentre of an outbreak of a pandemic called COVID-19 by the World Health Organisation. The detection of this virus by rRTPCR (Real-Time Reverse Transcription-Polymerase Chain Reaction) tests reported high false negative rate. The manifestations of CXR (Chest X-Ray) images contained salient features of the virus. The objective of this paper is to establish the application of an early automated screening model that uses low computational power coupled with raw radiology images to assist the physicians and radiologists in the early detection and isolation of potential positive COVID-19 patients, to stop the rapid spread of the virus in vulnerable countries with limited hospital capacities and low doctor to patient ratio in order to prevent the escalating death rates. MATERIALS AND METHODS: Our database consists of 447 and 447 CXR images of COVID-19 and Nofindings respectively, a total of 894 CXR images. They were then divided into 4 parts namely training, validation, testing and local/Aligarh dataset. The 4th (local/Aligarh) folder of the dataset was created to retest the diagnostics efficacy of our model on a developing nation such as India (Images from J.N.M.C., Aligarh, Uttar Pradesh, India). We used an Artificial Intelligence technique called CNN (Convolutional Neural Network). The architecture based on CNN used was MobileNet. MobileNet makes it faster than the ordinary convolutional model, while substantially decreasing the computational cost. RESULTS: The experimental results of our model show an accuracy of 96.33%. The F1-score is 93% and 96% for the 1st testing and 2nd testing (local/Aligarh) datasets (Tables 3.3 and 3.4). The false negative (FN) value, for the validation dataset is 6 (Fig. 3.6), for the testing dataset is 0 (Fig. 3.7) and that for the local/Aligarh dataset is 2 . The recall/sensitivity of the classifier is 93% and 96% for the 1st testing and 2nd testing (local/Aligarh) datasets (Tables 3.3 and 3.4). The recall/sensitivity for the detection of specifically COVID-19 (+) for the testing dataset is 88% and for the locally acquired dataset from India is 100%. The False Negative Rate (FNR) is 12% for the testing dataset and 0% for the locally acquired dataset (local/Aligarh). The execution time for the model to predict the input images and classify them is less than 0.1 s. DISCUSSION AND CONCLUSION: The false negative rate is much lower than the standard rRT-PCR tests and even 0% on the locally acquired dataset. This suggests that the established model with end-to-end structure and deep learning technique can be employed to assist radiologists in validating their initial screenings of Chest X-Ray images of COVID-19 in developed and developing nations. Further research is needed to test the model to make it more robust, employ it on multiclass classification and also try sensitise it to identify new strains of COVID-19. This model might help cultivate tele-radiology.

A novel mathematical model for COVID-19 with remedial strategies.

Coronavirus (COVID-19) outbreak from Wuhan, Hubei province in China and spread out all over the World. In this work, a new mathematical model is proposed. The model consists the system of ODEs. The developed model describes the transmission pathways by employing non constant transmission rates with respect to the conditions of environment and epidemiology. There are many mathematical models purposed by many scientists. In this model, " α E " and " α I ", transmission coefficients of the exposed cases to susceptible and infectious cases to susceptible respectively, are included. " δ " as a governmental action and restriction against the spread of coronavirus is also introduced. The RK method of order four (RK4) is employed to solve the model equations. The results are presented for four countries i.e., Pakistan, Italy, Japan, and Spain etc. The parametric study is also performed to validate the proposed model.