Are ESG Stocks Safe-Haven during COVID-19?

This study contributes to the debate on safe-haven characteristics of environmental, social, and governance (ESG) stocks during COVID-19 pandemic. Using wavelet coherence framework on four major ESG stock indices from global and emerging stock markets, and two proxies of COVID-19 fear over the period from February 5th, 2020, to March 18th, 2021, we find a strong and positive co-movement between health fear index of COVID-19 and returns on ESG stocks suggesting the existence of safe-haven properties in ESG stocks. However, we also observe a negative co-movement between stock market base proxy of COVID-19 and returns on ESG indices, suggesting that safe-haven properties of ESG stocks are contingent upon the proxy of COVID-19 pandemic. Our findings are of particular interest for the investors and asset managers who may use ESG stocks to diversify their portfolios during health crisis due to COVID-19 pandemic

On the Simulation of Turbulent Fluid-Structure Interaction

The fluid-structure interaction (FSI) phenomena are relevant in a significant number of naturally occurring as well as industrial applications. Simulations of FSI have gained noteworthy attention with rapid advancements of computational technology in the last decade. Efficiency and accuracy of these simulations are still a concern, specially with a turbulent flow, the challenge is compounded by an additional computational cost for a turbulence modeling approach. Partitioned coupling approaches owing to software modularity and reusability are favored by engineers to solve FSI problems. The turbulence in flow is simulated through models with varying levels of complexity and computational requirements. In industrial applications, the use of Reynolds Averaged Navier Stokes (RANS) modeling of turbulence is dominant, whereas turbulence resolving approaches like Large-Eddy simulation (LES) are still not considered feasible due to computational requirements. To get as much accuracy by using as least as possible computer resources, a reasonable compromise are hybrid RANS-LES of turbulence, which are becoming more and more frequent. The goal of this work is to enable efficient and reliable simulations of FSI in turbulent flow. To this end, validation studies of three different turbulence modeling approaches available in the in-house flow solver FASTEST are performed. The structural subproblem in the coupling environment is solved with the Finite Element Method based code FEAP, while the data transfer and interpolation on non-matching grid interfaces can be handled with MpCCI or preCICE. For this work, the turbulence modeling approaches in FASTEST are extended with an implementation of the Wall Adapting Local Eddy (WALE) viscosity model for LES, and a validation study of the model is performed for a two dimensional periodic hill flow test case. An economical method based on a Poisson equation for the calculation of the nearest wall distance is also implemented, which is required by some turbulence models. The accuracy of the method is assessed with two computations on stationary grids. In turbulent flow simulations with moving grids, the height of cells on a wall changes and it can make a wall treatment approach unsuitable. This issue is addressed with an implementation of wall boundary conditions that work regardless of the first cell position in a boundary layer. The implementation is tested on stationary grids in a channel flow with a variation of the first cell height on the wall. A test of the method with an FSI test case showed satisfactory results. Validation studies of a RANS and a hybrid RANS-LES approach are performed with simulations of two FSI test cases. The two and three dimensional RANS and the hybrid RANS-LES produce a good agreement with the experimental results for oscillation characteristics of the structure. A hybrid RANS-LES and an LES is performed for another FSI test case with a very dense mesh. The LES and the hybrid RANS-LES on two different, but relatively dense meshes produced very similar results with a satisfactory prediction of the structural deflections

Screening of Diabetes and HIV Infection in Newly Diagnosed Pulmonary Tuberculosis Patients

Objective: Aim of the study was to investigate the prevalence of diabetes and HIV infection by screening in newly diagnosed pulmonary tuberculosis patients. Methods: This cross sectional study was conducted in Pulmonology department Bahawal Victoria Hospital Bahawalpur.  From  1 June 2018 to 1 June 2019 after taking approval from the institutional ethical committee. Total 159 newly diagnosed pulmonary tuberculosis patients were recruited by non-probability consecutive sampling. Mean and SD was calculated for numerical variables like age , BMI, FBG, Hemoglobin and monthly income. Ferquancy and percentages were calculated for categorical variables like gender, smooking status, educational status, alcohol consumption, prevelance of HIV and diabetes, Ch square test was use to check significant different in PTB and Non PTB patients. P value of < 0.05 was taken as significant. Results: Significant difference was found between age (p=0.000), BMI (p=0.000), FBG (p=0.000), hemoglobin (p=0.000), gender (p=0.002) and alcohol consumption (p=0.034), in groups, except education status (p=0.090) and monthly income (p=0.068). The main outcome variables of this study were HIV infection and diabetes. HIV infection was noted in 3.1% (n=5) and 1.9% (n=3) patients for PTB and non-PTB group respectively. While, 8.2% (n=13) and 4.4% (n=4) patients suffered from diabetes, for both the groups respectively. Conclusion: The results of our study revealed that on screening of newly diagnosed pulmonary tuberculosis patients with HIV infection and diabetes, their prevalence was high as compared to non-pulmonary tuberculosis group. But this difference was statistically non significant (P value 0.474 and 0.166). Key words:   Pulmonary tuberculosis, Diabetes, HIV infection DOI: 10.7176/JMPB/55-21 Publication date:May 31st 201

Frequency of various risk factors for Meconium aspiration syndrome

Objective: To study the frequency of various factor leading to meconium aspiration syndrome. Material & Method: This present descriptive cross sectional study was carried out at Department of Pediatrics Medicine Bahawal Victoria  Hospital Multan. for 6 months i.e. from October 8, 2018 to April 8, 2019. The non-probability, consecutive sampling technique was used. Newborns having staining of vocal cords and respiratory distress were included in this study. ABG and X ray Chest was done in all neonates. Factors like, Post-term pregnancy, IUGR, thick meconium, low APGAR score at 1 and 5 minutes were noted. All the collected data was entered and analyzed on SPSS version 23. Chi square and T test were used to check significant relation of risk factors with meconium aspiration syndrome. P value of 0,05 was consider significant. Results: Among total enrolled 150 babies, the mean age of babies was 37.37±18.96 hours, the male to female ratio of the babies was 1.03:1. The mean maternal age was 28.85±6.602 years. The thick meconium was observed in 89(59.33%) patients, 79(52.7%) patients went through vaginal delivery, postdate pregnancy was noted in 68(45.3%) patients, IUGR was observed in 52(34.7%) patients and poor APGAR score at 1 min was noted in 79(52.7%) patients. Conclusion: The observations of our study revealed that Meconium aspiration syndrome has significant relation with maternal age(P value 0.000), postdated pregnancy(P Value 0.001), IUGR (P value 0.021), poor APGAR score at 5 minutes( P value 0.034), and thick meconium(P value 0.000). Keywords: Postdate, Meconium  Aspiration , Syndrome, APGAR, Pregnancy DOI: 10.7176/JMPB/55-19 Publication date:May 31st 201

Are Cryptos Safe-Haven Assets during COVID-19? Evidence from Wavelet Coherence Analysis

We use wavelet coherence analysis on global COVID-19 fear index, cryptocurrency market specific implied volatility index (VCRIX) and cryptocurrency returns to investigate safe-haven properties of cryptocurrencies during COVID-19 pandemic. The findings of our paper show that a non-financial market-based proxy of market stress that represents fear of households and retail investors reveals cryptocurrencies as safe-haven assets; however, a financial market-based proxy of the market turbulence exposes that cryptocurrencies behave like traditional assets during the times of COVID-19 pandemic. Our findings support that long-term investors can invest in the cryptocurrency market to hedge the risks during the COVID-19 pandemic

Cyclicality of Capital Adequacy Ratios in Heterogeneous Environment: a Non-linear Panel Smooth Transition Regression Explanation

This study aims to investigate the cyclicality of capital adequacy ratios (CARs) in US bank holding companies using a new business cycle index and a non-linear panel smooth transition regression model. The suggested index can predict US business activity with a higher accuracy than existing proxies, while the regression methodology deals with the heterogeneity bias of linear models and can capture asymmetric effects, thus improving forecasting efficiency. Our results show that the equity capital to assets ratio is countercyclical, while the risk-based capital adequacy ratios are procyclical. In addition, the response of capital adequacy ratios to changes in economic activity is asymmetric across recessions and expansions. The findings of this study can assist policymakers and bank regulators as the estimation of capital adequacy ratios using the non-linear method and new proxy of BC can improve both the time-lag and accuracy issues in the regulators’ decision making and results in improved compliance behavior of the banks