This study aims to explore the impact of audit characteristics and gender diversity on firm performance across family and non-family firms in Bangladesh. Using data of 61 non-family and 48 family firms from 2013 to 2019, this study applies system generalised method of moments approach to carry out regression analysis. Next, the consistency of results is detected by a full sample interaction analysis. In case of non-family firm, this study documents that Big4 audit firms (Big4) and female directors on board (FDR) have significant positive impact on firm performance. Conversely, audit meeting frequency (AMF) contributes negatively to the firm performance. Unfortunately, audit committee size (ACS) and audit committee independence (ACI) have no significant contribution on firm performance. In case of family firms, this study finds that ACS and ACI have significant negative impact on firm performance. Besides, Big4, AMF and FDR have no significant contribution on firm performance. It reflects that corporate governance mechanisms in family firm are not working well and even to some extent detrimental to the firm performance. It, ultimately, demands for reforms in corporate governance framework and incorporating new dimensions for family firms.

This study investigates the impact of board incentives as proxied by directors` remuneration on the financial performance of listed textile companies in Bangladesh. Using Generalized Method of Moments (GMM) and data pertaining to listed textile companies of Dhaka Stock Exchange (DSE) during the period from 2011 to 2017 (resulting in a total of 140 firm-year observations), we have estimated the firm performance equation involving directors' remuneration and board independence as the independent variables and some other control variables like firm age, size, leverage, and operating efficiency. The results reveal that there is a negative association between board remuneration and firm performance. In addition, this study finds no significant relationship between board independence and firm performance of the sample firms. Our findings suggest that higher pay to the board does not stimulate higher firm performance and, in turn, results in shareholders getting nothing in return from this and, hence, is a matter of great concern for them. Moreover, our results indirectly indicate that currently directors` remuneration in Bangladesh is not aligned with the firm performance, which has been emphasized in extant corporate governance literature. Besides, this paper further raises questions about the effectiveness of independent directors in the boards of textile firms in Bangladesh.

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Coronavirus SARS-CoV-2 referred to as COVID-19, is a both spreadable and infectious disease, which has footprinted a global pandemic and still infecting millions across the globe. At present, COVID-19 has made a devastating impact on our daily life. To detect coronavirus, some medical radiography technique is prominent such as chest X-ray images. This work represented the distinguishing features between normal and COVID-19 infected chest X-ray images through Discrete Wavelet transform (DWT) and Histogram of Oriented Gradients (HOG) methods which helps to indicate whether the person is COVID positive or negative. DWT and HOG transformations were performed to extract the features from the chest x-ray images. Support Vector Machine (SVM) classifier is used to the chest x-ray images for model training and validation. To evaluate the performance of the model accuracy, sensitivity, specificity and precision were calculated. DWT-SVM model provides the accuracy of 98.58%, the sensitivity of 98.38%, the specificity of 98.47% and the precision of 98.48% whereas the HOG-SVM model provides the accuracy of 99.39%, the sensitivity of 99.19%, the specificity 99.28% and precision 99.29%. So, the result indicates that the HOG-SVM model shows better performance than the DWT-SVM model. The experimental results may help the medical personnel to diagnose easily and to take the necessary steps for better treatment.