The role of internal auditing on corporate governance: its effects of economic and environmental performance.

Internal auditing has been an elementary and powerful component of corporate governance in business strategies. It is highly acknowledged as an important business control system in the realm of quality management. Business performance does not come by itself; it needs plenty of aids and capabilities. Existing studies have investigated the business performance with fewer outcomes in corporate sustainability, firm, and environmental performance. We present analysis and validated improvised hypothesis through structural equation modeling (SEM), using analysis of a moment structures (AMOS), on empirical evidence gathered from 304 Chief Executive Officer (CEOs) in Top Multinational Companies of Pakistan (TMCP). In this paper, we examine the role of internal audit functionality as an influencing factor via corporate governance in corporate sustainability, firm performance, and environmental performance. Moreover, business quality and performance are maintained using functions such as interests of shareholders, personnel and finance. Results suggest that internal audit functionality and corporate governance significantly influence corporate sustainability, firm performance, and environmental performance. Additionally, CEOs and top managers of TMCP are advised to concentrate on internal audit functionality with a mediating role of corporate governance that in turn encourages corporate sustainability, firm performance, and environmental performance.

The link between green innovations, corporate performance, ESG activities, and sharing economy.

In current years (environment, social, and governance), ESG activities in various countries have been focus more attention their stakeholders by enterprises. The world largest developing country China. The Chinese registered Enterprises ESG performance helps to apprehend the deficiencies of their sustainable ability and development for boost the organizations value. Furthermore, enterprises must balance the allocation of resources between green innovation investment and ESG activities in the future as a result of the interaction effect between these two factors. This research examines the effects of environmental, social, and governance issues on financial and non-financial performance at registered Chinese manufacturing firms since 2009 to 2019. Green innovation is also tested as a moderating factor. Results show that environment, common, and governance performance has negative influence on the firm financial performance. On the other hand, its negative effects on financial performance will be enhanced. The environmental activities have negatively affected financial performance but green innovation has positively regulated them. Non-financial performance is positively impacted by the ESG performance. The ESG general performance and the environmental performance have positive influence on corporate reputation with the improvement of green innovation levels increase. Corporate financial performance is influenced by green innovation and social activities in a substitutional manner.

The effect of neural network architecture on virtual H&E staining: Systematic assessment of histological feasibility.

Conventional histopathology has relied on chemical staining for over a century. The staining process makes tissue sections visible to the human eye through a tedious and labor-intensive procedure that alters the tissue irreversibly, preventing repeated use of the sample. Deep learning-based virtual staining can potentially alleviate these shortcomings. Here, we used standard brightfield microscopy on unstained tissue sections and studied the impact of increased network capacity on the resulting virtually stained H&E images. Using the generative adversarial neural network model pix2pix as a baseline, we observed that replacing simple convolutions with dense convolution units increased the structural similarity score, peak signal-to-noise ratio, and nuclei reproduction accuracy. We also demonstrated highly accurate reproduction of histology, especially with increased network capacity, and demonstrated applicability to several tissues. We show that network architecture optimization can improve the image translation accuracy of virtual H&E staining, highlighting the potential of virtual staining in streamlining histopathological analysis.

COVID-19 and NSTEMI Outcomes among Hospitalized Patients in the United States and Racial Disparities in Mortality: Insight from National Inpatient Sample Database.

The COVID-19 pandemic has impacted healthcare delivery to patients with non-ST-segment elevation myocardial infraction (NSTEMI). The aim of our retrospective study is to determine the effect of COVID-19 on inpatient NSTEMI outcomes and to investigate whether changes in cardiac care contributed to the observed outcomes. After multivariate adjustment, we found that NSTEMI patients with COVID-19 had a higher rate of inpatient mortality (37.3% vs. 7.3%, adjusted odds ratio: 4.96, 95% CI: 4.6−5.4, p < 0.001), increased length of stay (9.9 days vs. 5.4 days, adjusted LOS: 3.6 days longer, p < 0.001), and a higher cost of hospitalization (150,000 USD vs. 110,000 USD, inflation-adjusted cost of hospitalization: 36,000 USD higher, p < 0.001) in comparison to NSTEMI patients without COVID-19, despite a lower burden of pre-existing cardiac comorbidity. NSTEMI patients with COVID-19 also received less invasive cardiac procedures (coronary angiography: 8.7% vs. 50.3%, p < 0.001; PCI: 4.8% vs. 29%, p < 0.001; and CABG: 0.7% vs. 6.2%, p < 0.001). In our study, we observed increased mortality and in-hospital complications to be a combined effect of COVID-19 infection and myocardial inflammation as a result of cytokine storm, prothrombic state, oxygen supply/demand imbalance and alterations in healthcare delivery from January to December 2020.

Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling.

The Meyal oil field (MOF) is among the most important contributors to Pakistan's oil and gas industry. Northern Pakistan's Potwar Basin is located in the foreland and thrust bands of the Himalayan mountains. The current research aims to delineate the hydrocarbon potential, reservoir zone evaluation, and lithofacies identification through the utilization of seven conventional well logs (M-01, M-08, M-10, M-12, M-13P, and M-17). We employed the advanced unsupervised machine-learning method of self-organizing maps for lithofacies identification and the novel Quanti Elan model technique for comprehensive multimineral evaluation. The shale volume, porosity, permeability, and water saturation (petrophysical parameters) of six wells were evaluated to identify the reservoir potential and prospective reservoir zones. Well-logging data and self-organizing maps were used in this study to provide a less costly method for the objective and systematic identification of lithofacies. According to the SOM and Pickett plot analyses, the zone of interest is mostly made up of pure limestone oil zone, whereas the sandy and dolomitic behavior with a mixture of shale content shows non-reservoir oil-water and water zones. The reservoir has good porosity values that range from 0 to 18%, but there is a high water saturation of up to 45% in reservoir production zones. The presence of shale in the entire reservoir interval has a negative effect on the permeability value, but the petrophysical properties of the Meyal oil reservoir are good enough to permit hydrocarbon production. According to the petrophysical estimates, the Meyal oil field's Sakesar and Chorgali Formations are promising reservoirs, and new prospects for drilling wells in the southern and central portions of the eastern portion of the research area are recommended.

CPSP/HSE Postgraduate Overseas Rotational Programme: Residents' Perspective.

OBJECTIVE: To get direct upward feedback from the residents of first batch of CPSP/HSE Postgraduate Scholarship Programme. STUDY DESIGN: Mixed methods qualitative research study. PLACE AND DURATION OF STUDY: CPSP, Regional Office, Lahore, in June 2015. METHODOLOGY: It is a mixed-method study that was conducted in June, 2015. Data was collected through an email survey with 33 medical residents doing their rotation in Ireland; and focus group discussions were carried out with 8 residents, who had successfully completed their rotation. Data were collected through pre-designed questionnaires comprising of open- and close-ended questions. The data were entered into SPSS version 21 and analyzed. RESULTS: The mean age of residents was 29.9 &plusmn;1.1 years, 7 (21.2%) were females and 24 (72.7%) respondents were males. Residents agreed that HSE programme has improved their evidence-based decision making (mean score of 3.3 &plusmn;1.2) and enhanced professionalism (mean score of 3.6 &plusmn;1.1). They disagreed that training has polished their procedural skills (mean score 2.4 &plusmn;1.2). The identified strengths of the programme are: adopting a systematic approach towards patients, evidence-based decision making, better exposure and opportunities, financial stability and development of communication skills. The weaknesses are: less exposure to procedural skills, difficulty in synopsis and dissertation writing and difficulty in adjustment with rotational schedules. CONCLUSION: Residents of CPSP/HSE Programme believed that CPSP/HSE has improved their professionalism, communication skills and increased their future opportunities for career growth. Better communication between CPSP focal person and residents will help sort out many minor but important issues.