Linkages among stock markets, precious metals and hedge funds: An empirical investigation of the Asia-Pacific region : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University

This study examines the linkages among the stock market, precious metals and hedge funds in the 12 countries of Asia-Pacific region. Using weekly data from 1997 to 2018, this study investigates the existence of price linkages, cointegration and the relationships between the markets. The data divided into sub-samples comprising times representing the 1997 Asian financial crisis, the 2007-2008 Global financial crisis and the 2010 Eurozone crisis to obtain an in-depth understanding of the impact on the linkages among the markets during three significant financial crises. Both long-run and short-run associations between the variables are investigated. To do this, the Engle and Granger two step, Johansen cointegration techniques, Vector Error Correction Modelling and Granger causality tests are used with the main objective of examining the price co-movement between the variables. The study also uses bivariate and trivariate econometric techniques to provide sufficient evidence regarding the linkages among the markets and the impact of the international stock market by introducing another variable, i.e., the US Dow Jones. To investigate the nature of the volatility spillover among the markets, we employed GARCH and EGARCH modelling. The main findings show that stock prices and precious metals seem to be independent and not cointegrated. Stock market prices and precious metals prices did not show any volatility spillover effect. Overall, there is no evidence of these two variables moving together either in the long- or short-run. The results show evidence of an asymmetric spillover effect from stock returns to precious metals market prices in some countries under analysis, with no evidence of a causal relationship running from precious metals towards stock market prices. In the volatility analysis, there is some commonality regarding the behaviour of the variables, with a unidirectional spillover effect between the markets. The analysis of the stock markets and hedge funds shows that hedge fund returns do not seem to be affected by movements in stock markets; the findings show no volatility spillover effect among stock market returns and hedge funds that suggests that these two markets are unrelated. This study also expanded the literature on the hedge funds industry that is considered an independent market where no other market significantly affects hedge fund performance. The reason is that hedge funds are actively managed by fund managers based on performance incentives. This property of hedge funds forces the managers to modify their portfolio diversification as the market shows volatility or vulnerability. With regard to the effects of hedge funds on other asset classes, there is an opportunity for future research to expand the qualitative analysis. This study investigates the price stability properties of precious metals during the 1997 Asian Financial Crisis, 2007-2008 Global Financial Crisis and 2010 Eurozone Crisis. To analyse the interaction between precious metals we use the ICSS algorithm along with GARCH model to evaluate how the number of rapid changes in volatility of precious metals has been reduced. The results suggest gold is the most stable of the precious metals. However, silver, platinum and palladium showed positive price correlation when the US Dow Jones market was unstable. These results imply that: 1) the correlation among stocks in Asia Pacific countries has little to no significant impact on the price movement of precious metals, but the US Dow Jones has an influence on precious metals markets except gold, which means investors can reap this benefit from diversification; 2) like precious metals, hedge funds are completely independent from the stock market price volatility and can be a stable investment avenue for diversification; and 3) investors in the Asia-Pacific region can systematically increase their portfolio returns by going short with the gold investments with low price co-movement and long on silver, platinum and palladium with high co-movement with stock prices

Current challenges of digital health interventions in Pakistan: Mixed methods analysis

Background: Digital health is well-positioned in low and middle-income countries (LMICs) to revolutionize health care due, in part, to increasing mobile phone access and internet connectivity. This paper evaluates the underlying factors that can potentially facilitate or hinder the progress of digital health in Pakistan.Objective: The objective of this study is to identify the current digital health projects and studies being carried out in Pakistan, as well as the key stakeholders involved in these initiatives. We aim to follow a mixed-methods strategy and to evaluate these projects and studies through a strengths, weaknesses, opportunities, and threats (SWOT) analysis to identify the internal and external factors that can potentially facilitate or hinder the progress of digital health in Pakistan.Methods: This study aims to evaluate digital health projects carried out in the last 5 years in Pakistan with mixed methods. The qualitative and quantitative data obtained from field surveys were categorized according to the World Health Organization\u27s (WHO) recommended building blocks for health systems research, and the data were analyzed using a SWOT analysis strategy.Results: Of the digital health projects carried out in the last 5 years in Pakistan, 51 are studied. Of these projects, 46% (23/51) used technology for conducting research, 30% (15/51) used technology for implementation, and 12% (6/51) used technology for app development. The health domains targeted were general health (23/51, 46%), immunization (13/51, 26%), and diagnostics (5/51, 10%). Smartphones and devices were used in 55% (28/51) of the interventions, and 59% (30/51) of projects included plans for scaling up. Artificial intelligence (AI) or machine learning (ML) was used in 31% (16/51) of projects, and 74% (38/51) of interventions were being evaluated. The barriers faced by developers during the implementation phase included the populations\u27 inability to use the technology or mobile phones in 21% (11/51) of projects, costs in 16% (8/51) of projects, and privacy concerns in 12% (6/51) of projects.Conclusions: We conclude that while digital health has a promising future in Pakistan, it is still in its infancy at the time of this study. However, due to the coronavirus disease 2019 (COVID-19) pandemic, there is an increase in demand for digital health and implementation of health outcomes following global social distancing protocols, especially in LMICs. Hence, there is a need for active involvement by public and private organizations to regulate, mobilize, and expand the digital health sector for the improvement of health care systems in countries

Activated Protein C Ameliorates Tubular Mitochondrial Reactive Oxygen Species and Inflammation in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is an emerging pandemic, paralleling the worldwide increase in obesity and diabetes mellitus. DKD is now the most frequent cause of end-stage renal disease and is associated with an excessive risk of cardiovascular morbidity and mortality. DKD is a consequence of systemic endothelial dysfunction. The endothelial-dependent cytoprotective coagulation protease activated protein C (aPC) ameliorates glomerular damage in DKD, in part by reducing mitochondrial ROS generation in glomerular cells. Whether aPC reduces mitochondrial ROS generation in the tubular compartment remains unknown. Here, we conducted expression profiling of kidneys in diabetic mice (wild-type and mice with increased plasma levels of aPC, APChigh mice). The top induced pathways were related to metabolism and in particular to oxidoreductase activity. In tubular cells, aPC maintained the expression of genes related to the electron transport chain, PGC1-α expression, and mitochondrial mass. These effects were associated with reduced mitochondrial ROS generation. Likewise, NLRP3 inflammasome activation and sterile inflammation, which are known to be linked to excess ROS generation in DKD, were reduced in diabetic APChigh mice. Thus, aPC reduces mitochondrial ROS generation in tubular cells and dampens the associated renal sterile inflammation. These studies support approaches harnessing the cytoprotective effects of aPC in DKD

Application of Natural Language Processing (NLP) Techniques in E-Governance

E-Governance is the public sector’s use of information and communication technologies with the aim of improving information and service delivery, encouraging citizen participation in the decision-making process and making government more accountable, transparent and effective. Effective and efficient e-Governments deploy Information and Communication Technology Systems to deliver services through multiple channels that are accessible, fast, secure, reliable, seamless, and coherent. To implement better G2G, G2B, G2E and G2C services we should not only utilize ICT, we have to be also serious about implementing Natural Language Processing (NLP) Techniques to reach up to the masses and make e-governance successful one. This paper shows the need of applying NLP technologies in the field of e-governance and also tries to focus on the issues, which can be resolved very easily with the help of these modern technologies. It also shows the advantages of applying NLP in e-governance. Key words: e-Governance, natural language processing, NLP, ICT. 1

Assessing and predicting operation variables for doctors employing industry 4.0 in health care industry using an adaptive neuro-fuzzy inference system (ANFIS) approach

The chief objective of this study is to employ a predictive software called adaptive neuro-fuzzy inference system (ANFIS) approach which assess stress amongst doctors employing industry 4.0 technology during their surgeries. This study further investigates factors contributing the operation accuracy, sensitivity and specificity amongst doctors. Also, the effective performance of doctors can be optimized through earlier prediction for percentage of incorporating Industry 4.0 technologies. Survey was conducted amongst doctors using industry 4.0 technologies who provided unbiased answers to several queries in the questionnaire. The ANFIS model was employed to predict success rate of surgeries through models build with the aid of several input parameters. The outcomes such as accuracy, sensitivity and specificity were studied while employing Industry 4.0 technology which were considered significant factors influencing the perceived various kinds of surgeries in different domains. Moreover, the results of the ANFIS modelling approach showed that with increase in percentage of industry 4.0 machines in medical equipment, the operations sensitivity and accuracy increased, hence the most critical predictors. While specificity did not have any major impact on the surgeries. Henceforth, doctors can take preventive actions and simultaneously plan their work load with the aid of industry 4.0, providing better health benefits to patients making the healthcare industry much more efficient and stress-free

Impact of artificial intelligent and industry 4.0 based products on consumer behaviour characteristics: A meta-analysis-based review

In the modern era, computers using artificial intelligence (AI) and industry 4.0 have found acceptance since its application in renewable energy sectors thereby optimising the cost and efficiency of the equipment. Despite its importance, lack of comprehensive literature has been reported in the past highlighting its relationship with consumer behaviour (CB) in the market considering the modern women's in the sustainable energy field. Findings from 10 studies furnish that physiological, social, personal and economical aspects significantly impact women consumer behaviour when categorized on the perception for intention to buy, acceptance and need for recognition. The current review paper is the first distinguishable review highlighting the importance of stipulating the relationship between artificial intelligence and characteristics of consumer behaviour in the field of sustainable energies. The paper synthesises previous findings by developing a model with the aid of meta-analysis. The review and organization procedure were simultaneously verified. Eventually, outcomes of the review stipulated intention to buy area, which requires utmost importance in order to establish and maintain a healthy attitude of consumers towards women entrepreneurs and industry 4.0. In future, this review will establish a roadmap to researchers, thereby guiding to collect technology information and analyse the applications in sustainability and CB. This paper aims to enhance our expertise and simultaneously develop a feasible relationship between consumer behaviour and computer based renewable technologies by addressing different concerns related to implementation of robots at home and outlining the investigation programs for the future experiments

Computer Malware Classification, Factors, and Detection Techniques: A Systematic Literature Review (SLR)

A Systematic Literature Review (SLR) was conducted using tailored searches based on our study topic. We completed all SLR processes, including periodic reviews as SLR. Researchers may find out about the justification, the review procedure, and the research question by using search keywords. This paper describes the trial approach to elaborate the search keywords, resources, restrictions, and validations that were, and explores search strategies made. The reviews are carried out by assessing the publication's quality, devising a data extraction approach, and synthesizing the results. All four research questions were used to analyze the papers concerning the findings.  Finally, reports on the categorization of computer malware were analyzed for their detection methods, factors, and how they infiltrate computer systems have been published. SLR identifies the element, characteristics, and detection techniques that are explained in this research paper. Computer malware infects the computer system. This comprehensive literature review's is mainly based on recommendations by earlier studies