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Hyperuricemia refers to elevated serum uric acid concentration above the upper limit of normal. Objective: To determine hyperuricemia in patients presenting with acute ischemic stroke to the Neurology ward of Lady Reading Hospital, Peshawar. Methods: A total of 153 patients were observed to the frequency of hyperuricemia in patients presenting with acute ischemic stroke. Study design was cross sectional study which was conducted for the period of 6 months. The total Sample size was calculated by using WHO sample size calculator. It was calculated using the World Health Organization software. Results: A total of 153 patients were observed to the frequency of hyperuricemia in patients presenting with acute ischemic stroke. Mean age of study participants was 52.45±1.14 years. Distribution of hyperuricemia was 114(74.5%). Mean serum uric acid level among cases of acute ischemic stroke was 06.15 ± 01.91 mg/dl while the mean serum uric acid level among control group was 05.1 ± 01.4 mg/dl. The results were highly significant p-value < 0.0001. Conclusions: Serum uric acid levels can be used to predict stroke risk. Moreover, serum uric acid can be utilized to stratify risk following a stroke. Long-term prospective research is needed to determine the involvement of serum uric acid in ischemic stroke. A trial of serum uric acid reducing medications in stroke patients as well as those at high risk of stroke may also be worthwhile.

The capital markets are highly interconnected in the modern economic system, and it is one of the most vulnerable sectors to any financial and natural disaster occurring around the globe. The COVID-19 pandemic not only affects the capital market of the host nation but also creates problems in other parts of the world’s capital markets as well. The main objective of this event study is to empirically analyze the impacts of the COVID-19 pandemic on the daily stock market returns in Pakistan, which is a fast-growing and emerging market in South Asia. For this, we used secondary data to evaluate the effects of COVID-19 in different dimensions i.e., total cases, new cases, total deaths, new deaths, and the positive rate on the daily stock returns of 531 listed companies in the Pakistan stock exchange over the period of March 2020 to November 2021. For stationarity of the variables, we applied an augmented Dickey-Fuller (ADF) unit root test. The results of the study obtained through ARCH family regression estimation revealed that the total number of cases, new cases, and the positive rate are negatively affecting the stock market returns in Pakistan while the total deaths and new deaths are positively affecting the stock market returns during the pandemic.

Recently, credit disbursement and fossil fuel utilization increased to enhance wheat production so peasants could benefit from the green revolution. To look at the impact of credit disbursement, fossil fuel utilization, and the determinants of the green revolution were arranged to investigate the association among them. For this purpose, the study employed the time series in the perspective of Pakistan, spanning 1971 to 2019. Modern econometrics techniques like Johansen cointegration, vector autoregressive and impulse response function were employed along with a number of diagnostics tests. Evidence of the Johansen model shows significant long-run cointegration among the green revolution, credit disbursement, fossil fuel, and total wheat production. The Johansen test elaborates that 1% increase in credit disbursement and fossil fuel increases the total wheat production by 0.57% and 0.04 % respectively. Moreover, the determinants of the green revolution also positively affect wheat production. While the coefficient, residual and stability diagnostic tests are in favor of the study. The findings of the impulse response function state that all the concerned variables positively affect the total wheat production in the coming years. The study suggested that the government and private sector should invest in research and development to introduce the organic chemical and forming to avoid soil fertility and environmental degradation.

It is acknowledged that environmental degradation, climate change and the atmosphere's temperature are increasing due to the emission of greenhouse gasses. Therefore, a speedy response is required to lessen the severe effects of greenhouse gases. The present study has analyzed the influence of electric consumption, fiscal development, globalization, and trade openness on carbon emission using the latest dataset and modern econometric techniques. To accomplish the said objectives, the study has employed Johansen cointegration, autoregressive distributed lag model (ARDK), and block exogeneity. The results specify that with the 1% increase in electric consumption, fiscal development, globalization and trade openness, the carbon dioxide emission increases by 0.01%, 0.04%, 0.68%, and 0.25%, respectively. Moreover, the results also indicated that the environmental Kuznets curve is prevailing in the Malaysian economy because an inverted U-shape connection occurs between carbon and GDP2. On the basis of data diagnostics, it is determined that the ARDL model is credible, stable, and reliable. Further, block exogeneity affirms the long-term affiliation among the factors and concludes that all the factors under analysis contribute to the environmental deterioration in the Malaysian economy. Therefore, the government may design an environmental or pollution tax policy to minimize carbon emissions. Green energy should be produced and consumed as it is environmental friendly and helps to reduce temperature and atmospheric pollution.