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This study analyses the impact of natural resource rent on financial development to test the resource curse hypothesis in Saudi Arabia on quarterly data span from 1985Q1 to 2017Q4. We employ two novel methodologies at same time such as nonlinear autoregressive model (NARDL) and Wavelet-based quantile-on-quantile estimation to check the asymmetric behaviour of natural resource rent on financial development. The findings of NARDL confirm the nonlinear behaviour of natural resource rent with financial development. The results also show real GDP, gross capital formation and institutional quality affect financial development positively. The empirical results of Wavelet-based quantile-on-quantile estimation method also reveal the heterogeneous response of natural resource rent effect when decomposes into different quantiles that become positive to negative. The results further explain that the natural resource rent has a positive effect in short-run, but it exerts an adverse effect on financial development after attaining stability.

Oil price fluctuations have vital importance in macroeconomic performance. Our study demonstrates the impact of oil price fluctuations on the trade balance and economic growth in Pakistan. We employ a linear autoregressive distributed lag model (ARDL) for the period 1970-2018. The results showed that oil price negatively affected the total trade balance in Pakistan other control variables like the real effective exchange rate, real GDP (Home country) and financial development also negatively affected. While real GDP (Foreign country) influenced trade balance positively. In the second model, the results showed that oil price negatively affected economic growth in Pakistan and other control variables like government expenditure, financial development and gross capital formation are positively affected. The study results are useful for policymakers and government officials for making the policies regarding long-run economic growth as well as trade balance improvement.

Analyzing the factors affecting human capital at household level increases the productivity of people living in developing countries. A primary data was collected through a household survey to study the factors affecting human capital in Southern Punjab using Ordinary Least Squares (OLS) regression technique. The findings show that the location of the household in rural areas, occupation of the household head in the primary sector, household size, household poverty and female/male ratio shows significant and negatively affecting the human capital of the households in Southern Punjab. Moreover, per capita income, number of earners in the household, remittances are significant and positively affecting the human capital of the households in Southern Punjab. The annual budget allocation for education in Pakistan is very low, so Government should allocate a significant amount of funds to the education sector.

Multiclass classification of brain tumors is an important area of research in the field of medical imaging. Since accuracy is crucial in the classification, a number of techniques are introduced by computer vision researchers; however, they still face the issue of low accuracy. In this article, a new automated deep learning method is proposed for the classification of multiclass brain tumors. To realize the proposed method, the Densenet201 Pre-Trained Deep Learning Model is fine-tuned and later trained using a deep transfer of imbalanced data learning. The features of the trained model are extracted from the average pool layer, which represents the very deep information of each type of tumor. However, the characteristics of this layer are not sufficient for a precise classification; therefore, two techniques for the selection of features are proposed. The first technique is Entropy–Kurtosis-based High Feature Values (EKbHFV) and the second technique is a modified genetic algorithm (MGA) based on metaheuristics. The selected features of the GA are further refined by the proposed new threshold function. Finally, both EKbHFV and MGA-based features are fused using a non-redundant serial-based approach and classified using a multiclass SVM cubic classifier. For the experimental process, two datasets, including BRATS2018 and BRATS2019, are used without increase and have achieved an accuracy of more than 95%. The precise comparison of the proposed method with other neural nets shows the significance of this work.

This study attempts to explore the impact of environmental quality, real exchange rate and institutional performance on tourism receipts in East-Asia and Pacific region. A new methodology dynamic c...

One of the challenging tasks for governments is to curtail the production and consumption of single-use plastic bags. Despite multiple advantages of plastic and its ubiquity, the environmental damage of single-use plastic bags is irreversible. However, policy intervention by the governments is also a need of the time to reduce its production and consumption. This study provides a strategic analysis of government policy options regarding the ban on single-use plastic production in Pakistan. A game-theoretic model is developed to examine the behavior of plastic bag producers vis-a-vis the government’s climate change policy. The study concludes that game theory is very effective in analyzing the efficient promulgation and productive implementation of environmental management policy regarding banning single-use plastic in Pakistan.

This research is an endeavor to reveal the dynamic association of real exchange rate volatility with real and monetary shocks and particularly with international financial integration in selected eight Latin American countries during 1992-2018. The estimation strategy employed in this research is the Generalized Method of Moments (GMM) to empirically obtain consistent estimates. Empirical results strongly supported the significant negative impact of financial integration on real exchange rate volatility when financial integration is approximated by the Chinn-Ito index. Furthermore, output volatility and money supply volatility both significantly contributed to increasing real exchange rate instability. An important policy implication is that process of financial integration needs to be more strengthened and shocks to output and money supply needs to be reduced to achieve lesser fluctuations of the real exchange rate in Latin American countries.

The current examination ascertains the impact of foreign direct investment, urbanization, economic growth, fossil fuel consumption on carbon emissions in eleven rising Asian economies. Panel data has been scrutinized from 1990 to 2018, and (ARDL)/PMG model is executed. The outcomes of the model exemplify that in these growing Asian economies, the triumph to cuitivate economic growth, foreign direct investment, urbanization and fossil fuels are bestowing CO2 emissions and deteriorating the environmental circumstances at the regional level. Moreover, the conclusions emphasis that foreign direct investment is a source of environmental humiliation and increases carbon emissions at the regional level. Furthermore, outcomes of the investigate also confirmes the existence of (EKC) in these eleven emerging Asian economies. The study also suggest that by lessening the consumption of fossil fuel energy and encouragement of an environmental responsive economic growth policy will be suitable for the affluence in these emerging developing Asian economies and also the rest of world.

This study spells out the role of financial inclusion (FI) to accelerate the efficiency of Islamic banks in Pakistan for the period of 2007 to 2016. It examines the effect of a specially developed broad-based FI index on technical efficiency of Islamic banks through panel ARDL approach along with to explore the macroeconomic as well as bank-specific factors of efficiency. The findings exhibit the possible connection between Islamic banking and financial inclusion in Pakistan. The study offers a variety of useful policy implications for public policy towards effective progress on the National Financial Inclusion Strategy in the country.

The Households having low socio-economic status possess less resource in term of wealth and income to resist against any kind of external shocks. Apart from heath shocks (physical and mental disabilities) there are numerous other factors that force them to follow subsistence life style having low per capita income. A primary level data has been collected to examine the socio economic status of households in Southern Punjab for the year 2019.The findings show that household size, occupation, dependency ratio, mental disability and physical disability are negatively affecting economic development across the region. However, age, education of the household head, own house, spouse ‘s participation, remittances, number of earners in the household and value of physical assets are increasing economic development in Southern Punjab. Developing strategies, adequate planning and their timely implementation is very crucial for the government to pursue the process of economic growth and development of the poor countries like Pakistan.

This research study is an attempt to explore the nonlinear relationship between domestic and foreign income and deficit in the trade balance for a sample of 13 high deficit Asian countries from 1990 to 2019. Furthermore, the study also moderates the role of financial development and carbon emissions with trade balance. The study results validated the existence of a nonlinear relationship between trade balance and domestic and foreign income. For this purpose, three different types of model are formulated. The first model was of the benchmark type, which contains only the domestic and foreign income effect, while in the other two models, the role of financial development and carbon emissions is also included. The estimated results evinced the existence of U shape relationship for domestic income and inverted U shape curve for World income. The results revealed that it would be very suitable for selected countries to boost up domestic income. Because of it, the deficit in trade balance will start to decline. The financial development and carbon emissions are found to be a significant contributor to reduce the deficit in the trade balance.

The main objective of the study is to explore asymmetric impact of oil price on environmental degradation in Pakistan over the period 1975-2018. The study employs the nonlinear autoregressive distributive lag (NARDL) method to check the asymmetric connection of oil price with carbon dioxide (CO2) emissions which represents environmental degradation along with gross capital formation, energy consumption, foreign direct investment and population. The NARDL result expresses that there is different effect of oil price as we break it into positive and negative changes, and decrease in oil price has a greater effect on environmental degradation in Pakistan. The other variables, FDI and energy consumption and population, have a positive and significant effect on CO2 emission. The study provides the policies for policymakers and government officials after uncovering the asymmetric relationship between oil and other variables with an environment that would be helpful in policymaking for Pakistan.

Economic growth is a researchable debate in the context of trade openness relation in testing trade-led growth hypothesis. This study explores the relation of economic growth with trade openness to test the trade-led growth hypothesis by using a recently developed nonlinear ARDL model over the period 1984-2017 in Pakistan. The results reveal that trade openness affects economic growth differently when it decomposes into positive and negative components, and trade openness decrease has a more impact on economic growth in the presence of labor, capital, FDI and institutional performance as control variables. The mixed relationship of openness-growth in the long-run does not completely verify the trade-led growth and shows non-linear impacts of trade openness on economic growth in Pakistan. The study suggests the policies for government officials and policymakers after unearthing the asymmetric association between trade openness and economic growth that would help to make trade policies for Pakistan.

Renewable energy decreases the threat of energy insecurity. Solar energy systems are proving to be an easy and cheaper solution to energy crisis worldwide. Developing countries including Pakistan have augmented efforts to boost the current solar capacity. The identification of desired solar power point plant fabrication requires robust analysis of several factors. Adequate research has not been done on the site selection process for solar projects in Pakistan. This study identifies and proposes multiple point states having solar energy potential. Based on the multiple main and sub-criteria obtained from the literature, a mathematical formulation has been used to install the solar projects at rural areas of Pakistan. An empirical assessment of the off-grid rural solar power projects in Pakistan has also been conducted in this case study. The results reveal that mass, money supply and ratio are important, while the transmission on the matrix, the cost of land and the sun were generated. The study found the district of Barkhan (R2) of Baluchistan to be the most ideal site, followed by Jacobabad (R3) and Mastung (R3). With respect to economic viability, this study found that solar energy systems provide electricity which is much cheaper than conventional energy supplied in the country. This study could be useful reference for South Asian countries including India, Bangladesh, and Afghanistan, which are currently electrifying remote and rural areas through solar energy system.

Employment is very cogent macroeconomic factor in economic decision making. People in the labor force take decisions to assume various employment statuses in their economic life. This study shows a pragmatic analysis of the factors that determine the employment status in district Multan, based on primary data set of 250 respondents collected through stratified sampling. Multiple Logit technique has been applied. The findings of the study have shown that a range of socio-economic and demographic factors are responsible to determine the employment status. The study is also furnished with some relevant policy implications.

Objectives: To investigate the role of high dose atorvastatin in controlling cough improving lung function and exercise capacity in patients with bronchiectasis. Study Design: Cross Sectional Study. Setting: From outdoor of respiratory unit of Nishtar hospital Multan. Period: January 2016 to September 2018. Material & Methods: Total 58 patients were enrolled having clinically significant bronchiectasis having productive cough and were clinically stable. Consecutive sampling was done and patients were divided into two groups by lottery method. Group A received high dose atorvastatin 80mg once daily for 6 months and group B received placebo for 6 months. Patients in both groups received other standard medical treatment. Consent was taken from these patients and approval was taken of this research from ethical committee. Data was analyzed by SPSS volume 22. Qualitative variables OD data like gender, age, smoking status were statistically calculated by percentage and chi square test was applied to check the significance. Quantitative variables like LCQ score, FEV1, FVC and its ratio and 6-minute walk test were calculated in mean and standard deviation and significance checked with t test. P value of less than .005 was considered significant. Results: The mean FEV1, FVC, FEV2/FVC, WBC, CRP and LCQ score unit for the statin group was 2.44±0.73 L, 3.36±0.84 L, 67.42±6.21, 6.94±1.89×109 cells per L, 6.35±1.21 mg/L and 15.40±3.62 respectively. While, the mean FEV1, FVC, FEV2/FVC, WBC, CRP and LCQ score unit for the placebo group was 2.10±0.86 L, 2.82±1.11 L, 67.31±3.09, 6.53±2.55×109 cells per L, 9.21±6.39 mg/L and 13.56±2.73 respectively. The difference was statistically significant for FVC (p=0.038), CRP (p=0.022) and LCQ score units (p=0.033). The mean FEV1, FVC, FEV1/FVC, improvement in 6MWT and improvement in LCQ scores units for the statin group was 0.0517±0.31 L, -0.0172±0.32 L, 0.000±0.20, -0.1354±0.48 m and 2.2±1.08 units respectively. Improvement in LCQ score> 1.3 units was observed in n=7 (24.1%) patients. While, the mean FEV1, FVC, FEV1/FVC, improvement in 6MWT and improvement in LCQ scores units for the placebo group was 0.061±0.24 L, -0.0483±0.30 L, 0.179±0.29, 0.001±0.47 m and -0.7214±0.25 units respectively. Improvement in LCQ score> 1.3 units was observed in n=12 (41.4%) patients. The difference was statistically significant for improvement in LCQ score units (p=0.000). Conclusion: Statins can be used in controlling the cough in patients with bronchiectasis. But its role in improving lung function test and exercise capacity need further research and investigation.

Domestic trade plays a key role in China's rapid economic progress. However, the increased domestic trade causes significant variations in carbon emission transfer among provinces. This study adopted the multi-region input-output (MRIO) model and social network analysis (SNA) to estimate the carbon emission transfer. Furthermore, the carbon emission transfer network characteristics among 30 provinces and 27 sectors were analyzed by using interprovincial input-output tables for 2007, 2010, and 2012. The results showed that (1) Large differences exist in carbon emission transfer flow and its network characteristics between provinces. (2) The three industrial sectors of metal smelting and pressing sector, power, heat production, and supply sector, petroleum processing, coking, and nuclear fuel processing sector have high carbon emission transfer and pose a strong influence on the carbon emission transfer network. (3) Provinces of the eastern region have a "bidirectional spillover" role, while those of the western region have a mediating role as an "agent." Provinces of the central region have a "main inflow" role. Finally, useful policy implications and suggestions of this study are summarized.

Lung cancer is a fatal type of cancer and it causes of severe deaths of approximately 422 people every day, worldwide. However, an early diagnosis is an expedient requirement for increasing the chances of human survival. In this regard the existing techniques of tumor detection, CT scans are mostly utilized to recognize the infected regions, nevertheless, the major challenges of CT images are low visibility of tumor regions, negative rates, to name but a few. In this work, we propose a novel design of contrast stretching based classical features fusion process for localizing the of lungs cancer classification. The proposed method encompasses three significant steps: firstly, contrast of original CT images is improved by gamma correction max intensity weights approach. Secondly, multiple texture, point, and geometric features are extracted from contrast images, which are later subjected to a serial canonical correlation-based fusion. Thirdly, zero values and negative features are replaced by an entropy-based approach, followed by weighted NCA for selection. Most discriminate features are fed into ensemble classifier for final classification. The validation of the proposed method is conducted on publicly available dataset: Lungs Data Science Bowl 2017 to achieving maximum accuracy of 99.4%. The numerical results clearly show that the performance of our proposed method outperforms in comparison with several existing methods with greater accuracy.

Background COVID-19 has posed unique challenges for adolescents in different dimensions of their life including education, home and social life, mental and physical health. Whether the impact is positive or negative, its significance on the overall shaping of adolescents’ lives cannot be overlooked. The aim of the present study was to explore impacts of the pandemic on the adolescents’ everyday lives in Pakistan. Methods Following ethical approval, this cross-sectional study was conducted through September to December, 2020 via an online survey on 842 adolescents with the mean age of 17.14 ± SD 1.48. Socio-demographic data and Epidemic Pandemic Impact Inventory-Adolescent Adaptation (EPII-A) was used to assess the multi-dimensional effects of the pandemic. Results Among the 842 participants, 84% were girls. Education emerged as the most negatively affected Pandemic domain (41.6–64.3%). Most of the adolescents (62.0–65.8%) had reported changes in responsibilities at home including increased time spent in helping family members. Besides, increase in workload of participants and their parents was prominent (41.8% & 47.6%). Social activities were mostly halted for approximately half (41–51%) of the participants. Increased screen time, decreased physical activity and sedentary lifestyle were reported by 52.7%, 46.3% and 40.7% respectively. 22.2–62.4% of the adolescents had a direct experience with quarantine, while 15.7% experienced death of a close friend or relative. Positive changes in their lives were endorsed by 30.5–62.4% respondents. Being male and older adolescents had significant association with negative impact across most domains (p.05). Conclusions Results have shown that COVID-19 exert significant multidimensional impacts on the physical, psycho-social, and home related domains of adolescents that are certainly more than what the previous researches has suggested.

Pests are always the main source of field damage and severe crop output losses in agriculture. Currently, manually classifying and counting pests is time consuming, and enumeration of population accuracy might be affected by a variety of subjective measures. Additionally, due to pests’ various scales and behaviors, the current pest localization algorithms based on CNN are unsuitable for effective pest management in agriculture. To overcome the existing challenges, in this study, a method is developed for the localization and classification of pests. For localization purposes, the YOLOv5 is trained using the optimal learning hyperparameters which more accurately localize the pest region in plant images with 0.93 F1 scores. After localization, pest images are classified into Paddy with pest/Paddy without pest using the proposed quantum machine learning model, which consists of fifteen layers with two-qubit nodes. The proposed network is trained from scratch with optimal parameters that provide 99.9% classification accuracy. The achieved results are compared to the existing recent methods, which are performed on the same datasets to prove the novelty of the developed model.

Diabetic retinopathy (DR) is a major reason of blindness around the world. The ophthalmologist manually analyzes the morphological alterations in veins of retina, and lesions in fundus images that is a time-taking, costly, and challenging procedure. It can be made easier with the assistance of computer aided diagnostic system (CADs) that are utilized for the diagnosis of DR lesions. Artificial intelligence (AI) based machine/deep learning methods performs vital role to increase the performance of the detection process, especially in the context of analyzing medical fundus images. In this paper, several current approaches of preprocessing, segmentation, feature extraction/selection, and classification are discussed for the detection of DR lesions. This survey paper also includes a detailed description of DR datasets that are accessible by the researcher for the identification of DR lesions. The existing methods limitations and challenges are also addressed, which will assist invoice researchers to start their work in this domain.

The skin is the human body’s largest organ and its cancer is considered among the most dangerous kinds of cancer. Various pathological variations in the human body can cause abnormal cell growth due to genetic disorders. These changes in human skin cells are very dangerous. Skin cancer slowly develops over further parts of the body and because of the high mortality rate of skin cancer, early diagnosis is essential. The visual checkup and the manual examination of the skin lesions are very tricky for the determination of skin cancer. Considering these concerns, numerous early recognition approaches have been proposed for skin cancer. With the fast progression in computer-aided diagnosis systems, a variety of deep learning, machine learning, and computer vision approaches were merged for the determination of medical samples and uncommon skin lesion samples. This research provides an extensive literature review of the methodologies, techniques, and approaches applied for the examination of skin lesions to date. This survey includes preprocessing, segmentation, feature extraction, selection, and classification approaches for skin cancer recognition. The results of these approaches are very impressive but still, some challenges occur in the analysis of skin lesions because of complex and rare features. Hence, the main objective is to examine the existing techniques utilized in the discovery of skin cancer by finding the obstacle that helps researchers contribute to future research.

This study examined the potential impacts of entrepreneurial leadership on followers' psychological wellbeing and proactive work behavior through sustainable employability and work uncertainty in a sample of 218 employees employed in SMEs of Pakistan. Hierarchical regression results demonstrated that entrepreneurial leadership was positively connected with sustainable employability and negatively linked with work uncertainty. Sequentially, sustainable employability was positively correlated with proactive work behavior and employees' psychological wellbeing, and work uncertainty was negatively associated with proactive work behavior and employees' psychological wellbeing during the COVID-19 crisis. Furthermore, bootstrapping confirmed the mediation effects of work uncertainty and sustainable employability on proactive work behavior and the psychological wellbeing of employees. Sustainable employability did not mediate the relationship between entrepreneurial leadership and psychological wellbeing. Mediators, sustainable employability, and work uncertainty positively linked employees' psychological wellbeing and proactive work behavior. The results highlighted the significant roles of sustainable employability and work uncertainty and interpreted why entrepreneurial leadership may affect employees' positive behaviors.

Objectives: To compare ureterovesical jet frequency in non-obstructed versus obstructed ureter secondary to ureteric stone using ultrasonography in patients presenting with ureteral stones. Study design: Cross-sectional prospective study. Place of study and duration: Urology Department, The Kidney Centre Post Graduate Training Institute from May 16 to November 15, 2019. Methods: This study included 97 patients having presented in the emergency department with acute renal colic and were diagnosed as having ureteral stones on a non-contrast-enhanced computed tomography (NCCT). The ureteric jet frequency was measured by Doppler ultrasonography by our radiologist with the Hitachi Aloka F-37 ultrasound machine after they underwent CT. Patients were asked to drink 750-1000 ml of liquids 15-20 minutes before their ultrasonographic examination of both kidneys, ureters, and urinary bladder. The kidney size (length and width) and presence/absence of hydronephrosis were evaluated by grayscale ultrasound. Then, with the help of color Doppler ultrasonography, the frequency of the ureteric jet was recorded. Results: The patient's mean age was 46.66 ± 3.21 years ranging from 37 to 56 years. There were 58 (59.8%) male and 39 (40.2%) female cases. The mean cumulative stone size was 9.77 ± 2.65 mm. According to stone location, 44 (45.4%) cases had upper ureteric, 24 (24.7%) cases had mid ureteric, and 29 (29.9%) cases had lower ureteric stone. The mean obstructive side jet frequency was 0.70/min ± 0.49, and the non-obstructive side jet frequency was 2.89/min ± 1.29 (P < 0.05). Conclusions: The mean obstructive side jet frequency was 0.70 ± 0.49/min, which, if we compare to the non-obstructed normal ureter, is significantly less. Hence, color Doppler ultrasonography can be helpful to patients who were previously diagnosed with ureteral stones on NCCT to see if their stone has passed. This can be a very cost-effective modality especially in resource-poor countries where repeat CT can be very expensive. The results from this study can also be used in a specific population (i.e., pregnancy) where the use of imaging modalities that involve ionizing radiation is prohibited.

The tremendous increase of greenhouse gases puts adverse effects on environmental degradation, unemployment, and economic growth. Against this backdrop, and implementing the more recent estimation approach, the present study investigates the validity of the novel environmental Phillips curve (i.e., inverse relationship between unemployment and environmental degradation) carried by Kashem and Rahman (2020). The unique contribution of this research is to examine the three environmental indicators (CO2, CH4, and ecological footprint) as a dependent variable with the same independent variables, i.e., unemployment rate, energy consumption, economic growth, foreign direct investment, and globalization, from 1975 to 2014 in Pakistan. The results validate a negative relationship of unemployment rate with CO2, CH4, and ecological footprint in the long run that proves the existence of environment Philips curve for Pakistan. However, a positive association is observed for energy consumption and CO2, CH4, and ecological footprint. The positive connection of energy consumption and environmental indicators determined that not only CO2 emissions rather CH4 and ecological footprint play an equal role in environmental degradation. Furthermore, in the long run foreign direct investment improves environmental sustainability for CO2, and ecological footprint thus proved the pollution halo hypothesis for Pakistan. Probing the effects of globalization that badly pollutes environmental sustainability. Therefore, the policymakers should focus on innovations and technological improvements to contemplate both environmental degradation and unemployment. There is a need for sudden actions for energy consumption plans in Pakistan for the nation’s health, economic growth, and environmental sustainability.

This paper aims to examine the differences in financial resilience of Islamic and Conventional Commercial banks with respect to the short term and long-term perspectives to pliability. The selected banks are compared on their resilience quotient exhibited by Liquidity Coverage Ratio (LCR) and Z-Scores. This study evaluates cross country panel data of 157 listed and non-listed licensed Islamic banks located in 22 countries and same number of their conventional commercial counterparts, through a period of 1998 to 2018. The data were collected through BANKSCOPE database and World Bank publications. Ratio analysis and Multiple Regression analysis were applied on data to analyze the extent of resilience of both Islamic and Conventional banks.The findings suggest that there are considerable differences in short term and long term resilience quotient of Islamic and Conventional commercial banks. Where Islamic banks have relatively enervated position than Commercial banks on liquidity frontier, they hold a more resilient position with respect to z-score. ROE and Capital adequacy are two important factors that have a significant impact on bank resilience.This research is different from all past researches with respect to methodological, aeon and acclimatization perspective. Resilience is a relatively new phenomenon adopted from complex adaptive ecosystems and most studies in this area are of theoretical nature. Moreover, the fact that this research has considered not only the long term but also short-term resilience perspective, adds to its overall value and originality.

Fintech is the merger of two terms: finance and technology. Islamic finance provides financial services to the customers in accordance to the rules and regulations prescribed by Shariah. As Islamic finance is growing by leaps and bounds since the last two decades, and so is FinTech, in the last decade. The main objective of Islamic finance is to enhance the economic growth in the society with the use of Shariah compliant financial solutions. Likewise, FinTech provides cost effective solutions for the companies and especially startups that help in the reduction of their costs and improvement in business processes. Financial industry is a very elusive yet important sector in the society, and hence heavily regulated by the regulators. The introduction of FinTech in countries, especially developing countries like Pakistan can help to boost economic growth but this will increase the workload of regulators as they must ensure stability of the financial system and to protect it from frauds/crises. Hence, proper monitoring by the regulatory authorities is crucial to avoid cyber-attack, data leakages and data theft as it can lead to misuse of the information. For the good results of FinTech, not only the users but the regulators have to be aware with the structure and functioning of the system and the regulations should be in place proactively. This paper focuses on the three main aspects namely: explaining the FinTech, opportunities for Islamic financial institutions and the challenges/issues faced by the institutions in implementing FinTech solutions. The paper also provides the current status of FinTech application globally and the potential in it to serve the poorer segments of society. The review of literature approach is used for the paper.

The contemporary debate on globalization and gender equality has a strong impact on economic growth. The present study analyzes the impacts of globalization and gender parity on economic growth in the Organization of Islamic Cooperation (OIC) 47 member countries for the period (1991-2017), using System GMM panel data technique. The results of system GMM have also been empirically estimated by making two groups (viz., low-income and high-income OIC member countries from the World Bank data classification, 2019) to examine the robustness of globalization and gender parity on economic growth. The results reveal that there is a negative impact of globalization on economic growth in the overall sample of OIC countries. When estimated by decomposing low-income countries and high-income countries, globalization has a significantly positive impact on economic growth in the case of high-income OIC countries, whereas globalization slashes GDP in the case of low-income OIC countries. The study finds that there is a positive impact of gender parity (ratio of female to male labor force work participation) on economic growth. Moreover, foreign remittances, government expenditures, capital formation, and human capital are also becoming the causes of a significant increase in economic growth in OIC member countries.

Background: N-Acetylcysteine and 3% hypertonic saline are being used effectively for sputum clearance in chronic cases of bronchiectasis for quite some time. However, their use in acute condition of the disease seems to be underexplored. The objective of our study is to compare the role of nebulized N-acetylcysteine and 3% hypertonic saline in clearing the airway in patients with acute exacerbation of bronchiectasis. Material and Methods: A total of 136 confirmed cases of bronchiectasis were enrolled in this study. This randomized controlled trial was done in chest ward of Nishtar Hospital Multan from January 2015 to March 2017. Sampling was done by non-probability consecutive sampling and patients were divided into two groups A and B by lottery method. Verbal informed consent was taken from all participants. Group A participants received nebulization of N acetylcysteine mixed in normal saline for ten minutes, while group B participants were nebulized with 10ml of 3% hypertonic saline for ten minutes. Group B was active control group in the study. Data was collected on pre-designed Proforma, and analyzed by SPSS version 22. Numerical variables such as saturation, weight of sputum, age and blood pressure was analyzed by using t test. These were considered significant if the p value was equal or less than 0 .05. For qualitative variables chi square test was applied. Results: The mean O2 saturation of Group A, before and after treatment, was 92.11±3.07% and 94.47±2.18%, respectively. The difference was statistically significant (p value =0.001). The sputum weight of Group A, before and after treatment, was 2.63±2.39 g and 7.41±1.38 g, respectively. The difference was statistically significant (p value =0.001). The frequency of rhonchi of Group A, before and after treatment, was 52% and 76%, respectively. The difference was statistically significant (p value =0.003). While, for Group B, the mean O2 saturation, before and after treatment, was 92.36±3.13% and 93.49±2.27%, respectively. The difference was statistically significant (p value =0.012). The sputum weight, before and after treatment, was 3.11±2.01 g and 5.56±1.02 g, respectively. The frequency of rhonchi, before and after treatment, was 45% and 74% respectively. Again, the difference was statistically significant. Conclusion: Both nebulized N-acetylcysteine and 3% hypertonic saline cause airway clearance by enhancing sputum expectoration in patients with acute exacerbation of bronchiectasis equally. Both these agents also improve oxygen saturation in acute exacerbation of bronchiectasis significantly.

The present research endeavors to evaluate whether trade liberalization, foreign direct investment inflows and environmental quality affect the economic growth in Pakistan and China. These have crucial role in the economies and pragmatic for formulating economic growth policies. The secondary data is used for all the variables. The ARDL bounds testing approach to cointegration is applied to evaluate the determinants included in the model for both countries. The results of the research conclude that trade liberalization and foreign direct investment both have positive impact on economic growth while environmental pollution has negative impact on economic growth in long-run.

This study analyzed the association between household employment and household poverty using logit regression on survey data of Multan District. It is found that qualification of household head, gender of household head, household employment rate, number of males employed in formal sector, number of females employed in informal sector, females permitted to paid work outside home, female’s autonomy to utilize household resources, possession of agricultural land, residence, possession of livestock and government health facility in household’s vicinity have significantly negative impact on probability of household’s poverty. Household size and number of children (≤ 5 years) are positively associated with household poverty. It is suggested that empowering women and creating productive employment opportunities in both formal and informal sectors may help to reduce poverty..

This study examines the relationship between trade liberalization, gender inequality and economic development in 18 selected developing countries over the time period from 1993 to 2017. Panel ARDL approach has been employed to examine the relationship among variables. The results of the study suggest that trade openness and gender inequality in education and employment, and female to male ratio have negative impact on GDP per capita in developing countries. Based on these results and keeping in view the importance of trade openness and gender equality for economic development, this study is useful to suggest that export led trade policy and provision of equal opportunities to both male and female in education and employment should be adopted in order to achieve higher levels of economic development and for bringing gender equality in all economic activities.