Impact of FDI and Trade Balance on Economic Growth during 1990-2014, a Case Study of Pakistan

Purpose:The purpose of this study is to investigate the impact of macroeconomic variables, Foreign Direct Investment and Trade Balance on the Economic Growth (GDP) on Pakistan economy by using the 25 years data from the time period 1990-2014.Methodology:For the empirical finding time series annually data are used to monitor by examination the stationarity of all dependent and independent variables. Unit root (ADF) test are used to check the stationarity of all the variables. Additionally The Johansen co-integrated test to check the long run relationship in the middle of the variables and to see the short run relationship VECM are used. All the variables are significant, and goodness of fit use regression the econometric model is analyses.Findings:The study found that there is significant impact of independent variables Foreign Direct Investment and Trade Balance on dependent variable GDP. And the signs of co-efficient shows, Trade Balance have negative relation with GDP while Foreign Direct Investment has positive relation with GDP. Keywords: Unit Root , Co-integrated , ECM , Regression , FDI , Trade Balanc

Digital Twin Concept, Method and Technical Framework for Smart Meters

Smart meters connect smart grid electricity suppliers and users. Smart meters have become a research hotspot as smart grid applications like demand response, power theft prevention, power quality monitoring, peak valley time of use prices, and peer-to-peer (P2P) energy trading have grown. But, as the carriers of these functions, smart meters have technical problems such as limited computing resources, difficulty in upgrading, and high costs, which to some extent restrict the further development of smart grid applications. To address these issues, this study offers a container-based digital twin (CDT) approach for smart meters, which not only increases the user-facing computing resources of smart meters but also simplifies and lowers the overall cost and technical complexity of meter changes. In order to further validate the effectiveness of this method in real-time applications on the smart grid user side, this article tested and analyzed the communication performance of the digital twin system in three areas: remote application services, peer-to-peer transactions, and real-time user request services. The experimental results show that the CDT method proposed in this paper meets the basic requirements of smart grid user-side applications for real-time communication. The container is deployed in the cloud, and the average time required to complete 100 P2P communications using our smart meter structure is less than 2.4 seconds, while the average time required for existing smart meter structures to complete the same number of P2P communications is 208 seconds. Finally, applications, the future development direction of the digital twin method, and technology architecture are projected

Persistence of post-COVID lung parenchymal abnormalities during the three-month follow-up

Introduction: COVID-19-associated pulmonary sequalae have been increasingly reported after recovery from acute infection. Therefore, we aim to explore the charactersitics of persistent lung parenchymal abnormalities in patients with COVID-19.Material and methods: An observational study was conducted in patients with post-COVID lung parenchymal abnormalities from April till September 2020. Patients ≥18 years of age with COVID-19 who were diagnosed as post-COVID lung parenchymal abnormality based on respiratory symptoms and HRCT chest imaging after the recovery of acute infection. Data was recorded on a structured pro forma, and descriptive analysis was performed using Stata version 12.1.Results: A total of 30 patients with post-COVID lung parenchymal abnormalities were identified. The mean age of patients was 59.1 (SD 12.6), and 27 (90.0%) were males. Four HRCT patterns of lung parenchymal abnormalities were seen; organizing pneumonia in 10 (33.3%), nonspecific interstitial pneumonitis in 17 (56.7%), usual interstitial pneumonitis in 12 (40.0%) and probable usual interstitial pneumonitis in 14 (46.7%). Diffuse involvement was found in 15 (50.0%) patients, while peripheral predominance in 15 (50.0%), and other significant findings were seen in 8 (26.7%) patients. All individuals were treated with corticosteroids. The case fatality rate was 16.7%. Amongst the survivors, 32.0% recovered completely, 36.0% improved, while 32.0% of the patients had static or progressive disease.Conclusion: This is the first study from Southeast Asia that identified post-COVID lung parenchymal abnormalities in patients who had no pre-existing lung disease highlighting the importance of timely recognition and treatment of this entity that might lead to fatal outcome

Co-Integration Between Fertility and Human Development Indicators: Evidence from Pakistan

The main focus of this paper is to investigate the long run co-integration and short run dynamics between fertility decline and development indicators in Pakistan. Bound Testing approach (ARDL) and VECM are applied on annual time series data from 1971-2010 after finding mixed order of integration of the series through Ng -Perron unit root test. The results show that long run co-integration and short run dynamics exist between total fertility rate and Human Development Indicators (secondary school enrollment, life expectancy at birth and GDP per capita). Secondary school enrollment and life expectancy at birth prove the negative and significant impact on fertility, while GDP per capita indicated the positive but insignificant impact on fertility. The findings of study suggest that more resources should be invested in human capital formation through the provision of better education and health facilities to keep the fertility on declining

Co-Integration Between Fertility and Human Development Indicators: Evidence from Pakistan

The main focus of this paper is to investigate the long run co-integration and short run dynamics between fertility decline and development indicators in Pakistan. Bound Testing approach (ARDL) and VECM are applied on annual time series data from 1971-2010 after finding mixed order of integration of the series through Ng -Perron unit root test. The results show that long run co-integration and short run dynamics exist between total fertility rate and Human Development Indicators (secondary school enrollment, life expectancy at birth and GDP per capita). Secondary school enrollment and life expectancy at birth prove the negative and significant impact on fertility, while GDP per capita indicated the positive but insignificant impact on fertility. The findings of study suggest that more resources should be invested in human capital formation through the provision of better education and health facilities to keep the fertility on declining

The prevalence of bipolar spectrum disorder in medical students of Pakistan

Background: Bipolar affective disorder is cyclic swinging of mood between mania or hypo-mania and depression. Bipolar disorder is the sixth leading cause of disability worldwide and has a lifetime prevalence of about 1 to 3% in the general population. Despite a growing body of knowledge on bipolar spectrum disorder (BSD), relatively little is known about the clinical characteristics of BSD in medical students. This study evaluates the prevalence and severity of BSD in medical students in relation to certain socio-demographic factors like age, sex and class of education.Methods: A questionnaire based study was done on 298 medical students of Nishtar Medical University, Multan and Shaikh Zayed Medical College, Rahim Yar Khan chosen on basis of random sampling to test the prevalence of bipolar spectrum disorders using Mood Disorder questionnaire (MDQ). Out of these students 161 were males and 137 were females. Students were interviewed to obtain information about age, sex and academic year of education.Results: According to mood disorder questionnaire scoring, of the total 298 students 80 (26.84%) screened positive for bipolar spectrum disorder (BSD). Among 80 students who screened positive for BSD 43 (53.75%) are males while 37 (46.25%) are females. Class-wise distribution of BSD is as follows: Out of 80 students screened positive 15 (18.75%) are from 2nd year, 22 (27.5%) from 3rd year and 43 (53.75) from 4th year. Age-wise distribution of BSD is as following: Students of age 19, 20, 21, 22 and 23 years suffering from BSD were 5 (6.25%), 17 (21.25%), 23(28.75),22 (27.5%) and 13 (16.25%) respectively.Conclusions: In our study, the estimated rate of prevalence for bipolar spectrum disorder among medical students of Pakistan is 26.84%. There was no significant difference in prevalence on the basis of gender. Prevalence was increasing with both age and class wise distribution

Smart Meter Development Using Digital Twin Technology for Green Energy Distribution Optimization

This study proposes a digital twin (DT) approach and technical framework for smart meters to solve potential implementation and development problems and adapt to the new energy revolution trend and increase smart grid network security. DT models were deployed in the cloud and edge using a smart meter DT demonstration system. This paper evaluates the DT system's communication performance in real-time smart grid application through three dimensions: remote application service for smart grid user side, P2P transaction on the user side, and user real-time request service. This study's container-based decision tree strategy for smart meters meets the smart grid's real-time communication requirements for user-side applications

In vitro evaluation of antimicrobial and cytotoxic potential of Epimedium grandiflorum hydroethanolic extract as natural medicine

Medicinal plants are used as fundamental and low-cost source for remedy of numbers of infectious and metabolic diseases in developing and developed countries. Current research work was planned to evaluate the antibacterial, antifungal, and cytotoxic potential of hydroethanolic extract of E. grandiflorum. It was found that selected natural medicinal herb have significant (p<0.05) antibacterial activities tested against Bacillus subtilis, Staphylococcus aureus, Pasteurella multocida, Escherichia coli, Klebsiella pneumoniae, Acinetobacter species, Pseudomonas Species and Salmonella Species. The results of bacterial biofilm inhibition also explored that selected natural herb has significant (p<0.05) capacity to prevent the microbial biofilm particularly at higher dose. The results of antifungal activities showed that selected medicinal plant has significant (p<0.05) antifungal potential evaluated against Aspergillus flavus, Aspergillus niger, Aspergillus terreus, Fusarium solani, Alternata alternaria, and Schizophyllum species. Moreover, the results of mutagenicity test and DNA damage preventive test explored that selective medicinal plant has significant (p<0.05) DNA protective capacity or in other words it is non-mutagenic or cytotoxic in nature. It could be concluded that E. grandiflorum could be a potential candidate as therapeutic agent to manage infectious diseases especial bacterial and fungal infections with non-toxic nature

Design a framework for IoT- Identification, Authentication and Anomaly detection using Deep Learning: A Review

The Internet of Things (IoT) connects billions of smart gadgets so that they may communicate with one another without the need for human intervention. With an expected 50 billion devices by the end of 2020, it is one of the fastest-growing industries in computer history. On the one hand, IoT technologies are critical in increasing a variety of real-world smart applications that can help people live better lives. The cross-cutting nature of IoT systems, on the other hand, has presented new security concerns due to the diverse components involved in their deployment. For IoT devices and their inherent weaknesses, security techniques such as encryption, authentication, permissions, network monitoring, \& application security are ineffective. To properly protect the IoT ecosystem, existing security solutions need to be strengthened. Machine learning and deep learning (ML/DL) have come a long way in recent years, and machine intelligence has gone from being a laboratory curiosity to being used in a variety of significant applications. The ability to intelligently monitor IoT devices is an important defense against new or negligible assaults. ML/DL are effective data exploration techniques for learning about 'normal' and 'bad' behavior in IoT devices and systems. Following a comprehensive literature analysis on Machine Learning methods as well as the importance of IoT security within the framework of different sorts of potential attacks, multiple DL algorithms have been evaluated in terms of detecting attacks as well as anomaly detection in this work. We propose a taxonomy of authorization and authentication systems in the Internet of Things based on the review, with a focus on DL-based schemes. The authentication security threats and problems for IoT are thoroughly examined using the taxonomy supplied. This article provides an overview of projects that involve the use of deep learning to efficiently and automatically provide IoT applications

An annotated checklist of Coccinellidae with four new records from Pakistan (Coleoptera, Coccinellidae)

Some new ladybird (Coleoptera: Coccinellidae) records collected during the last four years across Sindh are reported. A first preliminary checklist of ladybirds from Sindh is presented, consisting of one subfamily, ten tribes, 21 genera, and 29 species including four new records, namely Bulaea lichatschovii (Hummel), Exochomus pubescens Küster, Scymnus (Pullus) latemaculatus Motschulsky, Scymnus (Pullus) syriacus Marseul, and four varieties of the species Cheilomenes sexmaculatus (Fabricius)