Social Entrepreneurship in Pakistan: Challenges and Prospects

Social Entrepreneurship (SE) benefits the society by helping to achieve social and economic goals. SE is receiving scholarly attention around the globe but its development is still moderate in Pakistan. Despite the growing trend, the dominant focus of scholars remains the ideological debate about the meaning and definition of SE. Such an approach inhibits the exploration of its other facets. Casting the gap in literature, this paper aims to find out the challenges and prospects that social entrepreneurs face in their journey, specifically in Pakistan. Keeping in view the emerging importance of this sector, this study discusses the findings of 14 in-depth semi-structured interviews conducted with leading social entrepreneurs, practitioners and academicians related to the field to understand the phenomenon at hand. Drawing upon the findings of the study, useful insights have been put forth as its theoretical contribution. Moreover, local and national government can benefit from the findings to enhance consciousness regarding the fourth sector of the economy, eventually augmenting the available social capital

Potential bioactive coating system for high-performance absorbable magnesium bone implants

Magnesium alloys are considered the most suitable absorbable metals for bone fracture fixation implants. The main challenge in absorbable magnesium alloys is their high corrosion/degradation rate that needs to be controlled. Various coatings have been applied to magnesium alloys to slow down their corrosion rates to match their corrosion rate to the regeneration rate of the bone fracture. In this review, a bioactive coating is proposed to slow down the corrosion rate of magnesium alloys and accelerate the bone fracture healing process. The main aim of the bioactive coatings is to enhance the direct attachment of living tissues and thereby facilitate osteoconduction. Hydroxyapatite, collagen type I, recombinant human bone morphogenetic proteins 2, simvastatin, zoledronate, and strontium are six bioactive agents that show high potential for developing a bioactive coating system for high-performance absorbable magnesium bone implants. In addition to coating, the substrate itself can be made bioactive by alloying magnesium with calcium, zinc, copper, and manganese that were found to promote bone regeneration

Proximate and sensory analysis of wheat bread supplemented with Nigella sativa oil and Nigella sativa extract

Wheat is one of the important food crops worldwide while wheat bread is the most commonly consumed form of it in different populations. As Nigella sativa is rich in several phytochemicals that possess disease preventive properties hence, the proximate and sensory analysis of the breads supplemented with Nigella sativa extract and oil have been discussed in this study. Nigella sativa is one of the famous medicinal plants that has been used for treatment of various illnesses in different parts of the world. Compositional analysis revealed that Nigella sativa extract supplemented bread contains 14.75% moisture content, 10.32% crude fat content, 4.40 % ash and 3.55 % crude fiber, 11.89% crude protein and 55.09% Nitrogen Free Extract (NFE). In comparison, analysis of Nigella sativa oil supplemented revealed that it contains 14.23%, moisture content, 10.53% crude fat content, 4.10% ash and 3.20 % crude fiber, 11.79% crude protein and 56.15% NFE. Sensory evaluation was evaluated using 9 points-hedonic scale. Maximum score for overall acceptability was recorded for Nigella sativa extract fortified bread. In the meantime, the requests for wheat-based items with value addition are developing quickly in the previous couple of decades, as customers understood that eating foods with medical advantages is superior to taking medicine. The breads fortified with Nigella sativa will not only meet the consumer demands in terms of sensory attributes but might also aid in improving their health

Efficient Contact Tracing for pandemics using blockchain

Blockchain technologies have been benefiting many industries by being decentralized, secure and confidential. They offer great potential in pandemic impacted scenarios as well. Contact tracing helps to mitigate the transmission of disease by alerting people who may have been exposed so they can act on time to protect themselves. Contact tracing systems face some challenges related to issues of medical privacy, data security and transparency. Multiple researches show concern that contact tracing discourages people to seek medication because of the fear of loss of data, subsequent stigma, discrimination, or abuse. In this paper, we discuss how contact tracing can be improved using blockchain technology and could be able to solve these issues. The aim of our proposed system would be to reduce the impact of pandemic, to implement this merger of the blockchains and the Contact tracing app and to ensure user privacy and avoid data misuse by incorporating a symmetric key cryptographic mechanism. To tackle the scalability related issues of Blockchain this framework uses IPFS, a distributed file storage system also known as Interplanetary File System. This blockchain based solution system will enhance contact tracing by making it more stable, secure, performant, highly useable and above all effective in the fight against any pandemic

Trends in antimicrobial resistance amongst pathogens isolated from blood and cerebrospinal fluid cultures in Pakistan (2011-2015): A retrospective cross-sectional study

While antimicrobial resistance (AMR) continues to be a major public health problem in Pakistan, data regarding trends of resistance among pathogenic bacteria remains scarce, with few studies presenting long-term trends in AMR. This study was therefore designed to analyze long-term AMR trends at a national level in Pakistan. We report here results of a comprehensive analysis of resistance, among pathogens isolated from blood and cerebrospinal fluid (CSF), between 2011 and 2015. Susceptibility data was obtained from a local laboratory with collection points all across Pakistan (Chughtai Laboratory). Resistance proportions to most commonly used antimicrobials were calculated for each pathogen over a period of five years. While Acinetobacter species demonstrated highest resistance rates to all tested antimicrobials, a sharp increase in carbapenem resistance was the most noticeable (50%-95%) between 2011-2015. Our results also highlight the presence of third and fourth generation cephalosporins resistance in Salmonella enterica serovar Typhi in Pakistan. Interestingly, where rise in AMR was being observed in some major invasive pathogens, decreasing resistance trends were observed in Staphylococcus aureus, against commonly used antimicrobials. Overall pathogens isolated from blood and CSF between 2011-2015, showed an increase in resistance towards commonly used antimicrobials

Can Economic Globalization Cure Unemployment in Pakistan? An Empirical Investigation

In the current economic climate of boosted economic globalization culture that results in an ease in the movement of resources from one corner of the globe to the other, unemployment is still a bitter reality. Using annual data for Pakistan from 1986 to 2020, an attempt was made in this study to empirically evaluate the long-run and short-run link between the unemployment rate and FDI, economic growth, and trade. Using the multivariate co-integration technique, the data were examined. The long-term link between the unemployment rate and explanatory variables was validated by Johansen's co-integration method. The data series' stationarity was verified using the Augmented Dickey-Fuller unit root test (ADF test), which demonstrates that all of the relevant variables are first-difference stationary. Results suggested a contradiction between the unemployment rate and foreign direct investment. Also, extensive studies found a conflict between economic expansion and the unemployment rate. While there is a long-term positive correlation between trade and the unemployment rate. Using the Impulse Response Function, short-run relationships are evaluated. &nbsp

Workplace Bullying effects on Family Incivility

This study has undertaken to inspect how “Workplace Bullying affects Family Incivility” mediated by negative emotions. We additionally tested that if there is any moderation of neuroticism exists between relationship of emotions and family incivility. The focus of the past research work or even the most recent research was the health of the affected, their performance in the organization, psychological impacts, people working in the private sectors, health sector such as nurses and medical attendants, leadership effectiveness & employees’ productivity, intention to leave the organization etc. Different sectors are combined in this research work for example, responses of the respondents working in both public and private sectors are included. Moreover, it is also strived in this research work to get the opinion of medical practitioners about how the Workplace Bullying affects or can affects the life of the individual negatively. Data were collected from the employees of different corporate jobs in Lahore, Pakistan. 109 workers complete the questionnaires and finally, 109 legal responses were used for the SPSS analysis. The analytical findings revealed that there is a positive relationship exists between “Workplace Bullying affects Family Incivility” By understanding that workplace bullying has determinable impacts on family incivility and corporate workers performances, administrations and supervisors should offer better support for employees in handling family incivility and help them to uphold an improved stability between work and family life

Abstractive text summarization of low-resourced languages using deep learning

Background Humans must be able to cope with the huge amounts of information produced by the information technology revolution. As a result, automatic text summarization is being employed in a range of industries to assist individuals in identifying the most important information. For text summarization, two approaches are mainly considered: text summarization by the extractive and abstractive methods. The extractive summarisation approach selects chunks of sentences like source documents, while the abstractive approach can generate a summary based on mined keywords. For low-resourced languages, e.g., Urdu, extractive summarization uses various models and algorithms. However, the study of abstractive summarization in Urdu is still a challenging task. Because there are so many literary works in Urdu, producing abstractive summaries demands extensive research. Methodology This article proposed a deep learning model for the Urdu language by using the Urdu 1 Million news dataset and compared its performance with the two widely used methods based on machine learning, such as support vector machine (SVM) and logistic regression (LR). The results show that the suggested deep learning model performs better than the other two approaches. The summaries produced by extractive summaries are processed using the encoder-decoder paradigm to create an abstractive summary. Results With the help of Urdu language specialists, the system-generated summaries were validated, showing the proposed model’s improvement and accuracy