This article contributes to literature on corporate social responsibility exhibited by industrial clusters in developing countries. The authors conceptualize and empirically investigate the role of donor-funded CSR initiatives aimed at promoting collective action by cluster-based small- and medium-sized enterprises. A case study of the Sialkot football-manufacturing cluster in Pakistan indicates that donor-funded support of CSR initiatives in industrial clusters in developing countries may be short-lived, due to the political economy of aid, the national context of CSR implementation, tensions within SME (...) networks, and negative perceptions of CSR by the cluster-based SMEs themselves. The findings and implications of this analysis can inform both research and policy making in this area. (shrink)

We examine how corporate social responsibility (CSR) perceptions (association and participation) affect manager creativity at the workplace and its mediating link through organisational identification. We collected data from the National Forum of Environment and Health (NFEH) 2019 that awarded 52 companies in Pakistan. NFEH is a purely non-profit, non-governmental, and voluntary organisation registered under the Voluntary Social Welfare Agencies Ordinance 1961. We employed convenience sampling to collect data from managers of 52 CSR performing organisations in Pakistan. We analyse the data (...) with structural equation modelling (SEM) via R. Findings reveal that CSR association does not affect creativity. In contrast, CSR participation has a significant positive effect on manager creative performance. Furthermore, the decomposition analysis indicated that only in the case of CSR participation, OI has a mediating effect. (shrink)

In the ninth century (A.H.) the number of Sufis and their sects increased due to Timurids’ attention to Sufis, and as a consequence convents (Khaneqa) became one of the most important economical and political centers. Excessive wealth and spiritual influence of Sufis leaders particularly Sheikhs of Naqshbani kingdom result in Sufism power being twice as much so that, Timurid kings and Sultans used their spiritual influence to legitimize their rules and tried not only to respect and honor them but also, (...) to construct and operate their Khaneqas. Close relationship between Naqshbani’s leaders and Timurid Sultans had a great influence on most country’s affairs, particularly education and training as most of removal and installations in the field of educational affairs were under their views. In this survey, the impact of Naqshbandi’s Sheikhs on educational process during Timurid period was investigated and analyzed by citing library references and implementing analytical-descriptive method. (shrink)

The Kashmir issue, a principal reason for rivalry between India and Pakistan, has become the atomic flashpoint and a constant threat to the security of South Asia. The aim of this paper is to highlight the root causes of Kashmir disputes and the major events that contributed towards the Indo-Pak rivalry with respect to Kashmir. The paper highlights present political conditions in the Indian-held Kashmir also shows the role of India, Pakistan, and the United Nations in Kashmir Dispute. In the (...) end, a conclusion is presented for the devalued relations of India and Pakistan in the setting of Kashmir and its effects are analyzed. (shrink)

In the area of machine learning, different techniques are used to train machines and perform different tasks like computer vision, data analysis, natural language processing, and speech recognition. Computer vision is one of the main branches where machine learning and deep learning techniques are being applied. Optical character recognition is the ability of a machine to recognize the character of a language. Pashto is one of the most ancient and historical languages of the world, spoken in Afghanistan and Pakistan. OCR (...) application has been developed for various cursive languages like Urdu, Chinese, and Japanese, but very little work is done for the recognition of the Pashto language. When it comes to handwritten character recognition, it becomes more difficult for OCR to recognize the characters as every handwritten character’s shape is influenced by the writer’s hand motion dynamics. The reason for the lack of research in Pashto handwritten character data as compared to other languages is because there is no benchmark dataset available for experimental purposes. This study focuses on the creation of such a dataset, and then for the evaluation purpose, a machine is trained to correctly recognize unseen Pashto handwritten characters. To achieve this objective, a dataset of 43000 images was created. Three Feed Forward Neural Network models with backpropagation algorithm using different Rectified Linear Unit layer configurations were trained and tested with this dataset. The simulation shows that Model 1 achieved accuracy up to 87.6% on unseen data while Model 2 achieved an accuracy of 81.60% and 3% accuracy, respectively. Similarly, loss was the lowest for Model 1 with 0.15 and 3.17 for training and testing, followed by Model 2 with 0.7 and 4.2 for training and testing, while Model 3 was the last with loss values of 6.4 and 3.69. The precision, recall, and f-measure values of Model 1 were better than those of both Model 2 and Model 3. Based on results, Model 1 is found to be the most efficient as compared to the other two models in terms of accuracy to recognize Pashto handwritten characters. (shrink)

The primary aim was to assess the role of mental and physical health of COVID-19 and its psychological impact in the general population of Pakistan during the first wave of COVID-19. It was hypothesized that there would be a significant predictive association among socio-demographic variables, psychological impact and mental health status resulting from COVID-19, and poor self-reported physical health would be significantly associated with adverse psychological impact and poor mental health status because of COVID-19. A cross-sectional survey research design was (...) used in which 1,361 respondents were sampled online during lockdown imposed in the country. The Impact of Events Scale-Revised was used to assess the psychological impact of COVID-19, and the Depression Anxiety Stress Scales was used to assess participants’ mental health status. 18% of the respondents reported moderate to severe event-specific distress, 22.6% reported moderate to severely extreme depression, 29% reported moderate to extreme anxiety, and 12.1% reported moderate to extreme stress. Female gender, having graduate-level education, currently studying, and self-reported physical symptoms were significantly associated with higher levels of psychological impact exhibited through higher scores on the IES-R and poorer mental health status exhibited through higher scores on the DASS-21. (shrink)

In this article, we solve nonlinear systems of third order KdV Equations and the systems of coupled Burgers equations in one and two dimensions with the help of two different methods. The suggested techniques in addition with Laplace transform and Atangana–Baleanu fractional derivative operator are implemented to solve four systems. The obtained results by implementing the proposed methods are compared with exact solution. The convergence of the method is successfully presented and mathematically proved. The results we get are compared with (...) exact solution through graphs and tables which confirms the effectiveness of the suggested techniques. In addition, the results obtained by employing the proposed approaches at different fractional orders are compared, confirming that as the value goes from fractional order to integer order, the result gets closer to the exact solution. Moreover, suggested techniques are interesting, easy, and highly accurate which confirm that these methods are suitable methods for solving any partial differential equations or systems of partial differential equations as well. (shrink)