Building World-Class University in Pakistan: Opportunities and Constraints

The article explores the issues of academic excellence in higher education to pursue a position in world-class universities. Two universities in Pakistan have been chosen for the site of this qualitative study, one which has achieved the status, and the other still aspiring. The triangulation has been reached by a document analysis of the quality reports submitted by the two universities, semi-structured interviews with the senior and middle management of the universities, deans, and director for Quality Enhancement Cells, and head of the departments of the selected universities. The primary data obtained have been compared and contrasted with the quality characteristics marked by standards for academic excellence. Research findings inform us that unawareness of the international quality standards, and its potential benefits, the disinterest of university leadership are the main problems, due to which Pakistani universities are lagging behind. The study proposes if proper understanding and meaningfulness is created through quality professionalism, it would become much easier to pursue quality assurance process to meet international standards. The findings of the study will be a unique contribution to the body of literature creating a point of interest to policymakers and quality assurance practitioners of the developing countries who are concerned about the academic excellence of Higher Education Institutions (HEIs) to accentuate in the significant areas which make any university, a world-class university

Ovarian pregnancy: an unusual presentation

Ovarian pregnancy is a rare type of ectopic pregnancy and usually, it ends with rupture before the end of the first trimester. The clinical picture generally mimics that of ruptured tubal ectopic pregnancy and hemorrhagic ovarian cyst. Transvaginal sonography may be helpful. We report a rare primary ruptured ovarian pregnancy in a 23 years lady

Synthesis and Biological Evaluation of Novel Gallic Acid Analogues as Potential Antimicrobial and Antioxidant Agents

A series of fifteen novel gallic acid esters (7a-o) was synthesized and structure was confirmed by spectral data. Antibiotic power of compounds was assessed against a panel of ten microbes while antioxidant activity was gauged by employing DPPH, ABTS and antilipid peroxidation assays. It was found that in comparison to lead, many of the synthesized derivatives implied much improved broad spectrum antimicrobial effect. Most effective compound found was 7c specifically against resistant gram-negative strains such as P. aeruginosa, E. coli and E. aerogenes. Potent antioxidant capacity was exhibited by7a and 7d in electron transfer assays while 7j and 7c provided maximum shielding against lipid peroxidation. Structure-activity analysis revealed that analogues with electron -withdrawing substituent particularly chloro group stand out as much better antibiotic agent. This study suggests that halogenated gallic acid analogues might be promising pharmacological candidates in view of further drug development. This work is licensed under a Creative Commons Attribution 4.0 International License

Furin and the adaptive mutation of SARS-COV2: A computational framework

SARS-2 virus has reached its most harmful mutated form and has damaged the world's economy, integrity, health system and peace to a limit. An open problem is to address the release of antibodies after the infection and after getting the individuals vaccinated against the virus. The viral fusion process is linked with the furin enzyme and the adaptation is linked with the mutation, called D614G mutation. The cell-protein studies are extremely challenging. We have developed a mathematical model to address the process at the cell-protein level and the delay is linked with this biological process. Genetic algorithm is used to approximate the parametric values. The mathematical model proposed during this research consists of virus concentration, the infected cells count at different stages and the effect of interferon. To improve the understanding of this model of SARS-CoV2 infection process, the action of interferon (IFN) is quantified using a variable for the non-linear mathematical model, that is based on a degradation parameter gamma. This parameter is responsible for the delay in the dynamics of this viral action. We emphasize that this delay responds to the evasion by SARS-CoV2 via antagonizing IFN production, inhibiting IFN signaling and improving viral IFN resistance. We have provided videos to explain the modeling scheme

Exploring the Role of Self-Efficacy on Individual Work Performance of Female Police Constables in Pakistan: A Conceptual Framework

In Pakistan, the number of female police constables is significantly lower than that of their male counterparts, resulting in increased discrimination that often negatively impacts their self-efficacy. This conceptual paper examines the influence of self-efficacy on the individual work performance of female police constables in Pakistan. Various theories were explored to identify the factors affecting work performance. One such theory, individual work performance theory, defines different dimensions of work performance, including task performance, counterproductive work behaviour, and contextual performance. Another key theory, the social cognitive theory of self-efficacy, analyses the relationship between self-efficacy and work performance, emphasising the mediating dimensions of work performance. This theory posits that individuals can effectively plan and execute actions to achieve specific goals through targeted behaviours. Building on these theoretical foundations, this paper proposes a conceptual framework illustrating the direct relationship between self-efficacy and work performance, along with the mediation of various performance dimensions and the influence of the workplace environment. Keywords: self-efficacy, work performance, task performance, counterproductive work behaviour, contextual work performanc

Analysis of rule-based and shallow statistical models for COVID-19 cough detection for a preliminary diagnosis

Coronavirus pandemic that has spread all over the world, is one of its kind in the recent past, that has mobilized researchers in areas such as (not limited to) pre-screening solutions, contact tracing, vaccine developments, and crowd estimation. Pre-screening using symptoms identification, cough classification, and contact tracing mobile applications gained significant popularity during the initial outbreak of the pandemic. Audio recordings of coughing individuals are one of the sources that can help in the pre-screening of COVID-19 patients. This research focuses on quantitative analysis of covid cough classification using audio recordings of coughing individuals. For analysis, we used three different publicly available datasets i.e., COUGHVID, NoCoCoDa, and a self-collected dataset through a web application. We observed that wet cough has more correlation with covid cough as opposed to dry cough. However, the classification model trained with wet and dry coughs, both, has similar test performance as that of the model trained with wet cough samples only. We conclude that audio-signal recordings of coughing individuals have the potential as a pre-screening test for COVID-19

Deployment of renewable energy in the province of Punjab – drivers and barriers

In this paper, drivers and barriers associated with deployment of solar, wind and hydro green energy generation in Pakistan’s second largest province Punjab have been explored. Through extensive analysis, it is established that foreign investments in local projects, advancement in renewable energy (RE) technologies such as energy storage systems, reduction in carbon emissions, provision of net-metering, and significant cost and energy savings are key factors in driving the use of renewable energy systems in the region. On the other hand, barriers towards the deployment of renewable energy generation are equipment theft, lack of trained personnel, site conservation issues, lack of long term policy, high transaction costs, financial and institutional barriers and power sector transmission losses. In order to overcome these barriers, substantial action is being taken by the Government of Punjab in the form of training programs, revised legislation, monitoring of installed renewable energy projects and proposing more efficient models of renewable energy generation

Synthetization and Characterization of Zinc Oxide Nanoparticles by X- Ray Diffractometry (XRD), Fourier Transforms, Infra-Red Spectroscopy (FT-IR), Scanning Electron Microscopy (SEM) and Antibacterial Activity Test

Purpose: Nanomaterials with their derivable potentials offer wide obtain ability and have recently aroused much attention for biomedical applications. Nowadays, nanomaterials-based colorimetric sensing is a quickly emerging field of sensing applications. Nanomaterials are considered as the main component of colorimetric determination of hydrogen peroxide to replace the natural enzyme-based sensors because of some associated intrinsic drawbacks. Considering the advantageous properties of ionic liquid (IL) for various applications, significant attention has been made to the use of ionic liquid stabilized metal NPs which may serve as a regulator to enhance the catalytic performance of the metal nanoparticles in the different IL reaction medium. Methodology: The peroxidase-like activity of IL coated metal NPs (IL-MNPs) have been considered for the catalytic oxidation reaction of chromogenic substrate 3,3,5,5- tetramethylbenzidine (TMB) in the presence of H2O2 at an estimated wavelength of 652 nm. Results: The synthesized metal nanoparticles (Ag) were produced using a chemical reduction method. Various characterization techniques like FTIR, UV-Visible spread Reflectance Spectroscopy [UV-VIS DRS], were employed, which verified the structure, nano-size and successful combination of metal dopant ion into the samples. The molecular structure of ionic liquid with varying cations was produced and confirmed by 1H-NMR spectroscopy. The ionic liquid was coated on metal nanoparticles to enhance their conductivity. Unique Contribution to Theory, Practice and Policy: Optimized reaction conditions like pH, temperature and catalyst dosage affect catalytic activity and color sensing properties. The coating of [Min] Ac on Ag achieved low detection limits and colorimetric detection of [Pyr] based Ag

The Impact of Debt Service and Inflation on Economic Growth in Pakistan: Evidence from ARDL Model and Approximate Bayesian Analysis

The economy of Pakistan has been facing instability and downward trends due to several factors, such as rising foreign debt and goods and services prices. The regression and ARDL models are applied by using R software. Adding lag values of variables become necessary to measure the long-run relationship. Using an ARDL model with GDP as response variable, inflation rate and debt service as explanatory variables, it is found that GDP has significant negative relationship with lagged values of GDP at t-2, t-4, inflation rate at t-2, and debt service. The multiple linear regression explains 24.5% of the variation, whereas the ARDL fits well and explains 82.9% of the variation. Utilizing Bayesian analysis with ABC-MCMC provides more precise estimates of model parameters than the ARDL model, as evidence by smaller posterior standard deviations compared to ARDL standard deviations. This approach yields a comprehensive posterior distribution of unknown parameters, encompassing both point estimates and credible intervals. In light of this, it can be inferred that Pakistans GDP growth from 2000 to 2021 has been impeded by escalating rates of debt service and inflation rate. It is recommended that the government and policymakers prioritize sustainable economic growth, implement measures to manage inflation, and effectively address the issue of debt burden