Examining the dimensions of corporate entrepreneurship construct: A validation study in the Pakistani banking context

Corporate Entrepreneurship is globally advancing phenomena.Organizations in the search of excellence, increase in their financial and non-financial gains are adopting corporate entrepreneurship for a better tomorrow. Prominent scholars played a significant role in the development, understanding and advancement of corporate entrepreneurship.In this respect, particularly for measuring the state of corporate entrepreneurial activities inside a firm, the researchers developed tools to measure and assess it.In pursuing that objective the Corporate Entrepreneurship Assessment Instrument (CEAI) was developed.As this instrument was mainly developed and tested in the United States and Canada therefore, in this study the psychometric properties of Corporate Entrepreneurship Assessment Instrument construct are assessed in the Pakistan’s context.Two hundred and sixty five bank branch managers from big five banks of Pakistan were surveyed.We analysed the data using Smart PLS 3.0 software due to its methodological usefulness. The findings demonstrated that the scale has adequate level of internal consistency reliability, convergent validity and discriminant validity for each CEAI dimension. Based on above findings, it is suggested that CEAI construct can be effective in measuring the corporate entrepreneurship in the banking sector of Pakistan.Therefore, the potential researchers are suggested to employ this tool in measuring corporate entrepreneurship in the developing countries and in Pakistan specially

Clinical Decision Support System for Unani Medicine Practitioners

Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.Comment: 59 pages, 11 figures, Computer Science Bachelor's Thesis on use of Artificial Intelligence in Clinical Decision Support System for Unani Medicine

Assessment of antimicrobial, antialgal and cytotoxic activities of crude extracts from rhizospheric and freshwater cyanobacterial strains

Background: This study describes the evaluation of antimicrobial, antialgal and cytotoxic activities of crude extracts from cyanobacterial strains isolated from rhizospheric and freshwater environment.Methods: Four cyanobacterial strains were isolated from freshwater and rhizospheric samples collected from various sites of University of the Punjab, Lahore, Pakistan. Selected strains were identified by 16S rDNA ribotyping as species of genera, Cyanothece (CY1), Synechococcus (CY2), Leptolyngbya (CY3) and Synechococcus (CY4). The organic extracts i.e., methanolic, ethanolic and acetonic of selected cyanobacterial strains were checked for antibacterial and cytotoxic activity. Antibacterial and antialgal activities of cyanobacterial extracts were determined against, four Gram positive and three Gram negative bacteria using Muller-Hinton (MH) agar well diffusion assay and two algal species using 96-well microtiter plate respectively. Cytotoxic activity was determined against Vero cells and Huh-7 cells.Results: The results showed that all cyanobacterial extracts showed activities against Gram positive bacteria while some of the extracts showed activity against Gram negative bacteria. Acetonic extract of CY4 and CY2 showed moderate discoloration against Chlamydomonas sp. and Chroococcus sp. respectively. In cytotoxicity bioassay, methanolic extracts of strain CY1 and CY2 were most active with an IC50 of 0.625 mg/ml against Vero cells while acetonic extract of strain CY1 showed highest activity against Huh-7 cells (p<0.05).Conclusion: The data of current study conclusively suggest that selected cyanobacteria may be an excellent source for further fractionation to obtain novel antibacterial, antialgal and anticancer substances.Keywords: Cyanobacteria; MTT bioassay; Microtiter plates; Antimicrobial activity; Cytotoxicity

Social and Macroeconomic Uncertainty and Private Savings: A Case Study of a Developing Economy

We examine the effects of various new variables relating to uncertainty and find that “social uncertainty” in the form of increased crime is leading to portfolio substitution from bank accounts towards savings in durable goods and other real assets in a typical low middle income economy of Pakistan. Accounting for the cultural phenomena of savings in gold and non-bank real assets in South Asia, we have modeled macroeconomic uncertainty through both the levels and the volatilities of gold prices and the stock market index, as well as income volatility. We find that higher social and macroeconomic uncertainty leads to larger precautionary savings in non-bank assets and thereby results in lower residual savings in the National Income Accounts; this result is robust and invariant to various measures of uncertainty. We also find support for the Permanent Income Life Cycle hypothesis and “weak form” evidence for Ricardian equivalence. Keywords: Private savings, Uncertainty, Consumer Durables JEL Classification: D81, E21, E6

A Review of the Implementation of NumPy and SciPy Packages in Science and Math

In the Python programming language, there are a number of simple case studies of scientific computing. It gives you a multidimensional array object,&nbsp;a lot of organisms (like arrays and masked arrays), and many fast ways to work with arrays.&nbsp;SciPy, which is also called "Sigh Pie," is free math, science, and engineering software. The NumPy library is what the SciPy library is built on. This makes it easy and quick to work with arrays with N dimensions. The SciPy library is made to work with NumPy arrays in particular. It has a lot of easy-to-use and effective numerical methods, like scalar optimization and integration. They work well together, are free, and are easy to set up on all common operating systems. NumPy and SciPy are both easy to learn and use. This paper explains the most popular application of these packages in math-focused scientific researc

Effects of Stretching and Positional Release on Calf Muscle Pain in Post- Natal Females

AbstractObjective: To determine the effects of stretching and positional release on calf muscle pain in postnatalfemales.Methodology: The quasi-experimental study was conducted on a sample of 40 subjects from October2022 to February 2023 at Arif Memorial Teaching Hospital Lahore. Non probability samplingtechnique was used. These subjects were allocated non-randomly in Group A and Group B. Stretchingwas performed on subjects of group A and positional release was performed on group B. The groupswere assessed before and after treatment by a numeric pain rating scale and ankle dorsiflexion Range,while SPSS V. 21 was used for pretest post-test comparison using paired sample t test at P value &lt;0.05.Results: The study comprised females with a mean age±sd of participants is 26.00±4.38 years. The preand post values on Numeric pain rating scale were 8.00±1.28, 2.47±1.33 respectively. While thedorsiflexion angle pretest was 6.53±1.280 and post-test was 12.53±2.780. There was significant differencein pre and post values and p value≤0.05, which show that the results were significant. Both stretchingand positional release were effective for postnatal calf pain. But results showed that Stretching wasmore effective than positional release.Conclusion: The study concluded that stretching is more effective in reducing calf muscle pain inpost-natal females compared to positional release.Keywords: Ankle dorsiflexion, Calf muscle tightness, Females, post-natal care, Positional release,Stretching, pain

Top Python-Based Deep Learning Packages: A Comprehensive Review

Deep learning has transformed artificial intelligence (AI) by empowering machines to execute intricate functions with unparalleled precision. The field claims an array of robust packages and libraries, among which Python, a prominent and celebrated programming language, has emerged as a pivotal choice for deep learning study and development. Python has become a leading language in deep learning due to its simplicity and the vast array of libraries available for developers and researchers.  This article thoroughly examines the most broadly adopted deep learning packages within the Python system. The packages under scrutiny include TensorFlow, PyTorch, Keras, Theano, and Caffe. We exactly assess each of these packages to establish their typical features and capabilities. Moreover, the review explores into an in-depth analysis of the assets and weaknesses inherent in each package. This detailed exploration prepares readers with the information necessary to make informed decisions regarding the variety of the most suitable packages custom-made to their specific needs. This comprehensive review aims to propose a nuanced understanding of the landscape of popular deep learning packages and support practitioners and researchers in creation strategic and well-informed choices for their deep learning actions

Vivax malaria and chloroquine resistance: a neglected disease as an emerging threat

In Pakistan, Plasmodium vivax contributes to major malaria burden. In this case, a pregnant woman presented with P. vivax infection and which was not cleared by chloroquine, despite adequate treatment. This is probably the first confirmed case of chloroquine-resistant vivax from Pakistan, where severe malaria due to P. vivax is already an emerging problem

Impact of Macro Specific Factor and Bank Specific Factor on Bank Liquidity using FMOLS Approach

By applying the fully modified ordinary least square (FMOLS), this study examines the impact of bank-specific factor and macro-specific factors on bank liquidity, for the period of 2000 to 2017. The bank specific factors include bank crises, bank size, total deposit, and profitability. While it considers a macro-specific factors GDP, inflation, monetary policy and unemployment. Findings reveal that based on time series data, we suggest that bank-specific and macro-specific factor significantly effect on bank liquidity. Empirical results reported that at 5 percent level of significance total deposit, GDP, bank size and unemployment have a negative impact on liquidity of the bank. While monetary policy, bank crisis and profitability have a positive impact on liquidity. Inflation has an insignificant relation with liquidity. The study reported new facts for increase more clear understanding of liquidity in a developing country like Pakistan

Investigation of Toxic Metals in the Tobacco of Pakistani Cigarettes Using Proton-Induced X-Ray Emission

A particle-induced X-ray emission (PIXE) study has been carried out to find out whether available local and imported cigarette brands in Pakistan have elevated concentration of metals or not. The results are compared within the brands examined in this study and with the results of related studies in literature. A sum of 19 different cigarette brands was purchased randomly from different Pakistani markets which included local and imported brands. The concentration of elements like Cd, Pb, Zn, Fe, Mn, Ni, Cu, and Co was investigated. Results showed that different cigarette brands have different metal contents. The mean concentration of the heavy metals is Cd—4.92 μg/g, Co—0.12 μg/g, Cu—0.97 μg/g, Ni—0.13 μg/g, Pb—1.02 μg/g, and Zn—12.91 μg/g per dry weight. Compared with the reported results of other international studies, Pakistani cigarettes are observed to have lower heavy metal contents except for cadmium which was higher. This study will provide adequate data for all concerned departments. This study will also create awareness among people about the toxicity of metals present in tobacco of cigarettes