Impact of Financial Leverage on Value of Firms: Evidence from Cement Sector of Pakistan

The purpose of this paper is to investigate the effect of financial leverage on firm’s value in cement sector of Pakistan. By selecting the appropriate panel econometric technique between fixed effects and random effects, the association between financial leverage and firm’s value of all cement companies listed on the Karachi Stock Exchange during 2008-2012 has been analyzed. The total number of listed cement companies at KSE is 19. The empirical results depict that financial leverage has positive and statistically significant association with value of firm which is represented by Tobin’s Q. It is apparent from these findings that cement companies of Pakistan can increase their value by creating a suitable mix of equity and debt in their capital structure. Among the control variables, firm size is negatively and insignificantly related with Tobin’s Q. Asset tangibility has inverse and significant relationship with Tobin’s Q. The liquidity is found to have positive and significant association with value of the cement companies which show that efficient working capital management leads to increased firm value. The conclusions of this study have practical implications for financial managers of cement sector to include a suitable amount of debt in their capital structure. Keywords: Pakistan, Financial leverage, Firm’s value, Cement secto

The impact of parents education, parents income, teacher education and locality of school on students relinquish school during primary level in DG Khan district

In this study, reasearcher examined the impact of parent's education, parents income, teacher education and locality of school on students relinquish school during primary level. The study data was collected from different urban and rural areas of D.G.Khan schools. The study used the multiple regressions to analyze the effect of parent's education, parent's income, teacher education and locality of school on students relinquished school during primary level of education. This research findings show that parent's education, parents income and teacher education were significant and locality of school was insignificant. It is concluded that parent's education, parents income, teacher education are affected to students relinquished school during primary level in the districtand locality of school has no affect on students relinquish school during primary

Comparison of efficacy of azithromycin plus levamisole versus azithromycin alone in the treatment of moderate to severe acne

Objective To compare the efficacy of azithromycin plus levamisole versus azithromycin alone in the treatment of moderate to severe acne. Patients and methods Ninety patients with moderate to severe acne were divided into two groups. Group A was given oral azithromycin 500mg/day, three days a week, plus oral levamisole 150mg/day, two days a week and group B was given oral azithromycin 500mg/day, three days a week. Patients were followed up at 4th and 8th week for efficacy and tolerability. Results Efficacy of treatment in Group A (given azithromycin plus levamisole) was seen in 36 (80%) patients while in Group B (oral azithromycin alone) efficacy was seen in 27 (60%) patients (p-value = 0.048). Conclusion Combination therapy with oral azithromycin plus levamisole is more efficacious as compared to oral azithromycin alone in the treatment of moderate to severe acne vulgaris. Key words Acne, azithromycin, levamisole. DOI: 10.7176/JMPB/58-05 Publication date: August 31st 201

Evaluating the impact of branding on music streaming services such as Spotify, Apple Music and Tidal have had on consumers

The aim of this study was to evaluate the impact of branding in the music streaming industry while considering the three companies, which include Spotify, Tidal and Apple Music. Following the quantitative research methodology, the researcher survey 80 music listeners in the university. Based on the results, the responses of participants were oriented towards Spotify. In regards to the preferences of music streaming services, Spotify lied on the first preference. Meanwhile, Apple Music lied at the second number. Whereas, Tidal lied on the third number followed by a minimal amount of responses for its services chosen by the consumers. Branding has main stake in the music streaming services industry. The evaluation of branding of three brands such as Tidal, Apple Music and Spotify provide the differing results. Tidal and Apple Music have good branding and its impact on the consumer choice. However, Tidal followed by Apple Music has lower impact when it comes to compare the results and responses with Spotify. Keywords: branding, music streaming services DOI: 10.7176/IKM/11-4-09 Publication date:August 31st 202

Combining Ability and Heteroses Analysis for Seed Yield and Yield Components in Brassica napus L.

Line × tester analysis of three testers and five lines of Brassica napus L. were used to estimate combining ability and heterosis of plant height, number of primary branches, number of secondary branches, 1000-seed weight and seed yield per plant. Significant mean squares of treatments for yield components and seed yield indicated significant genetic variations among the genotypes including parents and their crosses. Parents Vs crosses mean square indicated, average heterosis was significant for all the traits except plant height. Line × tester mean square was significant for all the traits. High GCA to SCA ratio; indicated the prime importance of additive genetic effects for all traits except seed yield per plant. Significant positive general combining ability (GCA) and specific combining ability (SCA) effects were observed. Most of the crosses had significant positive over better parent heterosis of seed yield, indicating that these hybrids were suitable candidates for improving these traits using combination method. Key words: Combining ability, Heteroses, Line × Tester, Brassica napus L

Supervised Machine Learning Models for Fake News Detection

Fake news or the distribution of disinformation has become one of the most challenging issues in society. News and information are churned out across online websites and platforms in real-time, with little or no way for the viewing public to determine what is real or manufactured. But an awareness of what we are consuming online is becoming apparent and efforts are underway to explore how we separate fake content from genuine and truthful information. The most challenging part of fake news is determining how to spot it. In technology, there are ways to help us do this. Supervised machine learning helps us to identify in a labelled dataset if a piece of information is fake or not. However, machine learning can be a black-box tool - a device, system or object which can be viewed in terms of its inputs and outputs – that focuses on one aspect of the problem and in doing so, isn’t addressing the bigger picture. To solve this issue, it is very important to understand how it works. The process of data pre-processing and the dataset labelling is part of this understanding. It is also worth knowing the algorithms mechanisms in order to choose the best one for the proposed project. Evaluating machine learning algorithms model is one way to get better results. Changing paths within algorithms is not a bad thing if it is addressing the limitations within. With this project, we have done just this, changing from Sports news detection using Twitter API to labelled datasets and as a result we have an original Gofaas dataset, Gofaas library R package and Gofaas WebApp. Machine Learning is a demanding subject but fascinating at the same time. We hope this modest project helps people to face these challenges and learn from our findings accordingly

Supervised Machine Learning Models for Fake News Detection

Fake news or the distribution of disinformation has become one of the most challenging issues in society. News and information are churned out across online websites and platforms in real-time, with little or no way for the viewing public to determine what is real or manufactured. But an awareness of what we are consuming online is becoming apparent and efforts are underway to explore how we separate fake content from genuine and truthful information. The most challenging part of fake news is determining how to spot it. In technology, there are ways to help us do this. Supervised machine learning helps us to identify in a labelled dataset if a piece of information is fake or not. However, machine learning can be a black-box tool - a device, system or object which can be viewed in terms of its inputs and outputs – that focuses on one aspect of the problem and in doing so, isn’t addressing the bigger picture. To solve this issue, it is very important to understand how it works. The process of data pre-processing and the dataset labelling is part of this understanding. It is also worth knowing the algorithms mechanisms in order to choose the best one for the proposed project. Evaluating machine learning algorithms model is one way to get better results. Changing paths within algorithms is not a bad thing if it is addressing the limitations within. With this project, we have done just this, changing from Sports news detection using Twitter API to labelled datasets and as a result we have an original Gofaas dataset, Gofaas library R package and Gofaas WebApp. Machine Learning is a demanding subject but fascinating at the same time. We hope this modest project helps people to face these challenges and learn from our findings accordingly

Estimation of Combining Ability for the Development of Hybrid Genotypes in Helianthus annuus L

Plant materials were developed by L×T crossing fashion of nine lines and four testers and their thirty six hybrids were sown in field during 2011 in RCBD design with three replications. Genetic variability, general and specific combining abilities among genotypes was assessed under the research area of department of plant breeding and genetics, university of agriculture, faisalabad, Pakistan. The Line G-93, and G-79 expressed highly significant GCA effects for days to flowering, days to maturity, internodal length, head diameter, %age of filled achenes, 100 achene weight, achene yield per plant and oil contents but they showed best general combiner. Among testers A-85 expressed highly significant GCA effects for days to flowering, days to maturity, 100 achene weight, achene yield per plant and oil contents whereas A-5 exibited best general combiner for days to flowering, days to maturity, internodal length, achene yield per plant and oil contents. The cross G-65×A-85 revealed highest SCA effect for days to 50% flowering and days to maturity, head diameter, 100 achene weight, achene yield per plant and oil contents. The results of analysis of variance were determine among entries for all the traits at significant level (p ? 0.01-0.05). Key words: GCA, SCA, line × tester, oil contents and yield

Bioavailability and Metabolic Pathway of Phenolic Compounds

As potential agents for preventing different oxidative stress-related diseases, phenolic compounds have attracted increasing attention with the passage of time. Intake of fruits, vegetables and cereals in higher quantities is linked with decreased chances of chronic diseases. In plant-based foods, phenolic compounds are very abundant. However, bio-accessibility and biotransformation of phenolic compound are not reviewed in these studies; therefore, a detailed action mechanism of phenolic compounds is not recognized. In this article, inclusive concept of different factors affecting the bioavailability of phenolic compounds and their metabolic processes is presented through which phenolic compounds go after ingestion