Comparative study of knowledge, attitude and practice of self-medication among undergraduate students of MBBS and BDS

Background: Comparative studies are quite useful in evaluating the current practices in self medication among a similar subset of population. Since, self medication is one of the major causes of promoting irrational use of drugs its burden needs to be estimated more so in students with medical background.Methods: The study was conducted in a tertiary care teaching medical college among MBBS and BDS students. A questionnaire was selected based on outcome of small surveys done prior to this current study was among the MBBS and BDS students to assess their Knowledge, attitude and practice (KAP) towards self medication. Data was analyzed and expressed as numbers and percentage.Results: Total 180 students participated in the study voluntarily (100 MBBS and 80 BDS). Knowledge regarding self medication was more seen in MBBS students as compared to dental students. Only five of MBBS students encountered ADR’s(Adverse drug reactions) due to self medication. Analgesic group of drugs was the most common medication used by both the groups and pain was the chief component for which drug therapy was used.Conclusions: This study showed that students had fair knowledge about self medication but it appeared to be more among MBBS students as compared to BDS, although knowledge about ADR’s was not up to the mark. The attitude and practice of self medication was similar in both the groups. Thus, it is important to impart proper knowledge about self medication among medical students and encouragement regarding ADR teaching should be promoted

Antibacterial finish of textile using papaya peels derived silver nanoparticles

The present study is aimed at the extracellular synthesis of highly stable silver nanoparticles for the development of nanosafe textile using the extracts of yellow papaya peel. Fabric is treated with nanoparticles using dip and dry method to observe the effect of antibacterial activity. The synthesized nanoparticles are also characterized and quantified. Due to their potent antibacterial activity, papaya peels derived silver nanoparticles can be incorporated into fabrics and the manufacturers can make textiles free from spoilage by microorganisms

Effect of enzyme treatment on wool fabric properties and dimensional stability

83-90In this study, the merino wool woven fabric has been treated with commercially available enzymes, i.e. transglutaminase, lipase, laccase and protease, at various concentrations (0.5–2.0% over the weight of fabric) to impart desirable shrink resistance without deterioration of the fabric properties. Protease enzyme treated wool fabric shows least area shrinkage (3.0%) followed by laccase enzyme (4.3%), lipase enzyme (4.9%) and transglutaminase enzyme (7.9%) treated fabrics, as compared to 13.3% of the untreated (blank) fabric. The specific reaction mechanism of various enzymes that cause a structural change and dimensional stability are also discussed. The tensile strength, extension-at-break, yellowness and whiteness indices of the enzyme treated fabrics are found comparable with the blank fabric, while frictional and handle properties are significantly improved. The enzyme process to impart shrink resistance to wool fabric is found sustainable, easy to scale up and due to comparable mechanical, frictional, handle, whiteness and yellowness properties, there is a potential of an industrial adaption

Effect of enzyme treatment on wool fabric properties and dimensional stability

In this study, the merino wool woven fabric has been treated with commercially available enzymes, i.e. transglutaminase, lipase, laccase and protease, at various concentrations (0.5–2.0% over the weight of fabric) to impart desirable shrink resistance without deterioration of the fabric properties. Protease enzyme treated wool fabric shows least area shrinkage (3.0%) followed by laccase enzyme (4.3%), lipase enzyme (4.9%) and transglutaminase enzyme (7.9%) treated fabrics, as compared to 13.3% of the untreated (blank) fabric. The specific reaction mechanism of various enzymes that cause a structural change and dimensional stability are also discussed. The tensile strength, extension-at-break, yellowness and whiteness indices of the enzyme treated fabrics are found comparable with the blank fabric, while frictional and handle properties are significantly improved. The enzyme process to impart shrink resistance to wool fabric is found sustainable, easy to scale up and due to comparable mechanical, frictional, handle, whiteness and yellowness properties, there is a potential of an industrial adaption.

CLINICAL PRESENTATION AND LIFESTYLE RELATED RISK FACTORS OF BREAST CANCER AMONG DIFFERENT AGE AND ETHNIC GROUPS

Breast cancer (BC) is one of the most frequent and leading cause of malignancies in females globally. In Pakistan, breast cancer is most frequently found in younger individuals and late stage presentation is the key feature for clinical diagnosis. Numbers of genetic factors are reported to be significantly associated with the manifestation of breast cancer. A number of factors including gender, age, genetic predisposition, familial vertical history, ethnicity and life style eventually leading to the development of the cancer. Therefore, we identified the role of biochemical characteristics of all participants in the development of breast cancer. 50 breast cancer patients were enrolled in this study. A written informed consent was taken from each of the patients prior to data collection through questionnaire. People belonging to different ethnic groups: Pashtoon was found to be the highest noteworthy figure of breast cancer patients with an overall of 14 (28%) followed by Afghani ethnic group with 7 (14%), Baloch 15 (30%), Hazara 8 (16%), Punjabi 3 (6%) and Sindhi 3 (6%). Key words: Breast cancer, Ethnic groups, Cenar Hospital, Balochistan

Towards AI ethics-led sustainability frameworks and toolkits: Review and research agenda

Artificial intelligence (AI) is instrumental in building human skills, accessing knowledge, creating businesses, addressing societal concerns–including environmental issues–and much more. However, unfair, inequitable, and biased data usage for AI deployments does exist and raises ethical and sustainability debates and concerns. AI deployment frameworks are majorly developed by standard societies/groups, technology organisations, analyst groups and federal/government agencies. The paper explores the central themes of AI ethics and sustainability frameworks in declarative standards and statements published by various institutions. The paper offers a thematic analysis of the literature on AI ethics-led sustainability frameworks using MAXQDA software and identifies common principles. We show that there are an established 28 AI ethics-led sustainability frameworks that agencies and groups have disseminated. As well, 6 practical AI ethics toolkits/products are evaluated to translate common AI ethics-led sustainability framework recommendations to deploy AI ethics-led sustainability toolkits programmatically. The research findings validate that beneficence, non-maleficence, justice, explainability, autonomy, privacy, and biasedness need severe attention and postulating algorithmic trust based on AI ethics-led sustainability frameworks. The paper contributes to the unique AI ethics-led sustainability body of knowledge to become a helpful resource for both praxis and researchers

Quantifying Stock News Relevance in Indian Markets: Stock News Relevance

Researchers have extensively tried machine learning algorithms in news classification and related quantitative finance domains in the past. Stock market investors look forward to being able to predict stock prices successfully not only to get the best returns but also to minimize the risk of losses with a forecast of stock prices and movement of the stock exchange depending upon the type of news. In this paper, we hypothesize that any news that comes to the market can broadly be classified into two types: Class A- News that has an effect such that it leads to a rise in the stock prices of the reference stock and a fall in the stock prices of its competitor stocks, or vice versa, and Class B- News that results in a simultaneous surge or decline in the stock prices of the reference stocks and its competitor stocks alike. This study is an effort to mathematically validate this hypothesis. This domain hasn’t been explored, and through our work, we try to demonstrate the capability of the existence of a pattern in the market, which could then be used for building automated trading strategies. We also adopt a unique approach to model the data as a supervised machine learning problem and by solving, on obtaining an accuracy of 66.5% we prove that such patterns exist and further suggest research inputs on ideas derived from this. &nbsp