Fatima Jinnah Women University

About: Fatima Jinnah Women University is a education organization based out in Rawalpindi, Pakistan. It is known for research contribution in the topics: Adsorption & Freundlich equation. The organization has 496 authors who have published 813 publications receiving 9067 citations.

Augmented photocatalytic, antibacterial and antifungal activity of prunosynthetic silver nanoparticles

Abstract: The present study has demystified the first and single step prunosynthesis of the spherical silver nanoparticles (AgNPs) from aqueous fruit extract of angiospermic plant, Prunus cerasifera, which has remarkable fusion of reducing cum stabilizing bioactive components (phenols, anthocyanins, carotenoids, flavonoids, organic acids, tannins and vitamins). Highly stable prunosynthetic AgNPs with 2.04 nm average crystallite size were synthesized in dark and in sunlight at optimized condition of temperature, time and P. cerasifera concentration. Synthesized nanoparticles were characterized through UV-Vis, FTIR, XRD, TGA, SEM and GCMS. Photocatalytic activity of prunosynthetic AgNPs was evaluated for methyl red, erichrome black, methyl blue, bromophenol blue and bromocresol green via UV-Vis. Degradation was achieved (<15 minutes) and expressed as pseudo-first-order kinetics. Prunosynthetic AgNPs demonstrated broad spectrum dose-dependent inhibition (in vitro) in comparison to standard antimicrobial drugs against pathogenic strains X. citri, P. syringae, A. niger, A. flavus, A. fumigatus, A. terreus, P. chrysogenum, F. solani and L. theobromae. Photocatalytic degradation results show the nanobioremediation potential of prunosynthetic AgNPs in indemnifying the persistent environmental pollutants. From the inherently higher inhibition rates for biomimetic prunosynthetic AgNPs, it is envisioned that these can be commercialized as future "green" nanobactericide and nanofungicide at industrial scale economically from nontoxic phytoconstituents.

A review on ethnobotany, phytochemistry and pharmacology of plant genus Caralluma R. Br

Abstract: Objectives Caralluma is a xerophytic genus used as traditional medicine for the treatment of diabetes, inflammation, leprosy, obesity and rheumatism. Objectives of this review are to establish a relationship between traditional uses and scientific studies by critically evaluating the available fragmented literature on ethnobotany, pharmacology, phytochemistry and toxicology of genus Caralluma. Key findings Ethnomedical uses of Caralluma have been recorded from various countries such as China, India, Iran and Pakistan for six major classes of diseases including diabetes and gastrointestinal disorders. This review indicated the efficacy of genus Caralluma in several in vitro and in vivo pharmacological properties such as antimicrobial, antioxidant and anticancer activity. These bioactivity might be due to the presence of certain classes of compounds in genus Caralluma including pregnane glycosides, flavonoid glycosides and flavones. Summary Traditional uses and scientific evaluation of Caralluma indicates that it is one of the most widely used genus in some parts of the world. Further studies on the structural activity relationship of some of the isolated compound may improve their biological potency as well as scientific exploitation of traditional uses of the genus.

Real time drowsiness detection using eye blink monitoring

Abstract: According to analysis reports on road accidents of recent years, it's renowned that the main cause of road accidents resulting in deaths, severe injuries and monetary losses, is due to a drowsy or a sleepy driver. Drowsy state may be caused by lack of sleep, medication, drugs or driving continuously for long time period. An increase rate of roadside accidents caused due to drowsiness during driving indicates a need of a system that detects such state of a driver and alerts him prior to the occurrence of any accident. During the recent years, many researchers have shown interest in drowsiness detection. Their approaches basically monitor either physiological or behavioral characteristics related to the driver or the measures related to the vehicle being used. A literature survey summarizing some of the recent techniques proposed in this area is provided. To deal with this problem we propose an eye blink monitoring algorithm that uses eye feature points to determine the open or closed state of the eye and activate an alarm if the driver is drowsy. Detailed experimental findings are also presented to highlight the strengths and weaknesses of our technique. An accuracy of 94% has been recorded for the proposed methodology.