Anti-Arthritic Activity of Bartogenic Acid Isolated from Fruits of Barringtonia racemosa Roxb. (Lecythidaceae)

The fruits of Barringtonia racemosa are prescribed in the ayurvedic literature for the treatment of pain, inflammation and rheumatic conditions. In present investigation, activity guided isolation of bartogenic acid (BA) and its evaluation in the Complete Freund's Adjuvant (CFA)-induced arthritis in rats is reported. Among the various extracts and fractions investigated preliminarily for carrageenan-induced acute inflammation in rats, the ethyl acetate fraction displayed potent anti-inflammatory activity. Large-scale isolation and characterization using chromatography and spectral study confirmed that the constituent responsible for the observed pharmacological effects was BA. Subsequently the BA was evaluated for effectiveness against CFA-induced arthritis in rats. The results indicate that at doses of 2, 5, and 10 mg kg−1 day−1, p.o., BA protects rats against the primary and secondary arthritic lesions, body weight changes and haematological perturbations induced by CFA. The serum markers of inflammation and arthritis, such as C-reactive protein and rheumatoid factor, were also reduced in the BA-treated arthritic rats. The overall severity of arthritis as determined by radiological analysis and pain scores indicated that BA exerts a potent protective effect against adjuvant-induced arthritis in rats. In conclusion, the present study validates the ethnomedicinal use of fruits of B. racemosa in the treatment of pain and inflammatory conditions. It further establishes the potent anti-arthritic effects of BA. However, additional clinical investigations are needed to prove the efficacy of BA in the treatment of various immuno-inflammatory disorders

Design and development of image processing algorithms for quantitative road traffic data analysis

High traffic volume monitoring and traffic congestion being a major concern for authorities, this project targets to design quantitative analysis algorithms based on image processing technique. Image processing techniques in MATLAB software were used to realize the requirements. Several other existing traffic data collection and monitoring techniques were studied prior to implementation of this project that included advantages and disadvantages of each technique. Traffic video footage samples were collected from express highways in both night and day conditions and extracted into frames before going through image segmentation techniques such as edge detection and background difference. Algorithms to obtain quantitative information such as vehicle count and vehicle speed were designed which incorporated to MATLAB Graphic User Interface (GUI) environment in which the results of processing were displayed with a number of user defined settings. Vehicle classification was also done based on its size. Further applications such as monitoring of heavy traffic were also developed. Results comparison between different segmentation methods was performed to check the best detection method. Edge detection techniques generally showed comparatively better results than other methods. Certain considerations that may affect the performance of the project and Recommendations for further improvements are discussed at the end of report. In a nutshell, this project provided the author an insight about numerous traffic data analysis techniques, algorithm development and data analysis.Bachelor of Engineerin