http://drr.vau.ac.lk/handle/123456789/556 Sun, 05 Apr 2026 18:46:29 GMT 2026-04-05T18:46:29Z http://drr.vau.ac.lk/handle/123456789/635 Qualitative and quantitative phytochemical analysis of leaves and flowers of the medicinal plant Ocimum tenuiflorum L. Panambara, P.A.H.R.; Rajkumar, G.; Sanmugarajah, V. In Traditional Medicine, different parts of Ocimum tenuiflorum Linn. (Lamiaceae) have been recommended for the management of respiratory system related diseases. Phytochemicals from medicinal plants are a significant source of conventional medical treatments. The goal of the current study was performed to assess for the occurrence of phytochemical compounds in leaves and flowers of Ocimum tenuiflorum L., which were collected from Jaffna district. The shade dried plant materials were ground and extracted with alcohol and water via the cold extraction procedure. These extracts of each part powder were used to detect the presence of phytochemicals. The total phenolic and tannin contents were estimated by the colorimetric technique. These assays were conducted in triplicate and the statistical values were expressed mean with standard deviation. Flavonoids, tannins, terpenoids, phenol, coumarins, aromatic amino acids and anthocyanin were found in ethanolic, methanolic and aqueous extracts of leaves and flowers of this plant. Highest total phenolic contents (µg GAE/g); methanolic leave, methanolic flower, ethanolic leave and ethanolic flower extracts were found to be 422.12±66.69, 386.06±14.44, 228.48±8.82 and 199.39±61.92 respectively. The total tannin contents (µg TAE/g) of all extracts were almost similar except for the methanolic extract of leaves which was higher (1.160±0.14). The present study revealed that the methanolic and ethanolic extract of leaves and flowers contains basic phytochemicals, and total phenol and tannin contents are higher in the methanolic extract of leaves and flowers of Ocimum tenuiflorum than in other extracts. Therefore, it can be used as therapeutic potential of nutraceuticals in the management of respiratory tract diseases. Thu, 03 Nov 2022 00:00:00 GMT http://drr.vau.ac.lk/handle/123456789/635 2022-11-03T00:00:00Z http://drr.vau.ac.lk/handle/123456789/634 Pathyapathya Ahara in Kasa and Swasa Chikitsa applicable for emerging respiratory infections: A review Ishara, M.D.P.; Wimalasiri, Y.S.G. Respiratory disorders impose an immense worldwide health issue. There were emergence of newly recognized Coronavirus, Severe Acute Respiratory Syndrome (SARS), Middle Eastern Respiratory Syndrome (MERS) and novel H1N1 Influenza. Kasa (Cough) and Swasa (Asthma) are two pathological conditions which are related to Pranavaha srotas (Respiratory System) in Ayurveda. One of the main principles of Ayurveda disease management is following wholesome (pathya) food and avoiding unwholesome (Apathya) food. This study was done to focus on Pathayapathya Ahara in Kasa and Swasa which are applicable in emerging Respiratory infections and to analyze the pharmacodynamic properties of that Pathyapathya Ahara. The relevant literature has been collected from the diverse Ayurvedic authentic texts, research journals, authentic internet sources and most mentioned Pathyapathya were analyzed. According to the data, the prominent taste is Madhura (Sweet), Katu (Pungent) and Tikta (Bitter) and prominent Veerya (Potency) is Ushna (Hot) Veerya which leads to pacified Vata Dosa. The prominent Guna are Laghu (Light), Guru (Heavy), Snigdha (Unctuous) and Theekshna (Sharpness). Furthermore, the main actions are Krimighna (anti-microbial), Vataghna, Kasahara (antitussive), Kanta Shodhana (beneficial to the throat), and Swasahara (anti-asthmatic). Dadhi (Curd), Kanda (Tubers) and Sheeta Veerya Anna have been mentioned as Apathya for both and Sarshapa, Mathsya have been mentioned as Apathya for Swasa. The proved scientific evidence regarding Pathya food in Kasa and Swasa show anti-inflammatory action. The emerging respiratory disorders cause hyper-inflammation in Respiratory system and this anti-inflammatory action will balance that condition. Therefore, it can be concluded that the Pathyapathya Ahara in Kasa and Shwasa can be applicable as the wholesome and unwholesome food for emerging Respiratory infections. Thu, 03 Nov 2022 00:00:00 GMT http://drr.vau.ac.lk/handle/123456789/634 2022-11-03T00:00:00Z http://drr.vau.ac.lk/handle/123456789/633 Respiratory and eye symptoms, and ventilatory functions; comparison among stone/granite quarry workers and general population in Kurunegala district, Sri Lanka Malwatte, N.S.M. A cross sectional study carried out with the aim to compare the prevalence of occupation related respiratory and eye symptoms and peak expiratory flow rates (PEFR) among quarry workers (N=290), (20–60 years) working (>6 months) in stone/granite quarries installed with mechanical crushers in the Kurunegala district. Comparison group (N=290) was selected from the general population (labourers), living beyond a radius of 2 km from a quarry site. Selection was done by cluster sampling method with probability proportional to size sampling technique. Interviewer administered questionnaires were used, based on British Medical Research Council questionnaire on respiratory symptoms and a questionnaire for eye symptoms developed with consensual validity from eye experts. PEFR was recorded by using a portable ST95 Spirometer. Differences between the prevalence of symptoms tested using the chi-squared test, results expressed as Odds ratio, 95% confidence intervals. Quarry workers vs comparison group; the prevalence of cough (95.9% vs 62.1%), phlegm (75.9% vs 52.8%), redness (47.9% vs 17.6%), gritty feeling (7.9% vs 1.7%), tearing (49% vs 10.7%), itching in the eyes (56.9% vs 14.1%) was significantly higher. The observed mean values of PEFR L/min among male (360.45 vs 391.79) and female (291.42 vs 376.77) quarry workers were significantly low which could be implicated to exposure duration and particulate concentration. However, current smokers (51.4% vs 18.6%) were significantly higher. In conclusion, quarry workers vs comparison group; the prevalence of respiratory and eye symptoms was significantly higher and mean PEFR value among male and female quarry workers was significantly low. Thu, 03 Nov 2022 00:00:00 GMT http://drr.vau.ac.lk/handle/123456789/633 2022-11-03T00:00:00Z http://drr.vau.ac.lk/handle/123456789/632 Application of neural network and clustering techniques for short term electricity demand forecasting Somarathne, E.D.T.; Wijayakulasooriya, J.V.; Karunasinghe, D.S.K. Many researchers around the world have investigated short term load forecasting (STLF) models based on various forecasting techniques to prepare a better generation plan. They inves tigated traditional techniques and then moved to modified traditional techniques and at present, soft computing techniques are being investigated. This research, with its focus on short-term load forecasting, aims to fill this gap by implementing a new cluster-based technique as well as artificial neural networks (ANNs) on a set of real time data of a period of five years, provided by Ceylon Elec tricity Board gathered for the period of 01-01-2009 to 31-12-2014 were taken at each half an hour. Both methodologies were applied with respect to each half hourly series and 48 numbers of predictions were obtained for the next 24 hours from each half hourly series. In clustering, the demand of a day was categorized as Low, Medium and High demands and then the category of the next day demand was observed by a probability-based method. Then the next day demand was computed by applying Gaussian mixture models. The data of first four years (70% of the dataset) were used to train the algorithm and last year (30% of the dataset) were used for testing. The models’ applicability and accuracy were compared with the predictions obtained by each of the two approaches. In the newly introduced clustering technique, the half hourly electricity demand of next 24 hours was computed by considering probability and based on Gaussian mixture models. The predictions provided by clustering technique consisted of less accuracy compared to those of ANN models. Thu, 03 Nov 2022 00:00:00 GMT http://drr.vau.ac.lk/handle/123456789/632 2022-11-03T00:00:00Z