Voltage Controller for Variable Speed Induction Generator Using Matrix Converter

The requirement of variable frequency and variable output voltage for standalone induction generator (IG) is necessary for many applications and is efficiently fulfilled by the development of Matrix Converter connected with voltage source inverter (VSI). The VSI is used to supply the reactive power to the induction generator. The Matrix Converter and VSI are controlled by efficient Space Vector Pulse Width Modulation control algorithm and are tested for R-L load. The simulation results of MC, IG and VSI are presented and the hardware results of VSI are also presented in this paper

Explicit MBR All-Symbol Locality Codes

Node failures are inevitable in distributed storage systems (DSS). To enable efficient repair when faced with such failures, two main techniques are known: Regenerating codes, i.e., codes that minimize the total repair bandwidth; and codes with locality, which minimize the number of nodes participating in the repair process. This paper focuses on regenerating codes with locality, using pre-coding based on Gabidulin codes, and presents constructions that utilize minimum bandwidth regenerating (MBR) local codes. The constructions achieve maximum resilience (i.e., optimal minimum distance) and have maximum capacity (i.e., maximum rate). Finally, the same pre-coding mechanism can be combined with a subclass of fractional-repetition codes to enable maximum resilience and repair-by-transfer simultaneously

GRNN-Immune Based Strategy for Estimating and Optimizing the Vibratory Assisted Welding Parameters to Produce Quality Welded Joints

Welding is the process of producing permanent joints with the application of pressure and/or heat energy. During welding operation, weldments may be subjected to uneven thermal stresses. These stresses influence the metallurgical structure of the component. Due to this, the strength of the weld joint is reduced. Therefore, vibratory weld treatment during welding has been proposed in the present work to enhance the flexural and impact strength of weldments. However, it is found that the mechanical properties have shown nonlinear behavior with the chosen input parameters. Hence, an efficient Neural Network (NN) based prediction tool is developed to approximate the mechanical properties of weldments without performing the experiments, output values can be predicted for the given input values. Further, an immune based strategy is integrated to the developed prediction tool in order to obtain desired quality welded joints.Welding is the process of producing permanent joints with the application of pressure and/or heat energy. During welding operation, weldments may be subjected to uneven thermal stresses. These stresses influence the metallurgical structure of the component. Due to this, the strength of the weld joint is reduced. Therefore, vibratory weld treatment during welding has been proposed in the present work to enhance the flexural and impact strength of weldments. However, it is found that the mechanical properties have shown nonlinear behavior with the chosen input parameters. Hence, an efficient Neural Network (NN) based prediction tool is developed to approximate the mechanical properties of weldments without performing the experiments, output values can be predicted for the given input values. Further, an immune based strategy is integrated to the developed prediction tool in order to obtain desired quality welded joints

MESUAFERRIN A-BIOACTIVE FLAVONOID ISOLATED FROM THE BARK OF MESUA FERREA L. AGAINST PHOSPHOLIPASE A2, CYCLOOXYGENASE AND LIPOXYGENASE: AN IN VITRO, IN VIVO AND IN SILICO APPROACH

Objective: The main objective of the present study was to evaluate the anti-inflammatory activity of isolated bioactive flavonoid Mesuaferrin-A from the bark of Mesuaferrea L. by in vitro, in vivo and in silico approach.Methods: To evaluate the effect of isolated bioactive flavonoid Mesuaferrin-A on arachidonic acid metabolizing enzymes (PLA2, COX-2 and 5-LOX) using in vitro methods, followed by carrageenan-induced paw edema model by in vivo and to determine the binding orientation and interactions of Mesuaferrin-A onarachidonic acid metabolizing enzymes (PLA2, COX-2 and 5-LOX) crystal proteins using molecular docking (in silico) studies.Results: Mesuaferrin-A exhibited a dose-dependent significant 5-LOX inhibitory and considerable COX-2 inhibitory activity by in vitro, The inhibitory activities of 5-LOX and COX-2 at 100µg/ml were found to be 78.67%, 81.03% with IC50 values of 45.22µg/ml and 35.74µg/ml respectively. Whereas Mesuaferrin-A showed less PLA2 inhibitory activity. Mesuaferrin-A showed 68.34% inhibitory activity at 400 mg/kg body weight at the late phase of carrageenan-induced paw edema, and In silico studies demonstrated that Mesuaferrin-A strongly binds with 5-LOX and COX-2, these strong binding affinity of Mesuaferrin-A on active site amino acids of 5-LOX and COX-2 may be responsible for inhibition of enzyme activity. Mesuaferrin-A showeda comparable 5-LOX and COX-2 inhibition activity with (positive control).Conclusion: It was concluded that Mesuaferrin-A act as 5-LOX and COX dual inhibitor, from the results it was suggests that Mesuaferrin-A, may be an effective preventive and therapeutic approach for patients with inflammatory-related diseases

ONE STEP QUANTIFICATION ANALYTICAL METHOD AND CHARACTERIZATION OF VALSARTAN BY LC-MS

Objective: To develop precise LC-MS method for the estimation of valsartan impurities and perform validation as per ICH guidelines.Methods: Valsartan (VLN) and its degradation products were analyzed by reverse phase high-performance liquid chromatography (RP-HPLC) using mobile phase water: acetonitrile: glacial acetic acid: phosphate buffer in the ratio of 500:500:1:0.5 v/v/v/v at 225 nm using column nucleosil C18, 125 ×4.0 mm, 5 µm. VLN sample (VLN SPL) thus obtained an unknown major impurity (UIMP) of 0.5 % at 0.38 retention time ratio (RRt) and purity of VLN was found to be 98.70 % respectively.Results: Estimation of VLN SPL total unknown impurities was found to be 1.3% by RP-HPLC. In similarly by liquid chromatography mass spectroscopy (LC-MS) a typical chromatogram of valsartan (VLN) at Rt 9.03 min and UIMP at Rt 3.3 min were recorded at a total run time of 23 min. Assay of VLN SPL was validated as per international council for harmonization (ICH) guidelines. Average % recovery was found to be 100.04 % for VLN SPL.Conclusion: The proposed work clearly indicates that the method can be easily adapted for the routine one step estimation of VLN active pharmaceutical ingredient (API)

Facial Skin Disease Detection using Image Processing

Busy lifestyle, modernization, increasing pollution and unhealthy diet have led to problems which people are neglecting. Not drinking enough water, stress and hormonal changes are causing problems to skin. Causes may be situational or genetic. Few skin conditions are minor while others can be life-threatening. The skin is the largest organ of the body and is composed of water, proteins, fats and minerals. Problems appear on outer layer of the skin that is epidermis. Skin diseases are considered to be the fourth most common cause of human illness. Skin diseases are observed to increase with age and were seen frequently in both men and women. Skin disorders can be temporary or permanent. Skin diseases have an impact on individual, family and social life caused by inadequate self-treatment which may also induce psychological problems. In recent years, use of computer technologies is becoming practically universal for both personal and professional issues. Facial skin problem identification and recognition has evolved to a great extent over the years. Detection of skin diseases is done using Convolution Neural Network (CNN) and image processing methods. CNN yields better performance in terms of accuracy, precision and results than the existing conventional methods. Image processing uses digital computer to process the images through an algorithm. We focus on features like skin tone, skin texture and color. We present a brief review about various facial skin problems providing more insight about the effective models and algorithms used

Phytochemical Screening and Antimicrobial Activity of the Leaf Extract of Mirabilis jalapa Against Pathogenic Microorganisms

Investigation of the phytochemical constituents and antimicrobial activity of the leaf extracts of Mirabilis jalapa were carried out using acetone, chloroform, ethanol and methanol. These extracts were subjected to screening of preliminary phytochemical tests. Phytochemical analysis showed the presence of alkaloids, flavanoids, phenols, glycosides, tannins, saponins and lignins. The methanol extract exhibited the largest zone of inhibition (21mm in dia with 500μg/disc extract) against Staphylococcus aureus and the highest inhibition of fungal radial mycelial growth (97.5% with 500μg/ml medium) against Aspergillus flavus. The methanol extract exhibited the lowest MIC against Staphylococcus aureus (39 μg/ml) and Aspergillus flavus (45μg/ml). It appeared that M. jalapa could be a potential natural source of new antimicrobial agent.Keywords: Mirabilis jalapa, leaf extract, phytochemicals, antimicrobial activity

Short Communication ADOPTION OF SOIL AND WATER CONSERVATION PRACTICES BY GROUNDNUT FARMERS a

ABSTRACT The study was conducted in Sira taluk of Tumkur district in Karnataka state to find out the adoption behavior of groundnut farmers with respect to soil and water conservation practices. One hundred farmers were interviewed personally with the help of a pre-tested schedule. It was found that a majority of the groundnut farmers had adopted simple and low cost soil and water conservation practices with respect to overall adoption of soil and water conservation practices, almost equal number of the farmers (33 percent) belong to high medium and adoption level. This indicates there is not much variation between the different overall adoption levels