Two new xanthons from Garcinia rigida leaves
Two new xanthons, musaxanthone (1) and asmaxanthone (2) were isolated from the leaves of Garcinia rigida. The structures were determined by means of spectroscopic analysis.
Antibakteri Ekstrak Kulit Batang Manggis Hutan (Garcinia Rigida Miq.)
A research on the antibacterial activity of n-hexane extract and the ethyl acetate Garcinia rigida Miq. Bark against Salmonella typhosa ATCC 14028, Staphylo-coccus aureus ATCC 29213 dan Bacillus subtilis ATCC 6633 has been carried out.The research was included the determination of the growth inhibition zona with the cylinder diffusion method and the minimum inhibitory concentration with the petri dish dilution method. The result of this study showed that the n-hexane extract of Garcinia rigidan Miq.bark did not give the growth inhibition zona ton Salmonella typhosa ATCC 14028, Staphylococcus aureus ATCC 29213 and Bacillus subtilisATCC 6633, but gave the minimum inhibitory concentration at 500 mg/ml for Sal-monella typhosan ATCC 14028, 250 mg/ml forn Staphylococcus aureusn ATCC 29213 and 125 mg/ml for Bacillus subtilis ATCC 6633. Whereas the ethyl acetateextract of Garcinia rigida Miq. bark gave the growth inhibition zona of concentra-tion 500, 250 and 125 mg/ml with average diameter to Salmonella typhosa ATCC 14028 were about 11.15, 9.05, 7.55 mm, to Staphylococcus aureus ATCC 29213were about 14.25, 11.10, 8.95 mm and to Bacillus subtilis ATCC 6633 were about 20.97, 15.00, 10.07 mm. The minimum inhibitory concentration to ethyl acetate extract to Salmonella typhosa ATCC 14028, Staphylococcus aureus ATCC 29213andn Bacillus subtilisn ATCC 6633 were about 250, 62,5 and 31,25 mg/ml respec-tively. As a conclusion, the ethyl acetate extract of Garcinia rigida Miq. bark had more better antibacterial activity than the n-hexane extract of Garcinia rigida Miq. Bark.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.