ABSTRACT
Twenty compounds were isolated from the aerial parts of Salvia willeana (Holmboe) Hedge, growing wild in Cyprus. These compounds comprise one new and one known acetophenone, one megastigmane glucoside, five phenolic derivatives, two caffeic acid oligomers, three flavonoids, two lignans, two triterpene acids, one monoterpene glucoside, and two fatty acids. The structures of the isolated compounds were established by means of NMR [(Rotating-frame OverhauserEffect SpectroscopY) (¹H-¹H-COSY (COrrelation SpectroscopΥ), ¹H-13C-HSQC (Heteronuclear Single Quantum Correlation), HMBC (Heteronuclear Multiple Bond Correlation), NOESY (Nuclear Overhauser Effect SpectroscopY), ROESY (Rotating-frame Overhauser Effect SpectroscopY)] and MS spectral analyses. This is the first report of the natural occurrence of 4-hydroxy-acetophenone 4-O-(3,5-dimethoxy-4-hydroxybenzoyl)-ß-d-glucopyranoside. A chemical review on the non-volatile secondary metabolites has been carried out. Based on the literature data, the analysis revealed that the chemical profile of S. willeana is close to that of S. officinalis L.
ABSTRACT
Five varieties of Ocimum basilicum L. namely lettuce, cinnamon, minimum, latifolia, and violetto were separately cultivated in field and greenhouse in the island Kefalonia (Greece). The effect of successive harvesting to the essential oil content was evaluated. In total 23 samples of essential oils (EOs) were analyzed by GC-FID and GC-MS. Ninety-six constituents, which accounted for almost 99% of the oils, were identified. Cluster analysis was performed for all of the varieties in greenhouse and field conditions, in order to investigate the possible differentiation on the chemical composition of the essential oils, obtained between harvests during growing period. Each basil variety showed a unique chemical profile, but also the essential oil composition within each variety seems to be differentiated, affected by the harvests and the cultivation site.
ABSTRACT
Extracting and validating emotional cues through analysis of users' facial expressions is of high importance for improving the level of interaction in man machine communication systems. Extraction of appropriate facial features and consequent recognition of the user's emotional state that can be robust to facial expression variations among different users is the topic of this paper. Facial animation parameters (FAPs) defined according to the ISO MPEG-4 standard are extracted by a robust facial analysis system, accompanied by appropriate confidence measures of the estimation accuracy. A novel neurofuzzy system is then created, based on rules that have been defined through analysis of FAP variations both at the discrete emotional space, as well as in the 2D continuous activation-evaluation one. The neurofuzzy system allows for further learning and adaptation to specific users' facial expression characteristics, measured though FAP estimation in real life application of the system, using analysis by clustering of the obtained FAP values. Experimental studies with emotionally expressive datasets, generated in the EC IST ERMIS project indicate the good performance and potential of the developed technologies.
