Fatty acid composition of oils of various types ofOlea europaea
The oil was extracted with n-hexane in a Soxhlet apparatus [6]. The composition and relative percentage amounts of the fatty aQids in the 0ils were studied by gas-liquid chromatography on a Chromi4 chromatograph with a 4 mm × 2.5 m column f~lled with 17% of ethylene succinate on Chromaton NAW-DMCS at 196°C. The fatty acids of the oils were chromatographed in the form of their methyl esters. The peaks of the fatty acfd methyl esters were identified from their relative retention times [7].
Fatty acid composition of oleaster pulp and pit oils
Fatty acid compositions of oleaster pulp and pit oils were determined by gas chromatography in 4 samples of different varieties. Pit oils were highly unsaturated, containing >90% linoleic, oleic, and linolenic acids, as well as traces of palmitoleic acid. Saturated fatty acids consisted of palmitic and stearic acids with traces of arachidic acid. Pulp oils showed fatty acid compositions entirely different from that of pit oils. They contained 9 saturated fatty acids, C12 to C24, some of them with high quantities, up to 34.9%, of the total fatty acids. Unsaturated fatty acids, mainly oleic and linoleic, with low quantities of palmitoleic and linolenic acids composed about one-third of the total fatty acids.
A natural language discourse model to explain linear programming models and solutions
Abstract This paper presents a natural language (i.e., English) discourse model to explain a linear programming model and, possibly, its computed solution (which need not be optimal). Drawing from earlier syntactic translations, a semantic model is presented, based on economic input-output relations commonly found in large-scale linear programs. These are then shown how to form rule-driven explanations, which comprises a fundamental component of an intelligent mathematical programming system.