Contents of vitamins, mineral elements, and some phenolic compounds in cultivated mushrooms.

The aim of the study was to determine the contents of mineral elements (Ca, K, Mg, Na, P, Cu, Fe, Mn, Cd, Pb, and Se), vitamins (B(1), B(2), B(12), C, D, folates, and niacin), and certain phenolic compounds (flavonoids, lignans, and phenolic acids) in the cultivated mushrooms Agaricus bisporus/white, Agaricus bisporus/brown, Lentinus edodes, and Pleurotus ostreatus. Selenium, toxic heavy metals (Cd, Pb), and other mineral elements were analyzed by ETAAS, ICP-MS, and ICP methods, respectively; vitamins were detected by microbiological methods (folates, niacin, and vitamin B(12)) or HPLC methods (other vitamins), and phenolic compounds were analyzed by HPLC (flavonoids) or GC--MS methods (lignans and phenolic acids). Cultivated mushrooms were found to be good sources of vitamin B(2), niacin, and folates, with contents varying in the ranges 1.8--5.1, 31--65, and 0.30--0.64 mg/100 g dry weight (dw), respectively. Compared with vegetables, mushrooms proved to be a good source of many mineral elements, e.g., the contents of K, P, Zn, and Cu varied in the ranges 26.7--47.3 g/kg, 8.7--13.9 g/kg, 47--92 mg/kg, and 5.2--35 mg/kg dw, respectively. A. bisporus/brown contained large amounts of Se (3.2 mg/kg dw) and the levels of Cd were quite high in L. edodes (1.2 mg/kg dw). No flavonoids or lignans were found in the mushrooms analyzed. In addition, the phenolic acid contents were very low.

Complexity of the consistency problem for certain Post classes.

The complexity of the consistency problem for several important classes of Boolean functions is analyzed. The classes of functions under investigation are those which are closed under function composition or superposition. Several of these so-called Post classes are considered within the context of machine learning with an application to breast cancer diagnosis. The considered Post classes furnish a user-selectable measure of reliability. It is shown that for realistic situations which may arise in practice, the consistency problem for these classes of functions is polynomial-time solvable.

Determination of flavonoids in plant material by HPLC with diode-array and electro-array detections.

A high-performance liquid chromatographic (HPLC) method with in-line connected diode-array (DAD) and electro-array (EC) detection to identify and quantify 17 flavonoids in plant-derived foods is described. Catechins were extracted from the samples using ethyl acetate, and quantification of these compounds was performed with the EC detector. Other flavonoids were quantified with DAD after acid hydrolysis. The methods developed were effective for the determination of catechins and other flavonoids in plant-derived foods. Responses of the detection systems were linear within the range evaluated, 20-200 ng/injection (DAD) and 20-100 ng/injection (EC), with correlation coefficients exceeding 0.999. Coefficient of variation was under 10.5%, and recoveries of flavonoids ranged from 70 to 124%. Purity of the flavonoid peaks was confirmed by combining the spectral and voltammetric data.

Nonlinear multivariate image filtering techniques.

In this paper, nonlinear multivariate image filtering techniques are proposed to handle color images corrupted by noise. First, we briefly review the principle of reduced ordering (R-ordering) and then define three R-orderings by selecting different central locations. Considering noise attenuation, edge preservation, and detail retention, R-ordering based multivariate filters are designed by combining the R-ordering schemes. To implement color image filtering more effectively, we develop them into a locally adaptive version. The output of the adaptive filter is the closest sample to a central location that is a weighted linear combination of the mean, the marginal median, and the center sample. As a result, we study an adaptive hybrid multivariate (AHM) filter consisting of the mean filter, the marginal median filter, and the identity filter. The performance of the two adaptive filtering techniques is compared with that of some nonadaptive ones. The examples of color image filtering show that the adaptive multivariate image filtering gives a rather good performance improvement.