Multi-elemental analysis of ready-to-eat “baby leaf” vegetables using microwave digestion and high-resolution continuum source atomic absorption spectrometry

The mineral content (phosphorous (P), potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu)) of eight ready-to-eat baby leaf vegetables was determined. The samples were subjected to microwave-assisted digestion and the minerals were quantified by High-Resolution Continuum Source Atomic Absorption Spectrometry (HR-CS-AAS) with flame and electrothermal atomisation. The methods were optimised and validated producing low LOQs, good repeatability and linearity, and recoveries, ranging from 91% to 110% for the minerals analysed. Phosphorous was determined by a standard colorimetric method. The accuracy of the method was checked by analysing a certified reference material; results were in agreement with the quantified value. The samples had a high content of potassium and calcium, but the principal mineral was iron. The mineral content was stable during storage and baby leaf vegetables could represent a good source of minerals in a balanced diet. A linear discriminant analysis was performed to compare the mineral profile obtained and showed, as expected, that the mineral content was similar between samples from the same family. The Linear Discriminant Analysis was able to discriminate different samples based on their mineral profile.

Variation in cuticular hydrocarbons among strains of the Anopheles gambiae sensu stricto by analysis of cuticular hydrocarbons using gas liquid chromatography of larvae

Cuticular hydrocarbons of larvae of individual strains of the Anopheles gambiae sensu stricto were investigated using gas liquid chromatography. Biomedical discriminant analysis involving multivariate statistics suggests that there was clear hydrocarbon difference between the Gambian(G3), the Nigerian (16CSS and, its malathion resistant substrain, REFMA) and the Tanzanian (KWA) strains. The high degree of segregation (95%) in hydrocarbons among the four strains investigated indicates that further analysis is needed to enable understanding of hydrocarbon variation in samples of An. gambiae especially from areas where these populations co-exist.

Analysis of antenal sensilla patterns of Rhodnius prolixus from Colombia and Venezuela

Antennal sensilla patterns were used to analyze population variation of domestic Rhodnius prolixus from six departments and states representing three biogeographical regions of Colombia and Venezuela. Discriminant analysis of the patterns of mechanoreceptors and of three types of chemoreceptors on the pedicel and flagellar segments showed clear differentiation between R. prolixus populations east and west of the Andean Cordillera. The distribution of thick and thin-walled trichoids on the second flagellar segment also showed correlation with latitude, but this was not seen in the patterns of other sensilla. The results of the sensilla patterns appear to be reflecting biogeographic features or population isolation rather than characters associated with different habitats and lend support to the idea that domestic R. prolixus originated in the eastern region of the Andes.

Capillaria spp. eggs in Patagonian archaeological sites: statistical analysis of morphometric data

Discriminant analysis was used to identify eggs of Capillaria spp. at specific level found in organic remains from an archaeological site in Patagonia, Argentina, dated of 6,540 ± 110 years before present. In order to distinguish eggshell morphology 149 eggs were measured and grouped into four arbitrary subsets. The analysis used on egg width and length discriminated them into different morphotypes (Wilks' lambda = 0.381, p < 0.05). The correlation analysis suggests that width was the most important variable to discriminate among the Capillaria spp. egg morphotypes (Pearson coefficient = 0.950, p < 0.05). The study of eggshell patterns, the relative frequency in the sample, and the morphometric data allowed us to correlate the four morphotypes with Capillaria species.

Sexual dimorphism of the human mandible: demonstration by elliptical Fourier analysis.

A new quantitative approach of the mandibular sexual dimorphism, based on computer-aided image analysis and elliptical Fourier analysis of the mandibular outline in lateral view is presented. This method was applied to a series of 117 dentulous mandibles from 69 male and 48 female individuals native of Rhenish countries. Statistical discriminant analysis of the elliptical Fourier harmonics allowed the demonstration of a significant sexual dimorphism in 97.1% of males and 91.7% of females, i.e. in a higher proportion than in previous studies using classical metrical approaches. This original method opens interesting perspectives for increasing the accuracy of sex identification in current anthropological practice and in forensic procedures.

On the Schoenberg transformations in data analysis: theory and illustrations

The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A distance-based discriminant algorithm and a robust multidimensional centroid estimate illustrate the theory, closely connected to the Gaussian kernels of Machine Learning.

EEG signal analysis via a cleaning procedure based on multivariate empirical mode decomposition

Artifacts are present in most of the electroencephalography (EEG) recordings, making it difficult to interpret or analyze the data. In this paper a cleaning procedure based on a multivariate extension of empirical mode decomposition is used to improve the quality of the data. This is achieved by applying the cleaning method to raw EEG data. Then, a synchrony measure is applied on the raw and the clean data in order to compare the improvement of the classification rate. Two classifiers are used, linear discriminant analysis and neural networks. For both cases, the classification rate is improved about 20%.

Where and how family members spend time at home? A quantitative analysis of the observational tracking on the everyday lives of Italian families

This paper examines a dataset that derives from an observational tracking, in order to analyze where and how middle-class working families spend time at home. We use an ethnographic approach to study the everyday lives of Italian dual-income middle-class families, with the aim to analyze quantitatively the use of home spaces and the types of activities of family members on weekday afternoons and evenings. The different analyses (multiple correspondence analysis, agglomerative hierarchical cluster, discriminant analysis) show how particular spaces and activities in these spaces are dominated by certain family members. We suggest a combination of qualitative and quantitative methodologies as useful tools to explore in detail the everyday lives of families, and to understand how family members use the domestic spaces. In particular, we consider relevant the use of quantitative analyses to examine ethnographic data, especially in connection with the methodological reflexivity among researchers

Looking beneath Dalí's paint: non-destructive canvas analysis

A new analytical method was developed to non-destructively determine pH and degree of polymerisation (DP) of cellulose in fibres in 19th 20th century painting canvases, and to identify the fibre type: cotton, linen, hemp, ramie or jute. The method is based on NIR spectroscopy and multivariate data analysis, while for calibration and validation a reference collection of 199 historical canvas samples was used. The reference collection was analysed destructively using microscopy and chemical analytical methods. Partial least squares regression was used to build quantitative methods to determine pH and DP, and linear discriminant analysis was used to determine the fibre type. To interpret the obtained chemical information, an expert assessment panel developed a categorisation system to discriminate between canvases that may not be fit to withstand excessive mechanical stress, e.g. transportation. The limiting DP for this category was found to be 600. With the new method and categorisation system, canvases of 12 Dalí paintings from the Fundació Gala-Salvador Dalí (Figueres, Spain) were non-destructively analysed for pH, DP and fibre type, and their fitness determined, which informs conservation recommendations. The study demonstrates that collection-wide canvas condition surveys can be performed efficiently and non-destructively, which could significantly improve collection management.

Texture analysis of computed tomography images of acute ischemic stroke patients

Computed tomography (CT) images are routinely used to assess ischemic brain stroke in the acute phase. They can provide important clues about whether to treat the patient by thrombolysis with tissue plasminogen activator. However, in the acute phase, the lesions may be difficult to detect in the images using standard visual analysis. The objective of the present study was to determine if texture analysis techniques applied to CT images of stroke patients could differentiate between normal tissue and affected areas that usually go unperceived under visual analysis. We performed a pilot study in which texture analysis, based on the gray level co-occurrence matrix, was applied to the CT brain images of 5 patients and of 5 control subjects and the results were compared by discriminant analysis. Thirteen regions of interest, regarding areas that may be potentially affected by ischemic stroke, were selected for calculation of texture parameters. All regions of interest for all subjects were classified as lesional or non-lesional tissue by an expert neuroradiologist. Visual assessment of the discriminant analysis graphs showed differences in the values of texture parameters between patients and controls, and also between texture parameters for lesional and non-lesional tissue of the patients. This suggests that texture analysis can indeed be a useful tool to help neurologists in the early assessment of ischemic stroke and quantification of the extent of the affected areas.

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

Morphometric analysis and taxonomic revision of the Vriesea paraibica complex (Bromeliaceae)

The species related to Vriesea paraibica (Bromeliaceae, Tillandsioideae) have controversial taxonomic limits. For several decades, this group has been identified in herbarium collections as V. x morreniana, an artificial hybrid that does not grow in natural habitats. The aim of this study was to assess the morphological variation in the V. paraibica complex through morphometric analyses of natural populations. Two sets of analyses were performed: the first involved six natural populations (G1) and the second was carried out on taxa that emerged from the first analysis, but using material from herbarium collections (G2). Univariate ANOVA was used, as well as discriminant analysis of 16 morphometric variables in G1 and 18 in G2. The results of the analyses of the two groups were similar and led to the selection of diagnostic traits of four species. Lengths of the lower and median floral bracts were significant for the separation of red and yellow floral bracts. Vriesea paraibica and V. interrogatoria have red bracts; these two species are differentiated by the widths of the lower and median portions of the inflorescence and by scape length. These structures are larger in the former and smaller in the latter. Of the species with yellow floral bracts, V. eltoniana is distinguished by longer leaf blades and scapes and V. flava is characterized by its shorter sepal lengths. (C) 2009 The Linnean Society of London, Botanical Journal of the Linnean Society, 2009, 159, 163-181.

ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Multiscale Curvature Analysis of Asphaltic Aggregate Particles

A new method for characterization and analysis of asphaltic mixtures aggregate particles is reported. By relying on multiscale representation of the particles, curvature estimation, and discriminant analysis for optimal separation of the categories of mixtures, a particularly effective and comprehensive methodology is obtained. The potential of the methodology is illustrated with respect to three important types of particles used in asphaltic mixtures, namely basalt, gabbro, and gravel. The obtained results show that gravel particles are markedly distinct from the other two types of particles, with the gabbro category resulting with intermediate geometrical properties. The importance of each considered measurement in the discrimination between the three categories of particles was also quantified in terms of the adopted discriminant analysis.

Content in metallic ions of wines from the Madeira and Azores archipelagos

This study determines for the first time Na, K, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb contents in wines from the archipelagos of Madeira and Azores (Portugal). The greater part of the mean content for the different parameters fell within the ranges described in the literature, except for sodium whose higher content may be due to the effect of marine spray. ANOVA was used to establish the metals with significant differences in mean content between the wines from both archipelagos, between table and liquor wines of Madeira, and between wines of Pico and Terceira Islands from the Azores archipelago. Principal component analysis shows differences in the wines according to the wine-making process and/or the equipment employed. Stepwise linear discriminant analysis achieves a good classification and validation of wines according to the archipelago of origin, and the island in the case of Azores wines.