Composition and antioxidant activity of honey from Africanized and stingless bees in Alagoas (Brazil): a multivariate analysis

The purpose of this study was to evaluate the antioxidant activity of honey from different entomological sources which were harvested in the dry season of 2008-2009 from distinct mesoregions of the State of Alagoas in the North East of Brazil. Honey produced by five different species of bees, even from the same region and season, showed a statistically significant difference (p <0.05) in the content of phenols, flavonoids and antioxidants, with higher levels of these compounds found in honey produced by Plebeia spp. and A. mellifera. Honey from stingless bees was quite different from that of A. mellifera, especially from the Plebeia spp. A dendrogram of the five species of bees showed the formation of 3 groups, one being formed by Apis mellifera, one by the genus Melipona (M. subnitida, M. quadrifasciata and M. scutellaris) and another formed by Plebeia spp.

Spatial analysis of leprosy incidence and associated socioeconomic factors

OBJECTIVE: To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. METHODS: Cases of leprosy that occurred between 1998 and 2007 in Sao Jose do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. RESULTS: While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. CONCLUSIONS: The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.

Use of a gold microelectrode for discrimination of gunshot residues

Gunshot residues (GSR) can be used in forensic evaluations to obtain information about the type of gun and ammunition used in a crime. In this work, we present our efforts to develop a promising new method to discriminate the type of gun [four different guns were used: two handguns (0.38 revolver and 0.380 pistol) and two long-barrelled guns (12-calibre pump-action shotgun and 0.38 repeating rifle)] and ammunition (five different types: normal, semi-jacketed, full-jacketed, green, and 3T) used by a suspect. The proposed approach is based on information obtained from cyclic voltammograms recorded in solutions containing GSR collected from the hands of the shooters, using a gold microelectrode; the information was further analysed by non-supervised pattern-recognition methods [(Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA)]. In all cases (gun and ammunition discrimination), good separation among different samples in the score plots and dendrograms was achieved. (C) 2012 Elsevier B.V. All rights reserved.

A comparative study on multiscale fractal dimension descriptors

Fractal theory presents a large number of applications to image and signal analysis. Although the fractal dimension can be used as an image object descriptor, a multiscale approach, such as multiscale fractal dimension (MFD), increases the amount of information extracted from an object. MFD provides a curve which describes object complexity along the scale. However, this curve presents much redundant information, which could be discarded without loss in performance. Thus, it is necessary the use of a descriptor technique to analyze this curve and also to reduce the dimensionality of these data by selecting its meaningful descriptors. This paper shows a comparative study among different techniques for MFD descriptors generation. It compares the use of well-known and state-of-the-art descriptors, such as Fourier, Wavelet, Polynomial Approximation (PA), Functional Data Analysis (FDA), Principal Component Analysis (PCA), Symbolic Aggregate Approximation (SAX), kernel PCA, Independent Component Analysis (ICA), geometrical and statistical features. The descriptors are evaluated in a classification experiment using Linear Discriminant Analysis over the descriptors computed from MFD curves from two data sets: generic shapes and rotated fish contours. Results indicate that PCA, FDA, PA and Wavelet Approximation provide the best MFD descriptors for recognition and classification tasks. (C) 2012 Elsevier B.V. All rights reserved.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Comparação do perfil químico entre cachaças de um mesmo vinho destiladas em alambiques e em colunas

Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.

Space-temporal dynamics of limnological variables in a floodplain wetland located at Ribeira do Iguape Valley (São Paulo, Brazil) at different hydrological periods

AIM: The main goal of this research was to investigate the influence of the hydrological pulses on the space-temporal dynamics of physical and chemical variables in a wetland adjacent to Jacupiranguinha River (São Paulo, Brazil); METHODS: Eleven sampling points were distributed among the wetland, a tributary by its left side and the adjacent river. Four samplings were carried out, covering the rainy and the dry periods. Measures of pH, dissolved oxygen, electrical conductivity and redox potential were taken in regular intervals of the water column using a multiparametric probe. Water samples were collected for the nitrogen and total phosphorus analysis, as well as their dissolved fractions (dissolved inorganic phosphorus, total dissolved phosphorus, ammoniacal nitrogen and nitrate). Total alkalinity and suspended solids were also quantified; RESULTS: The Multivariate Analysis of Variance showed the influence of the seasonality on the variability of the investigated variables, while the Principal Component Analysis gave rise in two statistical significant axes, which delimited two groups representative of the rainy and dry periods. Hydrological pulses from Jacupiranguinha River, besides contributing to the inputs of nutrients and sediments during the period of connectivity, accounted for the decrease in spatial gradients in the wetland. This "homogenization effect" was evidenced by the Cluster Analysis. The research also showed an industrial raw effluent as the main point source of phosphorus to the Jacupiranguinha River and, indirectly, to the wetland; CONCLUSIONS: Therefore, considering the scarcity of information about the wetlands in the study area, this research, besides contributing to the understanding of the influence of hydrological pulses on the investigated environmental variables, showed the need for adoption of conservation policies of these ecosystems face the increase anthropic pressures that they have been submitted, which may result in lack of their ecological, social and economic functions.

Brain activity and medical diagnosis: an EEG study

Abstract Background Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis Results The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. Conclusions PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

Population structure and distribution of UCA ( Brachyura: Ocypodidae) influenced by abiotic factors in a tropical estuary

Uca populations have an important functional and structural role in many estuarine ecosystems. These crabs exhibit distinct physiological tolerance to salinity gradients, which may partially explain their heterogeneous distribution. In order to investigate the population structure and distribution of Uca spp. in a tropical estuary, we sampled Uca crabs in replicated 0.75 m2 quadrats at six muddy plain areas during monthly intervals between July and November 2012 in spring tidal conditions. Environmental factors including water temperature, salinity, sediment total organic matter, chlorophyll-a, and granulometry were analyzed. We sampled a total of 2919 individuals distributed in three Uca species (U. uruguayensis, U. thayeri and U. maracoani), from which U. uruguayensis was dominant. The density and biomass of individuals were spatially and temporally heterogeneous. During October and November we found higher Uca spp. densities (71.3 ± 47.3 to 77.6 ± 44,5 ind. 0.75 m-²) and biomass (1.8 ± 1.1 to 2.1 ± 1.0 g 0.75 m-2 AFDW) if compared to the previous months, density (July 55,5± 44,1 August 52,5± 34,9 and September 47,7 ± 25,6 ind. 0,75m-²) and biomass in others months (July 1,0± 0,94 August 1,1 ± 0,72 and September 1,3±0,93 g 0.75 m-2 AFDW ). The same pattern was found for other variables, such as salinity (32 and 34), organic matter (30 and 67%) and chlorophyll-a (89 and 46 μg g-1). In two study areas we found this pattern which suggests that higher Uca productivity and food availability are related. A principal component analysis (PCA) suggests that salinity and granulometry (silt) can influence (60% correspondence) the distribution of U. maracoani. For U. uruguayensis and U. thayeri the PCA suggests chlorophyll-a was important, which is a good indicator for labile organic matter. Our study suggests that the population structure and distribution of Uca species may be regulated by food availability, supporting their utility as biological models for ecosystem monitoring.

Multivariate spectroscopic methods for the analysis of solutions

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins. In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

Development of a new galaxy classification technique and its application to the zCOSMOS survey

The purpose of this Thesis is to develop a robust and powerful method to classify galaxies from large surveys, in order to establish and confirm the connections between the principal observational parameters of the galaxies (spectral features, colours, morphological indices), and help unveil the evolution of these parameters from $z \sim 1$ to the local Universe. Within the framework of zCOSMOS-bright survey, and making use of its large database of objects ($\sim 10\,000$ galaxies in the redshift range $0 < z \lesssim 1.2$) and its great reliability in redshift and spectral properties determinations, first we adopt and extend the \emph{classification cube method}, as developed by Mignoli et al. (2009), to exploit the bimodal properties of galaxies (spectral, photometric and morphologic) separately, and then combining together these three subclassifications. We use this classification method as a test for a newly devised statistical classification, based on Principal Component Analysis and Unsupervised Fuzzy Partition clustering method (PCA+UFP), which is able to define the galaxy population exploiting their natural global bimodality, considering simultaneously up to 8 different properties. The PCA+UFP analysis is a very powerful and robust tool to probe the nature and the evolution of galaxies in a survey. It allows to define with less uncertainties the classification of galaxies, adding the flexibility to be adapted to different parameters: being a fuzzy classification it avoids the problems due to a hard classification, such as the classification cube presented in the first part of the article. The PCA+UFP method can be easily applied to different datasets: it does not rely on the nature of the data and for this reason it can be successfully employed with others observables (magnitudes, colours) or derived properties (masses, luminosities, SFRs, etc.). The agreement between the two classification cluster definitions is very high. ``Early'' and ``late'' type galaxies are well defined by the spectral, photometric and morphological properties, both considering them in a separate way and then combining the classifications (classification cube) and treating them as a whole (PCA+UFP cluster analysis). Differences arise in the definition of outliers: the classification cube is much more sensitive to single measurement errors or misclassifications in one property than the PCA+UFP cluster analysis, in which errors are ``averaged out'' during the process. This method allowed us to behold the \emph{downsizing} effect taking place in the PC spaces: the migration between the blue cloud towards the red clump happens at higher redshifts for galaxies of larger mass. The determination of $M_{\mathrm{cross}}$ the transition mass is in significant agreement with others values in literature.

Zur systematischen Relevanz von Juglandaceen-Blättern unter besonderer Berücksichtigung fossiler Funde aus der Grube Messel und dem Eckfelder Maar

In der vorliegenden Arbeit wurden die Blattmerkmale der Juglandaceen auf ihre systematische Verwertbarkeit hin untersucht. Ein Datensatz mit 62 Blattmerkmalen von 48 rezenten Juglandaceen-Arten wurde zusammengetragen. Zusätzlich wurden vier fossile Blattformen erfasst. Die fossilen Blätter stammen aus zwei Fundstätten des deutschen Eozäns. Der Datensatz wurde mit dem Computerprogramm MacClade® auf ein Phylogramm aus Manos und Stone (2001) übertragen (‚character mapping’). Zusätzlich wurde eine Hauptkomponentenanalyse mit dem Computerprogramm PAST® durchgeführt. Die meisten taxonomischen Einheiten der Juglandaceen konnten mithilfe des ‚character mapping’ wiedererkannt werden, die dafür verantwortlichen Blattmerkmale haben somit ihre systematische Signifikanz unter Beweis gestellt. Weiterhin konnte eine Evolutionstendenz des Induments belegt werden. Zwischen den ursprünglichen und den abgeleiteten Juglandaceen-Taxa ist eine zunehmende Differenzierung des Induments zu beobachten. Die fossilen Blattformen bildeten in der Hauptkomponentenanalyse eine eindeutig erkennbare Gruppierung, die von allen rezenten Taxa der Analyse separiert ist. Demnach lassen sie sich nicht durch einen Vergleich mit rezenten Blättern systematisch zuordnen. Die fossilen Blattformen der Juglandaceen bestätigen die hier belegte Evolutions-tendenz des Induments. Sie stehen mit ihren ursprünglichen Indumentstrukturen am Ausgangspunkt der Indumentevolution.

Computer simulations of two-dimensional colloidal crystals in confinement

Monte Carlo simulations are used to study the effect of confinement on a crystal of point particles interacting with an inverse power law potential in d=2 dimensions. This system can describe colloidal particles at the air-water interface, a model system for experimental study of two-dimensional melting. It is shown that the state of the system (a strip of width D) depends very sensitively on the precise boundary conditions at the two ``walls'' providing the confinement. If one uses a corrugated boundary commensurate with the order of the bulk triangular crystalline structure, both orientational order and positional order is enhanced, and such surface-induced order persists near the boundaries also at temperatures where the system in the bulk is in its fluid state. However, using smooth repulsive boundaries as walls providing the confinement, only the orientational order is enhanced, but positional (quasi-) long range order is destroyed: The mean-square displacement of two particles n lattice parameters apart in the y-direction along the walls then crosses over from the logarithmic increase (characteristic for $d=2$) to a linear increase (characteristic for d=1). The strip then exhibits a vanishing shear modulus. These results are interpreted in terms of a phenomenological harmonic theory. Also the effect of incommensurability of the strip width D with the triangular lattice structure is discussed, and a comparison with surface effects on phase transitions in simple Ising- and XY-models is made

Pyrolysis-Gas Chromatography-Mass Spectometry and Chemometric Analysis for the Characterization of Complex Matrices

The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.