Analysis of generalized interictal discharges using quantitative EEG

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantitative Chemical Profile and Multivariate Statistical Analysis of Alembic Distilled Sugarcane Spirit Fractions

Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.

Genotype x location x feeding interactions in Nellore cattle calculated through three-mode principal component analysis

The main objective of this study was to apply three-mode principal component analysis to assess the triple interaction (genotype x location x feeding) on direct genetic value for weight at 205 days of age. We used 60 sires with offspring in three regions of northeastern Brazil (Maranhao, Mata and Agreste, and Reconcavo Baiano) and raised on a pasture regime or with supplementation. There was no interaction between genotype and location, but there was a correlation between genotype and direct effect of feeding. The use of sires should be dictated according to the system of rearing of their offspring.

Multivariate analysis in the maximum strength performance

This study performed an exploratory analysis of the anthropometrical and morphological muscle variables related to the one-repetition maximum (1RM) performance. In addition, the capacity of these variables to predict the force production was analyzed. 50 active males were submitted to the experimental procedures: vastus lateralis muscle biopsy, quadriceps magnetic resonance imaging, body mass assessment and 1RM test in the leg-press exercise. K-means cluster analysis was performed after obtaining the body mass, sum of the left and right quadriceps muscle cross-sectional area (Sigma CSA), percentage of the type II fibers and the 1RM performance. The number of clusters was defined a priori and then were labeled as high strength performance (HSP1RM) group and low strength performance (LSP1RM) group. Stepwise multiple regressions were performed by means of body mass, Sigma CSA, percentage of the type II fibers and clusters as predictors' variables and 1RM performance as response variable. The clusters mean +/- SD were: 292.8 +/- 52.1 kg, 84.7 +/- 17.9 kg, 19249.7 +/- 1645.5 mm(2) and 50.8 +/- 7.2% for the HSP1RM and 254.0 +/- 51.1 kg, 69.2 +/- 8.1 kg, 15483.1 +/- 1 104.8 mm(2) and 51.7 +/- 6.2 %, for the LSP1RM in the 1RM, body mass, Sigma CSA and muscle fiber type II percentage, respectively. The most important variable in the clusters division was the Sigma CSA. In addition, the Sigma CSA and muscle fiber type II percentage explained the variance in the 1RM performance (Adj R-2 = 0.35, p = 0.0001) for all participants and for the LSP1RM (Adj R-2 = 0.25, p = 0.002). For the HSP1RM, only the Sigma CSA was entered in the model and showed the highest capacity to explain the variance in the 1RM performance (Adj R-2 = 0.38, p = 0.01). As a conclusion, the muscle CSA was the most relevant variable to predict force production in individuals with no strength training background.

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures. (C) 2011 Elsevier B.V. All rights reserved.

PXRF and multivariate statistics analysis of pre-colonial pottery from northeast of Brazil

Portable system of energy dispersive X-ray fluorescence was used to determine the elemental composition of 68 pottery fragments from Sambaqui do Bacanga, an archeological site in Sao Luis, Maranhao, Brazil. This site was occupied from 6600 BP until 900 BP. By determining the element chemical composition of those fragments, it was possible to verify the existence of engobe in 43 pottery fragments. Obtained from two-dimensional graphs and hierarchical cluster analysis performed in fragments of stratigraphies from surface and 113-cm level, and 10 to 20, 132 and 144-cm level, it was possible to group these fragments in five distinct groups, according to their stratigraphies. The results of data grouping (two-dimensional graphics) are in agreement with hierarchical cluster analysis by Ward method. Copyright (C) 2011 John Wiley & Sons, Ltd.

cDNA-AFLP analysis of Psidium guajava L. cultivars under water stress and mechanical injury: methodological implications

Studies involving amplified fragment length polymorphism (cDNA-AFLP) have often used polyacrylamide gels with radiolabeled primers in order to establish best primer combinations, to analyze, and to recover transcript-derived fragments. Use of automatic sequencer to establish best primer combinations is convenient, because it saves time, reduces costs and risks of contamination with radioactive material and acrylamide, and allows objective band-matching and more precise evaluation of transcript-derived fragments intensities. This study aimed at examining the gene expression of commercial cultivars of P. guajava subjected to water and mechanical injury stresses, combining analyses by automatic sequencer and fluorescent kits for polyacrylamide gel electrophoresis. Firstly, 64 combinations of EcoRI and MseI primers were tested. Ten combinations with higher number of polymorphic fragments were then selected for transcript-derived fragments recovering and cluster analysis, involving 45 saplings of P. guajava. Two groups were obtained, one composed by the control samplings, and another formed by samplings undergoing stress, with no clear distinction between stress treatments. The results revealed the convenience of using a combination of automatic sequencer and fluorescent kits for polyacrylamide gel electrophoreses to examine gene expression profiles. The Unweighted Pair Group Method with Arithmetic Mean analysis using Euclidean distances points out a similar induced response mechanism of P. guajava undergoing water stress and mechanical injury.

Fra openness ed embeddedness: network analysis di un distretto industriale glocale.

Il distretto è un luogo relazionale dinamico dove le imprese danno luogo a differenti comportamenti economici di vario genere e natura, cooperando in un certo senso per lo sviluppo e la crescita del distretto stesso. In un primo momento di formazione del distretto si sono delineati comportamenti di tipo path dependent per vantaggi economici dovuti alla distribuzione delle imprese nel territorio, ma con il tempo si sono cominciati ad avere comportamenti espansionistici differenti sia dall'interno che dall'esterno del distretto influendo direttamente sulla struttura del stesso. É ragionevole dunque pensare che gli attori guardino al rapporto “locale/globale” con una sorta di "strabismo", da un lato leggendo il distretto (dall’interno come dall’esterno) come un luogo privilegiato per la formazione di economie di prossimità, dall’altro puntando a disporre le catene produttive nello spazio globale, alla ricerca dei vantaggi derivanti da un minor costo del lavoro o dalla immediata prossimità dei mercati di sbocco. il distretto viene dunque attraversato da dinamiche che lo globalizzano ma, al contempo, ne preservano (almeno per ora) la specificità. Non è più possibile leggere la sua forma economica solo nella logica della embeddedness, e non sarebbe certo corretto farlo solo in chiave di openness. Si tratta dunque di interrogarsi sul rapporto più di integrazione/complementarità che di contrapposizione fra openness ed embeddedness. In questa tesi verrà descritto un metodo d'approccio per dare un valore al fenomeno di Openness e Embeddedness presente nel distretto partendo da un dataset di dati relazionali ricavati da due database economici Amadeus e Aida. Non essendo possibile trovare pubblicamente dati sulle reti di fornitura delle singole aziende, siamo partiti dai dati relazionali di cinque aziende “seme”, ed attraverso una ricerca ricorsiva nelle relazioni di azionariato/partecipazione, siamo riusciti ad ottenere un campione di analisi che ci permette di mettere in luce tramite la custer analysis le principali tipologie di reti di imprese presenti nel distretto ed estese nello spazio globale.

An Analysis of Living Conditions in Rural Villages in China. A New Geography of the Country.

Analysts, politicians and international players from all over the world look at China as one of the most powerful countries on the international scenario, and as a country whose economic development can significantly impact on the economies of the rest of the world. However many aspects of this country have still to be investigated. First the still fundamental role played by Chinese rural areas for the general development of the country from a political, economic and social point of view. In particular, the way in which the rural areas have influenced the social stability of the whole country has been widely discussed due to their strict relationship with the urban areas where most people from the countryside emigrate searching for a job and a better life. In recent years many studies have mostly focused on the urbanization phenomenon with little interest in the living conditions in rural areas and in the deep changes which have occurred in some, mainly agricultural provinces. An analysis of the level of infrastructure is one of the main aspects which highlights the principal differences in terms of living conditions between rural and urban areas. In this thesis, I first carried out the analysis through the multivariate statistics approach (Principal Component Analysis and Cluster Analysis) in order to define the new map of rural areas based on the analysis of living conditions. In the second part I elaborated an index (Living Conditions Index) through the Fuzzy Expert/Inference System. Finally I compared this index (LCI) to the results obtained from the cluster analysis drawing geographic maps. The data source is the second national agricultural census of China carried out in 2006. In particular, I analysed the data refer to villages but aggregated at province level.

Institutional Processes and Discursive Strategies: Rhetoric and Vocabulary Analysis of CSR and Sustainability

The candidate tackled an important issue in contemporary management: the role of CSR and Sustainability. The research proposal focused on a longitudinal and inductive research, directed to specify the evolution of CSR and contribute to the new institutional theory, in particular institutional work framework, and to the relation between institutions and discourse analysis. The documental analysis covers all the evolution of CSR, focusing also on a number of important networks and associations. Some of the methodologies employed in the thesis have been employed as a consequence of data analysis, in a truly inductive research process. The thesis is composed by two section. The first section mainly describes the research process and the analyses results. The candidates employed several research methods: a longitudinal content analysis of documents, a vocabulary research with statistical metrics as cluster analysis and factor analysis, a rhetorical analysis of justifications. The second section puts in relation the analysis results with theoretical frameworks and contributions. The candidate confronted with several frameworks: Actor-Network-Theory, Institutional work and Boundary Work, Institutional Logic. Chapters are focused on different issues: a historical reconstruction of CSR; a reflection about symbolic adoption of recurrent labels; two case studies of Italian networks, in order to confront institutional and boundary works; a theoretical model of institutional change based on contradiction and institutional complexity; the application of the model to CSR and Sustainability, proposing Sustainability as a possible institutional logic.

Long-term patterns of subjective wellbeing in schizophrenia: cluster, predictors of cluster affiliation, and their relation to recovery criteria in 2842 patients followed over 3 years

To study the longitudinal patterns of subjective wellbeing in schizophrenia using cluster analysis and their relation to recovery criteria, further to examine predictors for cluster affiliation, and to evaluate the sensitivity and specificity of baseline subjective wellbeing cut-offs for cluster affiliation.

Fine-scale population structure analysis of seven local Swiss sheep breeds using genome-wide SNP data

As part of the global sheep Hapmap project, 24 individuals from each of seven indigenous Swiss sheep breeds (Bundner Oberländer sheep (BOS), Engadine Red sheep (ERS), Swiss Black-Brown Mountain sheep (SBS), Swiss Mirror sheep (SMS), Swiss White Alpine (SWA) sheep, Valais Blacknose sheep (VBS) and Valais Red sheep (VRS)), were genotyped using Illumina’s Ovine SNP50 BeadChip. In total, 167 animals were subjected to a detailed analysis for genetic diversity using 45 193 informative single nucleotide polymorphisms. The results of the phylogenetic analyses supported the known proximity between populations such as VBS and VRS or SMS and SWA. Average genomic relatedness within a breed was found to be 12 percent (BOS), 5 percent (ERS), 9 percent (SBS), 10 percent (SMS), 9 percent (SWA), 12 percent (VBS) and 20 percent (VRS). Furthermore, genomic relationships between breeds were found for single individuals from SWA and SMS, VRS and VBS as well as VRS and BOS. In addition, seven out of 40 indicated parent–offspring pairs could not be confirmed. These results were further supported by results from the genome-wide population cluster analysis. This study provides a better understanding of fine-scale population structures within and between Swiss sheep breeds. This relevant information will help to increase the conservation activities of the local Swiss sheep breeds.

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.

Geochemical provenance analysis of fine-grained sediment of sediment core AND1-1

Bulk chemical fine-grained sediment compositions from southern Victoria Land glacimarine sediments provide significant constraints on the reconstruction of sediment provenance models in the McMurdo Sound during Late Cenozoic time. High-resolution (~ 1 ka) geochemical data were obtained with a non-destructive AVAATECH XRF Core Scanner (XRF-CS) on the 1285 m long ANDRILL McMurdo Ice Shelf Project (MIS) sediment core AND-1B. This data set is complemented by high-precision chemical analyses (XRF and ICP-OES) on discrete samples. Statistical analyses reveal three geochemical facies which are interpreted to represent the following sources for the sediments recovered in the AND-1B core: 1) local McMurdo Volcanic Group (MVG) rocks, 2) Transantarctic Mountain rocks west of Ross Island (W TAM), and 3) Transantarctic Mountain rocks from more southerly areas (S TAM). Data indicate in combination with other sediment facies analyses (McKay et al., 2009, doi:10.1130/B26540.1) and provenance scenarios (Talarico and Sandroni, 2009, doi:10.1016/j.gloplacha.2009.04.007) that diamictites at the drill site are largely dominated by local sources (MVG) and are interpreted to indicate cold polar conditions with dry-based ice. MVG is interpreted to indicate cold polar condition with dry-based ice. A mixture of MVG and W TAM is interpreted to represent polar conditions and the S TAM facies is interpreted to represent open-marine conditions. Down-core variations in geochemical facies in the AND-1B core are interpreted to represent five major paleoclimate phases over the past 14 Ma. Cold polar conditions with major MVG influence occur below 1045 mbsf and above 120 mbsf. A section of warmer climate conditions with extensive peaks of S TAM influence characterizes the rest of the core, which is interrupted by a section from 525 to 855 mbsf of alternating influences of MVG and W TAM.