Brazilian roasted coffee oil obtained by mechanical expelling: compositional analysis by GC-MS

A preliminary analysis by GC-MS comparing the mass spectrum of the compounds with the Wiley 275 L mass spectral data base was used to identify the fatty acids and mainly, some volatile compounds responsible for the flavor of the roasted coffee oil. The oil was obtained by mechanical expelling of Brazilian beans (Coffea arabica) roasted at 238ºC for 10 minutes. Different sample preparation methodologies such as headspace, adsorbent suction trapping and esterification were used. It was possible to identify pyrazines, pyridines, furan derivatives and other compounds not reported in the literature.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Coreferentiality: A New Method for the Hypothesis-Based Analysis of Phenotypes Characterized by Multivariate Data

Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult.

Influence of Cavity Preparation with Er:YAG Laser on Enamel Adjacent to Restorations Submitted to Cariogenic Challenge In Situ: A Polarized Light Microscopic Analysis

Background and Objectives: Er:YAG laser has been used for caries removal and cavity preparation, using ablative parameters. Its effect on the margins of restorations submitted to cariogenic challenge has not yet been sufficiently investigated. The aim of this study was to assess the enamel adjacent to restored Er:YAG laser-prepared cavities submitted to cariogenic challenge in situ, under polarized light microscopy. Study Design/Materials and Methods: Ninety-one enamel slabs were randomly assigned to seven groups (n = 13): I, II, III-Er:YAG laser with 250 mJ, 62.5 J/cm(2), combined with 2, 3, and 4 Hz, respectively; IV, V, VI-Er:YAG laser with 350 mJ, 87.5 J/cm(2), combined with 2, 3, and 4 Hz, respectively; VII-High-speed handpiece (control). Cavities were restored and the restorations were polished. The slabs were fixed to intra-oral appliances, worn by 13 volunteers for 14 days. Sucrose solution was applied to each slab six times per day. Samples were removed, cleaned, sectioned and ground to polarized light microscopic analysis. Demineralized area and inhibition zone width were quantitatively assessed. Presence or absence of cracks was also analyzed. Scores for demineralization and inhibition zone were determined. Results: No difference was found among the groups with regard to demineralized area, inhibition zone width, presence or absence of cracks, and demineralization score. Inhibition zone score showed difference among the groups. There was a correlation between the quantitative measures and the scores. Conclusion: Er:YAG laser was similar to high-speed handpiece, with regard to alterations in enamel adjacent to restorations submitted to cariogenic challenge in situ. The inhibition zone score might suggest less demineralization at the restoration margin of the irradiated substrates. Correlation between the quantitative measures and scores indicates that score was, in this case, a suitable complementary method for assessment of caries lesion around restorations, under polarized light microscopy. Lasers Surg. Med. 40:634-643, 2008. (c) 2008 Wiley-Liss, Inc.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Compositional analysis of biofilms formed by Staphylococcus aureus isolated from food sources

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00390

Compositional analysis of archaeological glasses

At CoDaWork'03 we presented work on the analysis of archaeological glass composi-tional data. Such data typically consist of geochemical compositions involving 10-12variables and approximates completely compositional data if the main component, sil-ica, is included. We suggested that what has been termed `crude' principal componentanalysis (PCA) of standardized data often identi ed interpretable pattern in the datamore readily than analyses based on log-ratio transformed data (LRA). The funda-mental problem is that, in LRA, minor oxides with high relative variation, that maynot be structure carrying, can dominate an analysis and obscure pattern associatedwith variables present at higher absolute levels. We investigate this further using sub-compositional data relating to archaeological glasses found on Israeli sites. A simplemodel for glass-making is that it is based on a `recipe' consisting of two `ingredients',sand and a source of soda. Our analysis focuses on the sub-composition of componentsassociated with the sand source. A `crude' PCA of standardized data shows two clearcompositional groups that can be interpreted in terms of di erent recipes being used atdi erent periods, reected in absolute di erences in the composition. LRA analysis canbe undertaken either by normalizing the data or de ning a `residual'. In either case,after some `tuning', these groups are recovered. The results from the normalized LRAare di erently interpreted as showing that the source of sand used to make the glassdi ered. These results are complementary. One relates to the recipe used. The otherrelates to the composition (and presumed sources) of one of the ingredients. It seemsto be axiomatic in some expositions of LRA that statistical analysis of compositionaldata should focus on relative variation via the use of ratios. Our analysis suggests thatabsolute di erences can also be informative

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table hasn rows and m columns and all probabilities are non-null. This kind of table can beseen as an element in the simplex of n · m parts. In this context, the marginals areidentified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclideanelements of the Aitchison geometry of the simplex can also be translated into the tableof probabilities: subspaces, orthogonal projections, distances.Two important questions are addressed: a) given a table of probabilities, which isthe nearest independent table to the initial one? b) which is the largest orthogonalprojection of a row onto a column? or, equivalently, which is the information in arow explained by a column, thus explaining the interaction? To answer these questionsthree orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independenttwo-way tables and fully dependent tables representing row-column interaction. Animportant result is that the nearest independent table is the product of the two (rowand column)-wise geometric marginal tables. A corollary is that, in an independenttable, the geometric marginals conform with the traditional (arithmetic) marginals.These decompositions can be compared with standard log-linear models.Key words: balance, compositional data, simplex, Aitchison geometry, composition,orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure,contingency table

A note on the dual scaling of dominance data and its relationship to correspondence analysis

Dual scaling of a subjects-by-objects table of dominance data (preferences,paired comparisons and successive categories data) has been contrasted with correspondence analysis, as if the two techniques were somehow different. In this note we show that dual scaling of dominance data is equivalent to the correspondence analysis of a table which is doubled with respect to subjects. We also show that the results of both methods can be recovered from a principal components analysis of the undoubled dominance table which is centred with respect to subject means.

Compositional analysis of archaeological glasses

At CoDaWork'03 we presented work on the analysis of archaeological glass composi- tional data. Such data typically consist of geochemical compositions involving 10-12 variables and approximates completely compositional data if the main component, sil- ica, is included. We suggested that what has been termed `crude' principal component analysis (PCA) of standardized data often identi ed interpretable pattern in the data more readily than analyses based on log-ratio transformed data (LRA). The funda- mental problem is that, in LRA, minor oxides with high relative variation, that may not be structure carrying, can dominate an analysis and obscure pattern associated with variables present at higher absolute levels. We investigate this further using sub- compositional data relating to archaeological glasses found on Israeli sites. A simple model for glass-making is that it is based on a `recipe' consisting of two `ingredients', sand and a source of soda. Our analysis focuses on the sub-composition of components associated with the sand source. A `crude' PCA of standardized data shows two clear compositional groups that can be interpreted in terms of di erent recipes being used at di erent periods, re ected in absolute di erences in the composition. LRA analysis can be undertaken either by normalizing the data or de ning a `residual'. In either case, after some `tuning', these groups are recovered. The results from the normalized LRA are di erently interpreted as showing that the source of sand used to make the glass di ered. These results are complementary. One relates to the recipe used. The other relates to the composition (and presumed sources) of one of the ingredients. It seems to be axiomatic in some expositions of LRA that statistical analysis of compositional data should focus on relative variation via the use of ratios. Our analysis suggests that absolute di erences can also be informative

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table has n rows and m columns and all probabilities are non-null. This kind of table can be seen as an element in the simplex of n · m parts. In this context, the marginals are identified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclidean elements of the Aitchison geometry of the simplex can also be translated into the table of probabilities: subspaces, orthogonal projections, distances. Two important questions are addressed: a) given a table of probabilities, which is the nearest independent table to the initial one? b) which is the largest orthogonal projection of a row onto a column? or, equivalently, which is the information in a row explained by a column, thus explaining the interaction? To answer these questions three orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independent two-way tables and fully dependent tables representing row-column interaction. An important result is that the nearest independent table is the product of the two (row and column)-wise geometric marginal tables. A corollary is that, in an independent table, the geometric marginals conform with the traditional (arithmetic) marginals. These decompositions can be compared with standard log-linear models. Key words: balance, compositional data, simplex, Aitchison geometry, composition, orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure, contingency table

Sexually Dimorphic Effect of the Val66Met Polymorphism of BDNF on Susceptibility to Alzheimer`s Disease: New Data and Meta-Analysis

Conflicting results have been reported as to whether genetic variations (Val66Met and C270T) of the brain-derived neurotrophic factor gene (RDNF) confer susceptibility to Alzheimer`s disease (AD). We genotyped these polymorphisms in a Japanese sample of 657 patients with AD and 525 controls, and obtained weak evidence of association for Val66Met (P = 0.063), but not for C270T. After stratification by sex, we found a significant allelic association between Val66Met and AD in women (P = 0.017), but not in men. To confirm these observations, we collected genotyping data for each sex from 16 research centers worldwide (4,711 patients and 4,537 controls in total). The meta-analysis revealed that there was a clear sex difference in the allelic association; the Met66 allele confers susceptibility to AD in women (odds ratio = 1.14, 95% CI 1.05-1.24, P = 0.002), but not in men. Our results provide evidence that the Met66 allele of BDNF has a sexually dimorphic effect on susceptibility to AD. (C) 2009 Wiley-Liss, Inc.

Peak Separation by Derivative Spectroscopy Applied to FTIR Analysis of Hydrolized Silica

Reliable spectral analysis is only achieved if the spectrum is thoroughly investigated in regard to all hidden and overlapped peaks. This paper describes the steps undertaken to find and separate such peaks in the range of 3000 to 4000 cm(-1) in the case of three different infrared absorption spectra of the glass surface of hydrolyzed silica optical fibers. Peak finding was done by the analysis of the second and fourth derivatives of the digital data, coupled with the available knowledge of infrared spectroscopy of silica-water interaction in the investigated range. Peak separation was accomplished by curve fitting with four different models. The model with the best fit was described by a sum of pure Gaussian peaks. Shoulder limit and detection limit maps were used to validate the revealed spectral features.

Biometric relationship analysis of the wet weight by carapace width to the swimming crab Arenaeus-cribrarius (Lamarck, 1818) (Crustacea, Brachyura, Portunidae)

The biometric relationship between the weigth and the carapace width in the swimming crab A. cribrarius was compared with the results from other portunid crabs studied previously. During November/1988 to October/1989, a total of 403 specimens (189 males and 214 females) were collected with otter-trawl nets in north coast of the São Paulo State, Brazil. The animals were measured (carapace width excluding lateral spines = LC! and weighed (wet weight = PE). The empiric points of this relation were fit according to the power function (Y = a.X(b)) for each sex, maturation phases and total of individuals. The relation PE x LC indicates that the mole's growth changes during the ontogenesys from isometric (in juvenile phase) to allometric positive (in adult phase). For the females the growth is isometric in the two phases. The weight grows in a higher proportion than the carapace width variable (allometric positive growth). The data can be grouped in a single equation (PE = 7.85.10(-5).LC(3.14)) for the convertion between the variables there was a greater similarity between the equations obtained far each sex. In spite of this, the males present the fattening grade value (''a'') slightly higher than that of the females, possibly because of the greater size reached in its devellopment. The mean weight of the males is greater than the females one (p < 0.01). In the range 80 proves 90mm the males were more abundant, probably due to the females terminal ecdysis is near this size. The females only have the mean weight greater than the males in the 60 proves 70mm range (p < 0.01) when the puberty molt occurs and they present morphological changes in their reproductive system.

Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

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