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

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.

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

Compositional analysis for an unbiased measure of soil aggregation

Soil aggregation is an index of soil structure measured by mean weight diameter (MWD) or scaling factors often interpreted as fragmentation fractal dimensions (D-f). However, the MWD provides a biased estimate of soil aggregation due to spurious correlations among aggregate-size fractions and scale-dependency. The scale-invariant D-f is based on weak assumptions to allow particle counts and sensitive to the selection of the fractal domain, and may frequently exceed a value of 3, implying that D-f is a biased estimate of aggregation. Aggregation indices based on mass may be computed without bias using compositional analysis techniques. Our objective was to elaborate compositional indices of soil aggregation and to compare them to MWD and D-f using a published dataset describing the effect of 7 cropping systems on aggregation. Six aggregate-size fractions were arranged into a sequence of D-1 balances of building blocks that portray the process of soil aggregation. Isometric log-ratios (ilrs) are scale-invariant and orthogonal log contrasts or balances that possess the Euclidean geometry necessary to compute a distance between any two aggregation states, known as the Aitchison distance (A(x,y)). Close correlations (r>0.98) were observed between MWD, D-f, and the ilr when contrasting large and small aggregate sizes. Several unbiased embedded ilrs can characterize the heterogeneous nature of soil aggregates and be related to soil properties or functions. Soil bulk density and penetrater resistance were closely related to A(x,y) with reference to bare fallow. The A(x,y) is easy to implement as unbiased index of soil aggregation using standard sieving methods and may allow comparisons between studies. (C) 2012 Elsevier B.V. All rights reserved.

Compositional analysis of teas from Australian supermarkets

Caffeine, total amino acids, water extract and moisture content are considered to be quality indicators for leaf teas and teabags. These analyses were examined in 20 leaf teas and 36 teabags sampled from Australian supermarkets. About 70% of the analysed samples showed a moisture content higher than Vie maximum accepted level, 6.5%, for tea storage and marketing by the tea industries and traders. Water appropriate extract of 15 samples out of 36 teabags was lower than that of the teas without teabags, which indicates that the quality of the paper used for teabags needs to be evaluated. Moreover, one of the black leaf tea samples was found to have a water extract below the lower limit of international standards. Four green and black teas of the same brand, claimed to contain less than 3% caffeine, were found to have 3-4%, the same as the other samples analysed in this study. The mean total contents of amino acids were 2.50% and 1.76% in black leaf teas and the teabags, respectively, whereas they were 3.44% and 2.28% in green leaf teas and the teabags, respectively. Furthermore, the weights of 28 teabags out of 36 samples were found to lie outside of the proposed +/- 2% variation accepted by the tea industries and traders, and 4 samples showed even larger variation, 10% being out of the proposed weights. This investigation also showed that the solubility of caffeine and water extract was affected by the permeability of teabags, whereas total amino acids were very variable. These results suggest that an efficient and practical quality control system for both imported and Australian-made teas in the Australian supermarkets should be developed, implemented and enforced. Chemical analysis should be a part of the system for establishing an objective assessment for the quality control. (c) 2004 Elsevier Ltd. All rights reserved.

Common Scientific Lexicon for Automatic Discourse Analysis of Scientific and Technical Texts

The paper reports on preliminary results of an ongoing research aiming at development of an automatic procedure for recognition of discourse-compositional structure of scientific and technical texts, which is required in many NLP applications. The procedure exploits as discourse markers various domain-independent words and expressions that are specific for scientific and technical texts and organize scientific discourse. The paper discusses features of scientific discourse and common scientific lexicon comprising such words and expressions. Methodological issues of development of a computer dictionary for common scientific lexicon are concerned; basic principles of its organization are described as well. Main steps of the discourse-analyzing procedure based on the dictionary and surface syntactical analysis are pointed out.

Effect of Mn concentration and atomic structure on the magnetic properties of Ge thin films

This work reports on the magnetic properties of Ge(100-x)Mn(x) (x=0-24 at. %) films prepared by cosputtering a Ge+Mn target and submitted to cumulative thermal annealing treatments up to 500 degrees C. Both as-deposited and annealed films were investigated by means of compositional analysis, Raman scattering spectroscopy, magnetic force microscopy, superconducting quantum interference device magnetometry, and electrical resistivity measurements. All as-deposited films (either pure or containing Mn) exhibit an amorphous structure, which changes to crystalline as the annealing treatments are performed at increasing temperatures. In fact, the magnetic properties of the present Ge(100-x)Mn(x) films are very sensitive to the Mn content and whether their atomic structure is amorphous or crystalline. More specifically: whereas the amorphous Ge(100-x)Mn(x) films (with high x) present a characteristic spin glass behavior at low temperature; after crystallization, the films (with moderate Mn contents) are ferromagnetic at room temperature. Moreover, the magnetic behavior of the films scales with their Mn concentration and tends to be more pronounced after crystallization. Finally, the semiconducting behavior of the films, experienced by previous optical studies, was confirmed through electrical measurements, which also indicate the dependence of the resistivity with the atomic composition of the films. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3520661]

A study on the pretreatment of a sugarcane bagasse sample with dilute sulfuric acid

Experiments based on a 2(3) central composite full factorial design were carried out in 200-ml stainless-steel containers to study the pretreatment, with dilute sulfuric acid, of a sugarcane bagasse sample obtained from a local sugar-alcohol mill. The independent variables selected for study were temperature, varied from 112.5A degrees C to 157.5A degrees C, residence time, varied from 5.0 to 35.0 min, and sulfuric acid concentration, varied from 0.0% to 3.0% (w/v). Bagasse loading of 15% (w/w) was used in all experiments. Statistical analysis of the experimental results showed that all three independent variables significantly influenced the response variables, namely the bagasse solubilization, efficiency of xylose recovery in the hemicellulosic hydrolysate, efficiency of cellulose enzymatic saccharification, and percentages of cellulose, hemicellulose, and lignin in the pretreated solids. Temperature was the factor that influenced the response variables the most, followed by acid concentration and residence time, in that order. Although harsher pretreatment conditions promoted almost complete removal of the hemicellulosic fraction, the amount of xylose recovered in the hemicellulosic hydrolysate did not exceed 61.8% of the maximum theoretical value. Cellulose enzymatic saccharification was favored by more efficient removal of hemicellulose during the pretreatment. However, detoxification of the hemicellulosic hydrolysate was necessary for better bioconversion of the sugars to ethanol.

A study of ternary Cu2SnS3 and Cu3SnS4 thin films prepared by sulfurizing stacked metal precursors

Thin films of Cu2SnS3 and Cu3SnS4 were grown by sulfurization of dc magnetron sputtered Sn–Cu metallic precursors in a S2 atmosphere. Different maximum sulfurization temperatures were tested which allowed the study of the Cu2SnS3 phase changes. For a temperature of 350 ◦C the films were composed of tetragonal (I -42m) Cu2SnS3. The films sulfurized at a maximum temperature of 400 ◦C presented a cubic (F-43m) Cu2SnS3 phase. On increasing the temperature up to 520 ◦C, the Sn content of the layer decreased and orthorhombic (Pmn21) Cu3SnS4 was formed. The phase identification and structural analysis were performed using x-ray diffraction (XRD) and electron backscattered diffraction (EBSD) analysis. Raman scattering analysis was also performed and a comparison with XRD and EBSD data allowed the assignment of peaks at 336 and 351 cm−1 for tetragonal Cu2SnS3, 303 and 355 cm−1 for cubic Cu2SnS3, and 318, 348 and 295 cm−1 for the Cu3SnS4 phase. Compositional analysis was done using energy dispersive spectroscopy and induced coupled plasma analysis. Scanning electron microscopy was used to study the morphology of the layers. Transmittance and reflectance measurements permitted the estimation of absorbance and band gap. These ternary compounds present a high absorbance value close to 104 cm−1. The estimated band gap energy was 1.35 eV for tetragonal (I -42m) Cu2SnS3, 0.96 eV for cubic (F-43m) Cu2SnS3 and 1.60 eV for orthorhombic (Pmn21) Cu3SnS4. A hot point probe was used for the determination of semiconductor conductivity type. The results show that all the samples are p-type semiconductors. A four-point probe was used to obtain the resistivity of these samples. The resistivities for tetragonal Cu2SnS3, cubic Cu2SnS3 and orthorhombic (Pmn21) Cu3SnS4 are 4.59 × 10−2 cm, 1.26 × 10−2 cm, 7.40 × 10−4 cm, respectively.

Simulation relations, interface complexity, and resource optimality for real-time hierachical systems

Compositional schedulability analysis of hierarchical realtime systems is a well-studied problem. Various techniques have been developed to abstract resource requirements of components in such systems, and schedulability has been addressed using these abstract representations (also called component interfaces). These approaches for compositional analysis incur resource overheads when they abstract components into interfaces. In this talk, we define notions of resource schedulability and optimality for component interfaces, and compare various approaches.

Analyzing shapes as compositions of distances

We propose to analyze shapes as “compositions” of distances in Aitchison geometry asan alternate and complementary tool to classical shape analysis, especially when sizeis non-informative.Shapes are typically described by the location of user-chosen landmarks. Howeverthe shape – considered as invariant under scaling, translation, mirroring and rotation– does not uniquely define the location of landmarks. A simple approach is to usedistances of landmarks instead of the locations of landmarks them self. Distances arepositive numbers defined up to joint scaling, a mathematical structure quite similar tocompositions. The shape fixes only ratios of distances. Perturbations correspond torelative changes of the size of subshapes and of aspect ratios. The power transformincreases the expression of the shape by increasing distance ratios. In analogy to thesubcompositional consistency, results should not depend too much on the choice ofdistances, because different subsets of the pairwise distances of landmarks uniquelydefine the shape.Various compositional analysis tools can be applied to sets of distances directly or afterminor modifications concerning the singularity of the covariance matrix and yield resultswith direct interpretations in terms of shape changes. The remaining problem isthat not all sets of distances correspond to a valid shape. Nevertheless interpolated orpredicted shapes can be backtransformated by multidimensional scaling (when all pairwisedistances are used) or free geodetic adjustment (when sufficiently many distancesare used)

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basicfunctionality has seen some conceptual improvement, containing now some facilitiesto work with and represent ilr bases built from balances, and an elaborated subsys-tem for dealing with several kinds of irregular data: (rounded or structural) zeroes,incomplete observations and outliers. The general approach to these irregularities isbased on subcompositions: for an irregular datum, one can distinguish a “regular” sub-composition (where all parts are actually observed and the datum behaves typically)and a “problematic” subcomposition (with those unobserved, zero or rounded parts, orelse where the datum shows an erratic or atypical behaviour). Systematic classificationschemes are proposed for both outliers and missing values (including zeros) focusing onthe nature of irregularities in the datum subcomposition(s).To compute statistics with values missing at random and structural zeros, a projectionapproach is implemented: a given datum contributes to the estimation of the desiredparameters only on the subcompositon where it was observed. For data sets withvalues below the detection limit, two different approaches are provided: the well-knownimputation technique, and also the projection approach.To compute statistics in the presence of outliers, robust statistics are adapted to thecharacteristics of compositional data, based on the minimum covariance determinantapproach. The outlier classification is based on four different models of outlier occur-rence and Monte-Carlo-based tests for their characterization. Furthermore the packageprovides special plots helping to understand the nature of outliers in the dataset.Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator,robustness, rounded zeros