Studies in stoichiometry with compositional data

Geochemical data that is derived from the whole or partial analysis of various geologic materialsrepresent a composition of mineralogies or solute species. Minerals are composed of structuredrelationships between cations and anions which, through atomic and molecular forces, keep the elementsbound in specific configurations. The chemical compositions of minerals have specific relationships thatare governed by these molecular controls. In the case of olivine, there is a well-defined relationshipbetween Mn-Fe-Mg with Si. Balances between the principal elements defining olivine composition andother significant constituents in the composition (Al, Ti) have been defined, resulting in a near-linearrelationship between the logarithmic relative proportion of Si versus (MgMnFe) and Mg versus (MnFe),which is typically described but poorly illustrated in the simplex.The present contribution corresponds to ongoing research, which attempts to relate stoichiometry andgeochemical data using compositional geometry. We describe here the approach by which stoichiometricrelationships based on mineralogical constraints can be accounted for in the space of simplicialcoordinates using olivines as an example. Further examples for other mineral types (plagioclases andmore complex minerals such as clays) are needed. Issues that remain to be dealt with include thereduction of a bulk chemical composition of a rock comprised of several minerals from which appropriatebalances can be used to describe the composition in a realistic mineralogical framework. The overallobjective of our research is to answer the question: In the cases where the mineralogy is unknown, arethere suitable proxies that can be substituted?Kew words: Aitchison geometry, balances, mineral composition, oxides

Clustering compositional data trajectories

Our essay aims at studying suitable statistical methods for the clustering ofcompositional data in situations where observations are constituted by trajectories ofcompositional data, that is, by sequences of composition measurements along a domain.Observed trajectories are known as “functional data” and several methods have beenproposed for their analysis.In particular, methods for clustering functional data, known as Functional ClusterAnalysis (FCA), have been applied by practitioners and scientists in many fields. To ourknowledge, FCA techniques have not been extended to cope with the problem ofclustering compositional data trajectories. In order to extend FCA techniques to theanalysis of compositional data, FCA clustering techniques have to be adapted by using asuitable compositional algebra.The present work centres on the following question: given a sample of compositionaldata trajectories, how can we formulate a segmentation procedure giving homogeneousclasses? To address this problem we follow the steps described below.First of all we adapt the well-known spline smoothing techniques in order to cope withthe smoothing of compositional data trajectories. In fact, an observed curve can bethought of as the sum of a smooth part plus some noise due to measurement errors.Spline smoothing techniques are used to isolate the smooth part of the trajectory:clustering algorithms are then applied to these smooth curves.The second step consists in building suitable metrics for measuring the dissimilaritybetween trajectories: we propose a metric that accounts for difference in both shape andlevel, and a metric accounting for differences in shape only.A simulation study is performed in order to evaluate the proposed methodologies, usingboth hierarchical and partitional clustering algorithm. The quality of the obtained resultsis assessed by means of several indices

Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Pandemic 2009 A(H1N1) infection requiring hospitalization of elderly Spanish adults.

To describe the clinical presentation and prognosis of elderly adults hospitalized with pandemic 2009 A(H1N1) influenza infection and to compare these data with those of younger patients. DESIGN: Prospective, observational, multicenter study. SETTING: Thirteen hospitals in Spain. PARTICIPANTS: Adults admitted to the hospital with confirmed pandemic 2009 A(H1N1) influenza infection. MEASUREMENTS: Demographic, clinical, laboratory, radiological, and outcome variables. RESULTS: Between June 12 and November 10, 2009, 585 adults with confirmed 2009 A(H1N1) influenza were hospitalized, of whom 50 (8.5%) were aged 65 and older (median age 72, range 65-87). Older adults (≥ 65) were more likely to have associated comorbidities (88.0% vs 51.2%; P < .001), primarily chronic pulmonary diseases (46.0% vs 27.3%; P < .001). Lower respiratory tract symptoms and signs such as dyspnea (60.0% vs 45.6%) and wheezing (46.0% vs 27.8%; P = .007) were also more common in these elderly adults, although pulmonary infiltrates were present in just 14 (28.0%) of the older adults, compared with 221 (41.3%) of the younger adults (P = .06). Multilobar involvement was less frequent in elderly adults with pulmonary infiltrates than younger adults with pulmonary infiltrates (21.4% vs 60.0%; P = .05). Rhinorrhea (4.0% vs 21.9%; P = .003), myalgias (42.0% vs 59.1%; P = .01), and sore throat (14.0% vs 29.2%; P = .02) were more frequent in younger adults. Early antiviral therapy (<48 hours) was similar in the two groups (34.0% vs 37.9%; P = .58). Two older adults (4.0%) died during hospitalization, compared with 11 (2.1%) younger adults (P = .30). CONCLUSION: Elderly adults with 2009 A(H1N1) influenza had fewer viral-like upper respiratory symptoms than did younger adults. Pneumonia was more frequent in younger adults. No significant differences were observed in hospital mortality.

First insights into the transcriptome and development of new genomic tools of a widespread circum-Mediterranean tree species, Pinus halepensis Mill.

Aleppo pine (Pinus halepensis Mill.) is a relevant conifer species for studying adaptive responses to drought and fire regimes in the Mediterranean region. In this study, we performed Illumina next-generation sequencing of two phenotypically divergent Aleppo pine accessions with the aims of (i) characterizing the transcriptome through Illumina RNA-Seq on trees phenotypically divergent for adaptive traits linked to fire adaptation and drought, (ii) performing a functional annotation of the assembled transcriptome, (iii) identifying genes with accelerated evolutionary rates, (iv) studying the expression levels of the annotated genes and (v) developing gene-based markers for population genomic and association genetic studies. The assembled transcriptome consisted of 48,629 contigs and covered about 54.6 Mbp. The comparison of Aleppo pine transcripts to Picea sitchensis protein-coding sequences resulted in the detection of 34,014 SNPs across species, with a Ka /Ks average value of 0.216, suggesting that the majority of the assembled genes are under negative selection. Several genes were differentially expressed across the two pine accessions with contrasted phenotypes, including a glutathione-s-transferase, a cellulose synthase and a cobra-like protein. A large number of new markers (3334 amplifiable SSRs and 28,236 SNPs) have been identified which should facilitate future population genomics and association genetics in this species. A 384-SNP Oligo Pool Assay for genotyping with the Illumina VeraCode technology has been designed which showed an high overall SNP conversion rate (76.6%). Our results showed that Illumina next-generation sequencing is a valuable technology to obtain an extensive overview on whole transcriptomes of nonmodel species with large genomes.

An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 differentcompositional datasets and modelled the first canonical variable using a segmented regression modelsolely based on an observation about the scatter plots. In this paper, multiple linear regressions areapplied to different datasets to confirm the validity of our proposed model. In addition to dating theunknown tephras by calibration as discussed previously, another method of mapping the unknown tephrasinto samples of the reference set or missing samples in between consecutive reference samples isproposed. The application of these methodologies is demonstrated with both simulated and real datasets.This new proposed methodology provides an alternative, more acceptable approach for geologists as theirfocus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age ofunknown tephra.Kew words: Tephrochronology; Segmented regression

Monitoring procedures in environmental geochemistry and compositional data analysis theory

First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by asimplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able togenerate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow definingmonitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated

The chemical variability at the surface of Mars: implications for exogenic processes

The chemical composition of sediments and rocks, as well as their distribution at theMartian surface, represent a long term archive of processes, which have formed theplanetary surface. A survey of chemical compositions by means of Compositional DataAnalysis represents a valuable tool to extract direct evidence for weathering processesand allows to quantify weathering and sedimentation rates. clr-biplot techniques areapplied for visualization of chemical relationships across the surface (“chemical maps”).The variability among individual suites of data is further analyzed by means of clr-PCA,in order to extract chemical alteration vectors between fresh rocks and their crusts andfor an assessment of different source reservoirs accessible to soil formation. Bothtechniques are applied to elucidate the influence of remote weathering by combinedanalysis of several soil forming branches. Vector analysis in the Simplex provides theopportunity to study atmosphere surface interactions, including the role andcomposition of volcanic gases

Statistical evidences of cyclic changes in volcanic gas chemistry composition by inverse modelling

The identification of compositional changes in fumarolic gases of active and quiescent volcanoes is one of the mostimportant targets in monitoring programs. From a general point of view, many systematic (often cyclic) and randomprocesses control the chemistry of gas discharges, making difficult to produce a convincing mathematical-statisticalmodelling.Changes in the chemical composition of volcanic gases sampled at Vulcano Island (Aeolian Arc, Sicily, Italy) fromeight different fumaroles located in the northern sector of the summit crater (La Fossa) have been analysed byconsidering their dependence from time in the period 2000-2007. Each intermediate chemical composition has beenconsidered as potentially derived from the contribution of the two temporal extremes represented by the 2000 and 2007samples, respectively, by using inverse modelling methodologies for compositional data. Data pertaining to fumarolesF5 and F27, located on the rim and in the inner part of La Fossa crater, respectively, have been used to achieve theproposed aim. The statistical approach has allowed us to highlight the presence of random and not random fluctuations,features useful to understand how the volcanic system works, opening new perspectives in sampling strategies and inthe evaluation of the natural risk related to a quiescent volcano

Elemental analysis of New Zealand Nephrite Jade (pounamu) for forensic purposes

Pounamu (NZ jade), or nephrite, is a protected mineral in its natural form following thetransfer of ownership back to Ngai Tahu under the Ngai Tahu (Pounamu Vesting) Act 1997.Any theft of nephrite is prosecutable under the Crimes Act 1961. Scientific evidence isessential in cases where origin is disputed. A robust method for discrimination of thismaterial through the use of elemental analysis and compositional data analysis is required.Initial studies have characterised the variability within a given nephrite source. This hasincluded investigation of both in situ outcrops and alluvial material. Methods for thediscrimination of two geographically close nephrite sources are being developed.Key Words: forensic, jade, nephrite, laser ablation, inductively coupled plasma massspectrometry, multivariate analysis, elemental analysis, compositional data analysis

Modulation of Higher-Order Olfaction Components on Executive Functions in Humans.

The prefrontal (PFC) and orbitofrontal cortex (OFC) appear to be associated with both executive functions and olfaction. However, there is little data relating olfactory processing and executive functions in humans. The present study aimed at exploring the role of olfaction on executive functioning, making a distinction between primary and more cognitive aspects of olfaction. Three executive tasks of similar difficulty were used. One was used to assess hot executive functions (Iowa Gambling Task-IGT), and two as a measure of cold executive functioning (Stroop Colour and Word Test-SCWT and Wisconsin Card Sorting Test-WCST). Sixty two healthy participants were included: 31 with normosmia and 31 with hyposmia. Olfactory abilities were assessed using the ''Sniffin' Sticks'' test and the olfactory threshold, odour discrimination and odour identification measures were obtained. All participants were female, aged between 18 and 60. Results showed that participants with hyposmia displayed worse performance in decision making (IGT; Cohen's-d = 0.91) and cognitive flexibility (WCST; Cohen's-d between 0.54 and 0.68) compared to those with normosmia. Multiple regression adjusted by the covariates participants' age and education level showed a positive association between odour identification and the cognitive inhibition response (SCWT-interference; Beta = 0.29; p = .034). The odour discrimination capacity was not a predictor of the cognitive executive performance. Our results suggest that both hot and cold executive functions seem to be associated with higher-order olfactory functioning in humans. These results robustly support the hypothesis that olfaction and executive measures have a common neural substrate in PFC and OFC, and suggest that olfaction might be a reliable cognitive marker in psychiatric and neurologic disorders.

Combined vemurafenib and cobimetinib in BRAF-mutated melanoma.

BACKGROUND The combined inhibition of BRAF and MEK is hypothesized to improve clinical outcomes in patients with melanoma by preventing or delaying the onset of resistance observed with BRAF inhibitors alone. This randomized phase 3 study evaluated the combination of the BRAF inhibitor vemurafenib and the MEK inhibitor cobimetinib. METHODS We randomly assigned 495 patients with previously untreated unresectable locally advanced or metastatic BRAF V600 mutation-positive melanoma to receive vemurafenib and cobimetinib (combination group) or vemurafenib and placebo (control group). The primary end point was investigator-assessed progression-free survival. RESULTS The median progression-free survival was 9.9 months in the combination group and 6.2 months in the control group (hazard ratio for death or disease progression, 0.51; 95% confidence interval [CI], 0.39 to 0.68; P<0.001). The rate of complete or partial response in the combination group was 68%, as compared with 45% in the control group (P<0.001), including rates of complete response of 10% in the combination group and 4% in the control group. Progression-free survival as assessed by independent review was similar to investigator-assessed progression-free survival. Interim analyses of overall survival showed 9-month survival rates of 81% (95% CI, 75 to 87) in the combination group and 73% (95% CI, 65 to 80) in the control group. Vemurafenib and cobimetinib was associated with a nonsignificantly higher incidence of adverse events of grade 3 or higher, as compared with vemurafenib and placebo (65% vs. 59%), and there was no significant difference in the rate of study-drug discontinuation. The number of secondary cutaneous cancers decreased with the combination therapy. CONCLUSIONS The addition of cobimetinib to vemurafenib was associated with a significant improvement in progression-free survival among patients with BRAF V600-mutated metastatic melanoma, at the cost of some increase in toxicity. (Funded by F. Hoffmann-La Roche/Genentech; coBRIM ClinicalTrials.gov number, NCT01689519.).

A Factor analysis of hidrochemical composition of Llobregat river basin

Hydrogeological research usually includes some statistical studies devised to elucidate mean background state, characterise relationships among different hydrochemical parameters, and show the influence of human activities. These goals are achieved either by means of a statistical approach or by mixing modelsbetween end-members. Compositional data analysis has proved to be effective with the first approach, but there is no commonly accepted solution to the end-member problem in a compositional framework.We present here a possible solution based on factor analysis of compositions illustrated with a case study.We find two factors on the compositional bi-plot fitting two non-centered orthogonal axes to the most representative variables. Each one of these axes defines a subcomposition, grouping those variables thatlay nearest to it. With each subcomposition a log-contrast is computed and rewritten as an equilibrium equation. These two factors can be interpreted as the isometric log-ratio coordinates (ilr) of three hiddencomponents, that can be plotted in a ternary diagram. These hidden components might be interpreted as end-members.We have analysed 14 molarities in 31 sampling stations all along the Llobregat River and its tributaries, with a monthly measure during two years. We have obtained a bi-plot with a 57% of explained totalvariance, from which we have extracted two factors: factor G, reflecting geological background enhanced by potash mining; and factor A, essentially controlled by urban and/or farming wastewater. Graphicalrepresentation of these two factors allows us to identify three extreme samples, corresponding to pristine waters, potash mining influence and urban sewage influence. To confirm this, we have available analysisof diffused and widespread point sources identified in the area: springs, potash mining lixiviates, sewage, and fertilisers. Each one of these sources shows a clear link with one of the extreme samples, exceptfertilisers due to the heterogeneity of their composition.This approach is a useful tool to distinguish end-members, and characterise them, an issue generally difficult to solve. It is worth note that the end-member composition cannot be fully estimated but only characterised through log-ratio relationships among components. Moreover, the influence of each endmember in a given sample must be evaluated in relative terms of the other samples. These limitations areintrinsic to the relative nature of compositional data

Quantifying rock fabrics: a test of autocorrelation of the spatial distribution of cristals

A novel test of spatial independence of the distribution of crystals or phases in rocksbased on compositional statistics is introduced. It improves and generalizes the commonjoins-count statistics known from map analysis in geographic information systems.Assigning phases independently to objects in RD is modelled by a single-trial multinomialrandom function Z(x), where the probabilities of phases add to one and areexplicitly modelled as compositions in the K-part simplex SK. Thus, apparent inconsistenciesof the tests based on the conventional joins{count statistics and their possiblycontradictory interpretations are avoided. In practical applications we assume that theprobabilities of phases do not depend on the location but are identical everywhere inthe domain of de nition. Thus, the model involves the sum of r independent identicalmultinomial distributed 1-trial random variables which is an r-trial multinomialdistributed random variable. The probabilities of the distribution of the r counts canbe considered as a composition in the Q-part simplex SQ. They span the so calledHardy-Weinberg manifold H that is proved to be a K-1-affine subspace of SQ. This isa generalisation of the well-known Hardy-Weinberg law of genetics. If the assignmentof phases accounts for some kind of spatial dependence, then the r-trial probabilitiesdo not remain on H. This suggests the use of the Aitchison distance between observedprobabilities to H to test dependence. Moreover, when there is a spatial uctuation ofthe multinomial probabilities, the observed r-trial probabilities move on H. This shiftcan be used as to check for these uctuations. A practical procedure and an algorithmto perform the test have been developed. Some cases applied to simulated and realdata are presented.Key words: Spatial distribution of crystals in rocks, spatial distribution of phases,joins-count statistics, multinomial distribution, Hardy-Weinberg law, Hardy-Weinbergmanifold, Aitchison geometry

When zero doesn't mean it and other geomathematical mischief

There is almost not a case in exploration geology, where the studied data doesn’tincludes below detection limits and/or zero values, and since most of the geological dataresponds to lognormal distributions, these “zero data” represent a mathematicalchallenge for the interpretation.We need to start by recognizing that there are zero values in geology. For example theamount of quartz in a foyaite (nepheline syenite) is zero, since quartz cannot co-existswith nepheline. Another common essential zero is a North azimuth, however we canalways change that zero for the value of 360°. These are known as “Essential zeros”, butwhat can we do with “Rounded zeros” that are the result of below the detection limit ofthe equipment?Amalgamation, e.g. adding Na2O and K2O, as total alkalis is a solution, but sometimeswe need to differentiate between a sodic and a potassic alteration. Pre-classification intogroups requires a good knowledge of the distribution of the data and the geochemicalcharacteristics of the groups which is not always available. Considering the zero valuesequal to the limit of detection of the used equipment will generate spuriousdistributions, especially in ternary diagrams. Same situation will occur if we replace thezero values by a small amount using non-parametric or parametric techniques(imputation).The method that we are proposing takes into consideration the well known relationshipsbetween some elements. For example, in copper porphyry deposits, there is always agood direct correlation between the copper values and the molybdenum ones, but whilecopper will always be above the limit of detection, many of the molybdenum values willbe “rounded zeros”. So, we will take the lower quartile of the real molybdenum valuesand establish a regression equation with copper, and then we will estimate the“rounded” zero values of molybdenum by their corresponding copper values.The method could be applied to any type of data, provided we establish first theircorrelation dependency.One of the main advantages of this method is that we do not obtain a fixed value for the“rounded zeros”, but one that depends on the value of the other variable.Key words: compositional data analysis, treatment of zeros, essential zeros, roundedzeros, correlation dependency