Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

Optimization and validation of a LIBS method for the determination of macro and micronutrients in sugar cane leaves

Laser induced breakdown spectrometry (LIBS) was applied for the determination of macro (P, K, Ca, Mg) and micronutrients (B, Cu, Fe, Mn and Zn) in sugar cane leaves, which is one of the most economically important crops in Brazil. Operational conditions were previously optimized by a neuro-genetic approach, by using a laser Nd:YAG at 1064 nm with 110 mJ per pulse focused on a pellet surface prepared with ground plant samples. Emission intensities were measured after 2.0 mu s delay time, with 4.5 mu s integration time gate and 25 accumulated laser pulses. Measurements of LIBS spectra were based on triplicate and each replicate consisted of an average of ten spectra collected in different sites (craters) of the pellet. Quantitative determinations were carried out by using univariate calibration and chemometric methods, such as PLSR and iPLS. The calibration models were obtained by using 26 laboratory samples and the validation was carried out by using 15 test samples. For comparative purpose, these samples were also microwave-assisted digested and further analyzed by ICP OES. In general, most results obtained by LIBS did not differ significantly from ICP OES data by applying a t-test at 95% confidence level. Both LIBS multivariate and univariate calibration methods produced similar results, except for Fe where better results were achieved by the multivariate approach. Repeatability precision varied from 0.7 to 15% and 1.3 to 20% from measurements obtained by multivariate and univariate calibration, respectively. It is demonstrated that LIBS is a powerful tool for analysis of pellets of plant materials for determination of macro and micronutrients by choosing calibration and validation samples with similar matrix composition.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

STATISTICAL EVALUATION OF MATURE LANDFILL LEACHATE TREATMENT BY HOMOGENEOUS CATALYTIC OZONATION

This study presents the results of a mature landfill leachate treated by a homogeneous catalytic ozonation process with ions Fe(2+) and Fe(3+) at acidic pH. Quality assessments were performed using Taguchi`s method (L(8) design). Strong synergism was observed statistically between molecular ozone and ferric ions, pointing to their catalytic effect on (center dot)OH generation. The achievement of better organic matter depollution rates requires an ozone flow of 5 L h(-1) (590 mg h(-1) O(3)) and a ferric ion concentration of 5 mg L(-1).

Multivariate analysis of sensory characteristics of coffee grains (Coffea arabica L.) in the region of upper Paranaiba

This study aimed to examine the sensory characteristics of the grains of 21 cultivars of Coffea arabica L. and Coffea canephora Pierre from the essays of genetic improvement of EPAMIG, located in Patrocinio Municipality, Minas Gerais State, where they were collected through cloths stripping method and washed. Subsequently to dry (11 to 12% moisture b.u.), we obtained the coffee designated as natural. The evaluated varieties were: Acaia Cerrado MG 1474; Bourbon Vermelho DATERRA; Catigua MG 1; Catigua MG 2; Catual Amarelo IAC 62; Catuai Vermelho IAC 15; H 419-3-1-4-2; H 419-6-2 -5-2; H 419-6-2-5-3; H 419-6-2-7-3 Vermelho; H 493-1-2-10; H 514-7-10-1 Vermelho; H 514-7-10-6; H 515-4-2-2; H 518-3-6-1; Icatu Amarelo IAC 3282; Mundo Novo 379-19; Mundo Novo TAO 376-4; Rubi MG 1192; Sacramento MG 1 and Topazio MG 1190, from 2005/2006 and 2006/2007 seasons. The cultivars according to the first principal component with notes above 80 points, regarded as superior drink according to attributes with the highest scores (flavor, sweetness, balance, acidity, clean drink, and aspect) were: Catigua MG2, Rubi MG 1192, 514-7-10-6 H, H 419-3-1-4-2, H 419-6-2-5-2, 493-1-2-10 H, H 514-7-10-1 Vermelho, Catigua MG1, Sacramento MG1, 419-6-2-5-3 H, H 515-9-2-2 and Catuai Amarelo IAC 62.

Genetic Diversity and a PCR-Based Method for Xanthomonas axonopodis Detection in Passion Fruit

Xanthomonas axonopodis pv. passiflorae causes bacterial spot in passion fruit. It attacks the purple and yellow passion fruit as well as the sweet passion fruit. The diversity of 87 isolates of pv. passiflorae collected from across 22 fruit orchards in Brazil was evaluated using molecular profiles and statistical procedures, including an unweighted pair-group method with arithmetical averages-based dendrogram, analysis of molecular variance (AMOVA), and an assigning test that provides information on genetic structure at the population level. Isolates from another eight pathovars were included in the molecular analyses and all were shown to have a distinct repetitive sequence-based polymerase chain reaction profile. Amplified fragment length polymorphism technique revealed considerable diversity among isolates of pv. passiflorae, and AMOVA showed that most of the variance (49.4%) was due to differences between localities. Cluster analysis revealed that most genotypic clusters were homogeneous and that variance was associated primarily with geographic origin. The disease adversely affects fruit production and may kill infected plants. A method for rapid diagnosis of the pathogen, even before the disease symptoms become evident, has value for producers. Here, a set of primers (Xapas) was designed by exploiting a single-nucleotide polymorphism between the sequences of the intergenic 16S-23S rRNA spacer region of the pathovars. Xapas was shown to effectively detect all pv. passiflorae isolates and is recommended for disease diagnosis in passion fruit orchards.

Biomonitoring method for the simultaneous determination of cadmium and lead in whole blood by electrothermal atomic absorption spectrometry for assessment of environmental exposure

The aim of this work is to propose a biomonitoring method for the simultaneous determination of Cd and Pb in whole blood by simultaneous electrothermal atomic absorption spectrometry for assessment of environmental levels. A volume of 200 mu L of whole blood was diluted in 500 mu L of 0.2% (w v(-1)) Triton(R) X-100 + 2.0% (v v(-1)) HNO3. Trichloroacetic acid was added for protein precipitation and the supernatant analyzed. A mixture of 250 mu g W + 200 mu g Rh as permanent and 2.0% (w v(-1)) NH4H2PO4 as co-injected modifiers were used. Characteristic masses and limits of detections (n = 20, 3s) for Cd and Pb were 1.26 and 33 pg and 0.026 mu g L-1 and 0.65 mu g L-1, respectively. Repeatability ranged from 1.8 to 6.8% for Cd and 1.2 to 1.7% for Pb. The trueness of method was checked by the analysis of three Reference Materials: Lyphocheck(R) Whole Blood Metals Control level 1 and Seronorm(TM) Trace Elements in Whole Blood levels 1 and 2. The found concentrations presented no statistical differences at the 95% confidence level. Blood samples from 40 volunteers without occupational exposure were analyzed and the concentrations ranged from 0.13 to 0.71 mu g L-1 (0.32 +/- 0.19 mu g L-1) for Cd and 9.3 to 56.7 mu g L-1 (25.1 +/- 10.8 mu g L-1) for Pb. (C) 2007 Elsevier B.V. All rights reserved.

Quantification of Listeria monocytogenes in minimally processed leafy vegetables using a combined method based on enrichment and 16S rRNA real-time PCR

Modern lifestyle markedly changed eating habits worldwide, with an increasing demand for ready-to-eat foods, such as minimally processed fruits and leafy greens. Packaging and storage conditions of those products may favor the growth of psychrotrophic bacteria, including the pathogen Listeria monocytogenes. In this work, minimally processed leafy vegetables samples (n = 162) from retail market from Ribeirao Preto, Sao Paulo, Brazil, were tested for the presence or absence of Listeria spp. by the immunoassay Listeria Rapid Test, Oxoid. Two L. monocytogenes positive and six artificially contaminated samples of minimally processed leafy vegetables were evaluated by the Most Probable Number (MPN) with detection by classical culture method and also culture method combined with real-time PCR (RTi-PCR) for 16S rRNA genes of L monocytogenes. Positive MPN enrichment tubes were analyzed by RTi-PCR with primers specific for L. monocytogenes using the commercial preparation ABSOLUTET (TM) QPCR SYBR (R) Green Mix (ABgene, UK). Real-time PCR assay presented good exclusivity and inclusivity results and no statistical significant difference was found in comparison with the conventional culture method (p < 0.05). Moreover, RTi-PCR was fist and easy to perform, with MPN results obtained in ca. 48 h for RTi-PCR in comparison to 7 days for conventional method. (C) 2009 Elsevier Ltd. All rights reserved.

A non-invasive method for silencing gene transcription in honeybees maintained under natural conditions

in the Apis mellifera post-genomic era, RNAi protocols have been used in functional approaches. However, sample manipulation and invasive methods such as injection of double-stranded RNA (dsRNA) can compromise physiology and survival. To circumvent these problems, we developed a non-invasive method for honeybee gene knockdown, using a well-established vitellogenin RNAi system as a model. Second instar larvae received dsRNA for vitellogenin (dsVg-RNA) in their natural diet. For exogenous control, larvae received dsRNA for GFP (dsGFP-RNA). Untreated larvae formed another control group. Around 60% of the treated larvae naturally developed until adult emergence when 0.5 mu g of dsVg-RNA or dsGFP-RNA was offered while no larvae that received 3.0 mu g of dsRNA reached pupal stages. Diet dilution did not affect the removal rates. Viability depends not only on the delivered doses but also on the internal conditions of colonies. The weight of treated and untreated groups showed no statistical differences. This showed that RNAi ingestion did not elicit drastic collateral effects. Approximately 90% of vitellogenin transcripts from 7-day-old workers were silenced compared to controls. A large number of samples are handled in a relatively short time and smaller quantities of RNAi molecules are used compared to invasive methods. These advantages culminate in a versatile and a cost-effective approach. (c) 2008 Elsevier Ltd. All rights reserved.

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

Improved comparison plot method for pore structure characterization of MCM-41

MCM-41 samples of various pore dimensions are synthesized. Plotting of nitrogen adsorption data at 77 K versus the statistical film thickness (comparison plot) reveals three distinct stages, with a characteristic of two points of inflection. The steep intermediate stage caused by capillary condensation occurred in the highly uniform mesopores. From the slopes of the sections before and after the condensation, the surface area of the mesopores is calculated. The linear portion of the last section is extrapolated to the adsorption axis of the comparison plot, and this intercept is used to obtain the volume of the mesopores. From the surface area and pore volume, average mesopore diameter is calculated, and the value thus obtained is in good agreement with the pore dimension obtained from powder X-ray diffraction measurements. The principle of the calculation as well as problems associated are discussed in detail.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Evaluation of three different adhesive systems using a bacterial method to develop secondary caries in vitro

Purpose: To assess the effects of three different dental adhesive systems on the formation of secondary root caries, in vitro, with a standardized interfacial gap in a filled cavity model. Methods: 40 sound human molars were selected and randomly assigned to four experimental groups: Clearfil SE Bond (CSEB), Xeno III (X-III), Scotchbond Multi-Purpose Plus (SBMP) and negative control (NC) without an adhesive system. After the standardized Class V cavity preparations on the buccal and lingual surfaces, restorations were placed with resin composite (Filtek Z250) using a standardized interfacial gap, using a 3 x 2 mm piece of 50 mu m metal matrix. The teeth were sterilized with gamma irradiation and exposed to a cariogenic challenge using a bacterial system with Streptococcus mutans. Depth and extension of wall lesions formed and the depth of outer lesions were measured by software coupled with light microscopy. Results: For wall lesion extension the ANOVA test showed differences between groups except between X-HI and SBMP (P= 0.294). The Tukey`s test of confidence intervals indicated smaller values for the CSEB group than for the others. For wall lesion depth the CSEB group also presented the smallest mean values of wall lesion depth when compared to the others (P< 0.0001) for all comparisons using Tukey`s test. Regarding outer lesion depth, all adhesives showed statistically similar behavior. SEM evaluation of the morphologic appearance of caries lesions confirmed the statistical results showing small caries lesion development for cavities restored with CSEB adhesive system, which may suggest that this adhesive system interdiffusion zone promoted a good interaction with subjacent dentin protecting the dental tissues from recurrent caries. (Am J Dent 2010;23:93-97).

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.