A SEARCH FOR UNRECOGNIZED CARBON-ENHANCED METAL-POOR STARS IN THE GALAXY

We have developed a new procedure to search for carbon-enhanced metal-poor (CEMP) stars from the Hamburg/ESO (HES) prism-survey plates. This method employs an extended line index for the CH G band, which we demonstrate to have superior performance when compared to the narrower G-band index formerly employed to estimate G-band strengths for these spectra. Although CEMP stars have been found previously among candidate metal-poor stars selected from the HES, the selection on metallicity undersamples the population of intermediate-metallicity CEMP stars (-2.5 <= [Fe/H] <= -1.0); such stars are of importance for constraining the onset of the s-process in metal-deficient asymptotic giant branch stars (thought to be associated with the origin of carbon for roughly 80% of CEMP stars). The new candidates also include substantial numbers of warmer carbon-enhanced stars, which were missed in previous HES searches for carbon stars due to selection criteria that emphasized cooler stars. A first subsample, biased toward brighter stars (B < 15.5), has been extracted from the scanned HES plates. After visual inspection (to eliminate spectra compromised by plate defects, overlapping spectra, etc., and to carry out rough spectral classifications), a list of 669 previously unidentified candidate CEMP stars was compiled. Follow-up spectroscopy for a pilot sample of 132 candidates was obtained with the Goodman spectrograph on the SOAR 4.1 m telescope. Our results show that most of the observed stars lie in the targeted metallicity range, and possess prominent carbon absorption features at 4300 angstrom. The success rate for the identification of new CEMP stars is 43% (13 out of 30) for [Fe/H] < -2.0. For stars with [Fe/H] < -2.5, the ratio increases to 80% (four out of five objects), including one star with [Fe/H] < -3.0.

Near infrared polarimetry of a sample of YSOs

Aims. Our goal is to study the physical properties of the circumstellar environment of young stellar objetcs (YSOs). In particular, the determination of the scattering mechanism can help us to constrain the optical depth of the disk and/or envelope in the near infrared. Methods. We used the IAGPOL imaging polarimeter along with the CamIV infrared camera at the LNA observatory to obtain near infrared polarimetry measurements in the H band of a sample of optically visible YSOs, namely, eleven T Tauri stars and eight Herbig Ae/Be stars. An independent determination of the disk (or jet) orientation was obtained for twelve objects from the literature. The circumstellar optical depth could then be estimated by comparing the integrated polarization position angle (PA) with the direction of the major axis of the disk projected onto the plane of the sky. Optically thin disks have, in general, a polarization PA that is perpendicular to the disk plane. In contrast, optically thick disks have polarization PAs parallel to the disks. Results. Among the T Tauri stars, three are consistent with having optically thin disks (AS 353A, RY Tau and UY Aur) and five with optically thick disks (V536 Aql, DG Tau, DO Tau, HL Tau and LkH alpha 358). Among the Herbig Ae/Be stars, two stars exhibit evidence of optically thin disks (Hen 3-1191 and VV Ser) and two of optically thick disks (PDS 453 and MWC 297). Our results seem consistent with optically thick disks at near infrared bands, which are more likely to be associated with younger YSOs. Marginal evidence of polarization reversal is found in RY Tau, RY Ori, WW Vul, and UY Aur. In the first three cases, this feature can be associated with the UXOR phenomenon. Correlations with the IRAS colors and the spectral index yielded evidence of an evolutionary segregation in which the disks tend to be optically thin when they are older.

Galaxy distribution and evolution around a sample of 2dF groups

Context. We study galaxy evolution and spatial patterns in the surroundings of a sample of 2dF groups. Aims. Our aim is to find evidence of galaxy evolution and clustering out to 10 times the virial radius of the groups and so redefine their properties according to the spatial patterns in the fields and relate them to galaxy evolution. Methods. Group members and interlopers were redefined after the identification of gaps in the redshift distribution. We then used exploratory spatial statistics based on the the second moment of the Ripley function to probe the anisotropy in the galaxy distribution around the groups. Results. We found an important anticorrelation between anisotropy around groups and the fraction of early-type galaxies in these fields. Our results illustrate how the dynamical state of galaxy groups can be ascertained by the systematic study of their neighborhoods. This is an important achievement, since the correct estimate of the extent to which galaxies are affected by the group environment and follow large-scale filamentary structure is relevant to understanding the process of galaxy clustering and evolution in the Universe.

SMALL MAMMAL PREY SELECTION BY TWO OWL SPECIES IN SOUTHEASTERN BRAZIL

A variety of factors influence prey selection by predators. Because Barn Owls (Tyto alba) and Burrowing Owls (Athene cunicularia) differ in size and foraging tactics, we expected differential predation on small mammal prey. We hypothesized that the Barn Owl, all active predator, would prey on smaller and younger individuals than the Burrowing Owl, a sit-and-wait predator. We used pellet analyses to evaluate selection of small mammals by the two owls in relation to prey), species, age, and size at the Ecological Station of Itirapina, state of Sao Paulo, in southeastern Brazil. Small mammals constituted most of the prey individuals and biomass in the diet of Barn Owls. Although Burrowing Owls consumed a wider range of taxa, small mammals represented one-third of all biomass consumed. With respect. to small mammals, Barn Owls foraged selectively relative to prey species, size, and age. Burrowing Owls foraged opportunistically relative to prey species, but selectively relative to prey size and age. Barn Owls selected smaller and younger (juvenile and subadult) individuals of the delicate vesper mouse (Calomys tener) and Burrowing Owls preyed more oil larger and older (subadult only) individuals. morphology and behavior of both prey and predators may explain this differential predation. Our data suggest that the active predator feeds oil smaller and younger prey, and the sit-and-wait predator took relatively larger and older prey.

Phylogenetic nomenclature and evolution of mannose-binding lectin (MBL2) haplotypes

Background: Polymorphisms of the mannose-binding lectin gene (MBL2) affect the concentration and functional efficiency of the protein. We recently used haplotype-specific sequencing to identify 23 MBL2 haplotypes, associated with enhanced susceptibility to several diseases. Results: In this work, we applied the same method in 288 and 470 chromosomes from Gabonese and European adults, respectively, and found three new haplotypes in the last group. We propose a phylogenetic nomenclature to standardize MBL2 studies and found two major phylogenetic branches due to six strongly linked polymorphisms associated with high MBL production. They presented high Fst values and were imbedded in regions with high nucleotide diversity and significant Tajima's D values. Compared to others using small sample sizes and unphased genotypic data, we found differences in haplotyping, frequency estimation, Fu and Li's D* and Fst results. Conclusion: Using extensive testing for selective neutrality, we confirmed that stochastic evolutionary factors have had a major role in shaping this polymorphic gene worldwide.

Diversification and Species Boundaries of Rhinebothrium (Cestoda; Rhinebothriidea) in South American Freshwater Stingrays (Batoidea; Potamotrygonidae)

Background: Neotropical freshwater stingrays (Batoidea: Potamotrygonidae) host a diverse parasite fauna, including cestodes. Both cestodes and their stingray hosts are marine-derived, but the taxonomy of this host/parasite system is poorly understood. Methodology: Morphological and molecular (Cytochrome oxidase I) data were used to investigate diversity in freshwater lineages of the cestode genus Rhinebothrium Linton, 1890. Results were based on a phylogenetic hypothesis for 74 COI sequences and morphological analysis of over 400 specimens. Cestodes studied were obtained from 888 individual potamotrygonids, representing 14 recognized and 18 potentially undescribed species from most river systems of South America. Results: Morphological species boundaries were based mainly on microthrix characters observed with scanning electron microscopy, and were supported by COI data. Four species were recognized, including two redescribed (Rhinebothrium copianullum and R. paratrygoni), and two newly described (R. brooksi n. sp. and R. fulbrighti n. sp.). Rhinebothrium paranaensis Menoret & Ivanov, 2009 is considered a junior synonym of R. paratrygoni because the morphological features of the two species overlap substantially. The diagnosis of Rhinebothrium Linton, 1890 is emended to accommodate the presence of marginal longitudinal septa observed in R. copianullum and R. brooksi n. sp. Patterns of host specificity and distribution ranged from use of few host species in few river basins, to use of as many as eight host species in multiple river basins. Significance: The level of intra-specific morphological variation observed in features such as total length and number of proglottids is unparalleled among other elasmobranch cestodes. This is attributed to the large representation of host and biogeographical samples. It is unclear whether the intra-specific morphological variation observed is unique to this freshwater system. Nonetheless, caution is urged when using morphological discontinuities to delimit elasmobranch cestode species because the amount of variation encountered is highly dependent on sample size and/or biogeographical representation.

Positive Selection Results in Frequent Reversible Amino Acid Replacements in the G Protein Gene of Human Respiratory Syncytial Virus

Human respiratory syncytial virus (HRSV) is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a ""flipflop'' phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.

Genetic variability and natural selection at the ligand domain of the Duffy binding protein in brazilian Plasmodium vivax populations

Background: Plasmodium vivax malaria is a major public health challenge in Latin America, Asia and Oceania, with 130-435 million clinical cases per year worldwide. Invasion of host blood cells by P. vivax mainly depends on a type I membrane protein called Duffy binding protein (PvDBP). The erythrocyte-binding motif of PvDBP is a 170 amino-acid stretch located in its cysteine-rich region II (PvDBP(II)), which is the most variable segment of the protein. Methods: To test whether diversifying natural selection has shaped the nucleotide diversity of PvDBP(II) in Brazilian populations, this region was sequenced in 122 isolates from six different geographic areas. A Bayesian method was applied to test for the action of natural selection under a population genetic model that incorporates recombination. The analysis was integrated with a structural model of PvDBP(II), and T-and B-cell epitopes were localized on the 3-D structure. Results: The results suggest that: (i) recombination plays an important role in determining the haplotype structure of PvDBP(II), and (ii) PvDBP(II) appears to contain neutrally evolving codons as well as codons evolving under natural selection. Diversifying selection preferentially acts on sites identified as epitopes, particularly on amino acid residues 417, 419, and 424, which show strong linkage disequilibrium. Conclusions: This study shows that some polymorphisms of PvDBP(II) are present near the erythrocyte-binding domain and might serve to elude antibodies that inhibit cell invasion. Therefore, these polymorphisms should be taken into account when designing vaccines aimed at eliciting antibodies to inhibit erythrocyte invasion.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

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.

Improving sample representativeness in environmental studies: a major component for the uncertainty budget

For environmental quality assessment, INAA has been applied for determining chemical elements in small (200 mg) and large (200 g) samples of leaves from 200 trees. By applying the Ingamells` constant, the expected percent standard deviation was estimated in 0.9-2.2% for 200 mg samples. Otherwise, for composite samples (200 g), expected standard deviation varied from 0.5 to 10% in spite of analytical uncertainties ranging from 2 to 30%. Results thereby suggested the expression of the degree of representativeness as a source of uncertainty, contributing for increasing of the reliability of environmental studies mainly in the case of composite samples.

Total carbon measurement in whole tropical soil sample

Soils are an important component in the biogeochemical cycle of carbon, storing about four times more carbon than biomass plants and nearly three times more than the atmosphere. Moreover, the carbon content is directly related on the capacity of water retention, fertility. among other properties. Thus, soil carbon quantification in field conditions is an important challenge related to carbon cycle and global climatic changes. Nowadays. Laser Induced Breakdown Spectroscopy (LIBS) can be used for qualitative elemental analyses without previous treatment of samples and the results are obtained quickly. New optical technologies made possible the portable LIBS systems and now, the great expectation is the development of methods that make possible quantitative measurements with LIBS. The goal of this work is to calibrate a portable LIBS system to carry out quantitative measures of carbon in whole tropical soil sample. For this, six samples from the Brazilian Cerrado region (Argisoil) were used. Tropical soils have large amounts of iron in their compositions, so the carbon line at 247.86 nm presents strong interference of this element (iron lines at 247.86 and 247.95). For this reason, in this work the carbon line at 193.03 nm was used. Using methods of statistical analysis as a simple linear regression, multivariate linear regression and cross-validation were possible to obtain correlation coefficients higher than 0.91. These results show the great potential of using portable LIBS systems for quantitative carbon measurements in tropical soils. (C) 2008 Elsevier B.V. All rights reserved.

Assessing sample representativeness for inorganic chemical investigation of invertebrates by INAA

The quality of environmental studies depends on the utilization of adequate sampling protocol and analytical method for obtaining reliable results and minimizing analytical uncertainties. In order to demonstrate the applicability of INAA for determining chemical element composition of invertebrates, this work evaluated sample representativeness in terms of subsampling and sample size. Br, Co, Fe, K, Na, Sc and Zn could be determined in very small samples despite increasing of analytical uncertainties. Special attention should be directed to invertebrate species with small structures because of the high chemical variation observed among different sample sizes tested.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.