Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Estudo comparativo de métodos para a determinação da concentração de carbono em solos com altos teores de Fe (Latossolos)

Soil organic matter (SOM) plays an important role in physical, chemical and biological properties of soil. Therefore, the amount of SOM is important for soil management for sustainable agriculture. The objective of this work was to evaluate the amount of SOM in oxisols by different methods and compare them, using principal component analysis, regarding their limitations. The methods used in this work were Walkley-Black, elemental analysis, total organic carbon (TOC) and thermogravimetry. According to our results, TOC and elemental analysis were the most satisfactory methods for carbon quantification, due to their better accuracy and reproducibility.

Fossil groups in the Millennium Simulation Evolution of the brightest galaxies

Aims. We create a catalogue of simulated fossil groups and study their properties, in particular the merging histories of their first-ranked galaxies. We compare the simulated fossil group properties with those of both simulated non-fossil and observed fossil groups. Methods. Using simulations and a mock galaxy catalogue, we searched for massive (>5 x 10(13) h(-1) M-circle dot) fossil groups in the Millennium Simulation Galaxy Catalogue. In addition, we attempted to identify observed fossil groups in the Sloan Digital Sky Survey Data Release 6 using identical selection criteria. Results. Our predictions on the basis of the simulation data are: (a) fossil groups comprise about 5.5% of the total population of groups/clusters with masses larger than 5 x 10(13) h(-1) M-circle dot. This fraction is consistent with the fraction of fossil groups identified in the SDSS, after all observational biases have been taken into account; (b) about 88% of the dominant central objects in fossil groups are elliptical galaxies that have a median R-band absolute magnitude of similar to-23.5-5 log h, which is typical of the observed fossil groups known in the literature; (c) first-ranked galaxies of systems with M > 5 x 10(13) h(-1) M-circle dot, regardless of whether they are either fossil or non-fossil, are mainly formed by gas-poor mergers; (d) although fossil groups, in general, assembled most of their virial masses at higher redshifts in comparison with non-fossil groups, first-ranked galaxies in fossil groups merged later, i.e. at lower redshifts, compared with their non-fossil-group counterparts. Conclusions. We therefore expect to observe a number of luminous galaxies in the centres of fossil groups that show signs of a recent major merger.

Fossil groups in the Millennium simulation Their environment and its evolution

Context. Fossil systems are defined to be X- ray bright galaxy groups ( or clusters) with a two- magnitude difference between their two brightest galaxies within half the projected virial radius, and represent an interesting extreme of the population of galaxy agglomerations. However, the physical conditions and processes leading to their formation are still poorly constrained. Aims. We compare the outskirts of fossil systems with that of normal groups to understand whether environmental conditions play a significant role in their formation. We study the groups of galaxies in both, numerical simulations and observations. Methods. We use a variety of statistical tools including the spatial cross- correlation function and the local density parameter Delta(5) to probe differences in the density and structure of the environments of "" normal"" and "" fossil"" systems in the Millennium simulation. Results. We find that the number density of galaxies surrounding fossil systems evolves from greater than that observed around normal systems at z = 0.69, to lower than the normal systems by z = 0. Both fossil and normal systems exhibit an increment in their otherwise radially declining local density measure (Delta(5)) at distances of order 2.5 r(vir) from the system centre. We show that this increment is more noticeable for fossil systems than normal systems and demonstrate that this difference is linked to the earlier formation epoch of fossil groups. Despite the importance of the assembly time, we show that the environment is different for fossil and non- fossil systems with similar masses and formation times along their evolution. We also confirm that the physical characteristics identified in the Millennium simulation can also be detected in SDSS observations. Conclusions. Our results confirm the commonly held belief that fossil systems assembled earlier than normal systems but also show that the surroundings of fossil groups could be responsible for the formation of their large magnitude gap.

Kinematic parameters and membership probabilities of open clusters in the Bordeaux PM2000 catalogue

Aims. We derive lists of proper-motions and kinematic membership probabilities for 49 open clusters and possible open clusters in the zone of the Bordeaux PM2000 proper motion catalogue (+ 11 degrees <= delta <= + 18 degrees). We test different parametrisations of the proper motion and position distribution functions and select the most successful one. In the light of those results, we analyse some objects individually. Methods. We differenciate between cluster and field member stars, and assign membership probabilities, by applying a new and fully automated method based on both parametrisations of the proper motion and position distribution functions, and genetic algorithm optimization heuristics associated with a derivative-based hill climbing algorithm for the likelihood optimization. Results. We present a catalogue comprising kinematic parameters and associated membership probability lists for 49 open clusters and possible open clusters in the Bordeaux PM2000 catalogue region. We note that this is the first determination of proper motions for five open clusters. We confirm the non-existence of two kinematic populations in the region of 15 previously suspected non-existent objects.

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.

Hubble parameter reconstruction from a principal component analysis: minimizing the bias

Aims. A model-independent reconstruction of the cosmic expansion rate is essential to a robust analysis of cosmological observations. Our goal is to demonstrate that current data are able to provide reasonable constraints on the behavior of the Hubble parameter with redshift, independently of any cosmological model or underlying gravity theory. Methods. Using type Ia supernova data, we show that it is possible to analytically calculate the Fisher matrix components in a Hubble parameter analysis without assumptions about the energy content of the Universe. We used a principal component analysis to reconstruct the Hubble parameter as a linear combination of the Fisher matrix eigenvectors (principal components). To suppress the bias introduced by the high redshift behavior of the components, we considered the value of the Hubble parameter at high redshift as a free parameter. We first tested our procedure using a mock sample of type Ia supernova observations, we then applied it to the real data compiled by the Sloan Digital Sky Survey (SDSS) group. Results. In the mock sample analysis, we demonstrate that it is possible to drastically suppress the bias introduced by the high redshift behavior of the principal components. Applying our procedure to the real data, we show that it allows us to determine the behavior of the Hubble parameter with reasonable uncertainty, without introducing any ad-hoc parameterizations. Beyond that, our reconstruction agrees with completely independent measurements of the Hubble parameter obtained from red-envelope galaxies.

Is PHEEM a multi-dimensional instrument? An international perspective

Aim: To look at the characteristics of Postgraduate Hospital Educational Environment Measure (PHEEM) using data from the UK, Brazil, Chile and the Netherlands, and to examine the reliability and characteristics of PHEEM, especially how the three PHEEM subscales fitted with factors derived statistically from the data sets. Methods: Statistical analysis of PHEEM scores from 1563 sets of data, using reliability analysis, exploratory factor analysis and correlations of factors derived with the three defined PHEEM subscales. Results: PHEEM was very reliable with an overall Cronbach`s alpha of 0.928. Three factors were derived by exploratory factor analysis. Factor One correlated most strongly with the teaching subscale (R=0.802), Factor Two correlated most strongly with the role autonomy subscale (R=0.623) and Factor Three correlated most strongly with the social support subscale (R=0.538). Conclusions: PHEEM is a multi-dimensional instrument. Overall, it is very reliable. There is a good fit of the three defined subscales, derived by qualitative methods, with the three principal factors derived from the data by exploratory factor analysis.

Diagnostic tool to analyse colour-magnitude diagrams of poorly populated stellar concentrations

The dynamical processes that lead to open cluster disruption cause its mass to decrease. To investigate such processes from the observational point of view, it is important to identify open cluster remnants (OCRs), which are intrinsically poorly populated. Due to their nature, distinguishing them from field star fluctuations is still an unresolved issue. In this work, we developed a statistical diagnostic tool to distinguish poorly populated star concentrations from background field fluctuations. We use 2MASS photometry to explore one of the conditions required for a stellar group to be a physical group: to produce distinct sequences in a colour-magnitude diagram (CMD). We use automated tools to (i) derive the limiting radius; (ii) decontaminate the field and assign membership probabilities; (iii) fit isochrones; and (iv) compare object and field CMDs, considering the isochrone solution, in order to verify the similarity. If the object cannot be statistically considered as a field fluctuation, we derive its probable age, distance modulus, reddening and uncertainties in a self-consistent way. As a test, we apply the tool to open clusters and comparison fields. Finally, we study the OCR candidates DoDz 6, NGC 272, ESO 435 SC48 and ESO 325 SC15. The tool is optimized to treat these low-statistic objects and to separate the best OCR candidates for studies on kinematics and chemical composition. The study of the possible OCRs will certainly provide a deep understanding of OCR properties and constraints for theoretical models, including insights into the evolution of open clusters and dissolution rates.

Cross-entropy optimizer: a new tool to study precession in astrophysical jets

Evidence of jet precession in many galactic and extragalactic sources has been reported in the literature. Much of this evidence is based on studies of the kinematics of the jet knots, which depends on the correct identification of the components to determine their respective proper motions and position angles on the plane of the sky. Identification problems related to fitting procedures, as well as observations poorly sampled in time, may influence the follow-up of the components in time, which consequently might contribute to a misinterpretation of the data. In order to deal with these limitations, we introduce a very powerful statistical tool to analyse jet precession: the cross-entropy method for continuous multi-extremal optimization. Only based on the raw data of the jet components (right ascension and declination offsets from the core), the cross-entropy method searches for the precession model parameters that better represent the data. In this work we present a large number of tests to validate this technique, using synthetic precessing jets built from a given set of precession parameters. With the aim of recovering these parameters, we applied the cross-entropy method to our precession model, varying exhaustively the quantities associated with the method. Our results have shown that even in the most challenging tests, the cross-entropy method was able to find the correct parameters within a 1 per cent level. Even for a non-precessing jet, our optimization method could point out successfully the lack of precession.

MODELING VERY LONG BASELINE INTERFEROMETRIC IMAGES WITH THE CROSS-ENTROPY GLOBAL OPTIMIZATION TECHNIQUE

We present a new technique for obtaining model fittings to very long baseline interferometric images of astrophysical jets. The method minimizes a performance function proportional to the sum of the squared difference between the model and observed images. The model image is constructed by summing N(s) elliptical Gaussian sources characterized by six parameters: two-dimensional peak position, peak intensity, eccentricity, amplitude, and orientation angle of the major axis. We present results for the fitting of two main benchmark jets: the first constructed from three individual Gaussian sources, the second formed by five Gaussian sources. Both jets were analyzed by our cross-entropy technique in finite and infinite signal-to-noise regimes, the background noise chosen to mimic that found in interferometric radio maps. Those images were constructed to simulate most of the conditions encountered in interferometric images of active galactic nuclei. We show that the cross-entropy technique is capable of recovering the parameters of the sources with a similar accuracy to that obtained from the very traditional Astronomical Image Processing System Package task IMFIT when the image is relatively simple (e. g., few components). For more complex interferometric maps, our method displays superior performance in recovering the parameters of the jet components. Our methodology is also able to show quantitatively the number of individual components present in an image. An additional application of the cross-entropy technique to a real image of a BL Lac object is shown and discussed. Our results indicate that our cross-entropy model-fitting technique must be used in situations involving the analysis of complex emission regions having more than three sources, even though it is substantially slower than current model-fitting tasks (at least 10,000 times slower for a single processor, depending on the number of sources to be optimized). As in the case of any model fitting performed in the image plane, caution is required in analyzing images constructed from a poorly sampled (u, v) plane.

DETECTABILITY AND ERROR ESTIMATION IN ORBITAL FITS OF RESONANT EXTRASOLAR PLANETS

We estimate the conditions for detectability of two planets in a 2/1 mean-motion resonance from radial velocity data, as a function of their masses, number of observations and the signal-to-noise ratio. Even for a data set of the order of 100 observations and standard deviations of the order of a few meters per second, we find that Jovian-size resonant planets are difficult to detect if the masses of the planets differ by a factor larger than similar to 4. This is consistent with the present population of real exosystems in the 2/1 commensurability, most of which have resonant pairs with similar minimum masses, and could indicate that many other resonant systems exist, but are currently beyond the detectability limit. Furthermore, we analyze the error distribution in masses and orbital elements of orbital fits from synthetic data sets for resonant planets in the 2/1 commensurability. For various mass ratios and number of data points we find that the eccentricity of the outer planet is systematically overestimated, although the inner planet`s eccentricity suffers a much smaller effect. If the initial conditions correspond to small-amplitude oscillations around stable apsidal corotation resonances, the amplitudes estimated from the orbital fits are biased toward larger amplitudes, in accordance to results found in real resonant extrasolar systems.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Lie algebra methods for the applications to the statistical theory of turbulence

Approximate Lie symmetries of the Navier-Stokes equations are used for the applications to scaling phenomenon arising in turbulence. In particular, we show that the Lie symmetries of the Euler equations are inherited by the Navier-Stokes equations in the form of approximate symmetries that allows to involve the Reynolds number dependence into scaling laws. Moreover, the optimal systems of all finite-dimensional Lie subalgebras of the approximate symmetry transformations of the Navier-Stokes are constructed. We show how the scaling groups obtained can be used to introduce the Reynolds number dependence into scaling laws explicitly for stationary parallel turbulent shear flows. This is demonstrated in the framework of a new approach to derive scaling laws based on symmetry analysis [11]-[13].

Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans. The average 5-year survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, HNSCC has a good prognosis, but most patients present metastatic disease at the time of diagnosis, which significantly reduces survival rate. Despite extensive research, no molecular markers are currently available for diagnostic or prognostic purposes. Methods: Aiming to identify differentially-expressed genes involved in laryngeal squamous cell carcinoma (LSCC) development and progression, we generated individual Serial Analysis of Gene Expression (SAGE) libraries from a metastatic and non-metastatic larynx carcinoma, as well as from a normal larynx mucosa sample. Approximately 54,000 unique tags were sequenced in three libraries. Results: Statistical data analysis identified a subset of 1,216 differentially expressed tags between tumor and normal libraries, and 894 differentially expressed tags between metastatic and non-metastatic carcinomas. Three genes displaying differential regulation, one down-regulated (KRT31) and two up-regulated (BST2, MFAP2), as well as one with a non-significant differential expression pattern (GNA15) in our SAGE data were selected for real-time polymerase chain reaction (PCR) in a set of HNSCC samples. Consistent with our statistical analysis, quantitative PCR confirmed the upregulation of BST2 and MFAP2 and the downregulation of KRT31 when samples of HNSCC were compared to tumor-free surgical margins. As expected, GNA15 presented a non-significant differential expression pattern when tumor samples were compared to normal tissues. Conclusion: To the best of our knowledge, this is the first study reporting SAGE data in head and neck squamous cell tumors. Statistical analysis was effective in identifying differentially expressed genes reportedly involved in cancer development. The differential expression of a subset of genes was confirmed in additional larynx carcinoma samples and in carcinomas from a distinct head and neck subsite. This result suggests the existence of potential common biomarkers for prognosis and targeted-therapy development in this heterogeneous type of tumor.