The Brera Multi-scale Wavelet (BMW) ROSAT HRI source catalog. I: the algorithm

We present a new detection algorithm based on the wavelet transform for the analysis of high energy astronomical images. The wavelet transform, due to its multi-scale structure, is suited for the optimal detection of point-like as well as extended sources, regardless of any loss of resolution with the off-axis angle. Sources are detected as significant enhancements in the wavelet space, after the subtraction of the non-flat components of the background. Detection thresholds are computed through Monte Carlo simulations in order to establish the expected number of spurious sources per field. The source characterization is performed through a multi-source fitting in the wavelet space. The procedure is designed to correctly deal with very crowded fields, allowing for the simultaneous characterization of nearby sources. To obtain a fast and reliable estimate of the source parameters and related errors, we apply a novel decimation technique which, taking into account the correlation properties of the wavelet transform, extracts a subset of almost independent coefficients. We test the performance of this algorithm on synthetic fields, analyzing with particular care the characterization of sources in poor background situations, where the assumption of Gaussian statistics does not hold. For these cases, where standard wavelet algorithms generally provide underestimated errors, we infer errors through a procedure which relies on robust basic statistics. Our algorithm is well suited for the analysis of images taken with the new generation of X-ray instruments equipped with CCD technology which will produce images with very low background and/or high source density.Comment: 8 pages, 6 figures, ApJ in pres

Study of the Correlation among Luminous Properties of Smart Glazing for Adaptive Energy Saving Buildings

A smart window, such as electrochromic or thermochromic windows, may not be able to accomplish at the same time energy efficiency and visual comfort functions, since satisfying one criterium interferes with the other. This recalls to the important issue of establishing precise relationships among parameters affecting energy, glare control, and color rendering tasks and the influence on them of glazing material composition and preparation technique. With this aim, the luminous properties of a number of advanced glazings found in literature and of three home-made electrochromic devices differing by material composition and/or preparation technique are analyzed in this study. The investigation has involved the determination of the CIE (Commission International de l'Eclairage) Color Rendering Index (CIE CRI), the Correlated Color Temperature (CCT), and the luminous transmittance coefficient (tau(V)) of the devices which are discussed with regard to their potential in absolving to energy and visual comfort tasks. Results lead to the main conclusion that the CIE CRI, CCT, and tau(V) indexes are clearly linked by an exponential correlation. At low tau(V) values (tau(V) < 0.5), however, the correlation weakens and the variation of the CIE CRI and CCT indexes becomes entirely material dependent. The influence of preparation technique appears to be irrelevant since the color rendering indexes appear to be well correlated to tau(V) over all the investigated tau(V) range

Circular local likelihood

We introduce a class of local likelihood circular density estimators, which includes the kernel density estimator as a special case. The idea lies in optimizing a spatially weighted version of the log-likelihood function, where the logarithm of the density is locally approximated by a periodic polynomial. The use of von Mises density functions as weights reduces the computational burden. Also, we propose closed-form estimators which could form the basis of counterparts in the multidimensional Euclidean setting. Simulation results and a real data case study are used to evaluate the performance and illustrate the results

Object-based representation and analysis of light and electron microscopic volume data using Blender

This is the final version of the article. Available from the publisher via the DOI in this record.BACKGROUND: Rapid improvements in light and electron microscopy imaging techniques and the development of 3D anatomical atlases necessitate new approaches for the visualization and analysis of image data. Pixel-based representations of raw light microscopy data suffer from limitations in the number of channels that can be visualized simultaneously. Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze. RESULTS: Here we exploit the advanced visualization capabilities and flexibility of the open-source platform Blender to visualize and analyze anatomical atlases. We use light-microscopy-based gene expression atlases and electron microscopy connectome volume data from larval stages of the marine annelid Platynereis dumerilii. We build object-based larval gene expression atlases in Blender and develop tools for annotation and coexpression analysis. We also represent and analyze connectome data including neuronal reconstructions and underlying synaptic connectivity. CONCLUSIONS: We demonstrate the power and flexibility of Blender for visualizing and exploring complex anatomical atlases. The resources we have developed for Platynereis will facilitate data sharing and the standardization of anatomical atlases for this species. The flexibility of Blender, particularly its embedded Python application programming interface, means that our methods can be easily extended to other organisms.The research leading to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/European Research Council Grant Agreement 260821

A note on nonparametric estimation of circular conditional densities

The conditional density offers the most informative summary of the relationship between explanatory and response variables. We need to estimate it in place of the simple conditional mean when its shape is not well-behaved. A motivation for estimating conditional densities, specific to the circular setting, lies in the fact that a natural alternative of it, like quantile regression, could be considered problematic because circular quantiles are not rotationally equivariant. We treat conditional density estimation as a local polynomial fitting problem as proposed by \cite{Fan et al.:1996} in the euclidean setting, and discuss a class of estimators in the cases when the conditioning variable is either circular or linear. Asymptotic properties for some members of the proposed class are derived. The effectiveness of the methods for finite sample sizes is illustrated by simulation experiments and an example using real data

Nonparametric estimating equations for circular probability density functions and their derivatives

We propose estimating equations whose unknown parameters are the values taken by a circular density and its derivatives at a point. Specifically, we solve equations which relate local versions of population trigonometric moments with their sample counterparts. Major advantages of our approach are: higher order bias without asymptotic variance inflation, closed form for the estimators, and absence of numerical tasks. We also investigate situations where the observed data are dependent. Theoretical results along with simulation experiments are provided

The BMW (Brera-Multiscale-Wavelet) Catalogue of Serendipitous X-ray Sources

In collaboration with the Observatories of Palermo and Rome and the SAX-SDC we are constructing a multi-site interactive archive system featuring specific analysis tools. In this context we developed a detection algorithm based on the Wavelet Transform (WT) and performed a systematic analysis of all ROSAT-HRI public data (~3100 observations +1000 to come). The WT is specifically suitable to detect and characterize extended sources while properly detecting point sources in very crowded fields. Moreover, the good angular resolution of HRI images allows the source extension and position to be accurately determined. This effort has produced the BMW (Brera Multiscale Wavelet) catalogue, with more than 19,000 sources detected at the 4.2 sigma level. For each source detection we have information on the X-ray flux and extension, allowing for instance to select complete samples of extended X-ray sources such as candidate clusters of galaxies or SNR's. Here we present an overview of first results from several undergoing projects which make use of the BMW catalogue.Comment: 7 pages, 6 postscript files, 2 gif images, to appear in the proceedings of the conference "Mining the Sky", August 2000, Garching, German

The BMW Deep X-ray Cluster Survey

We briefly describe the main features of the Brera Multi-Wavelet (BMW) survey of serendipitous X-ray clusters, based on the still unexploited ROSAT-HRI archival observations. Cluster candidates are selected from the general BMW catalogue of 20,000 sources based exclusively on their X-ray extension. Contrary to common wisdom, a clever selection of the HRI energy channels allows us to significantly reduce the background noise, thus greatly improving the ability to detect low surface-brightness sources as clusters. The resulting sample of ~250 candidates shows a very good sky coverage down to a flux \~3x10^-14 erg/s/cm^2 ([0.5-2.0] keV band), i.e comparable to existing PSPC-based deep survey, with a particularly interesting area of ~100 sq.deg. around fluxes ~10^-13 erg/s/cm^2, i.e. where highly-luminous, rare systems at z~0.6-1 can be detected. At the same time, the superior angular resolution of the instrument should avoid biases against intrinsically small systems, while easing the identification process (e.g. by spotting blends and AGN contaminants). While about 20% of the candidates are already identified with groups/clusters at z<0.3 on the DSS2 images, we have started a deep CCD imaging campaign to observe all sources associated to "blank fields". First results from these observations reveal a distant (z>0.5) bonafide cluster counterpart for ~80% of the targets.Comment: 3 pages, 2 figures; to appear in Proc. of the ESO/ECF/STSCI workshop on "Deep Fields", Garching Oct 2000, (Publ: Springer

Serum proteins profile in Comisana lambs during the first month of life

Abstract. The aim of the present study was to measure the serum total proteins and the serum protein fractions (albumin, α1-, α2-, β-, and γ- globulins) of ten newborn lambs (Comisana breed) during the first 30 days of life in order to obtain useful information for neonatal care. From each animal, blood samples were collected via jugular venipuncture at the same hour (9.00) every 3 days for 30 days starting from birth (day 0). The concentrations of serum total proteins and albumin, α1-, α2-, β-, γ- globulins, and Albumin/Globulins (A/G) ratio were determined using an automated electrophoresis system. One-way repeated measures analysis of variance (ANOVA), followed by Bonferroni's test, was used to determine significant differences between mean values of the studied parameters from the 1st to the 30th day of the experimental period. Data analysis of variance showed a statistical effect of days of life on total proteins, albumin, α1-globulins, β-globulins, γ-globulins and ratio A/G during the first 30 days of life (P<0.0001), while no statistical significant effect of days of life was observed on α2-globulins during the experimental period (P=0.27). The obtained results indicated that passive transfer status, determined from serum immunoglobulin concentration 24 hours after birth, is a significant source of variation in preweaning growth performance in dairy lambs. These finding make a contribution to the knowledge of physiological adaptation in lambs during the first 30 days of life and give useful information for the diagnosis and treatment of neonatal diseases