Catalog of quasars from the Kilo-Degree Survey Data Release 3

We present a catalog of quasars selected from broad-band photometric ugri data of the Kilo-Degree Survey Data Release 3 (KiDS DR3). The QSOs are identified by the random forest (RF) supervised machine learning model, trained on SDSS DR14 spectroscopic data. We first cleaned the input KiDS data from entries with excessively noisy, missing or otherwise problematic measurements. Applying a feature importance analysis, we then tune the algorithm and identify in the KiDS multiband catalog the 17 most useful features for the classification, namely magnitudes, colors, magnitude ratios, and the stellarity index. We used the t-SNE algorithm to map the multi-dimensional photometric data onto 2D planes and compare the coverage of the training and inference sets. We limited the inference set to r<22 to avoid extrapolation beyond the feature space covered by training, as the SDSS spectroscopic sample is considerably shallower than KiDS. This gives 3.4 million objects in the final inference sample, from which the random forest identified 190,000 quasar candidates. Accuracy of 97%, purity of 91%, and completeness of 87%, as derived from a test set extracted from SDSS and not used in the training, are confirmed by comparison with external spectroscopic and photometric QSO catalogs overlapping with the KiDS footprint. The robustness of our results is strengthened by number counts of the quasar candidates in the r band, as well as by their mid-infrared colors available from WISE. An analysis of parallaxes and proper motions of our QSO candidates found also in Gaia DR2 suggests that a probability cut of p(QSO)>0.8 is optimal for purity, whereas p(QSO)>0.7 is preferable for better completeness. Our study presents the first comprehensive quasar selection from deep high-quality KiDS data and will serve as the basis for versatile studies of the QSO population detected by this survey.Comment: Data available from the KiDS website at http://kids.strw.leidenuniv.nl/DR3/quasarcatalog.php and the source code from https://github.com/snakoneczny/kids-quasar

Morphometric parameters of cardiac implantable electronic device (CIED) pocket walls observed on device replacement

Background: The final stage of a conventional de-novo cardiac implantable electronic device (CIED) implantation procedure with transvenous lead insertion involves the formation of a pocket by tissue separation superficial to the pectoralis major muscle in the right or left infraclavicular region, where the device is subsequently placed. Over time, a scar “capsule” is formed around the CIED as a result of normal biological remodelling. Materials and methods: The purpose of this study was to analyse the structure and present the variations of CIED capsules observed during device replacement. The nature and extent of this local tissue remodelling, which had occurred from the time of device implantation to its replacement in 2016 (10 ± 3.1 years), was analysed in 100 patients (mean age 77.1 ± 14.5 years), including 45 women and 55 men. Results: The most prevalent types of “capsules” (70% of cases) were those with similar thickness of both walls or a slightly thicker posterior (&lt; 1.0 mm) than anterior wall (&lt; 0.5 mm). The second most common capsule type (23% of cases) was characterised by a significantly thicker posterior wall of scar tissue (&gt; 1.0 mm). The third group of capsules was characterised by various degrees of wall calcification (7% of cases). Conclusions: The extent and nature of scar tissue structure in the CIED pocket walls seem to correlate with the relative position of cardiac lead loops with respect to the device itself; where the more extensive scarring is likely to result from pocket wall irritation in the capsule formation phase due to lead movements underneath the device. The group of cases with calcified capsules was characterised by “old” device pockets (&gt; 13 years) and the oldest population (patients in their 80s and 90s)

Catalog of quasars from the Kilo-Degree Survey Data Release 3

We present a catalog of quasars selected from broad-band photometric ugri data of the Kilo-Degree Survey Data Release 3 (KiDS DR3). The QSOs are identified by the random forest (RF) supervised machine learning model, trained on Sloan Digital Sky Survey (SDSS) DR14 spectroscopic data. We first cleaned the input KiDS data of entries with excessively noisy, missing or otherwise problematic measurements. Applying a feature importance analysis, we then tune the algorithm and identify in the KiDS multiband catalog the 17 most useful features for the classification, namely magnitudes, colors, magnitude ratios, and the stellarity index. We used the t-SNE algorithm to map the multidimensional photometric data onto 2D planes and compare the coverage of the training and inference sets. We limited the inference set to r 0.8 is optimal for purity, whereas pQSO > 0.7 is preferable for better completeness. Our study presents the first comprehensive quasar selection from deep high-quality KiDS data and will serve as the basis for versatile studies of the QSO population detected by this survey

The AMANDA Neutrino Telescope and the Indirect Search for Dark Matter

With an effective telescope area of order 10^4 m^2, a threshold of ~50 GeV and a pointing accuracy of 2.5 degrees, the AMANDA detector represents the first of a new generation of high energy neutrino telescopes, reaching a scale envisaged over 25 years ago. We describe its performance, focussing on the capability to detect halo dark matter particles via their annihilation into neutrinos.Comment: Latex2.09, 16 pages, uses epsf.sty to place 15 postscript figures. Talk presented at the 3rd International Symposium on Sources and Detection of Dark Matter in the Universe (DM98), Santa Monica, California, Feb. 199

The AMANDA Neutrino Telescope: Principle of Operation and First Results

AMANDA is a high-energy neutrino telescope presently under construction at the geographical South Pole. In the Antarctic summer 1995/96, an array of 80 optical modules (OMs) arranged on 4 strings (AMANDA-B4) was deployed at depths between 1.5 and 2 km. In this paper we describe the design and performance of the AMANDA-B4 prototype, based on data collected between February and November 1996. Monte Carlo simulations of the detector response to down-going atmospheric muon tracks show that the global behavior of the detector is understood. We describe the data analysis method and present first results on atmospheric muon reconstruction and separation of neutrino candidates. The AMANDA array was upgraded with 216 OMs on 6 new strings in 1996/97 (AMANDA-B10), and 122 additional OMs on 3 strings in 1997/98.Comment: 36 pages, 23 figures, submitted to Astroparticle Physic

VIPERS: An Unprecedented View of Galaxies and Large-Scale Structure Halfway Back in the Life of the Universe

The VIMOS Public Extragalactic Redshift Survey (VIPERS) is an ongoing ESO Large Programme to map in detail the large-scale distribution of galaxies at 0.5 < z <1.2. With a combination of volume and sampling density that is unique for these redshifts, it focuses on measuring galaxy clustering and related cosmological quantities as part of the grand challenge of understanding the origin of cosmic acceleration. VIPERS has also been designed to guarantee a broader legacy, allowing detailed investigations of the properties and evolutionary trends of z~1 galaxies. The survey strategy exploits the specific advantages of the VIMOS spectrograph at the VLT, aiming at a final sample of nearly 100,000 galaxy redshifts to iAB = 22.5 mag, which represents the largest redshift survey ever performed with ESO telescopes. In this introductory article we describe the survey construction, together with early results based on a first sample of ~55,000 galaxies.Comment: 6 pages, 8 figures; introductory pape

Physicochemical and Biological Characterisation of Diclofenac Oligomeric Poly(3-hydroxyoctanoate) Hybrids as β-TCP Ceramics Modifiers for Bone Tissue Regeneration

Nowadays, regenerative medicine faces a major challenge in providing new, functional materials that will meet the characteristics desired to replenish and grow new tissue. Therefore, this study presents new ceramic-polymer composites in which the matrix consists of tricalcium phosphates covered with blends containing a chemically bounded diclofenac with the biocompatible polymer-poly(3-hydroxyoctanoate), P(3HO). Modification of P(3HO) oligomers was confirmed by NMR, IR and XPS. Moreover, obtained oligomers and their blends were subjected to an in-depth characterisation using GPC, TGA, DSC and AFM. Furthermore, we demonstrate that the hydrophobicity and surface free energy values of blends decreased with the amount of diclofenac modified oligomers. Subsequently, the designed composites were used as a substrate for growth of the pre-osteoblast cell line (MC3T3-E1). An in vitro biocompatibility study showed that the composite with the lowest concentration of the proposed drug is within the range assumed to be non-toxic (viability above 70%). Cell proliferation was visualised using the SEM method, whereas the observation of cell penetration into the scaffold was carried out by confocal microscopy. Thus, it can be an ideal new functional bone tissue substitute, allowing not only the regeneration and restoration of the defect but also inhibiting the development of chronic inflammation

The AMANDA Neutrino Telescope

With an effective telescope area of order $10^4$ m$^2$ for TeV neutrinos, a threshold near $\sim$50 GeV and a pointing accuracy of 2.5 degrees per muon track, the AMANDA detector represents the first of a new generation of high energy neutrino telescopes, reaching a scale envisaged over 25 years ago. We describe early results on the calibration of natural deep ice as a particle detector as well as on AMANDA's performance as a neutrino telescope.Comment: 12 pages, Latex2.09, uses espcrc2.sty and epsf.sty, 13 postscript files included. Talk presented at the 18th International Conference on Neutrino Physics and Astrophysics (Neutrino 98), Takayama, Japan, June 199