Search for unusual objects in the WISE Survey

Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in multidimensional parameter spaces. In this work, we present a new, automated method of outlier selection based on support vector machine (SVM) algorithm called one-class SVM (OCSVM), which uses the training data as one class to construct a model of 'normality' in order to recognize novel points. We test the performance of OCSVM algorithm on \textit{Wide-field Infrared Survey Explorer (WISE)} data trained on the Sloan Digital Sky Survey (SDSS) sources. Among others, we find $\sim 40,000$ sources with abnormal patterns which can be associated with obscured and unobscured active galactic nuclei (AGN) source candidates. We present the preliminary estimation of the clustering properties of these objects and find that the unobscured AGN candidates are preferentially found in less massive dark matter haloes ($M_{DMH}\sim10^{12.4}$) than the obscured candidates ($M_{DMH}\sim 10^{13.2}$). This result contradicts the unification theory of AGN sources and indicates that the obscured and unobscured phases of AGN activity take place in different evolutionary paths defined by different environments.Comment: 4 figures, 6 page

Automated novelty detection in the WISE survey with one-class support vector machines

Wide-angle photometric surveys of previously uncharted sky areas or wavelength regimes will always bring in unexpected sources whose existence and properties cannot be easily predicted from earlier observations: novelties or even anomalies. Such objects can be efficiently sought for with novelty detection algorithms. Here we present an application of such a method, called one-class support vector machines (OCSVM), to search for anomalous patterns among sources preselected from the mid-infrared AllWISE catalogue covering the whole sky. To create a model of expected data we train the algorithm on a set of objects with spectroscopic identifications from the SDSS DR13 database, present also in AllWISE. OCSVM detects as anomalous those sources whose patterns - WISE photometric measurements in this case - are inconsistent with the model. Among the detected anomalies we find artefacts, such as objects with spurious photometry due to blending, but most importantly also real sources of genuine astrophysical interest. Among the latter, OCSVM has identified a sample of heavily reddened AGN/quasar candidates distributed uniformly over the sky and in a large part absent from other WISE-based AGN catalogues. It also allowed us to find a specific group of sources of mixed types, mostly stars and compact galaxies. By combining the semi-supervised OCSVM algorithm with standard classification methods it will be possible to improve the latter by accounting for sources which are not present in the training sample but are otherwise well-represented in the target set. Anomaly detection adds flexibility to automated source separation procedures and helps verify the reliability and representativeness of the training samples. It should be thus considered as an essential step in supervised classification schemes to ensure completeness and purity of produced catalogues.Comment: 14 pages, 15 figure

Radio-Infrared Correlation for Local Dusty Galaxies and Dusty AGNs from the AKARI All Sky Survey

We use the new release of the AKARI Far-Infrared all sky Survey matched with the NVSS radio database to investigate the local ($z<0.25$) far infrared-radio correlation (FIRC) of different types of extragalactic sources. To obtain the redshift information for the AKARI FIS sources we crossmatch the catalogue with the SDSS DR8. This also allows us to use emission line properties to divide sources into four categories: i) star-forming galaxies (SFGs), ii) composite galaxies (displaying both star-formation and active nucleus components), iii) Seyfert galaxies, and iv) low-ionization nuclear emission-line region (LINER) galaxies. We find that the Seyfert galaxies have the lowest FIR/radio flux ratios and display excess radio emission when compared to the SFGs. We conclude that FIRC can be used to separate SFGs and AGNs only for the most radio-loud objects.Comment: 9 pages, accepted to PAS

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 North Ecliptic Pole Wide survey of AKARI: a near- and mid-infrared source catalog

We present a photometric catalog of infrared (IR) sources based on the North Ecliptic PoleWide field (NEP-Wide) survey of AKARI, which is an infrared space telescope launched by Japan. The NEP-Wide survey covered 5.4 deg2 area, a nearly circular shape centered on the North Ecliptic Pole, using nine photometric filter-bands from 2 - 25 {\mu}m of the Infrared Camera (IRC). Extensive efforts were made to reduce possible false objects due to cosmic ray hits, multiplexer bleeding phenomena around bright sources, and other artifacts. The number of detected sources varied depending on the filter band: with about 109,000 sources being cataloged in the near-IR bands at 2 - 5 {\mu}m, about 20,000 sources in the shorter parts of the mid-IR bands between 7 - 11 {\mu}m, and about 16,000 sources in the longer parts of the mid-IR bands, with \sim 4,000 sources at 24 {\mu}m. The estimated 5? detection limits are approximately 21 magnitude (mag) in the 2 - 5 {\mu}m bands, 19.5 - 19 mag in the 7 - 11 {\mu}m, and 18.8 - 18.5 mag in the 15 - 24 {\mu}m bands in the AB magnitude scale. The completenesses for those bands were evaluated as a function of magnitude: the 50% completeness limits are about 19.8 mag at 3 {\mu}m, 18.6 mag at 9 {\mu}m, and 18 mag at 18 {\mu}m band, respectively. To construct a reliable source catalog, all of the detected sources were examined by matching them with those in other wavelength data, including optical and ground-based near-IR bands. The final band-merged catalog contains about 114,800 sources detected in the IRC filter bands. The properties of the sources are presented in terms of the distributions in various color-color diagrams.Comment: Accepted for publication in A&A, 23 pages, 27 figure

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

Clustering of the AKARI NEP deep field 24<i>μ</i>m selected galaxies

Aims. We present a method of selection of 24 μm galaxies from the AKARI north ecliptic pole (NEP) deep field down to 150 μJy and measurements of their two-point correlation function. We aim to associate various 24 μm selected galaxy populations with present day galaxies and to investigate the impact of their environment on the direction of their subsequent evolution. Methods. We discuss using of Support Vector Machines (SVM) algorithm applied to infrared photometric data to perform star-galaxy separation, in which we achieve an accuracy higher than 80%. The photometric redshift information, obtained through the CIGALE code, is used to explore the redshift dependence of the correlation function parameter (r0) as well as the linear bias evolution. This parameter relates galaxy distribution to the one of the underlying dark matter. We connect the investigated sources to their potential local descendants through a simplified model of the clustering evolution without interactions. Results. We observe two different populations of star-forming galaxies, at zmed ∼ 0.25, zmed ∼ 0.9. Measurements of total infrared luminosities (LTIR) show that the sample at zmed ∼ 0.25 is composed mostly of local star-forming galaxies, while the sample at zmed ∼ 0.9 is composed of luminous infrared galaxies (LIRGs) with LTIR ∼ 1011.62 L⨀. We find that dark halo mass is not necessarily correlated with the LTIR: for subsamples with LTIR = 1011.15 L⨀ at zmed ∼ 0.7 we observe a higher clustering length (r0 = 6.21 ± 0.78 [h−1Mpc]) than for a subsample with mean LTIR = 1011.84 L⨀ at zmed ∼ 1.1 (r0 = 5.86 ± 0.69 h−1Mpc). We find that galaxies at zmed ∼ 0.9 can be ancestors of present day L∗ early type galaxies, which exhibit a very high r0 ∼ 8h−1 Mpc.</p

Automatised classification of WISE sources: first results, future prospects

Computational astrophysic