Stellar indices and kinematics in Seyfert 1 nuclei

We present spectra of 6 type 1 Seyfert galaxies, 2 Seyfert 2, a starburst galaxy and a compact narrow line radiogalaxy, taken in two spectral ranges centered around the near--IR CaII triplet (CaT) (at ~8600 Angstroms), and the Mgb stellar feature at 5180 Angstroms. We measured the equivalent width (EWs) of these features and the Fe52 and Fe53 spectral indices. We found that the strength of the CaT in type 1 Seyfert galaxies with prominent central point sources, is larger than what would be expected from the observed strength of the blue indices. This could be explained by the presence of red supergiants in the nuclei of Seyfert 1 galaxies. On the other hand, the blue indices of these galaxies could also be diluted by the strong FeII multiplets that can be seen in their spectra. We have also measured the stellar and gas velocity dispersions of the galaxies in the sample. The stellar velocity dispersions were measured using both, the Mgb and CaT stellar features. The velocity dispersion of the gas in the narrow line region (NLR) was measured using the strong emission lines [OIII] 5007, 4959 and [SIII] 9069. We compare the gas and star velocity dispersions and find that both magnitudes are correlated in Seyfert galaxies. Most of the Seyfert 1 we observe have stellar velocity dispersion somehow greater than that of the gas in the NLR.Comment: To appear in MNRAS, 18 pages, 9 figure

Thinking fast, thinking badly

We test for the construct validity of the cognitive reflection test (CRT) by eliciting response times. We find that incorrect answers to the CRT are quicker than correct answers. At the individual level, we classify subjects into impulsive and reflective, depending on whether they choose the incorrect intuitive answer or the correct answer the majority of the time. We show that impulsive subjects complete the test quicker than reflective subjects

Dynamical NNLO parton distributions

Utilizing recent DIS measurements (\sigma_r, F_{2,3,L}) and data on hadronic dilepton production we determine at NNLO (3-loop) of QCD the dynamical parton distributions of the nucleon generated radiatively from valencelike positive input distributions at an optimally chosen low resolution scale (Q_0^2 < 1 GeV^2). These are compared with `standard' NNLO distributions generated from positive input distributions at some fixed and higher resolution scale (Q_0^2 > 1 GeV^2). Although the NNLO corrections imply in both approaches an improved value of \chi^2, typically \chi^2_{NNLO} \simeq 0.9 \chi^2_{NLO}, present DIS data are still not sufficiently accurate to distinguish between NLO results and the minute NNLO effects of a few percent, despite of the fact that the dynamical NNLO uncertainties are somewhat smaller than the NLO ones and both are, as expected, smaller than those of their `standard' counterparts. The dynamical predictions for F_L(x,Q^2) become perturbatively stable already at Q^2 = 2-3 GeV^2 where precision measurements could even delineate NNLO effects in the very small-x region. This is in contrast to the common `standard' approach but NNLO/NLO differences are here less distinguishable due to the much larger 1\sigma uncertainty bands. Within the dynamical approach we obtain \alpha_s(M_Z^2)=0.1124 \pm 0.0020, whereas the somewhat less constrained `standard' fit gives \alpha_s(M_Z^2)=0.1158 \pm 0.0035.Comment: 44 pages, 15 figures; minor changes, footnote adde

Charmed nuclei within a microscopic many-body approach

Single-particle energies of the $\Lambda_c$ chamed baryon are obtained in several nuclei from the relevant self-energy constructed within the framework of a perturbative many-body approach. Results are presented for a charmed baryon-nucleon ($Y_cN$) potential based on a SU(4) extension of the meson-exchange hyperon-nucleon potential $\tilde A$ of the J\"{u}lich group. Three different models (A, B and C) of this interaction, that differ only on the values of the couplings of the scalar $\sigma$ meson with the charmed baryons, are considered. Phase shifts, scattering lengths and effective ranges are computed for the three models and compared with those predicted by the $Y_cN$ interaction derived in Eur. Phys. A {\bf 54}, 199 (2018) from the extrapolation to the physical pion mass of recent results of the HAL QCD Collaboration. Qualitative agreement is found for two of the models (B and C) considered. Our results for $\Lambda_c$-nuclei are compatible with those obtained by other authors based on different models and methods. We find a small spin-orbit splitting of the $p-, d-$ and $f-$wave states as in the case of single $\Lambda$-hypernuclei. The level spacing of $\Lambda_c$ single-particle energies is found to be smaller than that of the corresponding one for hypernuclei. The role of the Coulomb potential and the effect of the coupling of the $\Lambda_cN$ and $\Sigma_cN$ channels on the single-particle properties of $\Lambda_c-$nuclei are also analyzed. Our results show that, despite the Coulomb repulsion between the $\Lambda_c$ and the protons, even the less attractive one of our $Y_cN$ models (model C) is able to bind the $\Lambda_c$ in all the nuclei considered. The effect of the $\Lambda_cN-\Sigma_cN$ coupling is found to be almost negligible due to the large mass difference of the $\Lambda_c$ and $\Sigma_c$ baryons.Comment: 10 pages, 6 figures, 4 table

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

Automatically annotating column types with knowledge base(KB) concepts is a critical task to gain a basic understandingof web tables. Current methods rely on either table metadatalike column name or entity correspondences of cells in theKB, and may fail to deal with growing web tables with in-complete meta information. In this paper we propose a neu-ral network based column type annotation framework namedColNetwhich is able to integrate KB reasoning and lookupwith machine learning and can automatically train Convolu-tional Neural Networks for prediction. The prediction modelnot only considers the contextual semantics within a cell us-ing word representation, but also embeds the semantics of acolumn by learning locality features from multiple cells. Themethod is evaluated with DBPedia and two different web ta-ble datasets, T2Dv2 from the general Web and Limaye fromWikipedia pages, and achieves higher performance than thestate-of-the-art approaches

Variable Flavor Number Parton Distributions and Weak Gauge and Higgs Boson Production at Hadron Colliders at NNLO of QCD

Based on our recent NNLO dynamical parton distributions as obtained in the `fixed flavor number scheme', we generate radiatively parton distributions in the `variable flavor number scheme' where also the heavy quark flavors (c,b,t) become massless partons within the nucleon. Only within this latter factorization scheme NNLO calculations are feasible at present, since the required partonic subprocesses are only available in the approximation of massless initial-state partons. The NNLO predictions for gauge boson production are typically larger (by more than 1 sigma) than the NLO ones, and rates at LHC energies can be predicted with an accuracy of about 5%, whereas at Tevatron they are more than 2 sigma above the NLO ones. The NNLO predictions for SM Higgs boson production via the dominant gluon fusion process have a total (pdf and scale) uncertainty of about 10% at LHC which almost doubles at the lower Tevatron energies; they are typically about 20% larger than the ones at NLO but the total uncertainty bands overlap.Comment: 28 pages, 3 tables, 6 figure

Effect of self-healing additions on the development of mechanical strength of cement paste

Important research efforts have been recently focused on the development of self-healing cement composites. The healing mechanism, implemented within the material, must be automatically initiated as soon as the first signs of damage appear at the micro-scale. For doing so, two different additions have been developed to incorporate them simultaneously into the cementitious matrix: silica microcapsules containing an epoxy sealing compound (CAP) and nanosilica particles functionalized with amine groups (NS). As a first step to the development of a self-healing concrete with these two additions, their pozzolanic activity has been measured by an accelerated test. The high values of fixed lime obtained at 28 days (85% for CAP, 93% for NS and 88% for a mix of them) suggest that they are suitable for construction materials’ applications. Furthermore, the behaviour of the additions in an ordinary Portland cement paste with 20 wt.% of commercial micro-silica has been studied, considering the partial substitution of micro-silica by CAP, NS and their mix. High values of compressive strength (&gt;60 MPa) have been obtained in all cases after 28 days of hydration. However, while the addition of CAP induces a reduction of the compressive strength of the 24% with respect to the reference material, the addition of NS gives rise to a slight enhancement of the strength (5%) due to a pozzolanic reaction confirmed by X-ray diffraction data. Finally, in the presence of both CAP and NS, the beneficial effect of the nanosilica is counteracted by the microcapsules and a reduction of 28% is obtained for the compressive strength

Learning Semantic Annotations for Tabular Data

The usefulness of tabular data such as web tables critically depends on understanding their semantics. This study focuses on column type prediction for tables without any meta data. Unlike traditional lexical matching-based methods, we propose a deep prediction model that can fully exploit a table's contextual semantics, including table locality features learned by a Hybrid Neural Network (HNN), and inter-column semantics features learned by a knowledge base (KB) lookup and query answering algorithm.It exhibits good performance not only on individual table sets, but also when transferring from one table set to another