Discovery of a Nova-Like Cataclysmic Variable in the Kepler Mission Field

We announce the identification of a new cataclysmic variable star in the field of the Kepler Mission, KIC J192410.81+445934.9. This system was identified during a search for compact pulsators in the Kepler field. High-speed photometry reveals coherent large-amplitude variability with a period of 2.94 h. Rapid, large-amplitude quasi-periodic variations are also detected on time scales of ~1200 s and ~650 s. Time-resolved spectroscopy covering one half photometric period shows shallow, broad Balmer and He I absorption lines with bright emission cores as well as strong He II and Bowen blend emission. Radial velocity variations are also observed in the Balmer and He I emission lines that are consistent with the photometric period. We therefore conclude that KIC J192410.81+445934.9 is a nova-like variable of the UX UMa class in or near the period gap, and it may belong to the rapidly growing subclass of SW Sex systems. Based on 2MASS photometry and companion star models, we place a lower limit on the distance to the system of ~500 pc. Due to limitations of our discovery data, additional observations including spectroscopy and polarimetry are needed to confirm the nature of this object. Such data will help to further understanding of the behavior of nova-like variables in the critical period range of 3-4 h, where standard cataclysmic variable evolutionary theory finds major problems. The presence of this system in the Kepler mission field-of-view also presents a unique opportunity to obtain a continuous photometric data stream of unparalleled length and precision on a cataclysmic variable system.Comment: Accepted for publication in the Astronomical Journal. 8 pages, 7 figures, uses emulateapj

Spatially Correlated Cluster Populations in the Outer Disk of NGC 3184

We use deep (~27.5 mag V-band point-source limiting magnitude) V- and U-band LBT imaging to study the outer disk (beyond the optical radius R_25) of the non-interacting, face-on spiral galaxy NGC 3184 (D = 11.1 Mpc; R_25 = 11.1 kpc) and find that this outer disk contains >1000 objects (or marginally-resolved 'knots') resembling star clusters with masses ~10^2 - 10^4 M_sun and ages up to ~1 Gyr. We find statistically significant numbers of these cluster-like knots extending to ~1.4 R_25, with the redder knots outnumbering bluer at the largest radii. We measure clustering among knots and find significant correlation to galactocentric radii of 1.5 R_25 for knot separations <1 kpc. The effective integrated surface brightness of this outer disk cluster population ranges from 30 - 32 mag arcsec^-2 in V. We compare the HI extent to that of the correlated knots and find that the clusters extend at least to the damped Lyman-alpha threshold of HI column density (2e20 cm^-2; 1.62 R_25). The blue knots are correlated with HI spiral structure to 1.5 R_25, while the red knots may be correlated with the outer fringes of the HI disk to 1.7 R_25. These results suggest that outer disks are well-populated, common, and long-lasting features of many nearby disk galaxies.Comment: Accepted for publication in The Astrophysical Journal. 12 pages, 10 figure

Performance assessment of thermal bridge elements into a full scale experimental study of a building façade

In this paper, an experimental and numerical approach to the characterization of thermal bridges is presented. The need for this characterization was found within an experimental study in a 2 floor high facade. This facade was constructed with 3 concrete elements which were placed in it to produce a similar thermal bridge effect to the one created by floor slabs traditional building construction in Spain. Commonly applied thermal assessments perform one-dimensional heat transfer analysis over planar elements such as the facades studied in this experiment. However, it is well known that thermal bridges are locations in buildings where one-dimensional heat transfer analysis cannot be applied. This problem was approached by creating a numerical 2D thermal model which was calibrated against experimental data from several temperature and heat flux sensors which were located at specific points in the thermal bridge elements.Government of the Basque Countr

An X-ray View of Star Formation in the Central 3 kpc of NGC 2403

Archival Chandra observations are used to study the X-ray emission associated with star formation in the central region of the nearby SAB(s)cd galaxy NGC 2403. The distribution of X-ray emission is compared to the morphology visible at other wavelengths using complementary Spitzer, GALEX, and ground-based Halpha imagery. In general, the brightest extended X-ray emission is associated with HII regions and to other star-forming structures but is more pervasive; existing also in regions devoid of strong Halpha and UV emission. This X-ray emission has the spectral properties of diffuse hot gas (kT ~ 0.2keV) whose likely origin is in gas shock-heated by stellar winds and supernovae with < 20% coming from faint unresolved X-ray point sources. This hot gas may be slowly-cooling extra-planar remnants of past outflow events, or a disk component that either lingers after local star formation activity has ended or that has vented from active star-forming regions into a porous interstellar medium.Comment: 25 pages, accepted to A

Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers

Background: Rare endocrine cancers such as Adrenocortical Carcinoma (ACC) present a serious diagnostic and prognostication challenge. The knowledge about ACC pathogenesis is incomplete, and patients have limited therapeutic options. Identification of molecular drivers and effective biomarkers is required for timely diagnosis of the disease and stratify patients to offer the most beneficial treatments. In this study we demonstrate how machine learning methods integrating multi-omics data, in combination with system biology tools, can contribute to the identification of new prognostic biomarkers for ACC.Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. Additional regulators of the identified signature were discovered using Clarivate CBDD (Computational Biology for Drug Discovery) network propagation and hidden nodes algorithms on a curated network of molecular interactions (MetaBase™). The discriminative power of the multi-omics signature and their regulators was delineated by training a random forest classifier using 55 samples, by employing a 10-fold cross validation with five iterations. The prognostic value of the identified biomarkers was further assessed on an external ACC dataset obtained from GEO (GSE49280) using the Kaplan-Meier estimator method. An optimal prognostic signature was finally derived using the stepwise Akaike Information Criterion (AIC) that allowed categorization of samples into high and low-risk groups.Results: A multi-omics signature including genes, micro RNA's and methylation sites was generated. Systems biology tools identified additional genes regulating the features included in the multi-omics signature. RNA-seq, miRNA-seq and DNA methylation sets of features revealed a high power to classify patients from stages I-II and stages III-IV, outperforming previously identified prognostic biomarkers. Using an independent dataset, associations of the genes included in the signature with Overall Survival (OS) data demonstrated that patients with differential expression levels of 8 genes and 4 micro RNA's showed a statistically significant decrease in OS. We also found an independent prognostic signature for ACC with potential use in clinical practice, combining 9-gene/micro RNA features, that successfully predicted high-risk ACC cancer patients.Conclusion: Machine learning and integrative analysis of multi-omics data, in combination with Clarivate CBDD systems biology tools, identified a set of biomarkers with high prognostic value for ACC disease. Multi-omics data is a promising resource for the identification of drivers and new prognostic biomarkers in rare diseases that could be used in clinical practice

Solving the mu problem with a heavy Higgs boson

We discuss the generation of the mu-term in a class of supersymmetric models characterized by a low energy effective superpotential containing a term lambda S H_1 H_2 with a large coupling lambda~2. These models generically predict a lightest Higgs boson well above the LEP limit of 114 GeV and have been shown to be compatible with the unification of gauge couplings. Here we discuss a specific example where the superpotential has no dimensionful parameters and we point out the relation between the generated mu-term and the mass of the lightest Higgs boson. We discuss the fine-tuning of the model and we find that the generation of a phenomenologically viable mu-term fits very well with a heavy lightest Higgs boson and a low degree of fine-tuning. We discuss experimental constraints from collider direct searches, precision data, thermal relic dark matter abundance, and WIMP searches finding that the most natural region of the parameter space is still allowed by current experiments. We analyse bounds on the masses of the superpartners coming from Naturalness arguments and discuss the main signatures of the model for the LHC and future WIMP searches.Comment: Extended discussion of the LHC phenomenology, as published on JHEP plus an addendum on the existence of further extremal points of the potential. 47 pages, 16 figure

Star Cluster Populations in the Outer Disks of Nearby Galaxies

We present a Large Binocular Telescope (LBT) imaging study that characterizes the star cluster component of nearby galaxy outer disks (beyond the optical radius R_25). Expanding on the pilot project of Herbert-Fort et al. (2009), we present deep (~ 27.5 mag V-band point-source limiting magnitude) U- and V-band imaging of six galaxies: IC 4182, NGC 3351, NGC 4736, NGC 4826, NGC 5474, and NGC 6503. We find that the outer disk of each galaxy is populated with marginally-resolved star clusters with masses ~10^3 M_sun and ages up to ~ 1 Gyr (masses and ages are limited by the depth of our imaging and uncertainties are large given how photometry can be strongly affected by the presence or absence of a few stars in such low mass systems), and that they are typically found out to at least 2 R_25 but sometimes as far as 3 to 4 R_25- even beyond the apparent HI disk. The mean rate of cluster formation for 1 R_25<= R <= 1.5R_25 is at least one every ~2.5 Myr and the clusters are spatially correlated with the HI, most strongly with higher density gas near the periphery of the optical disk and with lower density neutral gas at the HI disk periphery. We hypothesize that the clusters near the edge of the optical disk are formed in the extension of spiral structure from the inner disk and are a fairly consistent phenomenon and that the clusters formed at the periphery of the HI disk are the result of accretion episodes.Comment: 23 pages, accepted for publication in Ap

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Individual and culture-level components of survey response styles: a multi-level analysis using cultural models of selfhood

Variations in acquiescence and extremity pose substantial threats to the validity of cross-cultural research that relies on survey methods. Individual and cultural correlates of response styles when using two contrasting types of response mode were investigated, drawing on data from 55 cultural groups across 33 nations. Using seven dimensions of self-other relatedness that have often been confounded within the broader distinction between independence and interdependence, our analysis yields more specific understandings of both individual- and culture-level variations in response style. When using a Likert scale response format, acquiescence is strongest among individuals seeing themselves as similar to others, and where cultural models of selfhood favour harmony, similarity with others and receptiveness to influence. However, when using Schwartz’s (2007) portrait-comparison response procedure, acquiescence is strongest among individuals seeing themselves as self-reliant but also connected to others, and where cultural models of selfhood favour self-reliance and self-consistency. Extreme responding varies less between the two types of response modes, and is most prevalent among individuals seeing themselves as self-reliant, and in cultures favouring self-reliance. Since both types of response mode elicit distinctive styles of response, it remains important to estimate and control for style effects to ensure valid comparisons

Being oneself through time: bases of self-continuity across 55 cultures

Self-continuity – the sense that one’s past, present, and future are meaningfully connected – is considered a defining feature of personal identity. However, bases of self-continuity may depend on cultural beliefs about personhood. In multilevel analyses of data from 7287 adults from 55 cultural groups in 33 nations, we tested a new tripartite theoretical model of bases of self-continuity. As expected, perceptions of stability, sense of narrative, and associative links to one’s past each contributed to predicting the extent to which people derived a sense of self-continuity from different aspects of their identities. Ways of constructing self-continuity were moderated by cultural and individual differences in mutable (vs. immutable) personhood beliefs – the belief that human attributes are malleable. Individuals with lower mutability beliefs based self-continuity more on stability; members of cultures where mutability beliefs were higher based self-continuity more on narrative. Bases of self-continuity were also moderated by cultural variation in contextualized (vs. decontextualized) personhood beliefs, indicating a link to cultural individualism-collectivism. Our results illustrate the cultural flexibility of the motive for self-continuity