Spectroscopy of the hot pulsating star Beta Cephei. Velocities and EWs from C,N,O and Si lines

Frequencies in oscillating $\beta$ Cephei stars are usually inferred by means of radial velocities measured from the SiIII triplet 4552-4574 A. These lines, relatively insensitive to the variation of Teff through a pulsation cycle, show small equivalent width variations. In this study we aimed to verify if the behavior of radial velocities and equivalent widths measured from other ions are compatible with the one observed from SiIII lines and than to verify the possible vertical stratification along the stellar atmosphere. For this reason we selected from our spectra a number of, unblended and well isolated, CII, NII and OII lines besides the famous SiIII triplet. All those lines cover the range in optical depth between -2.1 and -0.5. Unfortunately, we did not find any differences in the radial velocities behavior line-by-line and then we derived the frequency of the principal radial mode combining all the velocities derived from each spectral line separately. The inferred frequency was f1=5.249677+/-0.000007 c/d. Another important task we would like to accomplish with this paper is to make available to the community our large sample of spectroscopic data, that is 932 velocities and equivalent widths measured from our sample of C, N, O and Si lines. All the spectra were acquired at the 1-meter class telescope of the stellar station of the INAF - Osservatorio Astrofisico di Catania, in the period starting from July, the 27th 2005 to November, the 1st 2006.Comment: 10 pages, 5 figures, to be published in New Astronom

CAOS spectroscopy of Am stars Kepler targets

The {\it Kepler} space mission and its {\it K2} extension provide photometric time series data with unprecedented accuracy. These data challenge our current understanding of the metallic-lined A stars (Am stars) for what concerns the onset of pulsations in their atmospheres. It turns out that the predictions of current diffusion models do not agree with observations. To understand this discrepancy, it is of crucial importance to obtain ground-based spectroscopic observations of Am stars in the {\it Kepler} and {\it K2} fields in order to determine the best estimates of the stellar parameters. In this paper, we present a detailed analysis of high-resolution spectroscopic data for seven stars previously classified as Am stars. We determine the effective temperatures, surface gravities, projected rotational velocities, microturbulent velocities and chemical abundances of these stars using spectral synthesis. These spectra were obtained with {\it CAOS}, a new instrument recently installed at the observing station of the Catania Astrophysical Observatory on Mt. Etna. Three stars have already been observed during quarters Q0-Q17, namely: HD\,180347, HD\,181206, and HD\,185658, while HD\,43509 was already observed during {\it K2} C0 campaign. We confirm that HD\,43509 and HD\,180347 are Am stars, while HD 52403, HD\,50766, HD\,58246, HD\,181206 and HD\,185658 are marginal Am stars. By means of non-LTE analysis, we derived oxygen abundances from O{\sc I}$\lambda$7771--5{\AA} triplet and we also discussed the results obtained with both non-LTE and LTE approaches.Comment: accepted in MNRAS main journal 13 pages, 11 figures, 3 tables. arXiv admin note: text overlap with arXiv:1404.095

Spatially Resolved Temperature and Water Vapor Concentration Distributions in Supersonic Combustion Facilities by TDLAT

Detailed knowledge of the internal structure of high-enthalpy flows can provide valuable insight to the performance of scramjet combustors. Tunable Diode Laser Absorption Spectroscopy (TDLAS) is often employed to measure temperature and species concentration. However, TDLAS is a path-integrated line-of-sight (LOS) measurement, and thus does not produce spatially resolved distributions. Tunable Diode Laser Absorption Tomography (TDLAT) is a non-intrusive measurement technique for determining two-dimensional spatially resolved distributions of temperature and species concentration in high enthalpy flows. TDLAT combines TDLAS with tomographic image reconstruction. More than 2500 separate line-of-sight TDLAS measurements are analyzed in order to produce highly resolved temperature and species concentration distributions. Measurements have been collected at the University of Virginia's Supersonic Combustion Facility (UVaSCF) as well as at the NASA Langley Direct-Connect Supersonic Combustion Test Facility (DCSCTF). Due to the UVaSCF s unique electrical heating and ability for vitiate addition, measurements collected at the UVaSCF are presented as a calibration of the technique. Measurements collected at the DCSCTF required significant modifications to system hardware and software designs due to its larger measurement area and shorter test duration. Tomographic temperature and water vapor concentration distributions are presented from experimentation on the UVaSCF operating at a high temperature non-reacting case for water vitiation level of 12%. Initial LOS measurements from the NASA Langley DCSCTF operating at an equivalence ratio of 0.5 are also presented. Results show the capability of TDLAT to adapt to several experimental setups and test parameters

BoostingTree: parallel selection of weak learners in boosting, with application to ranking

Boosting algorithms have been found successful in many areas of machine learning and, in particular, in ranking. For typical classes of weak learners used in boosting (such as decision stumps or trees), a large feature space can slow down the training, while a long sequence of weak hypotheses combined by boosting can result in a computationally expensive model. In this paper we propose a strategy that builds several sequences of weak hypotheses in parallel, and extends the ones that are likely to yield a good model. The weak hypothesis sequences are arranged in a boosting tree, and new weak hypotheses are added to promising nodes (both leaves and inner nodes) of the tree using some randomized method. Theoretical results show that the proposed algorithm asymptotically achieves the performance of the base boosting algorithm applied. Experiments are provided in ranking web documents and move ordering in chess, and the results indicate that the new strategy yields better performance when the length of the sequence is limited, and converges to similar performance as the original boosting algorithms otherwise. © 2013 The Author(s)

Financial crises and the attainment of the SDGs: an adjusted multidimensional poverty approach

This paper analyses the impact of financial crises on the Sustainable Development Goal of eradicating poverty. To do so, we develop an adjusted Multidimensional Poverty Framework (MPF) that includes 15 indicators that span across key poverty aspects related to income, basic needs, health, education and the environment. We then use an econometric model that allows us to examine the impact of financial crises on these indicators in 150 countries over the period 1980–2015. Our analysis produces new estimates on the impact of financial crises on poverty’s multiple social, economic and environmental aspects and equally important captures dynamic linkages between these aspects. Thus, we offer a better understanding of the potential impact of current debt dynamics on Multidimensional Poverty and demonstrate the need to move beyond the boundaries of SDG1, if we are to meet the target of eradicating poverty. Our results indicate that the current financial distress experienced by many low-income countries may reverse the progress that has been made hitherto in reducing poverty. We find that financial crises are associated with an approximately 10% increase of extreme poor in low-income countries. The impact is even stronger in some other poverty aspects. For instance, crises are associated with an average decrease of government spending in education by 17.72% in low-income countries. The dynamic linkages between most of the Multidimensional Poverty indicators, warn of a negative domino effect on a number of SDGs related to poverty, if there is a financial crisis shock. To pre-empt such a domino effect, the specific SDG target 17.4 on attaining long-term debt sustainability through coordinated policies plays a key role and requires urgent attention by the international community

Private and Communication-Efficient Algorithms for Entropy Estimation

Modern statistical estimation is often performed in a distributed setting where each sample belongs to a single user who shares their data with a central server. Users are typically concerned with preserving the privacy of their samples, and also with minimizing the amount of data they must transmit to the server. We give improved private and communication-efficient algorithms for estimating several popular measures of the entropy of a distribution. All of our algorithms have constant communication cost and satisfy local differential privacy. For a joint distribution over many variables whose conditional independence is given by a tree, we describe algorithms for estimating Shannon entropy that require a number of samples that is linear in the number of variables, compared to the quadratic sample complexity of prior work. We also describe an algorithm for estimating Gini entropy whose sample complexity has no dependence on the support size of the distribution and can be implemented using a single round of concurrent communication between the users and the server. In contrast, the previously best-known algorithm has high communication cost and requires the server to facilitate interaction between the users. Finally, we describe an algorithm for estimating collision entropy that matches the space and sample complexity of the best known algorithm but generalizes it to the private and communication-efficient setting

A network-based target overlap score for characterizing drug combinations: High correlation with cancer clinical trial results

Drug combinations are highly efficient in systemic treatment of complex multigene diseases such as cancer, diabetes, arthritis and hypertension. Most currently used combinations were found in empirical ways, which limits the speed of discovery for new and more effective combinations. Therefore, there is a substantial need for efficient and fast computational methods. Here, we present a principle that is based on the assumption that perturbations generated by multiple pharmaceutical agents propagate through an interaction network and can cause unexpected amplification at targets not immediately affected by the original drugs. In order to capture this phenomenon, we introduce a novel Target Overlap Score (TOS) that is defined for two pharmaceutical agents as the number of jointly perturbed targets divided by the number of all targets potentially affected by the two agents. We show that this measure is correlated with the known effects of beneficial and deleterious drug combinations taken from the DCDB, TTD and Drugs.com databases. We demonstrate the utility of TOS by correlating the score to the outcome of recent clinical trials evaluating trastuzumab, an effective anticancer agent utilized in combination with anthracycline- and taxane-based systemic chemotherapy in HER2-receptor (erb-b2 receptor tyrosine kinase 2) positive breast cancer. © 2015 Ligeti et al

Growth charts in Cockayne syndrome type 1 and type 2

Cockayne syndrome (CS) is a multisystem degenerative disorder divided in 3 overlapping subtypes, with a continuous phenotypic spectrum: CS2 being the most severe form, CS1 the classical form and CS3 the late-onset form. Failure to thrive and growth difficulties are among the most consistent features of CS, leaving affected individuals vulnerable to numerous medical complications, including adverse effects of undernutrition, abrupt overhydration and overfeeding. There is thus a significant need for specific growth charts. We retrospectively collected growth parameters from genetically-confirmed CS1 and CS2 patients, used the GAMLSS package to construct specific CS growth charts compared to healthy children from WHO and CDC databases. Growth data were obtained from 88 CS patients with a total of 1626 individual growth data points. 49 patients were classified as CS1 and 39 as CS2 with confirmed mutations in CSB/ERCC6, CSA/ERCC8 or ERCC1 genes. Individuals with CS1 initially have normal growth parameters; microcephaly occurs from 2 months whereas onset of weight and height restrictions appear later, between 5 and 22 months. In CS2, growth parameters are already below standard references at birth or drop below the 5th percentile before 3 months. Microcephaly is the first parameter to show a delay, appearing around 2 months in CS1 and at birth in CS2. Height and head circumference are more severely affected in CS2 compared to CS1 whereas weight curves are similar in CS1 and CS2 patients. These new growth charts will serve as a practical tool to improve the nutritional management of children with CS.</p