12,778 research outputs found
KIC 9821622: An interesting lithium-rich giant in the Kepler field
We report the discovery of a new exceptional young lithium-rich giant, KIC
9821622, in the \textit{Kepler} field that exhibits an unusually large
enhancement of , Fe-peak, and \textit{r}-process elements. From
high-resolution spectra obtained with GRACES at Gemini North, we derived
fundamental parameters and detailed chemical abundances of 23 elements from
equivalent widths and synthesis analysis. By combining atmospheric stellar
parameters with available asteroseismic data, we obtained the stellar mass,
radius, and age. The data analysis reveals that KIC 9821622 is a Li-rich
(A(Li) = 1.80 0.2) intermediate-mass giant star ( = 1.64
) located at the red giant branch near the luminosity bump. We find
unexpectedly elevated abundances of Fe-peak and \textit{r}-process elements. In
addition, as previously reported, we find that this is a young star (2.37 Gyr)
with unusually high abundances of -elements ([/Fe] = 0.31). The
evolutionary status of KIC 9821622 suggests that its Li-rich nature is the
result of internal fresh Li that is synthesized through the Cameron-Fowler
mechanism near the luminosity bump. However, its peculiar enhancement of
, Fe-peak, and \textit{r}-process elements opens the possibility of
external contamination by material enriched by a supernova explosion. Although
it is less likely, planet accretion cannot be ruled out.Comment: Letter, 6 pages, 3 figures, Accepted for publication in A&A. - Some
language editing include
Returns to education and to experience within the EU: are there differences between wage earners and the self-employed?
This paper investigates the returns to education and to experience within the 15 pre-enlargement EU countries, distinguishing between wage earners and the self-employed. These returns are estimated by using a comparable data set coming from the European Community Household Panel during the period 1994-2000. To correct for the ability bias and recover the education coefficients, an Efficient Generalized Instrumental Variable technique is applied. Although the results differ across countries, two common features can be observed. First, the earnings-experience profiles indicate certain traits of competitiveness in the labor markets and, secondly, the returns to education show that signaling plays a relevant role in the earnings of workers.Returns to education, wage earners, self-employed, panel data, European Union
A new special class of Petrov type D vacuum space-times in dimension five
Using extensions of the Newman-Penrose and Geroch-Held-Penrose formalisms to
five dimensions, we invariantly classify all Petrov type vacuum solutions
for which the Riemann tensor is isotropic in a plane orthogonal to a pair of
Weyl alligned null directionsComment: 4 pages, 1 table, no figures. Contribution to the proceedings of the
Spanish Relativity Meeting 2010 held in Granada (Spain
Intelligent data analysis approaches to churn as a business problem: a survey
Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer’s intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.Peer ReviewedPostprint (author's final draft
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