The 22 Ne(p,γ) 23 Na reaction is one of the most uncertain reactions in the NeNa cycle and plays a crucial role in the creation of 23 Na, the only stable Na isotope. Uncertainties in the low-energy rates of this and other reactions in the NeNa cycle lead to ambiguities in the nucleosynthesis predicted from models of thermally pulsing AGB stars. This in turn complicates the interpretation of anomalous Na-O trends in globular cluster evolutionary scenarios. (2015) and is attributed to the interplay between the 23 Na(p,α) 20 Ne and 20 Ne(p,γ) 21 Na reactions, both of which remain fairly uncertain at the relevant temperature range.

Purpose – Knowledge management capabilities have proven to be key success factors for organizations within our increasingly information-based economy. Although knowledge management literature has a rich history, less is known about how an organization’s learning culture affects outcomes realized via knowledge management initiatives. Moreover, there is a dearth of understanding regarding how to successfully operationalize knowledge management activities in order to achieve performance in the dynamic logistics and supply chain management environment. Rooted in competence-based theory, the purpose of this paper is to examine the role that learning culture plays with regard to knowledge management capabilities, human capital, and organizational performance at logistics service providers. Design/methodology/approach – This study uses survey data from 448 managers and covariance based structural equation modeling to assess how knowledge management, learning culture, and human capital influence organizational performance. Findings – The results of this study indicate that knowledge management has a significant positive relationship with learning culture and human capital. There was also an indirect effect of knowledge management through learning culture on human capital and organizational performance. Interestingly, human capital did not have a significant relationship with organizational performance as hypothesized. Practical implications – The results support the vital role that leaders and managers have in creating a culture that is conducive to the success of knowledge management initiatives. Originality/value – This study goes beyond the simple direct relationship between knowledge management and personal and organizational outcomes that is usually examined by testing learning culture as an important mediator.

We describe the Keck Interferometer nuller theory of operation, data reduction, and on-sky performance, particularly as it applies to the nuller exozodiacal dust key science program that was carried out between 2008 February and 2009 January. We review the nuller implementation, including the detailed phasor processing involved in implementing the null-peak mode used for science data and the sequencing used for science observing. We then describe the Level 1 reduction to convert the instrument telemetry streams to raw null leakages, and the Level 2 reduction to provide calibrated null leakages. The Level 1 reduction uses conservative, primarily linear processing, implemented consistently for science and calibrator stars. The Level 2 processing is more flexible, and uses diameters for the calibrator stars measured contemporaneously with the interferometer's K-band cophasing system in order to provide the requisite accuracy. Using the key science data set of 462 total scans, we assess the instrument performance for sensitivity and systematic error. At 2.0 Jy we achieve a photometrically-limited null leakage uncertainty of 0.25% rms per 10 minutes of integration time in our broadband channel. From analysis of the Level 2 reductions, we estimate a systematic noise floor for bright stars of ∼0:2% rms null leakage uncertainty per observing cluster in the broadband channel. A similar analysis is performed for the narrowband channels. We also provide additional information needed for science reduction, including details on the instrument beam pattern and the basic astrophysical response of the system, and references to the data reduction and modeling tools.