Nearby Young, Active, Late-type Dwarfs in Gaia's First Data Release

The Galex Nearby Young Star Survey (GALNYSS) has yielded a sample of $\sim$2000 UV-selected objects that are candidate nearby ($D \stackrel{<}{\sim}$150 pc), young (age $\sim$10--100 Myr), late-type stars. Here, we evaluate the distances and ages of the subsample of (19) GALNYSS stars with Gaia Data Release 1 (DR1) parallax distances $D \le 120$ pc. The overall youth of these 19 mid-K to early-M stars is readily apparent from their positions relative to the loci of main sequence stars and giants in Gaia-based color-magnitude and color-color diagrams constructed for all Galex- and WISE-detected stars with parallax measurements included in DR1. The isochronal ages of all 19 stars lie in the range $\sim$10--100 Myr. Comparison with Li-based age estimates indicates a handful of these stars may be young main-sequence binaries rather than pre-main sequence stars. Nine of the 19 objects have not previously been considered as nearby, young stars, and all but one of these are found at declinations north of $+$30$^\circ$. The Gaia DR1 results presented here indicate that the GALNYSS sample includes several hundred nearby, young stars, a substantial fraction of which have not been previously recognized as having ages $\stackrel{<}{\sim}$100 Myr.Comment: 30 pages, 4 tables, 7 figures; to appear in The Astrophysical Journal; 1st replacement to correct typos/omissions in Table 3 and acknowledgments; 2nd replacement to incorporate corrections to ApJ proof

Managerial interpretation and innovation in the context of climate change

Firms have developed climate change strategies over the last decade in response to rising regulatory, social and competitive pressures. Increasingly, these strategies include the development of new products and services (P&S) to reducing the environmental impact of the firm and its customers. In this paper, I explore how managerial interpretation of climate change has evolved over time and how these changes in interpretation are associated with innovation outcomes. The existing literature suggests that interpreting environmental challenges as opportunities is more likely to lead to open and innovative strategies. Using qualitative survey data on 99 Global 500 firms over the period 2003 to 2009, I find that threat-based interpretation can in fact lead to positive innovation outcomes at early stages of new P&S development. I identify three main mechanisms through which the detailed identification of threats encourages innovation in response to climate change. Furthermore, I develop a temporal dimension to the relationship between interpretation and stages of P&S development. I find that at advanced stages of P&S development, a balanced and opportunity-focused interpretation becomes more important. The results imply that managerial interpretation can provide firms with added flexibility to provide innovative responses to social and environmental challenges. But the relationship between interpretation and innovation is not static, nor is it a question of threat or opportunity interpretation but a combination of the two at different times that provides flexibility

Microfluidic stochastic confinement enhances analysis of rare cells by isolating cells and creating high density environments for control of diffusible signals

Rare cells can be difficult to analyze because they either occur in low numbers or coexist with a more abundant cell type, yet their detection is crucial for diagnosing disease and maintaining human health. In this tutorial review, we introduce the concept of microfluidic stochastic confinement for use in detection and analysis of rare cells. Stochastic confinement provides two advantages: (1) it separates rare single cells from the bulk mixture and (2) it allows signals to locally accumulate to a higher concentration around a single cell than in the bulk mixture. Microfluidics is an attractive method for implementing stochastic confinement because it provides simple handling of small volumes. We present technologies for microfluidic stochastic confinement that utilize both wells and droplets for the detection and analysis of single cells. We address how these microfluidic technologies have been used to observe new behavior, increase speed of detection, and enhance cultivation of rare cells. We discuss potential applications of microfluidic stochastic confinement to fields such as human diagnostics and environmental testing