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Highly oriented, large area continuous composite nanofiber sheets made from surface-oxidized multiwalled carbon nanotubes (MWNTs) and polyacrylonitrile (PAN) were successfully developed using electrospinning. The preferred orientation of surface-oxidized MWNTs along the fiber axis was determined with transmission electron microscopy and electron(More)
Effective data visualization is a key part of the discovery process in the era of “big data”. It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding. Visualization is also essential in the data mining process, directing(More)
—An automated, rapid classification of transient events detected in the modern synoptic sky surveys is essential for their scientific utility and effective follow-up using scarce resources. This presents some unusual challenges: the data are sparse, heterogeneous and incomplete; evolving in time; and most of the relevant information comes not from the data(More)
Hyperinsulinemic hypoglycemia secondary to nesidioblastosis persisted in a 4-year-old girl despite a 95% pancreatectomy and high-dose diazoxide treatment. Current literature suggests that dietary treatment, specifically protein restriction, of patients who are receiving diazoxide is ineffective and that further surgical pancreatectomy is required. However,(More)
Astronomy has been at the forefront of the development of the techniques and methodologies of data intensive science for over a decade with large sky surveys and distributed efforts such as the Virtual Observatory. However, it faces a new data deluge with the next generation of synoptic sky surveys which are opening up the time domain for discovery and(More)
We describe the development of a system for an automated, iterative, real‐time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly using Bayesian approaches, due to the sparse nature, heterogeneity, and variable incompleteness of the available data.(More)
We describe the Meta-Institute for Computational Astrophysics (MICA), the first professional scientific organization based exclusively in virtual worlds (VWs). The goals of MICA are to explore the utility of the emerging VR and VWs technologies for scientific and scholarly work in general, and to facilitate and accelerate their adoption by the scientific(More)
We review some of the recent developments and challenges posed by the data analysis in modern digital sky surveys, which are representative of the information-rich astronomy in the context of Virtual Observatory. Illustrative examples include the problems of an automated star-galaxy classification in complex and heterogeneous panoramic imaging data sets,(More)