Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

Crystallography of fracture facets in a near-alpha titanium alloy

A faceted initiation site is observed in Ti-6242 alloy for both the cyclic and static-loading test conditions. In this experimental study, the crystallographic orientation of the facets has been determined using the electron backscattered diffraction (EBSD) technique in conjunction with the quantitative tilt fractography in a scanning electron microscope (SEM). Quantitative tilt fractography analysis has been used to determine the spatial orientation of fracture facets. The results indicate that the normal-fatigue (no-dwell) fracture facets are oriented at ∼5 deg with respect to the basal plane; the dwell-fatigue fracture facets are oriented at ∼10 to 15 deg with respect to the basal plane and the static-loading fracture facets are oriented at ∼20 deg with respect to the basal plane. These crystallographic orientation determinations of the fracture facets at the crack-initiation site can be used to obtain an idea about the type of loading that produced them.     

Synergistic interactions of etoposide and interleukin-1 alpha are not due to DNA damage in human melanoma cells

Family nursing, always a component of nursing, has been recently receiving increased attention through publications, educational programs, clinical practice settings and family nursing research. Nurses are in the best position to assist families experiencing the illness of a loved one, but often lack the skills and confidence necessary to assist with the psychosocial needs. The purpose of this paper is to describe the development and implementation of a family nursing program within a large, tertiary care facility. The program's evaluation is ongoing but early outcomes indicate that day-to-day nursing practice has been positively influenced and improved job satisfaction may result.     

Neural networks for contract bridge bidding

The objective of this study is to explore the possibility of capturing the reasoning process used in bidding a hand in a bridge game by an artificial neural network. We show that a multilayer feedforward neural network can be trained to learn to make an opening bid with a new hand. The game of bridge, like many other games used in artificial intelligence, can easily be represented in a machine. But, unlike most games used in artificial intelligence, bridge uses subtle reasoning over and above the agreed conventional system, to make a bid from the pattern of a given hand. Although it is difficult for a player to spell out the precise reasoning process he uses, we find that a neural network can indeed capture it. We demonstrate the results for the case of one-level opening bids, and discuss the need for a hierarchical architecture to deal with bids at all levels.