Looking Back to Move Forward: Measuring the Impact of Existing Digital Resources Relevant to Irish Archaeology

The proliferation of digital resources is an important manifestation of data sharing and knowledge sharing practice. There is an increasing recognition of the importance of understanding the actual impact of these resources on research and research practice. Impact assessment methodologies are emerging from this nascent scholarship and offer a means of demonstrating performance and utility. This study took a multi-strand approach, inspired by the Toolkit for the Impact of Digitised Scholarly Resources (TIDSR), to evaluate seven digital resources relating to Irish archaeology. The results indicated significant factors that can influence the impact of a digital resource, positively or negatively.     

Mobilizing Company Members' Full Innovative Potential

Most of the literature on innovation management highlights the fundamental role played by people in the innovation process and the need to fully develop the creative and innovative potential of organizations' members. This article offers the result of extensive research carried out among some of the most innovative companies in the Basque Country, a highly innovative region located in the north of Spain. It draws interesting conclusions about how these innovative companies combine strong leadership, human resource practices, and an organizational culture that enhances innovation capabilities among the company's employees. More specifically, it answers questions such as the following: Are human resources policies, leadership, and innovation culture implemented equally in Basque innovative companies? Do companies make the same effort in deploying these elements or routines and practices related to them? Can we see a pattern in the use of these elements among innovative firms? © 2012 Wiley Periodicals, Inc.     

Virtual life: self and identity redefined in the new media age

In this article, the author discusses her virtual reality installation The Parallel Dimension and goes on to explore the conflicts of identity experienced when a person is confronted with VR as a total immersion. She suggests that the various questions arising through this experience may lead us to a more ambivalent concept of the self.     

Fuzzy clustering based ET image fusion

Electrical tomography (ET) is a technique to visually reconstruct inhomogeneous medium distributions by injecting currents or voltages at the boundary of the medium and measuring the resulted changes in the investigated fields. The ET techniques have been widely used in industrial practices owing to the low cost, rapid response time, non-existent radiation exposure, and non-intrusive characteristics comparing to other tomographic modalities. However, the spatial resolution of ET images using single modality or single-driven patterns (adjacent pattern vs. opposite pattern for imaging reconstruction) is low, which may limit its applications. In this research, the application of fuzzy clustering based fusion techniques for ET imaging is studied. Both multi-modality imaging and multi-driven patterns are of interest. Specifically, two modality images are fused: Electrical Capacitance Tomography (ECT), which performs well for imaging material of large permittivity difference, and Electrical Resistance Tomography (ERT), which is suited for imaging materials having large conductivity differences. The research also explores the fusion of adjacent and opposite patterns for either ECT or ERT modalities. Experiments show that the proposed method can construct high quality ET images by discovering the strong complementary natures of the modalities and/or driven patterns.     

Virtual reality for collaborative e-learning

In the past, the term e-learning referred to any method of learning that used electronic delivery methods. With the advent of the Internet however, e-learning has evolved and the term is now most commonly used to refer to online courses. A multitude of systems are now available to manage and deliver learning content online. While these have proved popular, they are often single-user learning environments which provide little in the way of interaction or stimulation for the student. As the concept of lifelong learning now becomes a reality and thus more and more people are partaking in online courses, researchers are constantly exploring innovative techniques to motivate online students and enhance the e-learning experience. This article presents our research in this area and the resulting development of CLEV-R, a Collaborative Learning Environment with Virtual Reality. This web-based system uses Virtual Reality (VR) and multimedia and provides communication tools to support collaboration among students. In this article, we describe the features of CLEV-R, its adaptation for mobile devices and present the findings from an initial evaluation.     

Inferring the capacity of the vector Poisson channel with a Bernoulli model

The capacity defines the ultimate fidelity limits of information transmission by any system. We derive the capacity of parallel Poisson process channels to judge the relative effectiveness of neural population structures. Because the Poisson process is equivalent to a Bernoulli process having small event probabilities, we infer the capacity of multi-channel Poisson models from their Bernoulli surrogates. For neural populations wherein each neuron has individual innervation, inter-neuron dependencies increase capacity, the opposite behavior of populations that share a single input. We use Shannon's rate-distortion theory to show that for Gaussian stimuli, the mean-squared error of the decoded stimulus decreases exponentially in both the population size and the maximal discharge rate. Detailed analysis shows that population coding is essential for accurate stimulus reconstruction. By modeling multi-neuron recordings as a sum of a neural population, we show that the resulting capacity is much less than the population's, reducing it to a level that can be less than provided with two separated neural responses. This result suggests that attempting neural control without spike sorting greatly reduces the achievable fidelity. In contrast, single-electrode neural stimulation does not incur any capacity deficit in comparison to stimulating individual neurons.     

Methane coupling at low temperatures on Ru(0001) and Ru(11¯20) catalysts

The conversion of methane to higher hydrocarbons on single crystal Ru catalysts has been investigated using combined elevated-pressure kinetic measurements/surface science studies. The reaction consists of activation of methane on Ru(0001) and Ru(11¯20) surfaces to produce carbonaceous intermediates at temperatures between 350 and 700 K and rehydrogenation of these species to ethane and propane at 370 K. It is found that under the reaction conditions employed, the maximum yield in ethane/propane production occurs at 500 K on both surfaces. Influence of the hydrogenation temperature on the production of ethane and propane is also examined. On Ru(0001), the yields of ethane and propane maximize at = 400 K, whereas no maximum yield was observed on Ru(11 0) in the 300–500 K temperature range. Under optimum reaction conditions, hydrocarbon products consist of 16% ethane and 2% propane. High-resolution electron energy-loss spectroscopy (HREELS) has been used to identify various forms of hydrocarbonaceous intermediates following methane decomposition. An effort is made to relate the hydrocarbon intermediates identified by HREELS to the gas phase products observed in the elevated pressure experiments.     

Reduction of the bulk absorption coefficient in silicon optics for high-energy lasers through defect engineering

We engineered a factor-of-4 reduction in the bulk absorption coefficient over the 2.6-to-3.0-μm bandwidth in single-crystal Czochralski silicon optics for high-energy infrared lasers with high-temperature annealing treatments. Defect engineering adapted from the integrated circuit industry has been used to reduce the absorption coefficient across the 1.5-to-5-μm bandwidth for substrates up to 5 cm thick. A high-temperature oxygen-dispersion anneal dissolves precipitates and thermal donors that are present in the as-grown material. The process has been verified experimentally with Fourier transform infrared spectroscopy, infrared laser calorimetry, and Hall measurements. Reduction of the absorption coefficient results in less substrate heating and thermal distortion of the optical surface. The process is appropriate for other silicon infrared optics applications such as thermal-imaging systems, infrared windows, and spectrophotometers.