Sharing spaces, sharing lives - The impact of robot mobility on user perception of a home companion robot

Syrdal D.S., Dautenhahn K., Koay K.L., Walters M.L., Ho W.C. (2013) 'Sharing Spaces, Sharing Lives – The Impact of Robot Mobility on User Perception of a Home Companion Robot', In: Herrmann G., Pearson M.J., Lenz A., Bremner P., Spiers A., Leonards U. (eds) Social Robotics. ICSR 2013. Lecture Notes in Computer Science, Vol 8239. DOI: 10.1007/978-3-319-02675-6_32 Paper presented at the International Conference on Social Robotics, (ICSR) 2013, Bristol, UK, 27-29 October 2013. © Springer-Verlag Berlin Heidelberg 2013This paper examines the role of spatial behaviours in building human-robot relationships. A group of 8 participants, involved in a long-term HRI study, interacted with an artificial agent using different embodiments over a period of one and a half months. The robot embodiments had similar interactional and expressive capabilities, but only one embodiment was capable of moving. Participants reported feeling closer to the robot embodiment capable of physical movement and rated it as more likable. Results suggest that while expressive and communicative abilities may be important in terms of building affinity and rapport with human interactants, the importance of physical interactions when negotiating shared physical space in real time should not be underestimated

The epidemiology of heart failure: The Framingham Study

AbstractCongestive heart failure has become an increasingly frequent reason for hospital admission during the last 2 decades and clearly represents a major health problem. Data from the Framingham Heart Study indicate that the incidence of congestive heart failure increases with age and is higher in men than in women. Hypertension and coronary heart disease are the two most common conditions predating its onset. Diabetes mellitus and electrocardiographic left ventricular hypertrophy are also associated with an increased risk of heart failure. During the 1980s, the annual age-adjusted incidence of congestive heart failure among persons aged ≥ 45 years was 7.2 cases/1,000 in men and 4.7 cases/1,000 in women, whereas the age-adjusted prevalence of overt heart failure was 24/1,000 in men and 25/1,000 in women. Despite improved treatments for ischemic heart disease and hypertension, the age-adjusted incidence of heart failure has declined by only 11%/calendar decade in men and by 17%/calendar decade in women during a 40-year period of observation. In addition., congestive heart failure remains highly lethal, with a median survival time of 1.7 years in men and 3.2 years in women and a 5-year survival rate of 25% in men and 38% in women

Multiplier-less low-delay FIR and IIR wavelet filter banks with SOPOT coefficients

In this paper, a new family of multiplier-less two-channel low-delay wavelet filter banks using the PR structure in [3] and the SOPOT(sum-of-powers-of-two) representation is proposed. In particular, the functions α(z) and β(z) in the structure are chosen as nonlinear-phase FIR and IIR filters, and the design of such multiplier-less filter banks is performed using the genetic algorithm. The proposed design method is very simple to use, and is sufficiently general to construct low-delay wavelet bases with flexible length, delay, and number of zero at π (or 0) in their analysis filters. Several design examples are given to demonstrate the usefulness of the proposed method

Ingredient selection for plastic composite supports for L-(+)-lactic acid biofilm fermentation by Lactobacillus casei subsp. rhamnosus

Plastic composite supports containing 50% agricultural products (oat hulls, soybean hulls, yeast extract, soybean flour, dried bovine erythrocytes, bovine albumin, and/or mineral salts) and 50% (wt/wt) polypropylene were produced by high-temperature twin-screw extrusion. The research employed two half sets of a five-factorial fractional design (2(5 - 1)) to evaluate the effects of different agricultural components on the properties of the plastic composite supports and to select the best plastic composite support formulation for lactic acid fermentation. The biofilm population was affected by the contact angle and relative hydrophobicity of the supports (r = 0.79 to 0.82). Lactic acid was produced by the suspended cells (r = 0.96) and the biofilm on the plastic composite support discs (r = 0.85). Incorporation of yeast extract into plastic composite supports enhanced growth of free and attached cells in minimal medium (P \u3c 0.0001). The presence of soybean hulls, yeast extract, or mineral salts in plastic composite supports produced less hydrophobic supports (P \u3c 0.0001) and enhanced cell attachment (P \u3c 0.03). Under all conditions, suspended-cell and polypropylene disc controls gave negligible lactic acid production and cell density. Plastic composite supports containing soybean hulls, yeast extract, soybean flour, bovine albumin, and mineral salts gave the highest biofilm population (2.3 x 10(9) CFU/g of support), cell density (absorbance of 1.8 at 620 nm), and lactic acid concentration (7.6 g/liter) in minimal medium

Rapid optimization of stationary tokamak plasmas in RAPTOR: demonstration for the ITER hybrid scenario with neural network surrogate transport model QLKNN

This work presents a fast and robust method for optimizing the stationary radial distribution of temperature, density and parallel current density in a tokamak plasma and its application to first-principle-based modeling of the ITER hybrid scenario. A new solver is implemented in the RAPTOR transport code, enabling direct evaluation of the stationary solution to which the radial plasma profiles evolve. Coupled to a neural network emulation of the quasi-linear gyrokinetic QuaLiKiz transport model (QLKNN-hyper-10D), a first-principle-based estimate of the stationary state of the core plasma can be found at unprecedented computational speed (typically a few seconds on standard hardware). The stationary state solver is then embedded in a numerical optimization scheme, allowing the optimization of tokamak plasma scenarios in only a few minutes. The proposed method is applied to investigate the performance of ITER hybrid scenarios at different values of total plasma current, plasma density and pedestal height and for different power contributions in a heating mix consisting of electron cyclotron and neutral beam heating. Optimizing the radial distribution of electron cyclotron current drive (ECCD) deposition, the q profile is tailored to maximize the fusion gain Q, by maximizing the energy confinement predicted through the first-principles-based transport model, while satisfying q &gt; 1, avoiding sawtooth oscillations. It is found that optimal use of ECCD in ITER hybrid scenarios is to deposit power as close to the core as possible, while maintaining sufficient off-axis current drive to keep q above 1. Upper limits for the fusion gain Q are shown to be constrained either by minimum power requirements for the separatrix power flow to maintain H-mode or by minimum current drive requirements for q profile tailoring. Finally, it is shown that the ITER hybrid scenario operating window is significantly extended by an upgrade of the electron cyclotron power to 40 MW.</p

Neural network surrogate of QuaLiKiz using JET experimental data to populate training space

Within integrated tokamak plasma modeling, turbulent transport codes are typically the computational bottleneck limiting their routine use outside of post-discharge analysis. Neural network (NN) surrogates have been used to accelerate these calculations while retaining the desired accuracy of the physics-based models. This paper extends a previous NN model, known as QLKNN-hyper-10D, by incorporating the impact of impurities, plasma rotation, and magnetic equilibrium effects. This is achieved by adding a light impurity fractional density (n imp,light/n e) and its normalized gradient, the normalized pressure gradient (α), the toroidal Mach number (M tor), and the normalized toroidal flow velocity gradient. The input space was sampled based on experimental data from the JET tokamak to avoid the curse of dimensionality. The resulting networks, named QLKNN-jetexp-15D, show good agreement with the original QuaLiKiz model, both by comparing individual transport quantity predictions and by comparing its impact within the integrated model, JINTRAC. The profile-averaged RMS of the integrated modeling simulations is &lt;10% for each of the five scenarios tested. This is non-trivial given the potential numerical instabilities present within the highly nonlinear system of equations governing plasma transport, especially considering the novel addition of momentum flux predictions to the model proposed here. An evaluation of all 25 NN output quantities at one radial location takes ∼0.1 ms, 104 times faster than the original QuaLiKiz model. Within the JINTRAC integrated modeling tests performed in this study, using QLKNN-jetexp-15D resulted in a speed increase of only 60–100 as other physics modules outside of turbulent transport become the bottleneck.</p

Higher order parametric X-ray spectra in mosaic graphite and single silicon crystals

We have observed up to eight orders (n) in the spectra of parametric x-radiation, in the range 5-40 keV, produced by the interaction of a 90 Mev electron beam with mosaic graphite and 90 and 35 Mev beams with single silicon crystals. The measured yields and intensity ratios, I(2)/I(n= I), in graphite are not in agreement with the theory of PXR for mosaic crystals. In comparison, the yield and ratios of intensities in silicon are close to the predictions of PXR theory for perfect crystals. The bandwidths of spectral lines measured in both silicon and graphite are in good agreement with theoretical predictions, and are determined by the angular field of view of the detector.U.S. Department of EnergyDNANaval Postgraduate SchoolContract No. DE-FG03-91ER8109

Visual 3-D SLAM from UAVs

The aim of the paper is to present, test and discuss the implementation of Visual SLAM techniques to images taken from Unmanned Aerial Vehicles (UAVs) outdoors, in partially structured environments. Every issue of the whole process is discussed in order to obtain more accurate localization and mapping from UAVs flights. Firstly, the issues related to the visual features of objects in the scene, their distance to the UAV, and the related image acquisition system and their calibration are evaluated for improving the whole process. Other important, considered issues are related to the image processing techniques, such as interest point detection, the matching procedure and the scaling factor. The whole system has been tested using the COLIBRI mini UAV in partially structured environments. The results that have been obtained for localization, tested against the GPS information of the flights, show that Visual SLAM delivers reliable localization and mapping that makes it suitable for some outdoors applications when flying UAVs

Metabolomic analysis of low and high biofilm-forming Helicobacter pylori strains

The biofilm-forming-capability of Helicobacter pylori has been suggested to be among factors influencing treatment outcome. However, H. pylori exhibit strain-to-strain differences in biofilm-forming-capability. Metabolomics enables the inference of spatial and temporal changes of metabolic activities during biofilm formation. Our study seeks to examine the differences in metabolome of low and high biofilm-formers using the metabolomic approach. Eight H. pylori clinical strains with different biofilm-forming-capability were chosen for metabolomic analysis. Bacterial metabolites were extracted using Bligh and Dyer method and analyzed by Liquid Chromatography/Quadrupole Time-of-Flight mass spectrometry. The data was processed and analyzed using the MassHunter Qualitative Analysis and the Mass Profiler Professional programs. Based on global metabolomic profiles, low and high biofilm-formers presented as two distinctly different groups. Interestingly, low-biofilm-formers produced more metabolites than high-biofilm-formers. Further analysis was performed to identify metabolites that differed significantly (p-value < 0.005) between low and high biofilm-formers. These metabolites include major categories of lipids and metabolites involve in prostaglandin and folate metabolism. Our findings suggest that biofilm formation in H. pylori is complex and probably driven by the bacterium' endogenous metabolism. Understanding the underlying metabolic differences between low and high biofilm-formers may enhance our current understanding of pathogenesis, extragastric survival and transmission of H. pylori infections