Abstract
Raven is a Multi Object Adaptive Optics (MOAO) technical and science demonstrator which had its first light at the Subaru telescope on May 13-14, 2014. Raven was built and tested at the University of Victoria AO Lab before shipping to Hawai`i. Raven includes three open loop wavefront sensors (WFSs), a central laser guide star WFS, and two independent science channels feeding light to the Subaru IRCS spectrograph. Raven supports different kinds of AO correction: SCAO, open-loop GLAO and MOAO. The MOAO mode can use different tomographic reconstructors, such as Learn-&-Apply or a model-based reconstructor. This paper presents the latest results obtained in the lab, which are consistent with simulated performance, as well as preliminary on-sky results, including echelle spectra from IRCS. Ensquared energy obtained on sky in 140mas slit is 17%, 30% and 41% for GLAO, MOAO and SCAO respectively. This result confirms that MOAO can provide a level of correction in between GLAO and SCAO, in any direction of the field of regard, regardless of the science target brightness.

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Abstract
This paper presents the state of the art on interoperability developments for the social and solidarity economy (SSE) community web based information systems (WIS); it also presents a framework of interoperability for the SSE' WIS and the developments made in a research-in-progress PhD project in the last 3 years. A search on the bibliographic databases showed that so far there are no papers on interoperability initiatives on the SSE, so it was necessary to have other sources of information: a preliminary analysis of the WIS that support SSE activities; and interviews with the representatives of some of the world's most important SSE organisations. The study showed that the WIS are still not interoperable yet. In order to become interoperable a group of the SSE community has been developing a Dublin Corre Application Profile to be used by the SSE community as reference and binding to describe their resources. This paper also describes this on-going process. Copyright © 2014, IGI Global.

Abstract
This work focuses on the development of a pressure-loop controller for a hybrid brake-by-wire system, composed of a hydraulic link and an electro-mechanical actuator. Towards this goal, we will start by constructing a reduced model that is capable of capturing the fundamental dynamics of the actuator, which is particularly useful for control design purposes. Motivated by the large friction disturbances that affect the system, we also investigate linear-in-the-parameter models suitable for (online) model-based friction compensation. More specifically, results from the theory of function approximation, together with optimization techniques, are explored to approximate the Stribeck friction model through a linear-in-the-parameter model. This new linear-in-the-parameter model is then employed in the design of a control law for tracking the braking pressure of the hybrid brake-by-wire. The main features of this controller are the robustness to parametric uncertainties, thanks to the inclusion of a switching-sigma adaptive mechanism, and the attenuation of non-parametric disturbances with a continuous sliding mode action. The stability and robustness properties of the closed-loop system are investigated with the help of the Lyapunov method. Finally, experimental tests demonstrate the effectiveness of the proposed approach and its ability to handle disturbances.

Abstract
This paper determines to within a single measurement the minimum number of measurements required to successfully reconstruct a signal drawn from a Gaussian mixture model in the low-noise regime. The method is to develop upper and lower bounds that are a function of the maximum dimension of the linear subspaces spanned by the Gaussian mixture components. The method not only reveals the existence or absence of a minimum mean-squared error (MMSE) error floor (phase transition) but also provides insight into the MMSE decay via multivariate generalizations of the MMSE dimension and the MMSE power offset, which are a function of the interaction between the geometrical properties of the kernel and the Gaussian mixture. These results apply not only to standard linear random Gaussian measurements but also to linear kernels that minimize the MMSE. It is shown that optimal kernels do not change the number of measurements associated with theMMSE phase transition, rather they affect the sensed power required to achieve a target MMSE in the low-noise regime. Overall, our bounds are tighter and sharper than standard bounds on the minimum number of measurements needed to recover sparse signals associated with a union of subspaces model, as they are not asymptotic in the signal dimension or signal sparsity.

Abstract
Background: An increasingly aging society and consequently rising number of patients with poststroke-related neurological dysfunctions are forcing the rehabilitation field to adapt to ever-growing demands. Although clinical reasoning within rehabilitation is dependent on patient movement performance analysis, current strategies for monitoring rehabilitation progress are based on subjective time-consuming assessment scales, not often applied. Therefore, a need exists for efficient nonsubjective monitoring methods. Wearable monitoring devices are rapidly becoming a recognized option in rehabilitation for.quantitative measures. Developments in sensors, embedded technology, and smart textile are driving rehabilitation to adopt an objective, seamless, efficient, and cost-effective delivery system. This study aims to assist physiotherapists' clinical reasoning process through the incorporation of accelerometers as part of an electronic data acquisition system. Methods: A simple, low-cost, wearable device for poststroke rehabilitation progress monitoring was developed based on commercially available inertial sensors. Accelerometry data acquisition was performed for 4 first-time poststroke patients during a reach-press-return task. Results: Preliminary studies revealed acceleration profiles of stroke patients through which it is possible to quantitatively assess the functional movement, identify compensatory strategies, and help define proper movement. Conclusion: An inertial data acquisition system was designed and developed as.a low-cost option for monitoring rehabilitation. The device seeks to ease the data-gathering process by physiotherapists to complement current practices with accelerometry profiles and aid the development of quantifiable methodologies and protocols.