Abstract
Presently the interest in non-invasive devices for monitoring the cardiovascular system has increased in importance, especially in the diagnosis of some pathologies. The proposed optical device reveals an attractive instrumental solution for local pulse wave velocity (PWV) assessment and other hemodynamic parameters analysis, such as Augmentation Index (AIx), Subendocardial Viability Ratio (SEVR), Maximum Rate of Pressure Change (dP/dtmax) and Ejection Time Index (ETI). These parameters allow a better knowledge on the cardiovascular condition and management of many disease states. Two studies were performed in order to validate this technology. Firstly, a comparative test between the optical system and a gold-standard in PWV assessment was carried out. Afterwards, a large study was performed in 131 young subjects to establish carotid PWV reference values as well as other hemodynamic parameters and to find correlations between these and the population characteristics. The results allowed the use of this new technique as a reliable method to determine these parameters. For the total of subjects values for carotid PWV vary between 3-7.69 m s-1 a clear correlation with age and smoking status was found out. The Aix varies between -6.15% and 11.46% and exhibit a negative correlation with heart, and dP/dtmax parameter shows a significant decrease with age.

Abstract
The Arterial Pressure Waveform (APW) can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1) a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2) the acquired position and amplitude of onset, Systolic Peak (SP), Point of Inflection (Pi) and Dicrotic Wave (DW) were used for the computation of some morphological attributes; (3) pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4) classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic), J48 (decision tree) and RIPPER (rule-based induction); and (5) we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx). Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95%) and high area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (0.961). Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Abstract
A diffraction-limited 30-meters class telescope theoretically provides a 10 mas resolution limit in the near infrared. Modern coronagraphs offer the means to take full advantage of this angular resolution allowing to explore at high contrast, the innermost parts of nearby planetary systems to within a fraction of an astronomical unit: an unprecedented capability that will revolutionize our understanding of planet formation and evolution across the habitable zone. A precursor of such a system is the Subaru Coronagraphic Extreme AO project. SCExAO [9] uses advanced coronagraphic technique for high contrast imaging of exoplanets and disks as close as 1 ?/D from the host star. In addition to unusual optics, achieving high contrast at this small angular separation requires a wavefront sensing and control architecture which is optimized for exquisite control and calibration of low order aberrations. To complement the current near-IR wavefront control system driving a single MEMS type deformable mirror mounted on a tip-tilt mount, two high order and high sensitivity visible wavefront sensors have been integrated to SCEXAO: - a non-modulated Pyramid wavefront sensor (CHEOPS) which is a sensitivity improvement over modulated Pyramid systems now used in high performance astronomical AO, - a non-linear wavefront sensor [4] designed in 2012 by Subaru Telescope with the collaboration of the NRC-CNRC which is expected to improve significantly the achieved sensitivity of low order aberations measurements. We will present the CHEOPS last results measured in laboratory and during its first light downstream the Subaru AO188 instrument, and then conclude introducing the primary prototype of the SCExAO non-linear curvature wavefront sensor which is planned to be tested on sky in 2014.

Abstract
Laser-guide-star multiconjugate adaptive optics (MCAO) systems require natural guide stars (NGS) to measure tilt and tilt-anisoplanatism modes. Making optimal use of the limited number of photons coming from such, generally dim, sources is mandatory to obtain reasonable sky coverage, i.e., the probability of finding asterisms amenable to NGS wavefront (WF) sensing for a predefined WF error budget. This paper presents a Strehl-optimal (minimum residual variance) spatiotemporal reconstructor merging principles of modal atmospheric tomography and optimal stochastic control theory. Simulations of NFIRAOS, the first light MCAO system for the thirty-meter telescope, using ~500 typical NGS asterisms, show that the minimum-variance (MV) controller delivers outstanding results, in particular for cases with relatively dim stars (down to magnitude 22 in the H-band), for which lowtemporal frame rates (as low as 16 Hz) are required to integrate enough flux. Over all the cases tested ~21 nm rms median improvement in WF error can be achieved with the MV compared to the current baseline, a type-II controller based on a double integrator. This means that for a given level of tolerable residual WF error, the sky coverage is increased by roughly 10%, a quite significant figure. The improvement goes up to more than 20% when compared with a traditional single-integrator controller. © 2013 Optical Society of America.

Abstract
A new high-contrast imaging subtraction algorithm (TLOCI) is presented to maximize a planet signal-to-noise ratio. The technique uses an input spectrum and template PSFs to optimize the reference image coefficient determination to minimize the flux contamination via self-subtraction (thus maximizing its throughput wavelength per wavelength) of any planet that have a similar spectrum to the template spectrum in the image, while trying, at the same time, to maximize the speckle noise subtraction. The optimization is performed by a correlation matrix conditioning. Using laboratory Gemini Planet Imager data, the new algorithm is shown to be superior to the simple/double difference, polynomial fit and original LOCI algorithm. Copyright © 2013, International Astronomical Union.

Abstract
Non-linear curvature wave-front sensing (nlCWFS) delivers outstanding sensitivity and high dynamic range by lifting the linearity constraint of standard curvature wave-front sensing and working in the non-linear Fresnel (near-field) regime [Guyon, 2010]. The goals of this paper are twofold: 1) revisit the phase-diversity PD formalism and attempt to use this framework, originally developed for the Fraunhofer (far-field) regime, with nlCWFS signals and 2) develop formulae making explicit use of the Fresnel regime for later use with gradient-based non-linear minimisation methods.