Abstract
Contemporary AO systems, such as the Multi-Object Adaptive Optics system (MOAO) RAVEN currently associated with the Subaru Telescope, can suffer from significant Non-Common Path Aberrations (NCPA). These errors ultimately affect image quality and arise from optical path differences between the wavefront sensor (WFS) path and the science path. A typical correction of NCPA involves estimating the aberration phase and correcting the system with an offset on the deformable mirror (DM). We summarize two methods used to correct for NCPA on an experimental bench. We also successfully calibrate the NCPA on RAVEN using one of these methods. Finally, we report on some first science results with RAVEN, obtained after NCPA correction.

Abstract
Raven is a Multi-Object Adaptive Optics science demonstrator which has been used on-sky at Subaru telescope from May 2014 to July 2015. Raven has been developed at the University of Victoria AO Lab, in partnership with NRC, NAOJ and Tohoku University. Raven includes three open loop WFSs, a central laser guide star WFS, and two science pick-off arms feeding light to the Subaru IRCS spectrograph. Raven supports different AO modes: SCAO, open-loop GLAO and MOAO. This paper gives an overview of the instrument design, compares the on-sky performance of the different AO modes and presents some of the science results achieved with MOAO.

Abstract
Multi-object astronomical adaptive optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arcminutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular linear-quadratic-Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [J. Opt. Soc. Am. A 31, 101 (2014)], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wavefronts are never explicitly estimated in the volume, providing considerable computational savings on 10-m-class telescopes and beyond. We find that for Raven, a 10-m-class MOAO system with two science channels, the SA-LQG improves the limiting magnitude by two stellar magnitudes when both the Strehl ratio and the ensquared energy are used as figures of merit. The sky coverage is therefore improved by a factor of ~5. © 2015 Optical Society of America.

Abstract
Multi-object astronomical adaptive optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arcminutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular linear-quadratic-Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [J. Opt. Soc. Am. A 31, 101 (2014)], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wavefronts are never explicitly estimated in the volume, providing considerable computational savings on 10-m-class telescopes and beyond. We find that for Raven, a 10-m-class MOAO system with two science channels, the SA-LQG improves the limiting magnitude by two stellar magnitudes when both the Strehl ratio and the ensquared energy are used as figures of merit. The sky coverage is therefore improved by a factor of similar to 5. (C) 2015 Optical Society of America

Abstract
Obstructive Sleep Apnea (OSA) is a disease that affects approximately 4% of men and 2% of women worldwide but is still underestimated and underdiagnosed. The standard method for assessing this index, and therefore defining the OSA diagnosis, is polysomnography (PSG). Previous work developed relevant Bayesian network models but those were based only on variables univariatedly associated with the outcome, yielding a bias on the possible knowledge representation of the models. The aim of this work was to develop and validate new Bayesian network decision support models that could be used during sleep consult to assess the need for PSG. Bayesian models were developed using a) expert opinion, b) hill-climbing, c) naive Bayes and d) TAN structures. Resulting models validity was assessed with in-sample AUC and stratified cross-validation, also comparing with previously published model. Overall, models achieved good discriminative power (AUC>70%) and validity (measures consistently above 70%). Main conclusions are a) the need to integrate a wider range of variables in the final models and b) the support of using Bayesian networks in the diagnosis of obstructive sleep apnea.

Abstract
Liquid Nitrogen is one of the key refrigerating elements in cooling near infrared science instruments to reduce the dark, readout noises and thermal emissions in the near infrared originated from the instrument structure. Usually, a small liquid nitrogen tank connected to the near infrared instrument is auto filled from a large Dewar in order to maintain required low temperatures during the experiment for several hours. The detectors used in these instruments are quite expensive and they need to be cooled down steadily (< 2K/min) to avoid mechanical damage. The steady state cooling of the detector is the key requirement to be considered while cooling down the detector. In this paper, a controller is developed to auto-fill the liquid nitrogen tank and also to keep the refrigeration rate of the detector below 2K/min. A systematic survey of auto-filling controllers is studied. The auto-filling of liquid nitrogen from Dewar to tank is implemented with a standard on-off controller. To address the critical refrigeration rate of the detector, two approaches are studied: a) by fixed time pumping; b) by feedback the detector cooling rate. In this work we have used inexpensive equipment to develop this controller. It is very successfully used for GRAVITY acquisition camera, a near infrared instrument for European Southern Observatory. This controller has been stable and efficient for our experiment. This low cost controller can be used for any student laboratory and research.