Abstract
We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results presented in Correia and Teixeira [J. Opt. Soc. Am. A 31, 2763 (2014)] to the closed-loop case with predictive controllers and generalize the analytical modeling of Rigaut et al. [Proc. SPIE 3353, 1038 (1998)], Flicker [Technical Report (W. M. Keck Observatory, 2007)], and Jolissaint [J. Eur. Opt. Soc. 5, 10055 (2010)]. We follow closely the developments of Ellerbroek [J. Opt. Soc. Am. A 22, 310 (2005)] and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors while minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that ~60 nm rms error reduction can be achieved with the distributed Kalman filter embodying antialiasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ?/D separations (~1 - 5?/D) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

Abstract
Electricity markets are not only a new reality but also a constantly evolving sector, due to the high frequency of changes in their rules. Simulation tools combined with Artificial Intelligence techniques, particularly multi-agent simulation, can result in a sophisticated and very useful tool in this context.

Abstract
We consider the problem of robust model predictive control for linear sampled data dynamical systems subject to state and control constraints and additive and bounded disturbances. We propose a rigid tube model predictive control algorithm utilizing recent and topologically compatible notions for the sampled data forward reach sets as well as robust positively invariant sets. The proposed method inherits almost all desirable features associated with rigid tube model predictive control of discrete-time systems, and, in addition, it ensures robust constraint satisfaction and safety in a continuous-time sense.

Abstract
Virtual Reality environments are able to other natural interaction metaphors. However, it is dicult to accurately place virtual objects in the desired position and orientation using gestures in mid-air. Previous research concluded that the separation of degrees-of-freedom (DOF) can lead to beer results, but these benets come with an increase in time when performing complex tasks, due to the additional number of transformations required. In this work, we assess whether custom transformation axes can be used to achieve the accuracy of DOF separation without sacricing completion time. For this, we developed a new manipulation technique, MAiOR, which oers translation and rotation separation, supporting both 3-DOF and 1-DOF manipulations, using personalized axes for the laer. Additionally, it also has direct 6-DOF manipulation for coarse transformations, and scaled object translation for increased placement. We compared MAiOR against an exclusively 6-DOF approach and a widget-based approach with explicit DOF separation. Results show that, contrary to previous research suggestions, single DOF manipulations are not appealing to users. Instead, users favored 3-DOF manipulations above all, while keeping translation and rotation independent.

Abstract
We propose the use of modern proof assistants to specify, implement, and verify password quality checkers. We use the proof assistant Coq, focusing on Linux PAM, a widely-used implementation of pluggable authentication modules for Linux. We show how password quality policies can be expressed in Coq and how to use Coq’s code extraction features to automatically encode these policies as PAM modules that can readily be used by any Linux system. We implemented the default password quality policy shared by two widely-used PAM modules: pam_cracklib and pam_pwquality. We then compared our implementation with the original modules by running them against a random sample of 100,000 leaked passwords obtained from a publicly available database. In doing this, we demonstrated a potentially serious bug in the original modules. The bug was reported to the maintainers of Linux PAM and is now fixed.

Abstract
Although there are several studies analysing how innovation capabilities influence export performance, this study aims to present the impact of a set of internal innovation capabilities on export performance of small and medium-sized firms (SMEs), with the mediating role of entrepreneurial orientation contingent upon the proactive or reactive behaviour of the firms to external stimuli. The study involves the analysis of 147 questionnaire-based survey of managers from plastic manufacturing SMEs operating in Portugal that were subjected to a Partial Least Squares-Structural Equation Modelling (PLS-SEM) technique. The results show that proactive firms to external stimuli are not only better at innovating but also their entrepreneurial orientation capabilities underpin a better performance in international markets when compared with firms that react to external stimuli. This study has implications for SMEs aiming at increasing their export performance and innovativeness. For practitioners the findings of this study should enable SMEs owner/managers to better understand the possible impacts of innovation capabilities and entrepreneurial orientation on export performance, and thus lead to more effective SMEs management.