Abstract
In the last decade, the level of variable renewable energy sources (RESs) integrated in distribution network systems have been continuously growing. This adds more uncertainty to the system, which also faces all traditional sources of uncertainty and those pertaining to other emerging technologies such as demand response and electric vehicles. As a result, distribution system operators are finding it increasingly difficult to maintain an optimal daily operation of such systems. Such challenges/limitations are expected to be alleviated when distribution systems undergo the transformation process to smart grids, equipped with appropriate technologies such as energy storage systems (ESSs) and switchable capacitor banks (SCBs). These technologies offer more flexibility in the system, allowing effective management of the uncertainty in RESs. This paper presents a stochastic mixed integer linear programming (SMILP) model, aiming to optimally operate distribution network systems, featuring variable renewables, and minimizing the impact of RES uncertainty on the system's overall performance via ESSs and SCBs. A standard 41-bus distribution system is employed to show the effectiveness of the proposed S-MILP model. Simulation results indicate that strategically placed ESSs and SCBs can substantially alleviate the negative impact of RES uncertainty in the considered system.

Abstract
In this paper we introduce a new Android library, called ULTEMAT, for the delivery of ecological momentary assessments (EMAs) on mobile devices and we present its use in the MoodBuster app developed in the H2020 E-COMPARED project. We discuss context-aware, or event-based, triggers for the presentation of EMAs and discuss the potential they have to improve the effectiveness of mobile provision of mental health interventions as they allow for the delivery of assessments to the patients when and where these are most appropriate. Following this, we present the abilities of ULTEMAT to use such context-aware triggers to schedule EMAs and we discuss how a similar approach can be used for Ecological Momentary Interventions (EMIs).

Abstract
Here we present the first results from a MUSE/X-Shooter study of the jet from the classical T Tauri star TH 28. The combination of MUSE and X-Shooter enables us to take advantage of both spectro-imaging and broadband spectroscopy to comprehensively investigate the TH 28 jet. We present a MUSE spectro-image and PV plot of the Ha emission line and use flux ratios from the X-Shooter spectrum to estimate the mass accretion rate at log(?acc) = -9.4. Future work will focus on diagnostic analyses on both sets of data, including estimating the mass outflow rate (?out) and the extinction of the jet. © SAIt 2017.

Abstract
We design a graph-based framework for the analysis of access control policies that aims at easing the specification and verification tasks for security administrators. We consider policies in the category-based access control model, which has been shown to subsume many of the most well known access control models (e.g., MAC, DAC, RBAC). Using a graphical representation of category-based policies, we show how answers to usual administrator queries can be automatically computed, and properties of access control policies checked. We show applications in the context of emergency situations, where our framework can be used to analyse the interaction between access control and emergency management.

Abstract
This paper proposes and investigates a multilevel ac six-phase motor drive. The system is composed of five isolated three-leg voltage source inverters feeding the open-end windings of an asymmetrical six-phase induction motor (SPIM), which is adequate to generate multilevel voltages for high-power systems with voltage rating restrictions. A simple space vector pulse-width modulation (PWM) based on three similar individual planes and its implementation by means of equivalent level-shifted PWM are presented. A space vector pattern with a high number of voltage vectors redundancies is obtained. These redundancies and the application sequence of the voltage vectors are selected to minimize the amount of changes in the switching states and to decrease the harmonic distortion of the generated voltages. The vector pattern of this optimal modulation is obtained by analyzing only one plane and applied in the same way to the three planes as if they were independent. The developed PWM techniques have low computational complexity and are suitable for low-cost hardware implementations. Simulation results are used to compare the proposed topology with a conventional configuration in terms of harmonic distortion and semiconductor losses. Experimental results demonstrate the feasibility of the proposed drive system.

Abstract
In privacy-preserving processing of outsourced data a Cloud server stores data provided by one or multiple data providers and then is asked to compute several functions over it. We propose an efficient methodology that solves this problem with the guarantee that a honest-but-curious Cloud learns no information about the data and the receiver learns nothing more than the results. Our main contribution is the proposal and efficient instantiation of a new cryptographic primitive called Labeled Homomorphic Encryption (labHE). The fundamental insight underlying this new primitive is that homomorphic computation can be significantly accelerated whenever the program that is being computed over the encrypted data is known to the decrypter and is not secret—previous approaches to homomorphic encryption do not allow for such a trade-off. Our realization and implementation of labHE targets computations that can be described by degree-two multivariate polynomials. As an application, we consider privacy preserving Genetic Association Studies (GAS), which require computing risk estimates from features in the human genome. Our approach allows performing GAS efficiently, non interactively and without compromising neither the privacy of patients nor potential intellectual property of test laboratories.