Abstract
This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed. © Springer International Publishing Switzerland 2017.

Abstract
Machine Learning (ML) has been successfully applied to a wide range of domains and applications. One of the techniques behind most of these successful applications is Ensemble Learning (EL), the field of ML that gave birth to methods such as Random Forests or Boosting. The complexity of applying these techniques together with the market scarcity on ML experts, has created the need for systems that enable a fast and easy drop-in replacement for ML libraries. Automated machine learning (autoML) is the field of ML that attempts to answers these needs. We propose autoBagging, an autoML system that automatically ranks 63 bagging workflows by exploiting past performance and metalearning. Results on 140 classification datasets from the OpenML platform show that autoBagging can yield better performance than the Average Rank method and achieve results that are not statistically different from an ideal model that systematically selects the best workflow for each dataset. For the purpose of reproducibility and generalizability, autoBagging is publicly available as an R package on CRAN.

Abstract
Tactical production-distribution "planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.

Abstract
This paper describes an enhanced model for the Short Term Hydro Scheduling Problem, HSP, that includes the impact of operation decisions on the market prices and the possibility of adjusting the tailwater level and the generation and pumping efficiencies as a function of the flow. The solution approach uses an iterative procedure that solves in each iteration a linearized HSP problem using the linprog function of the MATLAB (R) Optimization Toolbox and that updates the value of the head to be used in the next iteration. The paper also includes results from a realistic Case Study based on the cascade of 9 hydro stations (4 of them with pumping) installed in the Portuguese section of the Douro River.

Abstract
In response to recent calls for further cross-disciplinary research on austerity and a deeper sociological understanding of the impact and aftermath of the economic crisis on individuals and societies, this article builds on extant austerity literature through an exploration of its effects on European men. Informed by theories of liminality and rites of passage, this qualitative investigation examines the experience of austerity from the perspective of 11 men through the three liminal stages of separation, transition and reaggregation and investigates its impact on their identity, responsibilities and expectations. Our findings reveal the negative experiences of alienation and outsiderhood alongside positive experiences of communitas, solidarity and comradeship. The study provides a nuanced understanding of modern male Europeans and their rites of passage' through austere times.

Abstract
The Pyramid wave-front sensor (WFS) is currently the baseline for several future adaptive optics (AO) systems, including the First light systems planned for the era of Extremely Large Telescopes (ELTs). Extensive investiga-tion into the Pyramid WFS aim to prepare for this new generation of AO systems, characterizing its behavior under realistic conditions and developing experimental procedures to optimise performance. An AO bench at Laboratoire d'Astrophysique de Marseille has been developed to analyze the behavior of the Pyramid and develop the necessary operational and calibration routines to optimize performance. The test bench comprises a Pyramid WFS, an ALPAO 9-9 deformable mirror (DM), a rotating phase screen to simulate atmospheric turbulence and imaging camera. The Pyramid WFS utilizes the low noise OCAM2 camera to image the four pupils and real time control is realized using the adaptive optics simulation software OOMAO (Object Oriented Matlab Adaptive Optics toolbox).1 Here we present the latest experimental results from the Pyramid test bench, including comparison with current Pyramid models and AO simulations. We focus on the calibration of the AO system and testing the impact of non-linear effects on the performance of the Pyramid. The results demonstrate good agreement with our current models, in particular with the addition of more realistic elements: non-common path aberrations and the optical quality of the Pyramid prism.