Abstract
This paper presents a new multi-agent decision support system with the purpose of aiding bilateral contract negotiators in the pre-negotiation phase, through the analysis of their possible opponents. The application area of this system is the electricity market, in which players trade a certain volume of energy at a specified price. Consequently, the main output of this system is the recommendation of the best opponent(s) to trade with and the target energy volume to trade with each of the opponents. These recommendations are achieved through the analysis of the possible opponents' past behavior, namely by learning on their past actions. The result is the forecasting of the expected prices against each opponent depending on the volume to trade. The expected prices are then used by a game-theory based model, to reach the final decision on the best opponents to negotiate with and the ideal target volume to be negotiated with each of them.

Abstract
Model-based matrix-free wavefront reconstruction algorithms have proven to provide highly accurate results for both Shack-Hartmann and pyramid wavefront sensors in various simulation environments (OCTOPUS, YAO, COMPASS, OOMAO). Previously, test bench as well as on-sky tests were performed with the CuReD for the Shack-Hartmann sensor providing a convincing performance level together with highly reduced computational efforts. The P-CuReD is a method with linear complexity for wavefront reconstruction from pyramid sensor data which employs the CuReD algorithm and a data preprocessing step converting pyramid signals into Shack-Hartmann-like data. Here we present experimental results for the pyramid sensor being controlled with the P-CuReD on the LOOPS test bench of the Laboratoire d’Astrophysique de Marseille. Through the example of the P-CuReD a comparison of control using matrix-free Fourier domain based methods to standard interaction-matrix-based approaches is provided.

Abstract
While the effects of innovation on employment have been a controversial issue in economic literature for several years, this economic puzzle is particularly relevant nowadays. We are witnessing tremendous technological developments which threaten to disrupt the labour market, due to their potential for significantly automating human labour. As such, this paper presents a qualitative study of the dynamics underlying the relationship between innovation and employment, using an agent-based model developed in Python. The model represents an economy populated by firms able to perform either Product Innovation (leading to the discovery of new tasks, which require human labour) or Process Innovation (leading to the automation of tasks previously performed by humans). The analysis led to three major conclusions, valid in this context. The first takeaway is that the Employment Rate in a given economy is dependent on the automation potential of the tasks in that economy and dependent on the type of innovation performed by firms in that economy (with Product Innovation having a positive effect on employment and Process Innovation having a negative effect). Second, in any given economy, if firms' propensity for product and process innovation, as well as the automation potential of their tasks are stable over time, the Employment Rate in that economy will tend towards stability over time. The third conclusion is that higher levels of Process Innovation and lower levels of Product Innovation, lead to a more intense decline of wage shares and to a wider gap between employee productivity growth and wage growth.

Abstract
The Robot Operating System (ROS) is one of the most popular open source robotic frameworks, and has contributed significantly to the fast development of robotics. Even though ROS provides many ready-made components, a robotic system is inherently complex, in particular regarding the architecture and orchestration of such components. Availability and analysis of a system's architecture at compile time is fundamental to ease comprehension and development of higher-quality software. However, ROS developers have to overcome this complexity relying mostly on testing and runtime visualisers. This work aims to enhance static-time support by proposing, firstly, a metamodel to describe the software architecture of ROS systems (the ROS Computation Graph) and, secondly, model extraction and visualisation tools for such architectural models. The provided tools allow users to specify custom-made queries over these models, enabling the static verification of relevant properties that had to be (manually) checked at runtime before.

Abstract
Each person carries digital devices that communicate with other person's devices and may transmit sensitive data. When the transmitted data is sensitive, it becomes necessary to implement secure mechanisms to hide the information and thus avoid it from being analyzed by third parties. This paper aims to present Ncryptr, a web-based application that allows its users to exchange encrypted instant messages in real time. Outside parties are unable to extract the contents of the messages exchanged between two or more users. Ncryptr allows its users to choose the type of encryption employed, being this a major distinction with others already existing instant messaging applications. The performance analysis is made by comparing the efficiency and latency time of different encryption methods, showing the pros and cons of using each one.

Abstract
Some coronagraph masks can be turned into wave front sensing masks thanks to minor modification. For instance, one only has to divide by two the depth of the central well to convert the Roddier & Roddier coronograph into the Zernike wave front sensor (WFS). Physically, the opposition of phase in coronagrapy becomes a quadrature phase in wave front sensing. Here, we replicate this idea to the Four Quadrant Phase Mask (FQPM) coronagraph by introducing a sensor that we call the iQuad WFS, generated by a mask which has the same geometrical structure as the FQPM but with a modified differential piston. An optical and mathematical description of this new WFS is firstly provided showing its great elegance and the central role played by the Hilbert transform in its understanding. We then compare its performance criteria with two classical wave front sensors. We finally show the iQuad sensor has major similarities to the Pyramid sensor making it a wonderful theoretical object to improve our understanding of this sensor.