Abstract
In preparation of future multiobject spectrographs (MOS) whose one of the major role is to provide an extensive statistical studies of high redshifted galaxies surveyed, the demonstrator CANARY has been designed to tackle technical challenges related to open-loop adaptive optics (AO) control with jointed Natural Guide Star and Laser Guide Star tomography. We have developed a point spread function (PSF) reconstruction algorithm dedicated to multiobject adaptive optics systems using system telemetry to estimate the PSF potentially anywhere in the observed field, a prerequisite to postprocess AO-corrected observations in integral field spectroscopy. We show how to handle off-axis data to estimate the PSF using atmospheric tomography and compare it to a classical approach that uses on-axis residual phase from a truth sensor observing a natural bright source. We have reconstructed over 450 on-sky CANARY PSFs and we get bias/1-s standard-deviation (std) of 1.3/4.8 on the H-band Strehl ratio (SR) with 92.3% of correlation between reconstructed and sky SR. On the full-width at half-maximum, we get, respectively, 2.94 mas, 19.9 mas, and 88.3% for the bias, std, and correlation. The reference method achieves 0.4/3.5/95% on the SR and 2.71 mas/14.9 mas/92.5% on the FWHM for the bias/std/correlation.

Abstract
Today, the variety of complex products, low volume and decreasing life cycles require a combination of multiple skills that, often, do not exist in a single organization. This raises the need to extend the traditional organization towards the extended virtual enterprise. During the last decade several research projects developed concepts, methods and tools to support the design and operation of the virtual enterprises. However, the impact in industry remains low mainly due to the lack of vertical and horizontal integration, both at business and technical level. Industry 4.0 may be the missing enabler for effective virtual enterprises, once it integrates both business entities and technical entities into a single concept - the Industry 4.0 component - thus enabling enhanced interoperability. This paper presents innovative Industry 4.0 approaches, concepts, methods and tools applied to real manufacturing environments, showing how they enable the creation of cyber-physical production systems leading to a flexible, efficient and seamlessly virtual enterprise.

Abstract
Among renewable power sources, wind energy is the most promising technology; however, the inter-temporal uncertainty of this source makes impossible its massive integration. Forecasting of wind generation is a key factor for the economical operation of the power system. Thus, the error related to this process is typically modeled by means of a determined probability distribution to be later incorporated to the unit scheduling and load dispatch optimization procedures. In this paper, wind power forecasting error has been modeled by using Weibull and Levy alpha-stable probability distributions and incorporated to the economic dispatch problem in order to probabilistically describe power production and generating cost. The proposed methodology is illustrated by analyzing a case study composed by 13 conventional generators; the obtained results are compared with Monte Carlo Simulation approach for evaluating and testing the capabilities of the proposed model, observing reasonable accuracy on the estimated results.

Abstract
Smart Cities are a key application domain for the Internet of Things (IoT), and it is coming nearer everyday through pilot trials and deployments in various cities around the world. In Porto, Portugal, a city-wide IoT Living Lab emerged after we deployed several testbeds, e.g. harbour and a city-scale vehicular networks, and carried out various experiments with the SenseMyCity crowdsensor. In this paper, we discuss how a standard Machine-to-Machine (M2M) middleware is a key enabler of our e-health platform and SenseMyCity crowdsensor, powered by the use of smartphones as M2M gateways. M2M standards provided by ETSI/oneM2M are essential for a paradigm shift, aiming at making the IoT truly interoperable without the need for human intervention. In this work, we map two applications that rely on the role of a smartphone as a gateway, which acts as a proxy to connect legacy devices to the IoT using a standard middleware. We illustrate the advantages of using M2M, and, as a proof-of-concept, we measure and quantify the energy savings obtained, showing improvements of smartphones' battery life.

Abstract
In tomographic adaptive-optics (AO) systems, errors due to tomographic wavefront reconstruction limit the performance and angular size of the scientific field of view (FoV), where AO correction is effective. We propose a multi time-step tomographic wavefront reconstruction method to reduce the tomographic error by using measurements from both the current and previous time steps simultaneously. We further outline the method to feed the reconstructor with both wind speed and direction of each turbulence layer. An end-to-end numerical simulation, assuming a multi-object AO (MOAO) system on a 30 m aperture telescope, shows that the multi timestep reconstruction increases the Strehl ratio (SR) over a scientific FoV of 10 arc min in diameter by a factor of 1.5-1.8 when compared to the classical tomographic reconstructor, depending on the guide star asterism and with perfect knowledge of wind speeds and directions. We also evaluate the multi time-step reconstruction method and the wind estimation method on the RAVEN demonstrator under laboratory setting conditions. The wind speeds and directions at multiple atmospheric layers are measured successfully in the laboratory experiment by our wind estimation method with errors below 2 ms-1. With these wind estimates, the multi time-step reconstructor increases the SR value by a factor of 1.2-1.5, which is consistent with a prediction from the end-to-end numerical simulation.

Abstract
In this work, we study the phenomena of dumping in a duopoly market through an infinitely repeated game. We consider two firms of different countries competing in the same country. When both firms are cooperating, if the foreign firm deviates from cooperation this can be interpreted as dumping and a period of punishment can be imposed to the foreign firm. After this, firms can play continuously the deviation-punishment game or compete à la Cournot. Previously, we observe that the repeated strategy of deviation-punishment is not adopted in the case of symmetric demand equations. Here, we observe that this strategy of repeated dumping can appear as the best repeated strategy when the demand equations are non-symmetric. © Springer-Verlag Berlin Heidelberg 2016.