Abstract
Advancing the field of research in Immersive Learning Environments requires avoiding the pitfalls of previous educational technologies. Studies must consider the actual use of these environments and the context where it occurs, not simply the technocentric perspectives on these environments. This paper provides an overview and analysis of surveys on this topic, in order to map the field and find out which information on actual uses of Immersive Learning Environments are reported, and hence which gaps need to be covered towards a robust, encompassing knowledge on their relationship with learning. Collected accounts of use were clustered via thematic analysis and contrasted with research areas in learning and technology, highlighting the gaps in the field and serving as a blueprint for research agendas on uses of immersive learning environments.

Abstract
The use of Autonomous Underwater Vehicles (AUVs) is increasingly seen as a cost-effective way to carry out underwater missions. Due to their long endurance and set of sensors onboard, AUVs may collect large amounts of data, in the order of Gbytes, which need to be transferred to shore. State of the art wireless technologies suffer either from low bitrates or limited range. Since surfacing may be unpractical, especially for deep sea operations, long-range underwater data transfer is limited to the use of low bitrate acoustic communications, precluding the timely transmission of large amounts of data. The use of data mules combined with short-range, high bitrate RF or optical communications has been proposed as a solution to overcome the problem. In this paper we describe the implementation and validation of UDMSim, a simulation platform for underwater data muling oriented systems that combines an AUV simulator and the Network Simulator 3 (ns-3). The results presented in this paper show a good match between UDMSim, a theoretical model, and the experimental results obtained by using an underwater testbed when no localization errors exist. When these errors are present, the simulator is able to reproduce the navigation of AUVs that act as data mules, adjust the throughput, and simulate the signal and connection losses that the theoretical model can not predict, but that will occur in reality. UDMSim is made available to the community to support easy and faster evaluation of data muling oriented underwater communications solutions, and enable offline replication of real world experiments.

Abstract
With the collapse of communism, some former communist States of Eastern Europe managed to muddle through their way to a market economy and entered the European Union. This brought about the acceleration of Foreign Direct Investment (FDI) among the European economies and accelerated the globalization process. Although there is plenty of research on FDI and trade among countries, the aim of this chapter is to analyze how trade between Portugal and the Czech Republic have evolved over form 2000 until 2015. The chapter seeks to complement previous studies on FDI and trade as Portugal and the Czech Republic are part of the European Union, but have had different historical, cultural, and economic paths. The main conclusion of the chapter is that trade between both countries has grown significantly. The main reason affecting trade between both countries is the economic unrest Portugal has been through since 2008.

Abstract
We present the status and plans for the Keck All sky Precision Adaptive optics (KAPA) program. KAPA includes four key science programs, an upgrade to the Keck I laser guide star (LGS) adaptive optics (AO) facility to improve image quality and sky coverage, AO telemetry based point spread function (PSF) estimates for all science exposures, and an educational component focused on broadening the participation of women and underrepresented groups in instrumentation. For the purpose of this conference we will focus on the AO facility upgrade which includes implementation of a new laser, wavefront sensor and real-time controller to support laser tomography, the laser tomography system itself, and modifications to an existing near-infrared tip-tilt sensor to support multiple natural guide star (NGS) and focus measurements.

Abstract
This paper introduces an Information Theoretic approach for Generalized State Estimation, aiming at achieving reliable topology and state variables co-estimation results, even in the presence of both topology errors and gross measurements. Attention is focused on the final bad data processing stage in which only relevant parts of the power network are represented at the bus-section level. The proposed generalized strategy applied at physical level relies on the superior outlier rejection properties of state estimators based on Maximum Correntropy, a concept borrowed from Information Theoretical Learning. A single objective function unifies the treatment of analog measurements and topology data, leading to an algorithm that does not require re-estimation runs for bad data suppression, and is simpler and more efficient than previously proposed co-estimation methods. Case studies conducted for distinct test-systems are presented, including various types of topology errors and simultaneous occurrence of topology and gross measurement errors. The results suggest that the proposed information-theoretic co-estimation algorithm is able to successfully provide bad data-free real-time network models even in the presence of multiple topology errors, simultaneous gross measurements and inaccurate topology information. Finally, additional tests confirm its superior computational performance as compared with other co-estimation algorithms.

Abstract
This paper studies the role of electricity demand response program (EDRP) in the co-operation of the electric power systems and the natural gas transmission system to facilitate integration of wind power generation. It is known that time-based uncertainty modeling has a critical role in co-operation of electricity and gas systems. Also, the major limitation of the hourly discrete time model (HDTM) is its inability to handle the fast sub-hourly variations of generation sources. Accordingly, in this paper, this limitation has been solved by the operation of both energy systems with a continuous time model (CTM). Also, a new fuzzy information gap decision theory (IGDT) approach has been proposed to model the uncertainties of the wind energy. Numerical results on the IEEE Reliability Test System (RTS) demonstrate the benefits of applying the continuous-time EDRP to improve the co-scheduling of both natural gas and electricity systems under wind power generation uncertainty.