Abstract
This paper describes the EmbodiMentor, an interaction concept and metaphor that aims to enable users to embody a different person or character's perspective, specify or modify his/her/its emotional elements and conditioning elements, and experience the resulting changes. Its use case scenario is the education and training of foreign languages and intercultural communication skills, were contextualization and first person experiences in common settings are key for practical skill acquisitions. It was born as the microscience-fiction prototype "Frances can't sleep. She crawls out of bed and with her EmbodiMentor runs through a range of a client's emotional states, pitching to each one. She then falls asleep." The application of the science fiction prototyping concept has been proven a strong approach to develop and investigate innovative applications of emerging technologies.

Abstract
Prior statistical knowledge of the turbulence such as turbulence strength, layer altitudes and the outer scale is essential for atmospheric tomography in adaptive-optics (AO). These atmospheric parameters can be estimated from measurements of multiple Shack-Hartmann wave-front sensors (SH-WFSs) by the SLOpe Detection And Ranging (SLODAR). In this paper, we present the statistics of the vertical CN2 and the outer scale L0 at Maunakea in Hawaii estimated from 60 hours telemetry data in total from multiple SH-WFSs of RAVEN, which is an on-sky multi-object AO demonstrator tested on the Subaru telescope. The mean seeing during the RAVEN on-sky observations is 0.475 arcsec, and 55% turbulence is below 1.5 km. The vertical profile of CN2 from the RAVEN SLODAR is consistent with the profiles from CFHT DIMM and MASS, and TMT site characterization.

Abstract
The present work evaluates the effect of gap in the density-dependent one-body momentum distribution, n(k, rho), at the Fermi surface on the calculation of the single-particle properties of nucleons, i.e., the momentum- and density-dependent single-particle potential and the nucleon effective mass, and also on the calculation of the ground-state binding energy of the selected closed-shell nuclei, i.e., O-16, Ca-40, and Ni-56. In order to do this, n(k, rho) is constructed by use of the calculations of the lowest-order constrained variational method for the symmetric nuclear matter with the Av(18) potential up to J(max) = 2 and 5. It is shown that the gap in n(k, rho) at the Fermi surface has no significant effect on the calculation of single-particle properties in the case of J(max) = 5. In the relevant evaluation of the ground-state binding energy of selected nuclei, it is seen that the binding energy of O-16, improved by including n(k, rho), is closer to the experimental data, contrary to Ca-40 and Ni-56.

Abstract
New media and social network sites (SNSs) currently play an important role in our society and in our daily practices (Boyd and Ellison 2008; Lister et al 2009; Watkins 2009; Papacharissi 2011). This necessarily affects the way we learn together, as explored in research spanning several areas. Regarding higher education, Facebook has an increasingly prominent position and is more widely investigated as an instructional tool in the college classroom than most SNSs (Tess 2013). From the perspective of teaching and learning, the Web 2.0 is seen as an enabler of a vision in which the student will find information potentially contradicting the knowledge acquired through the traditional formal learning process (Santos 2009). This feature leads to a continuous discussion of the facts, topics and subjects having an awareness of a common range of formal established knowledge shared in a given community and, at the same time, the joint reflection and debate within this same community. This new reality, in which the roles of the teacher and the student (or the roles of who teaches and who learns) become fuzzy, difficult to distinguish clearly, also brings the need for new ways to understand, describe, and explain the learning process and the ways in which it develops. In this paper we use the concept of social e-learning (Martins et al. 2012), building on the connectivist perspective (Siemens 2004, 2006, 2008). Social e-learning can be considered as a learning process whereby the Internet represents a space for participation, sharing, and collaboration, with new opportunities to create, share content, and interact with others (Bennett 2012) - an open door to build more open and flexible knowledge, where students build and rebuild their own path. A concrete format for its implementation is proposed and a genuine experience is presented and discussed. The social e-learning model presented in this article has been successfully applied in a training course in the field of business communication, held by Citeforma. Citeforma is a Portuguese vocational training centre, jointly managed by SITESE (a services workers and technicians union) and IEFP (the Portuguese Institute for Employment and Vocational Training).

Abstract

Abstract
In this paper, an agent-based model is proposed to improve market efficiency by using different Demand Response Programs (DRPs) in the day-ahead electricity market. To this end, both incentive-based and price-based DRPs are considered. On this basis, time of use, real time pricing, emergency demand response program, interruptible/curtailable services and critical peak pricing are investigated. The tariffs of the considered price-based programs and the amount of incentive in the incentive-based programs are optimized through the proposed model. Furthermore, a market power index, i.e., Share Weighted Average Lerner Index (SWALI) and the operation cost are used to evaluate the market efficiency and the market power. The proposed model optimizes the DRPs to improve the electricity market efficiency by using a multi-attribute decision-making approach. The results show that the market operator can mitigate the potential occurrence of market power in a power system by finding the optimal DRP.