Abstract
The purpose of this paper is to propose new model for emotional interaction that uses learning styles and student emotional state to adapt the user interface and learning path. This aims to reduce the difficulty and emotional stain that students encounter while interacting with learning platforms. To this end will be used techniques of Affective Computer that can capture the student emotional state and base on that change the course parameters (flow, organization or difficulty) or even an emotional interaction in order to recapture the student attention.

Abstract
Software connectors encapsulate interaction patterns between services in complex, distributed service-oriented applications. Such patterns encode the interconnection between the architectural elements in a system, which is not necessarily fixed, but often evolves dynamically. This may happen in response to faults, degrading levels of QoS, new enforced requirements or the re-assessment of contextual conditions. To be able to characterise and reason about such changes became a major issue in the project of trustworthy software. This paper discusses what reconfiguration means within coordination-based models of software design. In these models computation and interaction are kept separate: components and services interact anonymously through specific connectors encoding the coordination protocols. In such a setting, of which Reo is a paradigmatic illustration, the paper introduces a model for connector reconfigurations, from both a structural and a behavioural perspective.

Abstract
We describe the use of a phase-sensitive optical time domain reflectometer (phi OTDR) over an ultra-long Raman fiber laser cavity allowing fully distributed detection of vibrations over 125 km. Compared to a first-order Raman-assisted phi OTDR, this scheme shows an enhanced signal-to-noise ratio (SNR). This is due to the fact that the relative intensity noise introduced by the Raman amplification is mostly transferred to a lower frequency range, where the balanced detection implemented in the setup provides better suppression of the common-mode noise. The sensor was able to measure vibrations of up to 380 Hz (limit set by the time of flight of light pulses) in a distance of 125 km with a resolution of 10 m and an average SNR of 8 dB with no postprocessing. This implies a > 3 dB improvement in SNR over a first-order Raman-assisted setup with similar characteristics.

Abstract

Abstract
Nowadays, Magnetic Resonance Imaging is widely accepted and is becoming an increasingly useful imaging technique. For its functioning, in magnetic resonance equipments there are three main sources of electromagnetic fields: static magnetic fields, time-varying gradient fields and radiofrequencies fields. All of these fields have effects both on patients and workers. The main effect of radiofrequencies fields is heat deposition on human body, which causes tissue heating. There are international guidelines that establish occupational limits for its exposure. A good knowledge of radiofrequencies implications and its safety aspects is vital for better practices in magnetic resonance imaging.

Abstract
This paper presents a wide input range, low-power operational transconductance amplifier (OTA) in weak inversion. The OTA is implemented with tanh-triplets differential pairs, degenerated by a composite configuration to augment the input linear range, thus reducing further the harmonic distortion. Using MATLAB, the mismatch factor (A) of a typical multi-tanh triplet has been optimised for minimum harmonic distortion. The OTA is designed in UMC 0.13um CMOS technology with 1.2V supply. Simulations show that the input range can be extended to 300 mV, while keeping the HD3 below -80 dB. The average power consumption is 13nW, with an open loop-gain of 76 dB and a unity gain frequency of 250 Hz. The low harmonic distortion OTA can find potential applications in low-power and long time constant filters.