Abstract
A bidirectional transformation consists of pairs of transformations-a forward transformation get produces a target view from a source, while a putback transformation put puts back modifications on the view to the source-satisfying sensible roundtrip properties. Existing bidirectional approaches are get-based in that one writes (an artifact resembling) a forward transformation and a corresponding backward transformation can be automatically derived. However, the unavoidable ambiguity that stems from the underspecification of put often leads to unpredictable bidirectional behavior, making it hard to solve nontrivial practical synchronization problems with existing bidirectional transformation approaches. Theoretically, this ambiguity problem could be solved by writing put directly and deriving get, but differently from programming with get it is easy to write invalid put functions. An open challenge is how to check whether the definition of a putback transformation is valid, while guaranteeing that the corresponding unique get exists. In this paper, we propose, as far as we are aware, the first safe language for supporting putback-based bidirectional programming. The key to our approach is a simple but powerful language for describing primitive putback transformations. We show that validity of putback transformations in this language is decidable and can be automatically checked. A particularly elegant and strong aspect of our design is that we can simply reuse and apply standard results for treeless functions and tree transducers in the specification of our checking algorithms. © 2014 Springer International Publishing Switzerland.

Abstract
Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator. © Springer International Publishing Switzerland 2014.

Abstract
The point prediction quality is closely related to the model that explains the dynamic of the observed process. Sometimes the model can be obtained by simple algebraic equations but, in the majority of the physical systems, the relevant reality is too hard to model with simple ordinary differential or difference equations. This is the case of systems with nonlinear or nonstationary behaviour which require more complex models. The discrete time-series problem, obtained by sampling the solar radiation, can be framed in this type of situation. By observing the collected data it is possible to distinguish multiple regimes. Additionally, due to atmospheric disturbances such as clouds, the temporal structure between samples is complex and is best described by nonlinear models. This paper reports the solar radiation prediction by using hybrid model that combines support vector regression paradigm and Markov chains. The hybrid model performance is compared with the one obtained by using other methods like autoregressive (AR) filters, Markov AR models, and artificial neural networks. The results obtained suggests an increasing prediction performance of the hybrid model regarding both the prediction error and dynamic behaviour.

Abstract
We report a magnetic field sensor based on dual core photonic crystal fiber. By using coupled mode theory, the sensing characteristics of the sensor investigated. The sensitivity of the proposed sensor is of 172.54 pm/Oe. © OSA 2016.

Abstract
Rational terms or rational trees are terms with one or more infinite sub-terms but with a finite representation. Rational terms appeared as a side effect of omitting the occurs check in the unification of terms, but their support across Prolog systems varies and often fails to provide the expected functionality. A common problem is the lack of support for printing query bindings with rational terms. In this paper, we present a survey discussing the support of rational terms among different Prolog systems and we propose the integration of a Prolog predicate, that works in several existing Prolog systems, in order to overcome the technical problem of printing rational terms. Our rational term printing predicate could be easily adapted to work for the top query printouts, for user printing and for debugging purposes.

Abstract
An intrinsic fiber optic dosimeter (FOD) targeted to nuclear applications is presented. The proposed real-time dosimeter provides dose information based on the historic record over time of the effects of ionizing radiation on single-and multi-mode pure silica fibers, and also on PMMA plastic fibers. The effect of Co-60 gamma irradiation on optical links based on silica and plastic fibers were assessed, considering thermal environment effects over a wide range of variation of the operating parameters. Cerenkov radiation and radiation-induced absorption effects were in focus. The corresponding distortion and spectral transmission degradation were evaluated over wide range of the operating parameters. Radiation induced attenuation (RIA) has shown a spectral band dependent behaviour up to 840 Gy dose levels. The performance of different fibers was assessed against the performance of non-irradiated fibers. From the measurements of dose rate and total dose imparted by ionizing radiation in the fibers we verified that fibers with radiation resistance issues showed wavelength-dependent radiation sensitivity increasing with dose rate. Upon evaluation of correlations between the total dose, the induced loss at various dose rates and different wavelengths, it was concluded that intrinsic fiber dosimeters can be used for dose rates in the range 4 - 28 Gy/min., typical of severe radiation environments.