Abstract

Abstract
This paper describes a hybrid tool to perform Static Transmission Expansion Planning, STEP, studies and its application to the Garver6-Bus academic system and to the Southern Brazilian Transmission equivalent real system. The developed STEP tool integrates two phases as follows. The first one uses Constructive Heuristic Algorithms (CHA) to reduce the search space, and the second uses Particle Swarm Optimization (PSO) to identify the final solution. This hybridization between CHAs and PSO proved to be very effective and shows good performance to reduce the size of the STEP search space and to identify good quality solutions. These are relevant issues given the combinatorial nature of investment problems leading to the explosion of the number of alternative plans, one of the greatest difficulties faced in this planning problem.

Abstract
Aims and objectives. We developed a scale to assess the self-care behaviours developed by patients with end-stage renal disease to preserve the vascular network prior to construction of arteriovenous fistula. Background. The possibility of creation of an arteriovenous fistula depends on the existence of an arterial and venous network in good condition, namely the size and elasticity of the vessels. It is essential to teach the person to develop self-care behaviours for the preservation of the vascular network, regardless of the modality of dialysis selected. Design. Methodological study. Methods. The scale was developed based on clinical experience and research conducted by the researcher in the area of the vascular access for haemodialysis. The content of the scale was judged by two panels of experts for content validity. The revised version of the scale was administered to a convenience sample of 90 patients with end-stage renal disease. In the statistical analysis, we used the Cronbach's alpha, the Kaiser-Meyer-Olkin and scree plot and the principal component analysis with varimax rotation. Results. A principal component analysis confirmed the univariate structure of the scale (KMO = 0.759, Bartlett's sphericity test-approximate chi(2) 142.201, p < 0.000). Cronbach's a is 0.831, varying between 0.711-0.879. Conclusion. This scale revealed properties that allow its use to assess the patients self-care behaviours regarding the preservation of the vascular network. Relevance to clinical practice. This scale can be used to evaluate educational programmes for the development of self-care behaviours in the preservation of vascular network. This scale can identify not only the patients that are able to take care of their vascular network but also the proportion of patients who are not able to do it, that need to be educated.

Abstract
Extra virgin olive oils produced from three cultivars on different maturation stages were characterized using Raman spectroscopy. Chemometric methods (principal component analysis, discriminant analysis, principal component regression and partial least squares regression) applied to Raman spectral data were utilized to evaluate and quantify the statistical differences between cultivars and their ripening process. The models for predicting the peroxide value and free acidity of olive oils showed good calibration and prediction values and presented high coefficients of determination ( > 0.933). Both the R-2, and the correlation equations between the measured chemical parameters, and the values predicted by each approach are presented; these comprehend both PCR and PLS, used to assess SNV normalized Raman data, as well as first and second derivative of the spectra. This study demonstrates that a combination of Raman spectroscopy with multivariate analysis methods can be useful to predict rapidly olive oil chemical characteristics during the maturation process.

Abstract
This study pursues the operational improvement of urban transportation services. Non-foreseen events lead to the occurrence of delays, which are further propagated during the daily operations of bus services. This paper applies an optimization model to obtain robust schedules of bus lines. The model builds a new schedule which minimizes delays and anticipations from a set of observations. The decision variables are the slack time to be allocated at each segment of two subsequent stops. The solutions obtained are assessed with two robustness measures: price of robustness (i.e. the deviations from schedule) and the percentage of absorbed delays. The results obtained in a real-world case study (a bus line operating in Porto) are promising. © 2015, Springer International Publishing Switzerland.

Abstract
There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.