Abstract
This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn. Crown Copyright

Abstract
Purpose - Most industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. This is a tedious and time-consuming task that requires some technical expertise, and hence new approaches to robot programming are required. The purpose of this paper is to present a robotic system that allows users to instruct and program a robot with a high-level of abstraction from the robot language. Design/methodology/approach - The paper presents in detail a robotic system that allows users, especially non-expert programmers, to instruct and program a robot just showing it what it should do, in an intuitive way. This is done using the two most natural human interfaces (gestures and speech), a force control system and several code generation techniques. Special attention will be given to the recognition of gestures, where the data extracted from a motion sensor (three-axis accelerometer) embedded in the Wii remote controller was used to capture human hand behaviours. Gestures (dynamic hand positions) as well as manual postures (static hand positions) are recognized using a statistical approach and artificial neural networks. Findings - It is shown that the robotic system presented is suitable to enable users without programming expertise to rapidly create robot programs. The experimental tests showed that the developed system can be customized for different users and robotic platforms. Research limitations/implications - The proposed system is tested on two different robotic platforms. Since the options adopted are mainly based on standards, it can be implemented with other robot controllers without significant changes. Future work will focus on improving the recognition rate of gestures and continuous gesture recognition. Practical implications The key contribution of this paper is that it offers a practical method to program robots by means of gestures and speech, improving work efficiency and saving time. Originality/value - This paper presents an alternative to the typical robot teaching process, extending the concept of human-robot interaction and co-worker scenario. Since most companies do not have engineering resources to make changes or add new functionalities to their robotic manufacturing systems, this system constitutes a major advantage for small- to medium-sized enterprises.

Abstract
Wind energy is the renewable energy source considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or located offshore and these factors increase the referred operation and maintenance cost. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine. © 2011 Institute of Electrical Power.

Abstract
CdTe quantum dots (QDs), capped with mercaptopropionic acid (MPA), were synthesized and the variation of their fluorescence properties (steady state and lifetime)with pH was assessed in solution and when immobilized in a sol-gel host Three different sizes of CdTe QDs with excited state lifetimes ranging from 42 to 48 ns and with emission maximum at 540 nm (QD(540)). 580 nm (QD(580)) and 625 nm (QD(625)) were selected The solution pH affects the maximum emission wavelength (shifts to higher wavelengths of 23, 24 and 27 nm for QD(540), QD(550) and QP(625), respectively), the excited state lifetime and the fluorescence intensity in a reversible way. Linearization of the maximum emission wavelength variation with the pH allows the estimation of an apparent ionization constant (pK(a)) for each QD: 6.5 +/- 0.1 (QD(540)), 6.1 +/- 0.5 (QD(580)) and 5.4 +/- 0.3 (QD(625)) The variation of the QDs fluorescence properties was further explored using confocal laser scanning microscopy allowing the implementation of a new calibration method for pH imaging in solution QDs were successfully immobilized on the tip of an optical fiber by dip-coating using sal-gel procedure The immobilized QDs showed a similar pH behaviour to the one observed in solution and an apparent lifetime of 80,68 and 99 ns, respectively. The proposed QDs based methodology can be successfully used to monitor pH using wavelength encoded data in imaging and fiber optic sensing applications.

Abstract
This article presents a set of research studies that aim to adapt Carol Ryff's scales of psychological wellbeing (SPWB) and to analyze its psychometric properties in adolescents. The first two studies focused on the reliability and factorial validity of different Portuguese short versions of SPWB, revealing measurement models inadequacies and low internal consistency. In the third study we developed a shortened version (30 items), taking into account the application of psychometric criteria suggested by van Dierendonck (2005). The scales of this version revealed better reliability and adequate goodness of fit indices for the six-factor model, as proposed by Carol Ryff's PWB theory. Although further research focused on the psychometrical properties reanalysis of this shortened version of SPWB is needed, this article provides a contribution to the research and intervention on positive mental health during adolescence.

Abstract
The present research assessed the reliability, factorial validity and measurement invariance (by gender) of the Portuguese version of TEOSQ - Task and Ego Orientation in Sport Questionnaire (Fonseca & Biddle, 2001). Data were collected from 1010 physical education students with a mean age of 15.42 (SD=1.91). Factorial and invariance measurements were tested via confirmatory factorial analysis. Results supported internal consistency for the two proposed subscales (task and ego). Based on modification indices and theoretical justification the TEOSQp was reduced to 12 items with better goodness-of-fit indices for the oblique model. The results of gender invariance did not provide full empirical support to the multi-group equivalence assumption, being suggested that TEOSQp does not measure in the same way goal orientations for boys (orthogonal model) and girls (oblique model). In light of these results, conceptual, empirical and practical issues were discussed.