Abstract
In this paper we discuss the development and clinical evaluation of a wireless platform for health signs sensing. The sensors measure physical activity, ECG, blood oxygen saturation, temperature and respiratory rate. An important aspect of the approach is that the sensors are integrated into one waist-worn device. A mobile phone collects data from this device and uses data fusion in the scope of a decision support system to trigger additional measurements, classify health conditions or schedule future observations. In these decisions, the user's current physical activity plays an important role as the validity of many health signs measurements is strongly related to physical activity. Due to the integration of the sensors and the use of data fusion it is possible to accurately identify health risks and to react promptly. During clinical trials, for which proper ethical approval was obtained, the system was used by healthy elderly volunteers in Limerick (Ireland) and Ancona (Italy). Results of these trials are also discussed in this paper.

Abstract
Complete optical characterization of biological tissue is desirable to develop clinical methods using optical technologies. Particularly, to develop optical clearing methods in biological tissues, it is necessary to know the composition of the tissue, the percentage of each constituent and corresponding refractive indexes. To obtain such information for rat muscle, we used a simple method to characterize tissue constituents for both content percentage and refractive index. The study consisted on measuring mass with a precision weighting scale and the refractive index with an Abbe refractometer during tissue dehydration. With the collected data, we used a theoretical model to calculate the refractive index and percentage for both interstitial fluid and solid part of the rat muscle. The results obtained are in good agreement with data published by other authors, and were considered of vital information for the optical clearing studies that we planned to perform.

Abstract
During the 2004, 2005 and 2006 growing seasons, physiological and anatomical leaf characteristics and productivity were studied in field-grown grapevines (Vitis vinifera L.) cv. 'Touriga Franca' under ambient (C, 365 +/- 10 ppm) or elevated carbon dioxide vertical bar CO2 vertical bar, (E, 500 +/- 16 ppm) under Open-top chambers (OTC-C and OTC-E, respectively). The elevated vertical bar CO2 vertical bar concentration increased net photosynthetic rate (A), intrinsic water use efficiency (A/g(s)), leaf thickness, Mg concentration, C/N, K/N and Mg/N ratios and decreased stomatal density and N concentration. Nevertheless, stomatal conductance (g(s)), transpiration rate (E), photochemical efficiency (F-v/F-m), leaf water potential, SPAD-values and Red/Far-red ratio transmitted by leaves were not significantly affected by vertical bar CO2 vertical bar. Meanwhile, there is no evidence for downward acclimation of photosynthesis and stomatal conductance. Yield, cluster weight and vigour showed an increase in elevated vertical bar CO2 vertical bar treatment but yield to pruning mass ratio was unaffected. Despite elevated vertical bar CO2 vertical bar stimulates grapevine photosynthesis and yield, more long-term studies, particularly at sub-optimal nutrient and water availability, are needed in order to reveal the grapevine responses to climate change in the Mediterranean area.

Abstract
This paper presents the results of a series of experiments aiming at the optimisation of vital sign monitoring using textile electrodes to be used in a swimsuit The swimsuit will integrate sensors for the measurement of several physiological and biomechanical signals, this paper will focus on ECG and respiratory movement analysis The data obtained is mainly intended to provide tools for evaluation of high-performance swimmers, although applications can be derived for leisure sports and other situations A comparison between electrodes based on different materials and structures, behaviour in dry and wet environments, as well as the behaviour in different extension states, will be presented The influence of movement on the signal quality, both by the muscular electrical signals as well as by the displacement of the electrodes, will be discussed The final objective is the integration of the electrodes in the swimsuit by knitting them directly in the suit's fabric in a seamless knitting machine

Abstract
In this article, we introduce an iterative subspace system identification algorithm for MIMO linear parameter-varying systems with innovation-type noise models driven by general inputs and a measurable white noise time-varying parameter vector. The new algorithm is based on a convergent sequence of linear deterministic-stochastic state-space approximations, thus considered a Picard-based method. Such methods have proven to be convergent for the bilinear state-space system identification problem. Their greatest strength lies on the dimensions of the data matrices that are comparable to those of a linear subspace algorithm, thus avoiding the curse of dimensionality.

Abstract
In this paper a successive approximation approach for MIMO linear parameter varying (LPV) systems with affine parameter dependence is proposed. This new approach is based on an algorithm previously introduced by the authors, which elaborates on a convergent sequence of linear deterministic-stochastic state-space approximations. In the previous algorithm the bilinear term between the time varying parameter vector and the state vector is allowed to behave as a white noise process when the scheduling parameter is a white noise sequence. However, this is a strong limitation in practice since, most often than not, the scheduling parameter is imposed by the process itself and it is typically a non white noise signal. In this paper, the bilinear term is analysed for non white noise scheduling sequences. It is concluded that its behaviour depends on the input sequence itself and it ranges from acting as an independent colored noise source, mostly removed by the identification algorithm, down to a highly input correlated signal that may be incorrectly assumed as being part of the system subspace. Based on the premise that the algorithm performance can be improved by the noise energy reduction, the bilinear term is expressed as a function of past inputs, scheduling parameters, outputs, and states, and the linear terms are included in a new extended input.