Abstract
This paper presents experiments carried out with a prototype test chip provided by the IEEE P1149.4 Mixed-Signal Testing Working Group, which explore the architecture of the proposed analogue boundary module to implement simultaneous observation of power supply current and output voltage, towards mixed current/voltage testing of analogue and mixed-signal circuits.

Abstract
Higher-order statistics (HOS) are a powerful analysis tool in digital signal processing. The most difficult task to use it effectively is the estimation of higher-order moments of sampled data, taken from real systems. For applications that require real-time processing, the performance achieved by common microprocessors or digital signal processors is not good enough to carry out the large number of calculations needed for their estimation. This paper presents ProHos-1, an experimental vector processor for the estimation of the higher-order moments up to the fourth-order. The processor's architecture exploits the structure of the algorithm, to process in parallel four vectors of the input data in a pipe-lined fashion, executing the equivalent to 11 operations in each clock cycle. The design of dedicated control circuits led to high clock rate and small hardware complexity, thus suitable for implementation as an ASIC (Application Specific integrated Circuit).

Abstract
This paper describes the goals and some of the results obtained in the project entitled "Computerised Management of Greenhouses", that has started in November 1995. This project has a duration of three years and is sponsored by JNICT (Portuguese Institute for Scientific Research Funding). At present, the experimental set-up is composed of a greenhouse with a floor area of 210m(2) equipped with several actuators and sensors that are connected to an acquisition and control system developed at the Engineering Department of UTAD University. The set-points for the air temperature and humidity, CO2 concentration, soil moisture and ambient radiation inside the greenhouse are calculated on-line as a function of the greenhouse climate, outside weather and the specified optimal set of values for the plants, in this case tomato. The results show that the climate control system performs well and that has been achieved a reduction of the energy consumption compared with the case when the set-points are fixed. In the second year it will be implemented a distributed control system for monitoring and control the environment of four greenhouses located at the University campus. Also, in one of the greenhouses, will be used renewable energies such as the solar photovoltaic and the solar thermal energies. The first is to deliver power to the electronic equipment and to some of the actuators and the second for heating the greenhouses. During this period and the third year it will be implemented and compared different real-time control strategies with respect to set-point accuracy and energy consumption.

Abstract
Knowledge of the health of power transformers is important to prevent high costs caused by failures and to maintain the quality of the service. On-line monitoring and diagnosis seem to be the right way to reach this objective. In this paper a set of experiences related to the installation of vibration and temperature sensors inside a test transformer will be described. Different types of sensors have been tested, and some of them discarded because of induced electromagnetical noise. Some of the main results and conclusions are shown in this paper. These experiences are included in a more general project called TRAFES, whose main objective is the continuous monitoring and diagnosis of large power transformers.

Abstract
The common menopausal symptoms of a growing number of women treated for breast cancer poses difficult therapeutic decisions to the Gynaecologist. It has been extensively demonstrated that hormonal replacement therapy (HRT) is the most effective treatment of such symptoms, as well as protecting women from cardiovascular disease, osteoporosis and increased mortality related to these disorders. However, breast cancer is classically considered a contraindication to HRT. In this paper we review the existing evidence regarding the influence of HRT on breast cancer. A computerized bibliographical search (MEDLINE) of literature in the English-language literature published in the last 15 years was conducted, followed by a hand search of references found in these papers. Evidence on the response of breast cancer cells to HRT is derived from animal studies, tissue growth system experiments, indirect epidemiological data and clinical data. While the bulk of experimental evidence points towards a proliferative effect of estrogen on breast cancer cells, almost all clinical reports have found no adverse effects of HRT on these patients. In our opinion, currently existing evidence does not justify the denial of HRT to breast cancer patients whose quality of life is at stake. Such is the case of women with intense menopausal symptoms unresponsive to alternative therapies. This opinion is shared by numerous other authors and a small number of eminent institutions. We believe it is safer to avoid HRT, in asymptomatic women as long-term regimens would be needed for protection against cardiovascular disease and osteoporosis, and the risks of such regimens have yet to be evaluated. We also believe that large randomized trials are now ethically justified and greatly needed to obtain safer data on this subject.

Abstract
When inference is performed with the compositional rule of inference (CRI), fuzzy rules can be mathematically modelled by a pair of operators, the implication function and the modus ponens generating function, each pair being a possible model for the rule. Analyzing the firing condition of fuzzy rules, that is the condition the hypothesis and the observation must verify to infer a non trivial conclusion, it is possible to get a deeper understanding of the behaviour of the different models that can be used, and valuable semantical criteria can be obtained to select the best suitable model. The firing condition of any model can be expressed by means of a generalized possibility or necessity measure generated by its implication and modus ponens generating functions, measures that quantify the amount of uncertainty or possibilistic uncertainty of the conclusion. Two different types of possibility distributions can be identified as those concluded from different types of models, that is necessary and possible possibility distributions, corresponding to necessary and possible conclusions.