A spectral estimator using parallel-processing for use in a doppler blood-flow instrument

The work described here is part of a research program aiming to increase the sensitivity to disease detection using Doppler ultrasound by reducing the effects to the measurement procedure on the estimation of blood velocity and detection of flow disturbance.

Ichthyofauna of the Selvagens Islands. Do small coastal areas show high species richness in the northeastern Atlantic?

The Selvagens Islands are located in the northeastern Atlantic between the Canary Islands and Madeira Island. As a result of their small size, remote location and harsh sea conditions only a few studies have been conducted to describe their marine species diversity. We were able to identify 29 new coastal fish species, an increase of 33% in the ichthyofauna described for these islands (n = 88). There is a prevalence of species with tropical affinities and only 2.3% (n = 2) are endemic to Macaronesia. Considered a stepping-stone colonization vector from the nearest continental shore, as proposed by other authors for this region, the Selvagens Islands host 34.1% of the ichthyofauna described for the much larger Canary Islands (nspecies = 258, submerged area nSelvagensIs. = 2.3%) and 47.3% of the ichthyofauna described for the more distantly located Madeira Island (nspecies = 186, submerged area nSelvagensIs. = 17.9%). Interestingly, 6.8% (n = 6) of the species failed to bridge the gap between the Selvagens Islands and Madeira Island. Data collected so far showed no trend toward an increasing number of species with high dispersal capability. The Selvagens Islands are an example of a high coastal species diversity occurring even in very small areas of the northeastern Atlantic Ocean.

Organic-walled dinoflagellate cysts in recent sediments from the Guadiana river estuary, South-East Portugal

Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2007

Laminaria ochroleuca Bachelot de la Pylaie canopy effect on intertidal understorey benthic assemblages in northern Portugal

Dissertação de mest., Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010

Small Area Estimation of the Mean Price of the Habitation Transaction in Portugal: Methodological and Practical Issues

The Portuguese National Statistical Institute intends to produce estimations for the mean price of the habitation transation.

Estimation of unemployment rates in small areas of Portugal: a best linear unbiased prediction approach versus a hierarchical Bayes approach

The high level of unemployment is one of the major problems in most European countries nowadays. Hence, the demand for small area labor market statistics has rapidly increased over the past few years. The Labour Force Survey (LFS) conducted by the Portuguese Statistical Office is the main source of official statistics on the labour market at the macro level (e.g. NUTS2 and national level). However, the LFS was not designed to produce reliable statistics at the micro level (e.g. NUTS3, municipalities or further disaggregate level) due to small sample sizes. Consequently, traditional design-based estimators are not appropriate. A solution to this problem is to consider model-based estimators that "borrow information" from related areas or past samples by using auxiliary information. This paper reviews, under the model-based approach, Best Linear Unbiased Predictors and an estimator based on the posterior predictive distribution of a Hierarchical Bayesian model. The goal of this paper is to analyze the possibility to produce accurate unemployment rate statistics at micro level from the Portuguese LFS using these kinds of stimators. This paper discusses the advantages of using each approach and the viability of its implementation.

Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Adaptive generalized predictive control algorithm implemented over a DSP network

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Implementation of an daptive generalized predictive control algorithm over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Parallel implementation of an adaptive generalized predictive control algorithm

The Adaptive Generalized Predictive Control (AGPC) algorithm can be speeded up using parallel processing. Since the AGPC algorithm needs to be fed with the knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Real-time parameter estimation of dynamic temperature and humidity models for greenhouse adaptive climate control

A real-time parameter estimator for the climate discrete-time dynamic models of a greenhouse located at the North of Portugal are presented. The experiments showed that the second order models identified for the air temperature and humidity achieve a close agreement between simulated and experimantal data.

Parallel implementation of an adaptive generalized predictive control algorithm

The Adaptive Generalized Predictive Control (GPC) algorithm can be speeded up using parallel processing. Since the GPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Feed-backs between genetic structure and perturbation-driven decline in seagrass (Posidonia oceanica) meadows

We explored the relationships between perturbation-driven population decline and genetic/genotypic structure in the clonal seagrass Posidonia oceanica, subject to intensive meadow regression around four Mediterranean fish-farms, using seven specific microsatellites. Two meadows were randomly sampled (40 shoots) within 1,600 m2 at each site: the “impacted” station, 5–200 m from fish cages, and the “control” station, around 1,000 m downstream further away (considered a proxy of the pre-impact genetic structure at the site). Clonal richness (R), Simpson genotypic diversity (D*) and clonal sub-range (CR) were highly variable among sites. Nevertheless, the maximum distance at which clonal dispersal was detected, indicated by CR, was higher at impacted stations than at the respective control station (paired t-test: P < 0.05, N = 4). The mean number of alleles (Â) and the presence of rare alleles ( r) decreased at impacted stations (paired t-test: P < 0.05, and P < 0.02, respectively, N = 4). At a given perturbation level (quantified by the organic and nutrient loads), shoot mortality at the impacted stations significantly decreased with CR at control stations (R 2 = 0.86, P < 0.05). Seagrass mortality also increased with  (R 2 = 0.81, P < 0.10), R (R 2 = 0.96, P < 0.05) and D* (R 2 = 0.99, P < 0.01) at the control stations, probably because of the negative correlation between those parameters and CR. Therefore, the effects of clonal size structure on meadow resistance could play an important role on meadow survival. Large genotypes of P. oceanica meadows thus seem to resist better to fish farm-derived impacts than little ones. Clonal integration, foraging advantage or other size-related fitness traits could account for this effect.

Numerical techniques for modeling Doppler ultrasound spectra systems

Evaluation of blood-flow Doppler ultrasound spectral content is currently performed on clinical diagnosis. Since mean frequency and bandwidth spectral parameters are determinants on the quantification of stenotic degree, more precise estimators than the conventional Fourier transform should be seek. This paper summarizes studies led by the author in this field, as well as the strategies used to implement the methods in real-time. Regarding stationary and nonstationary characteristics of the blood-flow signal, different models were assessed. When autoregressive and autoregressive moving average models were compared with the traditional Fourier based methods in terms of their statistical performance while estimating both spectral parameters, the Modified Covariance model was identified by the cost/benefit criterion as the estimator presenting better performance. The performance of three time-frequency distributions and the Short Time Fourier Transform was also compared. The Choi-Williams distribution proved to be more accurate than the other methods. The identified spectral estimators were developed and optimized using high performance techniques. Homogeneous and heterogeneous architectures supporting multiple instruction multiple data parallel processing were essayed. Results obtained proved that real-time implementation of the blood-flow estimators is feasible, enhancing the usage of more complex spectral models on other ultrasonic systems.

Spatial variability of macroinvertebrate assemblages and the influence of hydrological and environmental variables along the Sigi River, Tanzania-East Africa

The study of investigating the spatial and temporal variability of macroinvertebrate and their relation to hydrology, hydraulic and environmental factors was done along the Sigi River during two sampling periods in the dry (March) and wet (May) periods of 2012. The river was demarcated based on slope ranges and five river zones were identified as mountains streams (MS), upper foothills (UF), lower foothills (LF), rejuvenated foothills (REJ) and mature lower river (MR). Samples of macroinvertebrate were collected from the five river zones and measurements of hydrological (discharge), hydraulics (Depth, velocity and Froude number) and Environmental (pH, Temperature, substrate, conductivity) parameters were done in each zone. In characterizing the macroinvertebrate assemblages along the Sigi River diversity indices (number of taxa, total abundances, Margalef richness index and ShannonWiener index) were calculated and the most representative species for the spatial and temporal variation were identified. Melanoides and Afronurous showed differences in abundance in two samplings periods while Cleopatra, Potamonautes, Ephemerythus, Neoperla, Caenis, Ceratogomphus and Cheumatopsyche showed significant difference among the river zones. Spearman rank correlation and Distance Linear Model (DistLM) used to revealed physical factors governing the macroinvertebrate assemblages distribution. The study demonstrated that the variation of physical factors like discharge, temperature, conductivity and pH have an important role in the spatial distribution of macroinvertebrate assemblages along the river and the life cycle of macroinvertebrate (Afronurus) is important in determining the temporal variability.