Neutron activation analysis of wheat samples

The deficiency of essential micronutrients and excess of toxic metals in cereals, an important food items for human nutrition, can cause public health risk. Therefore, before their consumption and adoption of soil supplementation, concentrations of essential micronutrients and metals in cereals should be monitored. This study collected soil and two varieties of wheat samples–Triticum aestivum L. (Jordão/bread wheat), and Triticum durum L. (Marialva/durum wheat) from Elvas area, Portugal and analyzed concentrations of As, Cr, Co, Fe, K, Na, Rb and Zn using Instrumental Neutron Activation Analysis (INAA) to focus on the risk of adverse public health issues. The low variability and moderate concentrations of metals in soils indicated a lower significant effect of environmental input on metal concentrations in agricultural soils. The Cr and Fe concentrations in soils that ranged from 93–117 and 26,400–31,300 mg/kg, respectively, were relatively high, but Zn concentration was very low (below detection limit <22 mg/kg) indicating that soils should be supplemented with Zn during cultivation. The concentrations of metals in roots and straw of both varieties of wheat decreased in the order of K>Fe>Na>Zn>Cr>Rb>As>Co. Concentrations of As, Co and Cr in root, straw and spike of both varieties were higher than the permissible limits with exception of a few samples. The concentrations of Zn in root, straw and spike were relatively low (4–30 mg/kg) indicating the deficiency of an essential micronutrient Zn in wheat cultivated in Portugal. The elemental transfer from soil to plant decreases with increasing growth of the plant. The concentrations of various metals in different parts of wheat followed the order: Root>Straw>Spike. A few root, straw and spike samples showed enrichment of metals, but the majority of the samples showed no enrichment. Potassium is enriched in all samples of root, straw and spike for both varieties of wheat. Relatively to the seed used for cultivation, Jordão presented higher transfer coefficients than Marialva, in particular for Co, Fe, and Na. The Jordão and Marialva cultivars accumulated not statistically significant different concentrations of different metals. The advantages of using INAA are the multielementality, low detection limits and use of solid samples (no need of digestion).

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Estudo do recife artificial a construir na Leirosa: aplicação de modelação numérica para simulação da propagação da agitação marítima

A temática dos recifes artificiais multifuncionais é relativamente recente, sendo que o primeiro recife artificial multifuncional construído data do ano de 1999 (Perth, Austrália). A palavra multifuncional está associada aos múltiplos propósitos que se podem atingir com a construção de uma estrutura destas, sendo eles, a proteção costeira, o aumento da biodiversidade local, a melhoria da qualidade das ondas para o Surf e a promoção do turismo ligado aos desportos de ondas. Para dar resposta a um caso de proteção costeira, na zona marítima adjacente à praia de Leirosa, Portugal, foi pensada uma construção de um recife artificial que funcione como obra de proteção do sistema dunar local e que, adicionalmente melhore as condições locais para a prática de Surf. Este trabalho descreve a análise de duas soluções de recife (em forma de “V”, formando um ângulo de 45º e 66º, entre si), através dos valores das características das ondas (altura, período e direção) e parâmetros de surfabilidade (linha de rebentação, número de Iribarren e ângulo de rebentação), para uma gama alargada de condições de agitação frequente. Para tal, foi necessário caracterizar a agitação marítima, através do modelo numérico SWAN para determinação dos casos de agitação mais frequentes na zona marítima adjacente ao local de implantação do recife e para, posteriormente, se proceder à sua utilização no modelo numérico DREAMS, que permitiu a simulação da propagação das ondas sobre o recife. A comparação dos resultados do modelo numérico DREAMS para as situações de com e sem recife (para as duas soluções de recife) permitiu avaliar a influência do mesmo em termos de alturas de onda, linha de rebentação e ângulo de rebentação, tendo-se chegado a resultados satisfatórios do ponto de vista do melhoramento das condições locais para a prática do Surf.

Controlo e optimização de sistemas AVAC recorrendo a técnicas de inteligência artificial

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Activation of effector immune cells promotes tumor stochastic extinction: A homotopy analysis approach

In this article we provide homotopy solutions of a cancer nonlinear model describing the dynamics of tumor cells in interaction with healthy and effector immune cells. We apply a semi-analytic technique for solving strongly nonlinear systems – the Step Homotopy Analysis Method (SHAM). This algorithm, based on a modification of the standard homotopy analysis method (HAM), allows to obtain a one-parameter family of explicit series solutions. By using the homotopy solutions, we first investigate the dynamical effect of the activation of the effector immune cells in the deterministic dynamics, showing that an increased activation makes the system to enter into chaotic dynamics via a period-doubling bifurcation scenario. Then, by adding demographic stochasticity into the homotopy solutions, we show, as a difference from the deterministic dynamics, that an increased activation of the immune cells facilitates cancer clearance involving tumor cells extinction and healthy cells persistence. Our results highlight the importance of therapies activating the effector immune cells at early stages of cancer progression.