Feasibility study on multifunctional artificial reefs for the Azores

Tese de Doutoramento, Geografia (Ordenamento do Território), 25 de Novembro de 2013, Universidade dos Açores.

Pittosporum Undulatum and Hedychium Gardnerianum: nutritive value and secondary metabolites on cattle reproductive performances

Hedychium gardnerianum (HG) and Pittospporum undulatum (PU) are invasive plants all over the world, being in the Azores supplied to cattle on periods of shortage food. As these plants produce secondary metabolites, including a diverse range of phytochemicals compounds, the aim of the presente study is to identify how these metabolites can be related to animal’s reproductive performances. For such purpose, plants were harvested on winter, compounds extracted by method of decoction and analysed by combination of liquid chromatography and mass spectrometry as well as highperformance liquid chromatography. For nutritive evaluations, Van Soest and Weende methodologies were used. In HG quercetin-3, 4'-di-O-betaglucopyranoside, myricetin rhamnoside, quercetin rhamnoside, and gibberellin A1 and A8 were identified, while for PU were found cafeic acid derivatives, including dicaffeoylquinic acid and caffeoylquinic acid. In nutritional terms, these plants can be considered as poor, presenting percentages of dry matter (DM%) of 16.34% and 40.39%, respectively for HG and PU. Values for ash 10.4%, crude protein (CP) 7.75%, neutral detergent fiber (NDF) 64.5, acid detergent fiber (ADF) 34.69%, acid detergent lignin (ADL) 3.47% and ether extract (EE) 2.03% were found for HG. For PU values were ash 6.64%, CP 6.11%, NDF 43.84%, acid ADF 35.57%, ADL 3.56% and EE 2.71%. This study clearly indicated that, besides their low nutritive values, these plants can be used to feed ruminants, especially when pasture lacks. Nevertheless, as some compounds, namely the caffeoylquinic and dicaffeoylquinic acids, are known to be associated to physiological reproductive mechanisms, one could speculate that these compounds can be directly or indirectly associated to reproductive performances in bovine fed with these plants.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

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

Environmental Decision Support: a Distributed Artificial Intelligence Approach

Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Antibody response in cattle after vaccination with inactivated and attenuated rabies vaccines

Despite the absence of current official reports showing the number of cattle infected by rabies, it is estimated that nearly 30,000 bovines are lost each year in Brazil. In order to minimize the important economic losses, control of the disease is achieved by eliminating bat colonies and by herd vaccination. In this study, we compare the antibody response in cattle elicited by vaccination with an attenuated ERA vaccine (AEvac) and an inactivated-adjuvanted PV (IPVvac) vaccine. The antibody titers were appraised by cell-culture neutralization test and ELISA, and the percentage of seropositivity was ascertained for a period of 180 days. IPVvac elicited complete seropositivity rates from day 30 to day 150, and even on day 180, 87% of the sera showed virus-neutralizing antibody titers (VNA) higher than 0.5IU/ml. There were no significant differences between the VNA titers and seropositivity rates obtained with IPVvac in the two methods tested. AEvac, however, elicited significantly lower titers than those observed in the group receiving inactivated vaccine. In addition, the profiles of antirabies IgG antibodies, evaluated by ELISA, and VNA, appraised by cell-culture neutralization test, were slightly different, when both vaccines were compared.

Trypanosoma cruzi parasitemia observed in immunocompromised patients: the importance of the artificial xenodiagnosis

Trypanosoma cruzi parasitemia observed in immunocompromised patients (transplant or positive HIV) occurred more frequently by the artificial xenodiagnosis method (10/38) compared with hemoculture (2/38), given the same quantity of blood. Other ways of diagnosis, like mice inoculation (5/38), QBC and buffy coat (2/38), were evaluated also. This result showed the importance of the artificial xenodiagnosis. The other techniques increased only one more patient positive.

Artificial antibodies for troponin T by its imprinting on the surface of multiwalled carbon nanotubes: Its use as sensory surfaces

A novel artificial antibody for troponin T (TnT) was synthesized by molecular imprint (MI) on the surface of multiwalled carbon nanotubes (MWCNT). This was done by attaching TnT to the MWCNT surface, and filling the vacant spaces by polymerizing under mild conditions acrylamide (monomer) in N,N′-methylenebisacrylamide (cross-linker) and ammonium persulphate (initiator). After removing the template, the obtained biomaterial was able to rebind TnT and discriminate it among other interfering species. Stereochemical recognition of TnT was confirmed by the non-rebinding ability displayed by non-imprinted (NI) materials, obtained by imprinting without a template. SEM and FTIR analysis confirmed the surface modification of the MWCNT. The ability of this biomaterial to rebind TnT was confirmed by including it as electroactive compound in a PVC/plasticizer mixture coating a wire of silver, gold or titanium. Anionic slopes of 50 mV decade−1 were obtained for the gold wire coated with MI-based membranes dipped in HEPES buffer of pH 7. The limit of detection was 0.16 μg mL−1. Neither the NI-MWCNT nor the MWCNT showed the ability to recognize the template. Good selectivity was observed against creatinine, sucrose, fructose, myoglobin, sodium glutamate, thiamine and urea. The sensor was tested successfully on serum samples. It is expected that this work opens new horizons on the design of new artificial antibodies for complex protein structures.

Biomimetic Sensor Potentiometric System for Doxycycline Antibiotic Using a Molecularly Imprinted Polymer as an Artificial Recognition Element

Molecular imprinting is a useful technique for the preparation of functional materials with molecular recognition properties. A Biomimetic Sensor Potentiometric System was developed for assessment of doxycycline (DOX) antibiotic. The molecularly imprinted polymer (MIP) was synthesized by using doxycycline as a template molecule, methacrylic acid (MAA) and/or acrylamide (AA) as a functional monomer and ethylene glycol dimethacrylat (EGDMA) as a cross-linking agent. The sensing elements were fabricated by the inclusion of DOX imprinted polymers in polyvinyl chloride (PVC) matrix. The sensors showed a high selectivity and a sensitive response to the template in aqueous system. Electrochemical evaluation of these sensors under static (batch) mode of operation reveals near-Nernstian response. MIP/MAA membrane sensor was incorporated in flow-through cells and used as detectors for flow injection analysis (FIA) of DOX. The method has the requisite accuracy, sensitivity and precision to assay DOX in tablets and biological fluids.

BoaVista – Sensor Dedicado de Visão Artificial Baseado em Hardware (Re)configurável

4º Festival Nacional de Robótica - Actas do Encontro Científico - Proceedings of the Scientific Meeting, Biblioteca Almeida Garrett, Palácio de Cristal – Porto, 23-24 Abril 2004