Completely supervised training algorithms for B-spline neural networks and neuro-fuzzy systems

Complete supervised training algorithms for B-spline neural networks and fuzzy rule-based systems are discussed. By interducing the relationship between B-spline neural networks and certain types of fuzzy models, training algorithms developed initially for neural networks can be adapted by fuzzy systems.

Neuro-genetic PID autotuning: time invariant case

The Proportional, Integral and Derivative (PID) controllers are widely used in induxtrial applications. Their popularity comes from their robust performance and also from their functional simplicity.

Automatic tuning of PID controllers using a neuro-genetic system

Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller turning problems. In this paper we propose to combine its joint use, by exploiting the nonlinear mapping capabilites of neural networks to model objective functions, and to use them to supply their values to a genetic algorithm which performs on-line minimization.

Training neuro-fuzzy models using evolution based algorithms

The normal design process for neural networks or fuzzy systems involve two different phases: the determination of the best topology, which can be seen as a system identification problem, and the determination of its parameters, which can be envisaged as a parameter estimation problem. This latter issue, the determination of the model parameters (linear weights and interior knots) is the simplest task and is usually solved using gradient or hybrid schemes. The former issue, the topology determination, is an extremely complex task, especially if dealing with real-world problems.

Ligand binding and signalling pathways of PTH receptors in sea bream (Sparus auratus) enterocytes

Whole animal studies have indicated that Ca2+ uptake by the gastrointestinal tract is regulated by the action of parathyroid hormone-related peptide (PTHrP) in teleost fish. We have characterised PTH receptors (PTHR) in piscine enterocytes and established, by using aminoterminal PTHrP peptides, the amino acid residues important for receptor activation and for stabilising the ligand/receptor complex. Ligand binding of 125I-(1–35tyr) PTHrP to the membrane fraction of isolated sea bream enterocytes revealed the existence of a single saturable high-affinity receptor (KD=2.59 nM; Bmax=71 fmol/mg protein). Reverse transcription/polymerase chain reaction with specific primers for sea bream PTH1R and PTH3R confirmed the mRNA expression of only the later receptor. Fugu (1–34) PTHrP increased cAMP levels in enterocytes but had no effect on total inositol phosphate accumulation. The aminoterminal peptides (2–34)PTHrP, (3–34)PTHrP and (7–34) PTHrP bound efficiently to the receptor but were severely defective in stimulating cAMP in enterocyte cells indicating that the first six residues of piscine (1–34)PTHrP, although not important for receptor binding, are essential for activation of the adenylate cyclase/phosphokinase A (AC-PKA)-receptor-coupled intracellular signalling pathway. Therefore, PTHrP in teleosts acts on the gastrointestinal tract through PTH3R and the AC-PKA intracellular signalling pathway and might regulate Ca2+ uptake at this site. Ligand-receptor binding and activity throughout the vertebrates appears to be allocated to the same amino acid residues of the amino-terminal domain of the PTHrP molecule.

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

Investigating the role of Annexin A2 in Epidermal Growth Factor (EGF) induced signalling in cancer

Dissertação de mestrado, Qualidade em Análises, Faculdade de Ciências e Tecnologia, Universidade do Algarve; Universitat de Barcelona; Gdansk University of Technology, Universidad de Cádiz, Universitas Bergensis; 2015

Brain-derived neurotrophic factor and adenosine signalling on amyloid-β peptide induced toxicity : impact on hippocampal function

Tese de doutoramento, Ciências Biomédicas (Neurociências), Universidade de Lisboa, Faculdade de Medicina, 2014

Neuro-glia-vascular alterations by common neonatal clinical conditions

Tese de doutoramento, Farmácia (Biologia Celular e Molecular), Universidade de Lisboa, Faculdade de Farmácia, 2014

Perturbation of Cytokinin and Ethylene-signalling Pathways Explain the Strong Rooting Phenotype Exhibited by Arabidopsis Expressing the Schizosaccharomyces Pombe mitotic inducer, cdc25.

Background Entry into mitosis is regulated by cyclin dependent kinases that in turn are phosphoregulated. In most eukaryotes, phosphoregulation is through WEE1 kinase and CDC25 phosphatase. In higher plants a homologous CDC25 gene is unconfirmed and hence the mitotic inducer Schizosaccharomyces pombe (Sp) cdc25 has been used as a tool in transgenic plants to probe cell cycle function. Expression of Spcdc25 in tobacco BY-2 cells accelerates entry into mitosis and depletes cytokinins; in whole plants it stimulates lateral root production. Here we show, for the first time, that alterations to cytokinin and ethylene signaling explain the rooting phenotype elicited by Spcdc25 expression in Arabidopsis. Results Expressing Spcdc25 in Arabidopsis results in increased formation of lateral and adventitious roots, a reduction of primary root width and more isodiametric cells in the root apical meristem (RAM) compared with wild type. Furthermore it stimulates root morphogenesis from hypocotyls when cultured on two way grids of increasing auxin and cytokinin concentrations. Microarray analysis of seedling roots expressing Spcdc25 reveals that expression of 167 genes is changed by > 2-fold. As well as genes related to stress responses and defence, these include 19 genes related to transcriptional regulation and signaling. Amongst these was the up-regulation of genes associated with ethylene synthesis and signaling. Seedlings expressing Spcdc25 produced 2-fold more ethylene than WT and exhibited a significant reduction in hypocotyl length both in darkness or when exposed to 10 ppm ethylene. Furthermore in Spcdc25 expressing plants, the cytokinin receptor AHK3 was down-regulated, and endogenous levels of iPA were reduced whereas endogeous IAA concentrations in the roots increased. Conclusions We suggest that the reduction in root width and change to a more isodiametric cell phenotype in the RAM in Spcdc25 expressing plants is a response to ethylene over-production. The increased rooting phenotype in Spcdc25 expressing plants is due to an increase in the ratio of endogenous auxin to cytokinin that is known to stimulate an increased rate of lateral root production. Overall, our data reveal important cross talk between cell division and plant growth regulators leading to developmental changes.

Neuro-Fuzzy based Identification of Meat Spoilage using an Electronic Nose

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). An adaptive fuzzy logic system model that utilizes a prototype defuzzification scheme has been developed to classify beef samples in their respective quality class and to predict their associated microbiological population directly from volatile compounds fingerprints. Results confirmed the superiority of the adopted methodology and indicated that volatile information in combination with an efficient choice of a modeling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

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. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Signalling in an international cournot model

We consider a trade policy model, where the costs of the home firm are private information but can be signaled through the output levels of the firm to a foreign competitor and a home policymaker. We study the influences of the non-homogeneity of the goods and of the uncertainty on the production costs of the home firm in the signalling strategies by the home firm. We show that some results obtained for homogeneous goods are not robust under non-homogeneity.

The Role of Actin-Capping Protein and Src signalling in tissue growth and apoptosis during Drosophila wing development

Dissertation presented to obtain the Ph.D degree in Developmental Biology

Non-assisted versus neuro-navigated and XperCT-guided external ventricular catheter placement: a comparative cadaver study.

BACKGROUND AND PURPOSE: Accurate placement of an external ventricular drain (EVD) for the treatment of hydrocephalus is of paramount importance for its functionality and in order to minimize morbidity and complications. The aim of this study was to compare two different drain insertion assistance tools with the traditional free-hand anatomical landmark method, and to measure efficacy, safety and precision. METHODS: Ten cadaver heads were prepared by opening large bone windows centered on Kocher's points on both sides. Nineteen physicians, divided in two groups (trainees and board certified neurosurgeons) performed EVD insertions. The target for the ventricular drain tip was the ipsilateral foramen of Monro. Each participant inserted the external ventricular catheter in three different ways: 1) free-hand by anatomical landmarks, 2) neuronavigation-assisted (NN), and 3) XperCT-guided (XCT). The number of ventricular hits and dangerous trajectories; time to proceed; radiation exposure of patients and physicians; distance of the catheter tip to target and size of deviations projected in the orthogonal plans were measured and compared. RESULTS: Insertion using XCT increased the probability of ventricular puncture from 69.2 to 90.2 % (p = 0.02). Non-assisted placements were significantly less precise (catheter tip to target distance 14.3 ± 7.4 mm versus 9.6 ± 7.2 mm, p = 0.0003). The insertion time to proceed increased from 3.04 ± 2.06 min. to 7.3 ± 3.6 min. (p < 0.001). The X-ray exposure for XCT was 32.23 mSv, but could be reduced to 13.9 mSv if patients were initially imaged in the hybrid-operating suite. No supplementary radiation exposure is needed for NN if patients are imaged according to a navigation protocol initially. CONCLUSION: This ex vivo study demonstrates a significantly improved accuracy and safety using either NN or XCT-assisted methods. Therefore, efforts should be undertaken to implement these new technologies into daily clinical practice. However, the accuracy versus urgency of an EVD placement has to be balanced, as the image-guided insertion technique will implicate a longer preparation time due to a specific image acquisition and trajectory planning.