Showing papers by "University of Seville published in 2007"

Generalized Predictive Control

Abstract: This chapter describes one of the most popular predictive control algorithms: Generalized Predictive Control (GPC). The method is developed in detail, showing the general procedure to obtain the control law and its most outstanding characteristics. The original algorithm is extended to include the cases of measurable disturbances and change in the predictor. Close derivations of this controller such as CRHPC and Stable GPC are also treated here, illustrating the way they can be implemented.

Resveratrol as an antioxidant and pro-oxidant agent: mechanisms and clinical implications.

Abstract: Resveratrol (3,4′,5-trihydroxystilbene) is found in various plants, including grapes, berries and peanuts. It is also present in wines, especially red wines. During the last years, it has been the focus of numerous in vitro and in vivo studies investigating its biological attributes, which include mainly antioxidant and anti-inflammatory activities, anti-platelet aggregation effect, anti-atherogenic property, oestrogen-like growth-promoting effect, growth-inhibiting activity, immunomodulation and chemoprevention. In fact, recently, it has been demonstrated that the stilbene blocks the multistep process of carcinogenesis at various stages: tumour initiation, promotion and progression. More recent results provide interesting insights into the effect of this compound on the life span of yeasts and flies, implicating the potential of resveratrol as an anti-aging agent in treating age-related human diseases. Nevertheless, depending on the concentration of the phytoalexin and the cell type, it has also been shown that resveratrol can exhibit pro-oxidant properties, leading to oxidative breakage of cellular DNA in the presence of transition metal ions such as copper. Recently, it has been proposed that such a pro-oxidant action could be a common mechanism for anticancer and chemopreventive properties of plant polyphenols. The present paper is intended to provide the reader up-to-date information on the antioxidant and pro-oxidant properties of resveratrol and its clinical implications.

A practical guide to analytical method validation, including measurement uncertainty and accuracy profiles

Abstract: The objective of analytical method validation is to ensure that every future measurement in routine analysis will be close enough to the unknown true value for the content of the analyte in the sample. Classical approaches to validation only check performance against reference values, but this does not reflect the needs of consumers. A holistic approach to validation also takes into account the expected proportion of acceptable results lying inside predefined acceptability intervals. In this article, we give a detailed step-by-step guide to analytical method validation, considering the most relevant procedures for checking the quality parameters of analytical methods. Using a holistic approach, we also explain the estimation of measurement uncertainty and accuracy profiles, which we discuss in terms of accreditation requirements and predefined acceptability limits.

Model Predictive Controllers

Abstract: This chapter describes the elements that are common to all Model Predictive controllers, showing the various alternatives used in the different implementations. Some of the most popular methods will later be reviewed to demonstrate their most outstanding characteristics.

Does Social Capital Affect Entrepreneurial Intentions

Abstract: Nowadays, the scientific community assigns both social context and entrepreneurs’ behavior as a central role in the growth and development of the world economy. However, the relationships between these two factors have not been sufficiently studied in business and economics. Therefore, in this paper, the specific influence of the new socioeconomic factor of social capital on the formation of entrepreneurial intentions will be analyzed. To test the theoretical hypotheses, an empirical study will be carried out using the Partial Least Squares (PLS) technique with data from a sample of young undergraduate students in the last year of their degree. This population has been selected because these individuals, according to different studies, show a higher propensity towards firm creation.

Deriving origin destination data from a mobile phone network

Abstract: Acquiring high-quality origin-destination (OD) information for traffic in a geographic area is both time consuming and expensive while using conventional methods such as household surveys or roadside monitoring. These methods generally present only a snapshot of traffic situation at a certain point in time, and they are updated in time intervals of up to several years. A technique was developed that makes use of the global system for mobile communications (GSM) mobile phone network. Instead of monitoring the flow of vehicles in a transportation network, the flow of mobile phones in a cell-phone network is measured and correlated to traffic flow. This methodology is based on the fact that a mobile phone moving on a specific route always tends to change the base station nearly at the same position. For a first pilot study, a GSM network simulator has been designed, where network data can be simulated, which is then extracted from the phone network, correlated, processed mathematically and converted into an OD matrix. Primary results show that the method has great potential, and the results inferred are much more cost-effective than those generated with traditional techniques. This is due to the fact that no change has to be made in the GSM network, because the information that is needed can readily be extracted from the base station database, that is the entire infrastructure needed is already in place

Constrained Model Predictive Control

Abstract: The control problem was formulated in the previous chapters considering all signals to possess an unlimited range. This is not very realistic because in practice all processes are subject to constraints. Actuators have a limited range of action and a limited slew rate, as is the case of control valves limited by a fully closed and fully open position and a maximum slew rate. Constructive or safety reasons, as well as sensor range, cause bounds in process variables, as in the case of levels in tanks, flows in pipes, and pressures in deposits. Furthermore, in practice, the operating points of plants are determined to satisfy economic goals and lie at the intersection of certain constraints. The control system normally operates close to the limits and constraint violations are likely to occur. The control system, especially for longrange predictive control, has to anticipate constraint violations and correct them in an appropriate way. Although input and output constraints are basically treated in the same way, as is shown in this chapter, the implications of the constraints differ. Output constraints are mainly due to safety reasons and must be controlled in advance because output variables are affected by process dynamics. Input (or manipulated) variables can always be kept in bound by the controller by clipping the control action to a value satisfying amplitude and slew rate constraints.

High-growth SMEs versus non-high-growth SMEs: a discriminant analysis

Abstract: The purpose of this paper is to analyse the main variables that allow one to distinguish between high-growth firms and non-high-growth firms. Theoretically, we discuss such differences through a combination of economic (external approach) and strategic (internal approach) visions. Empirically, this paper provides two differences with regard to previous literature: (1) the primary goal of our work is not to provide an outright explanation of firm growth; rather, we aim to establish what characteristics enable us to distinguish between high-growth and non-high-growth firms. This aspect determines the methodology used (discriminant analysis with dichotomic dependent variable); and (2) firm high growth is understood as an extraordinary growth in comparison with the average growth of other firms in the same industry, and not in absolute terms. The results show that in the main high-growth firms are different from moderate-growth firms or declining firms because of their smaller size (which is contrary to Gibra...

A Flexible Selective Harmonic Mitigation Technique to Meet Grid Codes in Three-Level PWM Converters

Abstract: Due to the development of new grid codes, power converters' output signal harmonic control is currently becoming extremely important in medium- and high-power applications. By taking this new scenario into account, a new method to generate switching three-level pulsewidth-modulation (PWM) patterns to meet specific grid codes is presented. The proposed method, which is named selective harmonic mitigation PWM , generates switching three-level PWM patterns with high quality from the point of view of harmonic content, avoiding the elimination of some specific harmonics and studying all harmonics and the total harmonic distortion as a global problem by using a general-purpose random-search heuristic algorithm. This fact leads to a drastic reduction or even avoidance of the bulky and costly grid connection tuned filters of power systems. Any harmonic shaping can be considered due to the flexibility of the method. Power devices switching constraints are considered to obtain directly applicable results. As a practical example, limits from one actual grid code have been used to get the experimental results by means of a 150-kVA three-level diode-clamped converter test bench. Comparisons between the proposed technique, optimized PWM and Selective Harmonic Elimination methods have been carried out. The results obtained with this new method greatly improve previous ones.

Multiple UAV cooperative searching operation using polygon area decomposition and efficient coverage algorithms

Abstract: This paper focuses on the problem of cooperatively searching a given area to detect objects of interest, using a team of heterogenous unmanned air vehicles (UAVs). The paper presents algorithms to divide the whole area taking into account UAV’s relative capabilities and initial locations. Resulting areas are assigned among the UAVs, who could cover them using a zigzag pattern. Each UAV has to compute the sweep direction which minimizes the number of turns needed along a zigzag pattern. Algorithms are developed considering their computational complexity in order to allow near-real time operation. Results demonstrating the feasibility of the cooperative search in a scenario of the COMETS multi-UAV project are presented.

Electricity Market Price Forecasting Based on Weighted Nearest Neighbors Techniques

Abstract: This paper presents a simple technique to forecast next-day electricity market prices based on the weighted nearest neighbors methodology. First, it is explained how the relevant parameters defining the adopted model are obtained. Such parameters have to do with the window length of the time series and with the number of neighbors chosen for the prediction. Then, results corresponding to the Spanish electricity market during 2002 are presented and discussed. Finally, the performance of the proposed method is compared with that of recently published techniques.

Differentiation of green, white, black, Oolong, and Pu-erh teas according to their free amino acids content.

Abstract: In this paper, the differentiation of green, black, Oolong, white, and Pu-erh teas has been carried out according to their free amino acid contents. Alanine, arginine, asparagine, aspartic acid, glutamic acid, isoleucine, histidine, leucine, phenylalanine, serine, theanine, threonine, and tyrosine have been determined by liquid chromatography with derivatization with o-phthalaldehyde and fluorescence detection. The chromatographic separation was achieved with a Hypersil ODS column and gradient elution. The amino acid contents were used as chemometric descriptors for classification purposes of different tea varieties. Principal component analysis, k-nearest neighbors, linear discriminant analysis, and artificial neural networks were applied to differentiate tea varieties. Using back-propagation multilayer perceptron artificial neural networks, 100% success in the classification was obtained. The most differentiating amino acids were glutamic acid, asparagine, serine, alanine, leucine, and isoleucine.

Small universal spiking neural P systems.

Abstract: In search for small universal computing devices of various types, we consider here the case of spiking neural P systems (SN P systems), in two variants: as devices that compute functions and as devices that generate sets of numbers. We start with the first case and we produce a universal spiking neural P system with 84 neurons. If a slight generalization of the used rules is adopted, namely, we allow rules for producing simultaneously several spikes, then a considerable reduction, to 49 neurons, is obtained. For SN P systems used as generators of sets of numbers, we find a universal system with restricted rules having 76 neurons and one with extended rules having 50 neurons.

Fama: Tooling a Framework for the Automated Analysis of Feature Models

Abstract: The automated analysis of feature models is recognized as one of the key challenges for automated software development in the context of Software Product Lines (SPL). However, after years of research only a few ad-hoc proposals have been presented in such area and the tool support demanded by the SPL community is still insufficient. In previous work we showed how the selection of a logic representation and a solver to handle analysis on feature models can have a remarkable impact in the performance of the analysis process. In this paper we present a first implementation of FAMA (FeAture Model Analyser). FAMA is a framework for the automated analysis of feature models integrating some of the most commonly used logic representations and solvers proposed in the literature. To the best of our knowledge, FAMA is the first tool integrating different solvers for the automated analyses of feature models.

Deletion of CASK in mice is lethal and impairs synaptic function

Abstract: CASK is an evolutionarily conserved multidomain protein composed of an N-terminal Ca2+/calmodulin-kinase domain, central PDZ and SH3 domains, and a C-terminal guanylate kinase domain. Many potential activities for CASK have been suggested, including functions in scaffolding the synapse, in organizing ion channels, and in regulating neuronal gene transcription. To better define the physiological importance of CASK, we have now analyzed CASK “knockdown” mice in which CASK expression was suppressed by ≈70%, and CASK knockout (KO) mice, in which CASK expression was abolished. CASK knockdown mice are viable but smaller than WT mice, whereas CASK KO mice die at first day after birth. CASK KO mice exhibit no major developmental abnormalities apart from a partially penetrant cleft palate syndrome. In CASK-deficient neurons, the levels of the CASK-interacting proteins Mints, Veli/Mals, and neurexins are decreased, whereas the level of neuroligin 1 (which binds to neurexins that in turn bind to CASK) is increased. Neurons lacking CASK display overall normal electrical properties and form ultrastructurally normal synapses. However, glutamatergic spontaneous synaptic release events are increased, and GABAergic synaptic release events are decreased in CASK-deficient neurons. In contrast to spontaneous neurotransmitter release, evoked release exhibited no major changes. Our data suggest that CASK, the only member of the membrane-associated guanylate kinase protein family that contains a Ca2+/calmodulin-dependent kinase domain, is required for mouse survival and performs a selectively essential function without being in itself required for core activities of neurons, such as membrane excitability, Ca2+-triggered presynaptic release, or postsynaptic receptor functions.

Evolution of the Intellectual Structure of Family Business Literature: A Bibliometric Study of FBR

Abstract: This article aims at identifying the characteristics of the family business as a differentiated field within management. For that aim, we use author co-citation analysis (ACA) to identify different research trends within the field, studying all the papers published in the Family Business Review from its foundation in 1988 through to the December 2005 issue. Results show that despite the literature being fragmented and showing a lack of consensus, we are facing, in Kuhn's words, a development of the research frontier by enlarging the number of approaches used for understanding the family business.