Model of sources: a proposal for the hierarchy, merging strategy and representation of the information sources in virtual models of historical buildings

Contributed to: Fusion of Cultures: XXXVIII Annual Conference on Computer Applications and Quantitative Methods in Archaeology – CAA2010 (Granada, Spain, Apr 6-9, 2010)

Dobutamine in Paediatric Population: A Systematic Review in Juvenile Animal Models

Objective: Although dobutamine is widely used in neonatal clinical practice, the evidence for its use in this specific population is not clear. We conducted a systematic review of the use of dobutamine in juvenile animals to determine whether the evidence from juvenile animal experiments with dobutamine supported the design of clinical trials in neonatal/ paediatric population. Methods: Studies were identified by searching MEDLINE (1946-2012) and EMBASE (1974-2012). Articles retrieved were independently reviewed by three authors and only those concerning efficacy and safety of the drug in juvenile animals were included. Only original articles published in English and Spanish were included. Results: Following our literature search, 265 articles were retrieved and 24 studies were included in the review: 17 focused on neonatal models and 7 on young animal models. Although the aims and design of these studies, as well as the doses and ages analysed, were quite heterogeneous, the majority of authors agree that dobutamine infusion improves cardiac output in a dose dependent manner. Moreover, the cardiovascular effects of dobutamine are influenced by postnatal age, as well as by the dose used and the duration of the therapy. There is inadequate information about the effects of dobutamine on cerebral perfusion to draw conclusions. Conclusion: There is enough preclinical evidence to ensure that dobutamine improves cardiac output, however to better understand its effects in peripheral organs, such as the brain, more specific and well designed studies are required to provide additional data to support the design of clinical trials in a paediatric population.

Practical applications of the likelihood, time transcendence and metadata in virtual models of heritage elements

Contributed to: III Bienal de Restauración Monumental: "Sobre la des-restauración" (Sevilla, Spain, Nov 23-25, 2006)

Time transcendence, metadata and future utilization in 3D models of point clouds for heritage elements

Contributed to: Virtual Retrospect 2007 (Pessac, France, Nov 14-16, 2007)

Algorithms for colour image processing based on neurological models

373 p. : il., gráf., fot., tablas

A review of travel time estimation and forecasting for advanced traveler information systems

Providing on line travel time information to commuters has become an important issue for Advanced Traveler Information Systems and Route Guidance Systems in the past years, due to the increasing traffic volume and congestion in the road networks. Travel time is one of the most useful traffic variables because it is more intuitive than other traffic variables such as flow, occupancy or density, and is useful for travelers in decision making. The aim of this paper is to present a global view of the literature on the modeling of travel time, introducing crucial concepts and giving a thorough classification of the existing tech- niques. Most of the attention will focus on travel time estimation and travel time prediction, which are generally not presented together. The main goals of these models, the study areas and methodologies used to carry out these tasks will be further explored and categorized.

Energy and information in Hodgkin-Huxley neurons

[EN]The generation of spikes by neurons is energetically a costly process and the evaluation of the metabolic energy required to maintain the signaling activity of neurons a challenge of practical interest. Neuron models are frequently used to represent the dynamics of real neurons but hardly ever to evaluate the electrochemical energy required to maintain that dynamics. This paper discusses the interpretation of a Hodgkin-Huxley circuit as an energy model for real biological neurons and uses it to evaluate the consumption of metabolic energy in the transmission of information between neurons coupled by electrical synapses, i.e., gap junctions. We show that for a single postsynaptic neuron maximum energy efficiency, measured in bits of mutual information per molecule of adenosine triphosphate (ATP) consumed, requires maximum energy consumption. For groups of parallel postsynaptic neurons we determine values of the synaptic conductance at which the energy efficiency of the transmission presents clear maxima at relatively very low values of metabolic energy consumption. Contrary to what could be expected, the best performance occurs at a low energy cost.

Mateda-2.0: Estimation of Distribution Algorithms in MATLAB

This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based on undirected and directed probabilistic graphical models. The implementation contains several methods commonly employed by EDAs. It is also conceived as an open package to allow users to incorporate different combinations of selection, learning, sampling, and local search procedures. Additionally, it includes methods to extract, process and visualize the structures learned by the probabilistic models. This way, it can unveil previously unknown information about the optimization problem domain. Mateda-2.0 also incorporates a module for creating and validating function models based on the probabilistic models learned by EDAs.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

Problems when generating virtual models representing real objects: Hondarribia walls

[EN] This paper is based in the following project:

Hunting spectro-temporal information in unevenly spaced paleoclimate time series

18 p.

Informazio-iturrien garrantzia berrikuntza teknologikoko jardueretarako

[EU]Gaur egunean bizi dugun krisi ekonomiko, produkzio ereduen transformazio eta globalizazioko testuinguruan, ikerketa, garapena eta berrikuntza (I+G+b) ezinbesteko faktoreak bilakatu dira herrialdeen hazkunde eta enpresen lidergo zein biziraupenerako. Berritasunaren bilatze horretan, egungo merkatuan enpresek etengabe egin beharreko egokitzapen teknologikoak direla eta, berrikuntza teknologikoak, hau da, produktuan edo prozesuan berritzeak, berebiziko garrantzia du. Gainera, oro har, lehiakortasunik ez galtzeko informazio estrategikoaren jabe izatea enpresentzat funtsezkoa bada ere, berrikuntza jarduerak aurrera eramateko oraindik ere gailentasun handiagoa dauka. Informazio estrategikoa iturri ezberdinetatik jaso daiteke eta horietako bakoitzari ematen zaion garrantzia ezberdina da. Lan honen helburua erlazio hori aztertzearena izanik, ondoriozta dezakegu, alde batetik, produktuan zein prozesuan berritzen duten enpresek, berrikuntza teknologikoak aurrera eramateko garaian, enpresa barnetik jasotako informazioari ematen diotela garrantzi gehien. Eta bestaldetik, instituzio publikoetatik, hau da, unibertsitate edo goi-ikasketetako zentroetatik, ikerketako erakunde publikoetatik edota zentro teknologikoetatik jasotako informazioari garrantzi gutxi ematen zaiola.

Countervailing incentives in adverse selection models. A synthesis

In this paper we propose a simple method of characterizing countervailing incentives in adverse selection problems. The key element in our characterization consists of analyzing properties of the full information problem. This allows solving the principal problem without using optimal control theory. Our methodology can also be applied to different economic settings: health economics, monopoly regulation, labour contracts, limited liabilities and environmental regulation.

Social, economic, and health impact of the respiratory syncytial virus: a systematic search

Background: Bronchiolitis caused by the respiratory syncytial virus (RSV) and its related complications are common in infants born prematurely, with severe congenital heart disease, or bronchopulmonary dysplasia, as well as in immunosuppressed infants. There is a rich literature on the different aspects of RSV infection with a focus, for the most part, on specific risk populations. However, there is a need for a systematic global analysis of the impact of RSV infection in terms of use of resources and health impact on both children and adults. With this aim, we performed a systematic search of scientific evidence on the social, economic, and health impact of RSV infection. Methods: A systematic search of the following databases was performed: MEDLINE, EMBASE, Spanish Medical Index, MEDES-MEDicina in Spanish, Cochrane Plus Library, and Google without time limits. We selected 421 abstracts based on the 6,598 articles identified. From these abstracts, 4 RSV experts selected the most relevant articles. They selected 65 articles. After reading the full articles, 23 of their references were also selected. Finally, one more article found through a literature information alert system was included. Results: The information collected was summarized and organized into the following topics: 1. Impact on health (infections and respiratory complications, mid-to long-term lung function decline, recurrent wheezing, asthma, other complications such as otitis and rhino-conjunctivitis, and mortality; 2. Impact on resources (visits to primary care and specialists offices, emergency room visits, hospital admissions, ICU admissions, diagnostic tests, and treatments); 3. Impact on costs (direct and indirect costs); 4. Impact on quality of life; and 5. Strategies to reduce the impact (interventions on social and hygienic factors and prophylactic treatments). Conclusions: We concluded that 1. The health impact of RSV infection is relevant and goes beyond the acute episode phase; 2. The health impact of RSV infection on children is much better documented than the impact on adults; 3. Further research is needed on mid-and long-term impact of RSV infection on the adult population, especially those at high-risk; 4. There is a need for interventions aimed at reducing the impact of RSV infection by targeting health education, information, and prophylaxis in high-risk populations.

Usage of substances and their dosage regimes in pharmacological animal models of schizophrenia

Background: Contrary to what is generally thought schizophrenia is a very common mental health issue. For this, several animal models are used to assess the illness in order to develop a definitive. The most widely spread paradigm is the use of pharmacological models. Aim: The aim of this review is to display which are the most used insults for the assessment of social behaviour related negative symptoms in animal models as well as to ascertain which is the most adequate regime. Design: Literature review. Methods: PubMed database was used for this article by the search of the indexed “schizophrenia”, “animal models”, “social behaviour” and “negative symptoms” descriptors. With the exception of a single article due to it value this review is based on articles from 10 years onwards. Besides, only clinical trials and reviews written in English or Spanish and that had laboratory rodents as target population were accepted. Results: The studies assessed agree that pharmacological models (specially those regarding the NMDA receptor antagonists) are a valuable means for the experimental investigation of negative symptoms in schizophrenia with the necessity to emphasise that only some negative symptoms (anhedonia and social interaction, mainly) can be experimentally assessed. Conclusions: There is not enough evidence regarding the fours aspects of this review. PCP, Ketamine or MK-801 in sub-acute dosage regimes are currently the most indicated insults to mimic schizophrenic symptoms in rodents, although further research in needed, albeit other substances are valuable as well. (In English language exclusively)