Acceso abierto real y potencial a la producción científica de un país. El caso argentino

Se aporta una metodología para estimar la disponibilidad real y potencial de la producción científica de un país, según el modelo de acceso de las revistas elegidas por los investigadores para publicar sus artículos. Se estudia el caso de la producción científica argentina del período 2008-2010 en medicina, física y astronomía, agricultura y ciencias biológicas, y ciencias sociales y humanidades. La producción fue recogida de la base de datos Scopus y los modelos de acceso de las revistas, determinados a partir de la consulta a DOAJ, e-revist@s, SciELO, RedALyC, PubMed, Romeo-Sherpa y Dulcinea. Se concluye que Argentina presenta condiciones muy favorables para liberar un alto porcentaje de la literatura científica generada en el país bajo la modalidad de acceso abierto a través de repositorios; y que la metodología es reproducible para realizar comparaciones con otros países y campos temáticos. Los resultados aportan conocimiento útil a los gestores de repositorios de las instituciones académicas y de investigación de cara a promocionar su desarrollo y justificar su sostenimiento

Acceso abierto real y potencial a la producción científica de un país. El caso argentino

Se aporta una metodología para estimar la disponibilidad real y potencial de la producción científica de un país, según el modelo de acceso de las revistas elegidas por los investigadores para publicar sus artículos. Se estudia el caso de la producción científica argentina del período 2008-2010 en medicina, física y astronomía, agricultura y ciencias biológicas, y ciencias sociales y humanidades. La producción fue recogida de la base de datos Scopus y los modelos de acceso de las revistas, determinados a partir de la consulta a DOAJ, e-revist@s, SciELO, RedALyC, PubMed, Romeo-Sherpa y Dulcinea. Se concluye que Argentina presenta condiciones muy favorables para liberar un alto porcentaje de la literatura científica generada en el país bajo la modalidad de acceso abierto a través de repositorios; y que la metodología es reproducible para realizar comparaciones con otros países y campos temáticos. Los resultados aportan conocimiento útil a los gestores de repositorios de las instituciones académicas y de investigación de cara a promocionar su desarrollo y justificar su sostenimiento

Acceso abierto real y potencial a la producción científica de un país. El caso argentino

Se aporta una metodología para estimar la disponibilidad real y potencial de la producción científica de un país, según el modelo de acceso de las revistas elegidas por los investigadores para publicar sus artículos. Se estudia el caso de la producción científica argentina del período 2008-2010 en medicina, física y astronomía, agricultura y ciencias biológicas, y ciencias sociales y humanidades. La producción fue recogida de la base de datos Scopus y los modelos de acceso de las revistas, determinados a partir de la consulta a DOAJ, e-revist@s, SciELO, RedALyC, PubMed, Romeo-Sherpa y Dulcinea. Se concluye que Argentina presenta condiciones muy favorables para liberar un alto porcentaje de la literatura científica generada en el país bajo la modalidad de acceso abierto a través de repositorios; y que la metodología es reproducible para realizar comparaciones con otros países y campos temáticos. Los resultados aportan conocimiento útil a los gestores de repositorios de las instituciones académicas y de investigación de cara a promocionar su desarrollo y justificar su sostenimiento

Validation of real time dispersion of Tritium clouds over the Western Mediterranean Basin in different assesments

Real time Tritium concentrations in air coming from an ITER-like reactor as source were coupled the European Centre Medium Range Weather Forecast (ECMWF) numerical model with the lagrangian atmospheric dispersion model FLEXPART. This tool ECMWF/FLEXPART was analyzed in normal operating conditions in the Western Mediterranean Basin during 45 days at summer 2010. From comparison with NORMTRI plumes over Western Mediterranean Basin the real time results have demonstrated an overestimation of the corresponding climatologically sequence Tritium concentrations in air outputs, at several distances from the reactor. For these purpose two clouds development patterns were established. The first one was following a cyclonic circulation over the Mediterranean Sea and the second one was based in the cloud delivered over the Interior of the Iberian Peninsula by another stabilized circulation corresponding to a High. One of the important remaining activities defined then, was the tool qualification. The aim of this paper is to present the ECMWF/FLEXPART products confronted with Tritium concentration in air data. For this purpose a database to develop and validate ECMWF/FLEXPART tritium in both assessments has been selected from a NORMTRI run. Similarities and differences, underestimation and overestimation with NORMTRI will allowfor refinement in some features of ECMWF/FLEXPART

Simulator of the JET real-time disruption predictor

A disruption predictor based on support vector machines (SVM) has been developed to be used in JET. The training process uses thousands of discharges and, therefore, high performance computing has been necessary to obtain the models. To this respect, several models have been generated with data from different JET campaigns. In addition, various kernels (mainly linear and RBF) and parameters have been tested. The main objective of this work has been the implementation of the predictor model under real-time constraints. A “C-code” software application has been developed to simulate the real-time behavior of the predictor. The application reads the signals from the JET database and simulates the real-time data processing, in particular, the specific data hold method to be developed when reading data from the JET ATM real time network. The simulator is fully configurable by means of text files to select models, signal thresholds, sampling rates, etc. Results with data between campaigns C23and C28 will be shown.

Multiple Hashing Integration for Real-Time Large Scale Part-to-Part Video Matching

A real-time large scale part-to-part video matching algorithm, based on the cross correlation of the intensity of motion curves, is proposed with a view to originality recognition, video database cleansing, copyright enforcement, video tagging or video result re-ranking. Moreover, it is suggested how the most representative hashes and distance functions - strada, discrete cosine transformation, Marr-Hildreth and radial - should be integrated in order for the matching algorithm to be invariant against blur, compression and rotation distortions: (R; _) 2 [1; 20]_[1; 8], from 512_512 to 32_32pixels2 and from 10 to 180_. The DCT hash is invariant against blur and compression up to 64x64 pixels2. Nevertheless, although its performance against rotation is the best, with a success up to 70%, it should be combined with the Marr-Hildreth distance function. With the latter, the image selected by the DCT hash should be at a distance lower than 1.15 times the Marr-Hildreth minimum distance.

Pulmonary Artery-Vein Segmentation in Real and Synthetic CT Images = Segmentación Arteria-Vena Pulmonares en Imágenes de CT Reales y Sintéticas

La tomografía axial computerizada (TAC) es la modalidad de imagen médica preferente para el estudio de enfermedades pulmonares y el análisis de su vasculatura. La segmentación general de vasos en pulmón ha sido abordada en profundidad a lo largo de los últimos años por la comunidad científica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciación entre irrigaciones arterial y venosa es aún un problema abierto. De hecho, la separación automática de arterias y venas está considerado como uno de los grandes retos futuros del procesamiento de imágenes biomédicas. La segmentación arteria-vena (AV) permitiría el estudio de ambas irrigaciones por separado, lo cual tendría importantes consecuencias en diferentes escenarios médicos y múltiples enfermedades pulmonares o estados patológicos. Características como la densidad, geometría, topología y tamaño de los vasos sanguíneos podrían ser analizados en enfermedades que conllevan remodelación de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores específicos que aún hoy en dípermanecen ocultos. Esta diferenciación entre arterias y venas también podría ayudar a la mejora y el desarrollo de métodos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los árboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los árboles vasculares del pulmón hace inabordable una separación manual de ambas estructuras en un tiempo realista, fomentando aún más la necesidad de diseñar herramientas automáticas o semiautomáticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva múltiples limitaciones en el desarrollo de sistemas de separación AV, en los cuales son necesarias imágenes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el diseño de imágenes sintéticas de TAC pulmonar podría superar estas dificultades ofreciendo la posibilidad de acceso a una base de datos de casos pseudoreales bajo un entorno restringido y controlado donde cada parte de la imagen (incluyendo arterias y venas) está unívocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales están fuertemente interrelacionados. Primero se describe el diseño de una estrategia para generar, automáticamente, fantomas computacionales de TAC de pulmón en humanos. Partiendo de conocimientos a priori, tanto biológicos como de características de imagen de CT, acerca de la topología y relación entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar vías aéreas, arterias y venas pulmonares sintéticas usando métodos de crecimiento iterativo, que posteriormente se unen para formar un pulmón simulado con características realistas. Estos casos sintéticos, junto a imágenes reales de TAC sin contraste, han sido usados en el desarrollo de un método completamente automático de segmentación/separación AV. La estrategia comprende una primera extracción genérica de vasos pulmonares usando partículas espacio-escala, y una posterior clasificación AV de tales partículas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje automático) y la inclusión de información de conectividad entre partículas. La validación de los fantomas pulmonares se ha llevado a cabo mediante inspección visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersión de estructuras y relación entre arterias y vías aéreas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sintéticamente. La evaluación del algoritmo de segmentación AV está basada en distintas estrategias de comprobación de la exactitud en la clasificación de vasos, las cuales revelan una adecuada diferenciación entre arterias y venas tanto en los casos reales como en los sintéticos, abriendo así un amplio abanico de posibilidades en el estudio clínico de enfermedades cardiopulmonares y en el desarrollo de metodologías y nuevos algoritmos para el análisis de imágenes pulmonares. ABSTRACT Computed tomography (CT) is the reference image modality for the study of lung diseases and pulmonary vasculature. Lung vessel segmentation has been widely explored by the biomedical image processing community, however, differentiation of arterial from venous irrigations is still an open problem. Indeed, automatic separation of arterial and venous trees has been considered during last years as one of the main future challenges in the field. Artery-Vein (AV) segmentation would be useful in different medical scenarios and multiple pulmonary diseases or pathological states, allowing the study of arterial and venous irrigations separately. Features such as density, geometry, topology and size of vessels could be analyzed in diseases that imply vasculature remodeling, making even possible the discovery of new specific biomarkers that remain hidden nowadays. Differentiation between arteries and veins could also enhance or improve methods processing pulmonary structures. Nevertheless, AV segmentation has been unfeasible until now in clinical routine despite its objective usefulness. The huge complexity of pulmonary vascular trees makes a manual segmentation of both structures unfeasible in realistic time, encouraging the design of automatic or semiautomatic tools to perform the task. However, this lack of proper labeled cases seriously limits in the development of AV segmentation systems, where reference standards are necessary in both algorithm training and validation stages. For that reason, the design of synthetic CT images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image (including arteries and veins) is differentiated unequivocally. In this Ph.D. Thesis we address both interrelated problems. First, the design of a complete framework to automatically generate computational CT phantoms of the human lung is described. Starting from biological and imagebased knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. These synthetic cases, together with labeled real CT datasets, have been used as reference for the development of a fully automatic pulmonary AV segmentation/separation method. The approach comprises a vessel extraction stage using scale-space particles and their posterior artery-vein classification using Graph-Cuts (GC) based on arterial/venous similarity scores obtained with a Machine Learning (ML) pre-classification step and particle connectivity information. Validation of pulmonary phantoms from visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems, show good correspondence between real and synthetic lungs. The evaluation of the Artery-Vein (AV) segmentation algorithm, based on different strategies to assess the accuracy of vessel particles classification, reveal accurate differentiation between arteries and vein in both real and synthetic cases that open a huge range of possibilities in the clinical study of cardiopulmonary diseases and the development of methodological approaches for the analysis of pulmonary images.

Are pharmacological randomised controlled clinical trials relevant to real-life asthma populations? : A protocol for an UNLOCK study from the IPCRG

Funding The IPCRG provided funding for this research project as an UNLOCK Group study for which the funding was obtained through an unrestricted grant by Novartis AG, Basel, Switzerland. Novartis has no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. This study will include data from the Optimum Patient Care Research Database and is undertaken in collaboration with Optimum Patient Care and the Respiratory Effectiveness Group.

Staphylococcus aureus genotyping using novel real-time PCR formats

One approach to microbial genotyping is to make use of sets of single-nucleotide polymorphisms (SNPs) in combination with binary markers. Here we report the modification and automation of a SNP-plus-binary-marker-based approach to the genotyping of Staphylococcus aureus and its application to 391 S. aureus isolates from southeast Queensland, Australia. The SNPs used were arcC210, tpi243, arcC162, gmk318, pta294, tpi36, tpi241, and pta383. These provide a Simpson's index of diversity (D) of 0.95 with respect to the S. aureus multilocus sequence typing database and define 61 genotypes and the major clonal complexes. The binary markers used were pvl, cna, sdrE, pT181, and pUB110. Two novel real-time PCR formats for interrogating these markers were compared. One of these makes use of light upon extension (LUX) primers and biplexed reactions, while the other is a streamlined modification of kinetic PCR using SYBR green. The latter format proved to be more robust. In addition, automated methods for DNA template preparation, reaction setup, and data analysis were developed. A single SNP-based method for ST-93 (Queensland clone) identification was also devised. The genotyping revealed the numerical importance of the South West Pacific and Queensland community-acquired methicillin-resistant S. aureus (MRSA) clones and the clonal complex 239 Aus-1/Aus-2 hospital-associated MRSA. There was a strong association between the community-acquired clones and pvl.

Towards effective indexing for very large video sequence database

With rapid advances in video processing technologies and ever fast increments in network bandwidth, the popularity of video content publishing and sharing has made similarity search an indispensable operation to retrieve videos of user interests. The video similarity is usually measured by the percentage of similar frames shared by two video sequences, and each frame is typically represented as a high-dimensional feature vector. Unfortunately, high complexity of video content has posed the following major challenges for fast retrieval: (a) effective and compact video representations, (b) efficient similarity measurements, and (c) efficient indexing on the compact representations. In this paper, we propose a number of methods to achieve fast similarity search for very large video database. First, each video sequence is summarized into a small number of clusters, each of which contains similar frames and is represented by a novel compact model called Video Triplet (ViTri). ViTri models a cluster as a tightly bounded hypersphere described by its position, radius, and density. The ViTri similarity is measured by the volume of intersection between two hyperspheres multiplying the minimal density, i.e., the estimated number of similar frames shared by two clusters. The total number of similar frames is then estimated to derive the overall similarity between two video sequences. Hence the time complexity of video similarity measure can be reduced greatly. To further reduce the number of similarity computations on ViTris, we introduce a new one dimensional transformation technique which rotates and shifts the original axis system using PCA in such a way that the original inter-distance between two high-dimensional vectors can be maximally retained after mapping. An efficient B+-tree is then built on the transformed one dimensional values of ViTris' positions. Such a transformation enables B+-tree to achieve its optimal performance by quickly filtering a large portion of non-similar ViTris. Our extensive experiments on real large video datasets prove the effectiveness of our proposals that outperform existing methods significantly.

Efficient update and retrieval of objects in a multiresolution geospatial database

Many emerging applications benefit from the extraction of geospatial data specified at different resolutions for viewing purposes. Data must also be topologically accurate and up-to-date as it often represents real-world changing phenomena. Current multiresolution schemes use complex opaque data types, which limit the capacity for in-database object manipulation. By using z-values and B+trees to support multiresolution retrieval, objects are fragmented in such a way that updates to objects or object parts are executed using standard SQL (Structured Query Language) statements as opposed to procedural functions. Our approach is compared to a current model, using complex data types indexed under a 3D (three-dimensional) R-tree, and shows better performance for retrieval over realistic window sizes and data loads. Updates with the R-tree are slower and preclude the feasibility of its use in time-critical applications whereas, predictably, projecting the issue to a one-dimensional index allows constant updates using z-values to be implemented more efficiently.

The design of robust protocols for distributed real-time systems

Modern distributed control systems comprise of a set of processors which are interconnected using a suitable communication network. For use in real-time control environments, such systems must be deterministic and generate specified responses within critical timing constraints. Also, they should be sufficiently robust to survive predictable events such as communication or processor faults. This thesis considers the problem of coordinating and synchronizing a distributed real-time control system under normal and abnormal conditions. Distributed control systems need to periodically coordinate the actions of several autonomous sites. Often the type of coordination required is the all or nothing property of an atomic action. Atomic commit protocols have been used to achieve this atomicity in distributed database systems which are not subject to deadlines. This thesis addresses the problem of applying time constraints to atomic commit protocols so that decisions can be made within a deadline. A modified protocol is proposed which is suitable for real-time applications. The thesis also addresses the problem of ensuring that atomicity is provided even if processor or communication failures occur. Previous work has considered the design of atomic commit protocols for use in non time critical distributed database systems. However, in a distributed real-time control system a fault must not allow stringent timing constraints to be violated. This thesis proposes commit protocols using synchronous communications which can be made resilient to a single processor or communication failure and still satisfy deadlines. Previous formal models used to design commit protocols have had adequate state coverability but have omitted timing properties. They also assumed that sites communicated asynchronously and omitted the communications from the model. Timed Petri nets are used in this thesis to specify and design the proposed protocols which are analysed for consistency and timeliness. Also the communication system is mcxielled within the Petri net specifications so that communication failures can be included in the analysis. Analysis of the Timed Petri net and the associated reachability tree is used to show the proposed protocols always terminate consistently and satisfy timing constraints. Finally the applications of this work are described. Two different types of applications are considered, real-time databases and real-time control systems. It is shown that it may be advantageous to use synchronous communications in distributed database systems, especially if predictable response times are required. Emphasis is given to the application of the developed commit protocols to real-time control systems. Using the same analysis techniques as those used for the design of the protocols it can be shown that the overall system performs as expected both functionally and temporally.

The development of a multi-function computer-assisted instruction system using a hierarchical database structure as the lesson compendium.

Computer-Based Learning systems of one sort or another have been in existence for almost 20 years, but they have yet to achieve real credibility within Commerce, Industry or Education. A variety of reasons could be postulated for this, typically: - cost - complexity - inefficiency - inflexibility - tedium Obviously different systems deserve different levels and types of criticism, but it still remains true that Computer-Based Learning (CBL) is falling significantly short of its potential. Experience of a small, but highly successful CBL system within a large, geographically distributed industry (the National Coal Board) prompted an investigation into currently available packages, the original intention being to purchase the most suitable software and run it on existing computer hardware, alongside existing software systems. It became apparent that none of the available CBL packages were suitable, and a decision was taken to develop an in-house Computer-Assisted Instruction system according to the following criteria: - cheap to run; - easy to author course material; - easy to use; - requires no computing knowledge to use (as either an author or student) ; - efficient in the use of computer resources; - has a comprehensive range of facilities at all levels. This thesis describes the initial investigation, resultant observations and the design, development and implementation of the SCHOOL system. One of the principal characteristics c£ SCHOOL is that it uses a hierarchical database structure for the storage of course material - thereby providing inherently a great deal of the power, flexibility and efficiency originally required. Trials using the SCHOOL system on IBM 303X series equipment are also detailed, along with proposed and current development work on what is essentially an operational CBL system within a large-scale Industrial environment.