3-d residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging.

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Comparison of antibiotic drops placed in the conjunctival cul-de-sac to antibiotic ointment applied to the lid margin in reduction of bacterial colonization on the lid margin.

PURPOSE: To compare the efficacy of antibiotic drops placed in the conjunctival cul-de-sac to antibiotic ointment applied to the lid margin in reduction of bacterial colonization on the lid margin. METHODS: A randomized, prospective, single-masked study was conducted on 19 patients with culture-proven colonization of bacteria on the lid margins. Ophthalmic eligibility criteria included the presence of > or =50 colony-forming units/mL (CFU/mL) of bacteria on both right and left lids. Each patient received one drop of ofloxacin in one eye every night for one week, followed by one drop once a week for one month. In the same manner, each patient received bacitracin ointment (erythromycin or gentamicin ointment if lid margin bacteria were resistant to bacitracin) to the lid margin of the fellow eye. Quantitative lid cultures were taken at initial visit, one week, one month, and two months. Fifteen volunteers (30 lids) served as controls. Lid cultures were taken at initial visit, one week, and one month. RESULTS: Both antibiotic drop and ointment reduced average bacterial CFU/mL at one week and one month. Average bacterial CFU/mL reestablished to baseline values at two months. There was no statistically significant difference between antibiotic drop and ointment in reducing bacterial colonization on the lid margin. CONCLUSION: Antibiotic drops placed in the conjunctival cul-de-sac appear to be as effective as ointment applied to the lid margins in reducing bacterial colonization in patients with > or =50 CFU/mL of bacteria on the lid margins.

Development of model observers applied to 3D breast tomosynthesis microcalcifications and masses

The development of model observers for mimicking human detection strategies has followed from symmetric signals in simple noise to increasingly complex backgrounds. In this study we implement different model observers for the complex task of detecting a signal in a 3D image stack. The backgrounds come from real breast tomosynthesis acquisitions and the signals were simulated and reconstructed within the volume. Two different tasks relevant to the early detection of breast cancer were considered: detecting an 8 mm mass and detecting a cluster of microcalcifications. The model observers were calculated using a channelized Hotelling observer (CHO) with dense difference-of-Gaussian channels, and a modified (Partial prewhitening [PPW]) observer which was adapted to realistic signals which are not circularly symmetric. The sustained temporal sensitivity function was used to filter the images before applying the spatial templates. For a frame rate of five frames per second, the only CHO that we calculated performed worse than the humans in a 4-AFC experiment. The other observers were variations of PPW and outperformed human observers in every single case. This initial frame rate was a rather low speed and the temporal filtering did not affect the results compared to a data set with no human temporal effects taken into account. We subsequently investigated two higher speeds at 5, 15 and 30 frames per second. We observed that for large masses, the two types of model observers investigated outperformed the human observers and would be suitable with the appropriate addition of internal noise. However, for microcalcifications both only the PPW observer consistently outperformed the humans. The study demonstrated the possibility of using a model observer which takes into account the temporal effects of scrolling through an image stack while being able to effectively detect a range of mass sizes and distributions.

The Fry method applied to an augen orthogneiss: Problems and results

The application of the Fry method to measure strain in deformed porphyritic granites is discussed. This method requires that the distribution of markers has to satisfy at least two conditions. It has to be homogeneous and isotropic. Statistics on point distribution with the help of a Morishita diagram can easily test homogeneity. Isotropy can be checked with a cumulative histogram of angles between points. Application of these tests to undeformed (Mte Capanne granite, Elba) and to deformed (Randa orthogneiss, Alps of Switzerland) porphyritic granite reveals that their K-feldspars phenocrysts both satisfy these conditions and can be used as strain markers with the Fry method. Other problems are also examined. One is the possible distribution of deformation on discrete shear-bands. Providing several tests are met, we conclude that the Fry method can be used to estimate strain in deformed porphyritic granites. (c) 2006 Elsevier Ltd. All rights reserved.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Chroma binary similarity and local alignment applied to cover song identification

We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the Music Information Retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music similarity algorithms.This article first presents a series of experiments carried outwith two state-of-the-art methods for cover song identification.We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or Dynamic Time Warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these characteristics is discussed, and the best-performing ones are finally applied to the newly proposed method. Multipleevaluations of this one confirm a large increase in identificationaccuracy when comparing it with alternative state-of-the-artapproaches.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Sedimentological and palaeohydrological responses to tectonics and climate in a small, closed lacustrine system: Oligocene As Pontes Basin (Spain)

A small, closed, lacustrine system developed during the restraining overstep stages of the Oligocene As Pontes strike-slip basin (Spain). The increase in basin accommodation and the headward spread of the drainage, which increased the water input, triggered a change from shallow, holomictic to deeper, meromictic conditions.

Availability of a soluble phosphorus source applied to soil samples with different acidicity levels

Considerations on the interactions of P in the soil-plant system have a long history, but are still topical and not yet satisfactorily understood. One concern is the effect of liming before or after application of soluble sources on the crop yield and efficiency of available P under these conditions. The aim of this study was to evaluate the effect of soil acidity on availability of P from a soluble source, based on plant growth and chemical extractants. Nine soil samples were incubated with a dose of 200 mg kg-1 P in soil with different levels of previously adjusted acidity (pH H2O 4.5; 5.0; 5.5; 6.0 and 6.5) and compared to soils without P application. After 40 days of soil incubation with a P source, each treatment was limed again so that all pH values were adjusted to 6.5 and then sorghum was planted. After the first and second liming the P levels were determined by the extractants Mehlich-1, Bray-1 and Resin, and the fractionated inorganic P forms. In general, the different acidity levels did not influence the P availability measured by plant growth and P uptake at the studied P dose. For some soils however these values increased or decreased according to the initial soil pH (from 4.5 to 6.5). Plant growth, P uptake and P extractable by Mehlich-1 and Bray-1 were significantly correlated, unlike resin-extractable P, at pH values raised to 6.5. These latter correlations were however significant before the second liming. The P contents extracted by Mehlich-1 and Bray-1 were significantly correlated with each other in the entire test range of soil acidity, even after adjusting pH to 6.5, besides depending on the soil buffering capacity for P. Resin was also sensitive to the properties that express the soil buffering capacity for P, but less clearly than Mehlich-1 and Bray-1. The application of triple superphosphate tended to increase the levels of P-Al, P-Fe and P-Ca and the highest P levels extracted by Bray-1 were due to a higher occurrence of P-Al and P-Fe in the soils.