NS4B Self-Interaction through Conserved C-Terminal Elements Is Required for the Establishment of Functional Hepatitis C Virus Replication Complexes.

Hepatitis C virus (HCV) is an important human pathogen, persistently infecting more than 170 million individuals worldwide. Studies of the HCV life cycle have become possible with the development of cell culture systems supporting the replication of viral RNA and the production of infectious virus. However, the exact functions of individual proteins, especially of nonstructural protein 4B (NS4B), remain poorly understood. NS4B triggers the formation of specific, vesicular membrane rearrangements, referred to as membranous webs, which have been reported to represent sites of HCV RNA replication. However, the mechanism of vesicle induction is not known. In this study, a panel of 15 mutants carrying substitutions in the highly conserved NS4B C-terminal domain was generated. Five mutations had only a minor effect on replication, but two of them enhanced assembly and release of infectious virus. Ten mutants were replication defective and used for selection of pseudoreversions. Most of the pseudoreversions also localized to the highly conserved NS4B C-terminal domain and were found to restore replication competence upon insertion into the corresponding primary mutant. Importantly, pseudoreversions restoring replication competence also restored heterotypic NS4B self-interaction, which was disrupted by the primary mutation. Finally, electron microscopy analyses of membrane alterations induced by NS4B mutants revealed striking morphological abnormalities, which were restored to wild-type morphology by the corresponding pseudoreversion. These findings demonstrate the important role of the C-terminal domain in NS4B self-interaction and the formation of functional HCV replication complexes.

Genesis of self-organized zebra textures in burial dolomites: Displacive veins, induced stress, and dolomitization

The dolomite veins making up rhythmites common in burial dolomites are not cement infillings of supposed cavities, as in the prevailing view, but are instead displacive veins, veins that pushed aside the host dolostone as they grew. Evidence that the veins are displacive includes a) small transform-fault-like displacements that could not have taken place if the veins were passive cements, and b) stylolites in host rock that formed as the veins grew in order to compensate for the volume added by the veins. Each zebra vein consists of crystals that grow inward from both sides, and displaces its walls via the local induced stress generated by the crystal growth itself. The petrographic criterion used in recent literature to interpret zebra veins in dolomites as cements - namely, that euhedral crystals can grow only in a prior void - disregards evidence to the contrary. The idea that flat voids did form in dolostones is incompatible with the observed optical continuity between the saddle dolomite euhedra of a vein and the replacive dolomite crystals of the host. The induced stress is also the key to the self-organization of zebra veins: In a set of many incipient, randomly-spaced, parallel veins just starting to grow in a host dolostone, each vein¿s induced stress prevents too-close neighbor veins from nucleating, or redissolves them by pressure-solution. The veins that survive this triage are those just outside their neighbors¿s induced stress haloes, now forming a set of equidistant veins, as observed.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

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.

Willigness to pay for long-term care coverage: the role of private information and self-insurance

Both public and private insurance for long-term care is undeveloped in some European countries such as in Spain and empirical evidence is still limited. This paper aims at exmining the determinants of the demand for Long Term Care (LTC) coverage in Spain using contingent valuation techniques. Our findings indicate that only one-fifth of the population is willing to pay to assure coverage decisions are significantly affected by private information asymmetry and housing tenure in giving rise to self-insurance reduces the probability of insurance being hypothetically purchased.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Systematic trends in self-consistent calculations of linear quantum wires

Systematic trends in the properties of a linear split-gate heterojunction are studied by solving iteratively the Poisson and Schrödinger equations for different gate potentials and temperatures. A two-dimensional approximation is presented that is much simpler in the numerical implementation and that accurately reproduces all significant trends. In deriving this approximation, we provide a rigorous and quantitative basis for the formulation of models that assumes a two-dimensional character for the electron gas at the junction.

Ground-state self-consistent calculation of quantum dots under magnetic fields: Addition spectrum

A density-functional self-consistent calculation of the ground-state electronic density of quantum dots under an arbitrary magnetic field is performed. We consider a parabolic lateral confining potential. The addition energy, E(N+1)-E(N), where N is the number of electrons, is compared with experimental data and the different contributions to the energy are analyzed. The Hamiltonian is modeled by a density functional, which includes the exchange and correlation interactions and the local formation of Landau levels for different equilibrium spin populations. We obtain an analytical expression for the critical density under which spontaneous polarization, induced by the exchange interaction, takes place.

Magnetic-field dependence of hole levels in self-assembled InGaAs quantum dots

Recent magnetotransport experiments of holes in InGaAs quantum dots [D. Reuter, P. Kailuweit, A. D. Wieck, U. Zeitler, O. Wibbelhoff, C. Meier, A. Lorke, and J. C. Maan, Phys. Rev. Lett. 94, 026808 (2005)] are interpreted by employing a multiband k¿p Hamiltonian, which considers the interaction between heavy hole and light hole subbands explicitly. No need of invoking an incomplete energy shell filling is required within this model. The crucial role we ascribe to the heavy hole-light hole interaction is further supported by one-band local-spin-density functional calculations, which show that Coulomb interactions do not induce any incomplete hole shell filling and therefore cannot account for the experimental magnetic field dispersion.