Obtenção e caracterização de filmes de misturas de amido resistence e pectina como estratégia para liberação cólon específica de fármacos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Synthese und Charakterisierung einer Hydrogelmatrix für die Multianalyt-Sensorik

Gegenstand und Ziel der vorliegenden Arbeit war die Synthese und Charakterisierung einer Hydrogelmatrix, welche für die Herstellung eines vielseitig verwendbaren Sensors, der mehrere Analyten (Proteine, DNA etc.) in hoher Verdünnung (c0 < 50 fM) aus kleinsten Probenmengen (Volumina <20 nl) schnell (t < 1 min) und parallel nachweisen kann, Verwendung finden soll. Der Fokus der Arbeit lag dabei in der Synthese und Charakterisierung von Copolymeren als Hydrogelmatrix, welche geeignetes temperaturabhängiges Verhalten zeigen. Die Copolymere wurden in eine dreidimensionale Netzwerkstruktur überführt und auf einer Goldoberfläche kovalent angebunden, um Delamination zu vermeiden und die Untersuchung mittels Oberflächenplasmonenresonanz-Spektroskopie (SPR) und Optischer Wellenleiter-Spektroskopie (OWS) zu erlauben. Weiterhin wurde das temperaturabhängige Verhalten der Polymernetzwerke in Wasser mittels optischen Messungen (SPR/OWS) untersucht, um Erkenntnisse über die Quell- und Kollabiereigenschaften des Hydrogels zu gewinnen. Um temperaturschaltbare Hydrogele herzustellen, wurden auf N-Isopropylacrylamid (NIPAAm) basierende Polymere synthetisiert. Es wurde sowohl die für Hydrogele übliche Methode der freien radikalischen Vernetzungspolymerisation in Wasser, wie eine neue, auf Benzophenoneinheiten basierende Syntheseroute, welche die freie radikalische Polymerisation in organischem Medium nutzt, verwendet. Die synthetisierten Polymere sind Copolymere aus N‑Isopropylacrylamid (NIPAAm) und 4-Methacryloyloxybenzophenon (MABP). NIPAAm ist dabei für das temperaturschaltbare Verhalten der Gele verantwortlich und MABP dient als Photovernetzer. Weitere Copolymere, die neben den genannten Monomeren noch andere Funktionen, wie z.B. ionische Gruppen oder Aktivesterfunktionen enthalten, wurden ebenfalls synthetisiert. Das temperaturabhängige Quellverhalten in Bezug auf die chemische Zusammensetzung wurde mit der Oberflächenplasmonenresonanz-Spektroskopie (SPR) und Optischen Wellenleiter-Spektroskopie (OWS) untersucht. Es zeigte sich, dass die Anwesenheit von Salz im Hydrogel (Natriumacrylat als Monomer, P4S) Inhomogenität, in Form eines Brechungsindexgradienten senkrecht zur Substratoberfläche, hervorruft. Dies ist nicht der Fall, wenn statt des Salzes die Säure (Methacrylsäure als Monomer, P4A) verwendet wird. Durch die Inhomogenität lassen sich die Filme mit dem Natriummethacrylat nicht mehr mit dem, üblicherweise zur Auswertung genutzten, Kastenmodell beschreiben. Die Anwendung der Wentzel-Kramers-Brillouin-Näherung (WKB) auf die Messdaten führt hingegen zu dem gewünschten Ergebnis. Man findet ein kastenähnliches Brechungsindexprofil für das Hydrogel mit der Säure (P4A) und ein Gradientenprofil für das Gel mit dem Salz (P4S). Letzteres ist nicht nur hydrophiler und insgesamt stärker gequollen, sondern ragt auch weiter in die überstehende Wasserphase hinein. Anhand eines säurehaltigen Hydrogels (P8A) konnte der quellungshemmende Einfluss von hohen Salzkonzentrationen gezeigt werden. Weiterhin wurde während des Quellvorgangs eine gewisse Anisotropie gefunden, die aber im vollständig gequollenen und vollständig kollabierten Zustand nicht mehr vorliegt. Anhand eines Hydrogels ohne ionisierbare Gruppen (P9) wurde die Reversibilität des Quell- und Kollabiervorgangs gezeigt. Bei einem Vergleich zwischen einem säurehaltigen Hydrogel (P8A, Quellgrad von 7,3) und einem ohne ionisierbare Gruppen (P9, Quellgrad von 6,1), hat die Anwesenheit der 8 mol% Säuregruppen eine leichte Verstärkung der Quellung um den Faktor 1,2 bewirkt. Rasterkraftmikroskopische Untersuchungen (AFM) an diesen beiden Hydrogelen im getrockneten Zustand, haben gezeigt, dass nach dem Quellen, Kollabieren und Trocknen bei beiden Gelen Porenstrukturen sehr unterschiedlicher Ausmaße vorliegen.

Evaluating perspectives for PRRS virus elimination from pig dense areas with a risk factor based herd index

Porcine reproductive and respiratory syndrome virus (PRRSV) is wide-spread in pig populations globally. In many regions of Europe with intensive pig production and high herd densities, the virus is endemic and can cause disease and production losses. This fuels discussion about the feasibility and sustainability of virus elimination from larger geographic regions. The implementation of a program aiming at virus elimination for areas with high pig density is unprecedented and its potential success is unknown. The objective of this work was to approach pig population data with a simple method that could support assessing the feasibility of a sustainable regional PRRSV elimination. Based on known risk factors such as pig herd structure and neighborhood conditions, an index characterizing individual herds' potential for endemic virus circulation and reinfection was designed. This index was subsequently used to compare data of all pig herds in two regions with different pig- and herd-densities in Lower Saxony (North-West Germany) where PRRSV is endemic. Distribution of the indexed herds was displayed using GIS. Clusters of high herd index densities forming potential risk hot spots were identified which could represent key target areas for surveillance and biosecurity measures under a control program aimed at virus elimination. In an additional step, for the study region with the higher pig density (2463 pigs/km(2) farmland), the potential distribution of PRRSV-free and non-free herds during the implementation of a national control program aiming at national virus elimination was modeled. Complex herd and trade network structures suggest that PRRSV elimination in regions with intensive pig farming like that of middle Europe would have to involve legal regulation and be accompanied by important trade and animal movement restrictions. The proposed methodology of risk index mapping could be adapted to areas varying in size, herd structure and density. Interpreted in the regional context, this could help to classify the density of risk and to accordingly target resources and measures for elimination.

University and school students' motivation for effortful thinking: Factor structure, reliability, and validity of the German Need for Cognition Scale

Need for cognition (NFC) reflects a relatively stable trait regarding the degree to which one enjoys and engages in cognitive endeavors. We examined whether the previously demonstrated one-dimensional structure of the German NFC Scale could be replicated in three samples of undergraduates and secondary school students. Moreover, we investigated the test-retest reliability of the German NFC Scale, which has not yet been tested. Further, we investigated whether the scale would be valid in a sample of secondary school students. Multigroup confirmatory factor analyses established the one-dimensional factor structure of the long form as well as the short form of the German NFC Scale for undergraduates (N = 559), students of academic track secondary schools (German Gymnasium; N = 555), and students of vocational track secondary schools (German Realschule; N = 486). The scale proved to have a high test-retest reliability in a university student sample (N = 43). For secondary school students, we again found a high test-retest reliability (N = 157), and also found the scale to be valid (N = 181).

Modeling Techniques for the High-Resolution Interpretation of Cryo-Electron Microscopy Reconstructions

Essential biological processes are governed by organized, dynamic interactions between multiple biomolecular systems. Complexes are thus formed to enable the biological function and get dissembled as the process is completed. Examples of such processes include the translation of the messenger RNA into protein by the ribosome, the folding of proteins by chaperonins or the entry of viruses in host cells. Understanding these fundamental processes by characterizing the molecular mechanisms that enable then, would allow the (better) design of therapies and drugs. Such molecular mechanisms may be revealed trough the structural elucidation of the biomolecular assemblies at the core of these processes. Various experimental techniques may be applied to investigate the molecular architecture of biomolecular assemblies. High-resolution techniques, such as X-ray crystallography, may solve the atomic structure of the system, but are typically constrained to biomolecules of reduced flexibility and dimensions. In particular, X-ray crystallography requires the sample to form a three dimensional (3D) crystal lattice which is technically di‑cult, if not impossible, to obtain, especially for large, dynamic systems. Often these techniques solve the structure of the different constituent components within the assembly, but encounter difficulties when investigating the entire system. On the other hand, imaging techniques, such as cryo-electron microscopy (cryo-EM), are able to depict large systems in near-native environment, without requiring the formation of crystals. The structures solved by cryo-EM cover a wide range of resolutions, from very low level of detail where only the overall shape of the system is visible, to high-resolution that approach, but not yet reach, atomic level of detail. In this dissertation, several modeling methods are introduced to either integrate cryo-EM datasets with structural data from X-ray crystallography, or to directly interpret the cryo-EM reconstruction. Such computational techniques were developed with the goal of creating an atomic model for the cryo-EM data. The low-resolution reconstructions lack the level of detail to permit a direct atomic interpretation, i.e. one cannot reliably locate the atoms or amino-acid residues within the structure obtained by cryo-EM. Thereby one needs to consider additional information, for example, structural data from other sources such as X-ray crystallography, in order to enable such a high-resolution interpretation. Modeling techniques are thus developed to integrate the structural data from the different biophysical sources, examples including the work described in the manuscript I and II of this dissertation. At intermediate and high-resolution, cryo-EM reconstructions depict consistent 3D folds such as tubular features which in general correspond to alpha-helices. Such features can be annotated and later on used to build the atomic model of the system, see manuscript III as alternative. Three manuscripts are presented as part of the PhD dissertation, each introducing a computational technique that facilitates the interpretation of cryo-EM reconstructions. The first manuscript is an application paper that describes a heuristics to generate the atomic model for the protein envelope of the Rift Valley fever virus. The second manuscript introduces the evolutionary tabu search strategies to enable the integration of multiple component atomic structures with the cryo-EM map of their assembly. Finally, the third manuscript develops further the latter technique and apply it to annotate consistent 3D patterns in intermediate-resolution cryo-EM reconstructions. The first manuscript, titled An assembly model for Rift Valley fever virus, was submitted for publication in the Journal of Molecular Biology. The cryo-EM structure of the Rift Valley fever virus was previously solved at 27Å-resolution by Dr. Freiberg and collaborators. Such reconstruction shows the overall shape of the virus envelope, yet the reduced level of detail prevents the direct atomic interpretation. High-resolution structures are not yet available for the entire virus nor for the two different component glycoproteins that form its envelope. However, homology models may be generated for these glycoproteins based on similar structures that are available at atomic resolutions. The manuscript presents the steps required to identify an atomic model of the entire virus envelope, based on the low-resolution cryo-EM map of the envelope and the homology models of the two glycoproteins. Starting with the results of the exhaustive search to place the two glycoproteins, the model is built iterative by running multiple multi-body refinements to hierarchically generate models for the different regions of the envelope. The generated atomic model is supported by prior knowledge regarding virus biology and contains valuable information about the molecular architecture of the system. It provides the basis for further investigations seeking to reveal different processes in which the virus is involved such as assembly or fusion. The second manuscript was recently published in the of Journal of Structural Biology (doi:10.1016/j.jsb.2009.12.028) under the title Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions. This manuscript introduces the evolutionary tabu search strategies applied to enable a multi-body registration. This technique is a hybrid approach that combines a genetic algorithm with a tabu search strategy to promote the proper exploration of the high-dimensional search space. Similar to the Rift Valley fever virus, it is common that the structure of a large multi-component assembly is available at low-resolution from cryo-EM, while high-resolution structures are solved for the different components but lack for the entire system. Evolutionary tabu search strategies enable the building of an atomic model for the entire system by considering simultaneously the different components. Such registration indirectly introduces spatial constrains as all components need to be placed within the assembly, enabling the proper docked in the low-resolution map of the entire assembly. Along with the method description, the manuscript covers the validation, presenting the benefit of the technique in both synthetic and experimental test cases. Such approach successfully docked multiple components up to resolutions of 40Å. The third manuscript is entitled Evolutionary Bidirectional Expansion for the Annotation of Alpha Helices in Electron Cryo-Microscopy Reconstructions and was submitted for publication in the Journal of Structural Biology. The modeling approach described in this manuscript applies the evolutionary tabu search strategies in combination with the bidirectional expansion to annotate secondary structure elements in intermediate resolution cryo-EM reconstructions. In particular, secondary structure elements such as alpha helices show consistent patterns in cryo-EM data, and are visible as rod-like patterns of high density. The evolutionary tabu search strategy is applied to identify the placement of the different alpha helices, while the bidirectional expansion characterizes their length and curvature. The manuscript presents the validation of the approach at resolutions ranging between 6 and 14Å, a level of detail where alpha helices are visible. Up to resolution of 12 Å, the method measures sensitivities between 70-100% as estimated in experimental test cases, i.e. 70-100% of the alpha-helices were correctly predicted in an automatic manner in the experimental data. The three manuscripts presented in this PhD dissertation cover different computation methods for the integration and interpretation of cryo-EM reconstructions. The methods were developed in the molecular modeling software Sculptor (http://sculptor.biomachina.org) and are available for the scientific community interested in the multi-resolution modeling of cryo-EM data. The work spans a wide range of resolution covering multi-body refinement and registration at low-resolution along with annotation of consistent patterns at high-resolution. Such methods are essential for the modeling of cryo-EM data, and may be applied in other fields where similar spatial problems are encountered, such as medical imaging.

Indexing and integrating multiple features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image's multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition's center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images have similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the dimensionality curse existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude. And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.

Toward efficient multifeature query processing

In many advanced applications, data are described by multiple high-dimensional features. Moreover, different queries may weight these features differently; some may not even specify all the features. In this paper, we propose our solution to support efficient query processing in these applications. We devise a novel representation that compactly captures f features into two components: The first component is a 2D vector that reflects a distance range ( minimum and maximum values) of the f features with respect to a reference point ( the center of the space) in a metric space and the second component is a bit signature, with two bits per dimension, obtained by analyzing each feature's descending energy histogram. This representation enables two levels of filtering: The first component prunes away points that do not share similar distance ranges, while the bit signature filters away points based on the dimensions of the relevant features. Moreover, the representation facilitates the use of a single index structure to further speed up processing. We employ the classical B+-tree for this purpose. We also propose a KNN search algorithm that exploits the access orders of critical dimensions of highly selective features and partial distances to prune the search space more effectively. Our extensive experiments on both real-life and synthetic data sets show that the proposed solution offers significant performance advantages over sequential scan and retrieval methods using single and multiple VA-files.

Indexing text and visual features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index imagersquos multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partitionrsquos center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images haves similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the ldquodimensionality curserdquo existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms imagersquos text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partitionrsquos center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude.

Artefactual structure from least squares multidimensional scaling

We consider the problem of illusory or artefactual structure from the visualisation of high-dimensional structureless data. In particular we examine the role of the distance metric in the use of topographic mappings based on the statistical field of multidimensional scaling. We show that the use of a squared Euclidean metric (i.e. the SSTRESs measure) gives rise to an annular structure when the input data is drawn from a high-dimensional isotropic distribution, and we provide a theoretical justification for this observation.

Two-dimensional viscoelastic discrete triangular system with negative-stiffness components

Potential applications of high-damping and high-stiffness composites have motivated extensive research on the effects of negative-stiffness inclusions on the overall properties of composites. Recent theoretical advances have been based on the Hashin-Shtrikman composite models, one-dimensional discrete viscoelastic systems and a two-dimensional nested triangular viscoelastic network. In this paper, we further analyze the two-dimensional triangular structure containing pre-selected negative-stiffness components to study its underlying deformation mechanisms and stability. Major new findings are structure-deformation evolution with respect to the magnitude of negative stiffness under shear loading and the phenomena related to dissipation-induced destabilization and inertia-induced stabilization, according to Lyapunov stability analysis. The evolution shows strong correlations between stiffness anomalies and deformation modes. Our stability results reveal that stable damping peaks, i.e. stably extreme effective damping properties, are achievable under hydrostatic loading when the inertia is greater than a critical value. Moreover, destabilization induced by elemental damping is observed with the critical inertia. Regardless of elemental damping, when the inertia is less than the critical value, a weaker system instability is identified.

Structure learning of context-specific graphical models

Abstract The ultimate problem considered in this thesis is modeling a high-dimensional joint distribution over a set of discrete variables. For this purpose, we consider classes of context-specific graphical models and the main emphasis is on learning the structure of such models from data. Traditional graphical models compactly represent a joint distribution through a factorization justi ed by statements of conditional independence which are encoded by a graph structure. Context-speci c independence is a natural generalization of conditional independence that only holds in a certain context, speci ed by the conditioning variables. We introduce context-speci c generalizations of both Bayesian networks and Markov networks by including statements of context-specific independence which can be encoded as a part of the model structures. For the purpose of learning context-speci c model structures from data, we derive score functions, based on results from Bayesian statistics, by which the plausibility of a structure is assessed. To identify high-scoring structures, we construct stochastic and deterministic search algorithms designed to exploit the structural decomposition of our score functions. Numerical experiments on synthetic and real-world data show that the increased exibility of context-specific structures can more accurately emulate the dependence structure among the variables and thereby improve the predictive accuracy of the models.

Hilbert Space Valued Signal Plus Noise Models: Analysis of Structural Breaks under High Dimensionality and Temporal Dependence

This thesis is concerned with change point analysis for time series, i.e. with detection of structural breaks in time-ordered, random data. This long-standing research field regained popularity over the last few years and is still undergoing, as statistical analysis in general, a transformation to high-dimensional problems. We focus on the fundamental »change in the mean« problem and provide extensions of the classical non-parametric Darling-Erdős-type cumulative sum (CUSUM) testing and estimation theory within highdimensional Hilbert space settings. In the first part we contribute to (long run) principal component based testing methods for Hilbert space valued time series under a rather broad (abrupt, epidemic, gradual, multiple) change setting and under dependence. For the dependence structure we consider either traditional m-dependence assumptions or more recently developed m-approximability conditions which cover, e.g., MA, AR and ARCH models. We derive Gumbel and Brownian bridge type approximations of the distribution of the test statistic under the null hypothesis of no change and consistency conditions under the alternative. A new formulation of the test statistic using projections on subspaces allows us to simplify the standard proof techniques and to weaken common assumptions on the covariance structure. Furthermore, we propose to adjust the principal components by an implicit estimation of a (possible) change direction. This approach adds flexibility to projection based methods, weakens typical technical conditions and provides better consistency properties under the alternative. In the second part we contribute to estimation methods for common changes in the means of panels of Hilbert space valued time series. We analyze weighted CUSUM estimates within a recently proposed »high-dimensional low sample size (HDLSS)« framework, where the sample size is fixed but the number of panels increases. We derive sharp conditions on »pointwise asymptotic accuracy« or »uniform asymptotic accuracy« of those estimates in terms of the weighting function. Particularly, we prove that a covariance-based correction of Darling-Erdős-type CUSUM estimates is required to guarantee uniform asymptotic accuracy under moderate dependence conditions within panels and that these conditions are fulfilled, e.g., by any MA(1) time series. As a counterexample we show that for AR(1) time series, close to the non-stationary case, the dependence is too strong and uniform asymptotic accuracy cannot be ensured. Finally, we conduct simulations to demonstrate that our results are practically applicable and that our methodological suggestions are advantageous.

The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

Mesoporous dye-doped titanium dioxide for micro-optoelectronic applications

Optically transparent, mesostructured titanium dioxide thin films were fabricated using an amphiphilic poly(alkylene oxide) block copolymer template in combination with retarded hydrolysis of a titanium isopropoxide precursor. Prior to calcination, the films displayed a stable hexagonal mesophase and high refractive indices (1.5 to 1.6) relative to mesostructured silica (1.43). After calcination, the hexagonal mesophase was retained with surface areas >300 m2 g-1. The dye Rhodamine 6G (commonly used as a laser dye) was incorporated into the copolymer micelle during the templating process. In this way, novel dye-doped mesostructured titanium dioxide films were synthesised. The copolymer not only directs the film structure, but also provides a solubilizing environment suitable for sustaining a high monomer-to-aggregate ratio at elevated dye concentrations. The dye-doped films displayed optical thresholdlike behaviour characteristic of amplified spontaneous emission. Soft lithography was successfully applied to micropattern the dye-doped films. These results pave the way for the fabrication and demonstration of novel microlaser structures and other active optical structures. This new, high-refractive index, mesostructured, dye-doped material could also find applications in areas such as optical coatings, displays and integrated photonic devices.