Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

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

Labour markets, worker protection and lifelong learning in a global economy: experiences and perspectives of Latin America and the Caribbean

Includes bibliography

The Role of Tax Policy in the Context of the Global Crisis: consequences and prospects

Includes bibliography

Empilhamento sísmico por superfície de reflexão comum: um novo algoritmo usando otimização global e local

O método de empilhamento sísmico por Superfície de Reflexão Comum (ou empilhamento SRC) produz a simulação de seções com afastamento nulo (NA) a partir dos dados de cobertura múltipla. Para meios 2D, o operador de empilhamento SRC depende de três parâmetros que são: o ângulo de emergência do raio central com fonte-receptor nulo (β₀), o raio de curvatura da onda ponto de incidência normal (R_NIP) e o raio de curvatura da onda normal (R_N). O problema crucial para a implementação do método de empilhamento SRC consiste na determinação, a partir dos dados sísmicos, dos três parâmetros ótimos associados a cada ponto de amostragem da seção AN a ser simulada. No presente trabalho foi desenvolvido uma nova sequência de processamento para a simulação de seções AN por meio do método de empilhamento SRC. Neste novo algoritmo, a determinação dos três parâmetros ótimos que definem o operador de empilhamento SRC é realizada em três etapas: na primeira etapa são estimados dois parâmetros (β°₀ e R°_NIP) por meio de uma busca global bidimensional nos dados de cobertura múltipla. Na segunda etapa é usado o valor de β°₀ estimado para determinar-se o terceiro parâmetro (R°_N) através de uma busca global unidimensional na seção AN resultante da primeira etapa. Em ambas etapas as buscas globais são realizadas aplicando o método de otimização Simulated Annealing (SA). Na terceira etapa são determinados os três parâmetros finais (β₀, R_NIP e R_N) através uma busca local tridimensional aplicando o método de otimização Variable Metric (VM) nos dados de cobertura múltipla. Nesta última etapa é usado o trio de parâmetros (β°₀, R°_NIP, R°_N) estimado nas duas etapas anteriores como aproximação inicial. Com o propósito de simular corretamente os eventos com mergulhos conflitantes, este novo algoritmo prevê a determinação de dois trios de parâmetros associados a pontos de amostragem da seção AN onde há intersecção de eventos. Em outras palavras, nos pontos da seção AN onde dois eventos sísmicos se cruzam são determinados dois trios de parâmetros SRC, os quais serão usados conjuntamente na simulação dos eventos com mergulhos conflitantes. Para avaliar a precisão e eficiência do novo algoritmo, este foi aplicado em dados sintéticos de dois modelos: um com interfaces contínuas e outro com uma interface descontinua. As seções AN simuladas têm elevada razão sinal-ruído e mostram uma clara definição dos eventos refletidos e difratados. A comparação das seções AN simuladas com as suas similares obtidas por modelamento direto mostra uma correta simulação de reflexões e difrações. Além disso, a comparação dos valores dos três parâmetros otimizados com os seus correspondentes valores exatos calculados por modelamento direto revela também um alto grau de precisão. Usando a aproximação hiperbólica dos tempos de trânsito, porém sob a condição de R_NIP = R_N, foi desenvolvido um novo algoritmo para a simulação de seções AN contendo predominantemente campos de ondas difratados. De forma similar ao algoritmo de empilhamento SRC, este algoritmo denominado empilhamento por Superfícies de Difração Comum (SDC) também usa os métodos de otimização SA e VM para determinar a dupla de parâmetros ótimos (β₀, R_NIP) que definem o melhor operador de empilhamento SDC. Na primeira etapa utiliza-se o método de otimização SA para determinar os parâmetros iniciais β°₀ e R°_NIP usando o operador de empilhamento com grande abertura. Na segunda etapa, usando os valores estimados de β°₀ e R°_NIP, são melhorados as estimativas do parâmetro R_NIP por meio da aplicação do algoritmo VM na seção AN resultante da primeira etapa. Na terceira etapa são determinados os melhores valores de β°₀ e R°_NIP por meio da aplicação do algoritmo VM nos dados de cobertura múltipla. Vale salientar que a aparente repetição de processos tem como efeito a atenuação progressiva dos eventos refletidos. A aplicação do algoritmo de empilhamento SDC em dados sintéticos contendo campos de ondas refletidos e difratados, produz como resultado principal uma seção AN simulada contendo eventos difratados claramente definidos. Como uma aplicação direta deste resultado na interpretação de dados sísmicos, a migração pós-empilhamento em profundidade da seção AN simulada produz uma seção com a localização correta dos pontos difratores associados às descontinuidades do modelo.

Companhias Antropofágicas de Segurança no Sul Global: narrativas de privatização da violência e construção de ameaças na Líbia e no Afeganistão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Clinical features of tic-related obsessive-compulsive disorder: results from a large multicenter study

Objective. To evaluate the clinical features of obsessive-compulsive disorder (OCD) patients with comorbid tic disorders (TD) in a large, multicenter, clinical sample. Method. A cross-sectional study was conducted that included 813 consecutive OCD outpatients from the Brazilian OCD Research Consortium and used several instruments of assessment, including the Yale-Brown Obsessive-Compulsive Scale, the Dimensional Yale-Brown Obsessive-Compulsive Scale, the Yale Global Tic Severity Scale (YGTSS), the USP Sensory Phenomena Scale, and the Structured Clinical Interview for DSM-IV Axis I Disorders. Results. The sample mean current age was 34.9 years old (SE 0.54), and the mean age at obsessive-compulsive symptoms (OCS) onset was 12.8 years old (SE 0.27). Sensory phenomena were reported by 585 individuals (72% of the sample). The general lifetime prevalence of TD was 29.0% (n=236), with 8.9% (n=72) presenting Tourette syndrome, 17.3% (n=5141) chronic motor tic disorder, and 2.8% (n=523) chronic vocal tic disorder. The mean tic severity score, according to the YGTSS, was 27.2 (SE 1.4) in the OCD1TD group. Compared to OCD patients without comorbid TD, those with TD (OCD1TD group, n=236) were more likely to be males (49.2% vs. 38.5%, p<005) and to present sensory phenomena and comorbidity with anxiety disorders in general: separation anxiety disorder, social phobia, specific phobia, generalized anxiety disorder, post-traumatic stress disorder, attention-deficit hyperactivity disorder, impulse control disorders in general, and skin picking. Also, the "aggressive," "sexual/religious," and "hoarding" symptom dimensions were more severe in the OCD+TD group. Conclusion. Tic-related OCD may constitute a particular subgroup of the disorder with specific phenotypical characteristics, but its neurobiological underpinnings remain to be fully disentangled.

Pancreatic islets from dexamethasone-treated rats show alterations in global gene expression and mitochondrial pathways

Chronic administration of glucocorticoids (GC) leads to characteristic features of type 2 diabetes in mammals. The main action of dexamethasone in target cells occurs through modulation of gene expression, although the exact mechanisms are still unknown. We therefore investigated the gene expression profile of pancreatic islets from rats treated with dexamethasone using a cDNA array screening analysis. The expression of selected genes and proteins involved in mitochondria] apoptosis was further analyzed by PCR and immunoblotting. Insulin, triglyceride and free fatty acid plasma levels, as well as glucose-induced insulin secretion, were significantly higher in dexamethasone-treated rats compared with controls. Out of 1176 genes, 60 were up-regulated and 28 were down-regulated by dexamethasone treatment. Some of the modulated genes are involved in apoptosis, stress response, and proliferation pathways. RT-PCR confirmed the cDNA array results for 6 selected genes. Bax alpha protein expression was increased, while Bcl-2 was decreased. In vivo dexamethasone treatment decreased the mitochondrial production of NAD(P)H, and increased ROS production. Concluding, our data indicate that dexamethasone modulates the expression of genes and proteins involved in several pathways of pancreatic-islet cells, and mitochondria dysfunction might be involved in the deleterious effects after long-term GC treatment.

Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.

Genetic features and molecular epidemiology of Enterococcus faecium isolated in two university hospitals in Brazil

The global emergence of vancomycin-resistant Enterococcus faecium (VREfm) has been characterized by a clonal spread of strains belonging to clonal complex 17 (CC17). Genetic features and clonal relationships of 53 VREfm isolated from patients in 2 hospitals in Ribeirao Preto, Sao Paulo, Brazil, during 2005-2010 were determined as a contribution to the Brazilian evolutionary history of these nosocomial pathogens. All isolates were daptomycin susceptible, vancomycin-resistant, and had the vanA gene. The predominant virulence genes were acm and esp. Only 5 VREfm isolated in 2005-2006 had intact Tn1546, while 81% showed Tn1546 with deleted left extremity and insertion of IS1251 between the vanS and vanH genes. Multilocus sequence typing analysis permitted the identification of 9 different sequence types (STs), with 5 being new ones (656, 657, 658, 659, and 660). Predominant STs were ST412 and ST478, all belonging to CC17, except ST658. This is the first report of the ST78 in Brazil. (c) 2012 Elsevier Inc. All rights reserved.

Multiresolution spherical wavelet analysis in global seismic tomography

Every seismic event produces seismic waves which travel throughout the Earth. Seismology is the science of interpreting measurements to derive information about the structure of the Earth. Seismic tomography is the most powerful tool for determination of 3D structure of deep Earth's interiors. Tomographic models obtained at the global and regional scales are an underlying tool for determination of geodynamical state of the Earth, showing evident correlation with other geophysical and geological characteristics. The global tomographic images of the Earth can be written as a linear combinations of basis functions from a specifically chosen set, defining the model parameterization. A number of different parameterizations are commonly seen in literature: seismic velocities in the Earth have been expressed, for example, as combinations of spherical harmonics or by means of the simpler characteristic functions of discrete cells. With this work we are interested to focus our attention on this aspect, evaluating a new type of parameterization, performed by means of wavelet functions. It is known from the classical Fourier theory that a signal can be expressed as the sum of a, possibly infinite, series of sines and cosines. This sum is often referred as a Fourier expansion. The big disadvantage of a Fourier expansion is that it has only frequency resolution and no time resolution. The Wavelet Analysis (or Wavelet Transform) is probably the most recent solution to overcome the shortcomings of Fourier analysis. The fundamental idea behind this innovative analysis is to study signal according to scale. Wavelets, in fact, are mathematical functions that cut up data into different frequency components, and then study each component with resolution matched to its scale, so they are especially useful in the analysis of non stationary process that contains multi-scale features, discontinuities and sharp strike. Wavelets are essentially used in two ways when they are applied in geophysical process or signals studies: 1) as a basis for representation or characterization of process; 2) as an integration kernel for analysis to extract information about the process. These two types of applications of wavelets in geophysical field, are object of study of this work. At the beginning we use the wavelets as basis to represent and resolve the Tomographic Inverse Problem. After a briefly introduction to seismic tomography theory, we assess the power of wavelet analysis in the representation of two different type of synthetic models; then we apply it to real data, obtaining surface wave phase velocity maps and evaluating its abilities by means of comparison with an other type of parametrization (i.e., block parametrization). For the second type of wavelet application we analyze the ability of Continuous Wavelet Transform in the spectral analysis, starting again with some synthetic tests to evaluate its sensibility and capability and then apply the same analysis to real data to obtain Local Correlation Maps between different model at same depth or between different profiles of the same model.

Knowledge Flows and Networks: the Interplay between Local and Global Linkages within Bangalore IT Cluster

This doctoral work gains deeper insight into the dynamics of knowledge flows within and across clusters, unfolding their features, directions and strategic implications. Alliances, networks and personnel mobility are acknowledged as the three main channels of inter-firm knowledge flows, thus offering three heterogeneous measures to analyze the phenomenon. The interplay between the three channels and the richness of available research methods, has allowed for the elaboration of three different papers and perspectives. The common empirical setting is the IT cluster in Bangalore, for its distinguished features as a high-tech cluster and for its steady yearly two-digit growth around the service-based business model. The first paper deploys both a firm-level and a tie-level analysis, exploring the cases of 4 domestic companies and of 2 MNCs active the cluster, according to a cluster-based perspective. The distinction between business-domain knowledge and technical knowledge emerges from the qualitative evidence, further confirmed by quantitative analyses at tie-level. At firm-level, the specialization degree seems to be influencing the kind of knowledge shared, while at tie-level both the frequency of interaction and the governance mode prove to determine differences in the distribution of knowledge flows. The second paper zooms out and considers the inter-firm networks; particularly focusing on the role of cluster boundary, internal and external networks are analyzed, in their size, long-term orientation and exploration degree. The research method is purely qualitative and allows for the observation of the evolving strategic role of internal network: from exploitation-based to exploration-based. Moreover, a causal pattern is emphasized, linking the evolution and features of the external network to the evolution and features of internal network. The final paper addresses the softer and more micro-level side of knowledge flows: personnel mobility. A social capital perspective is here developed, which considers both employees’ acquisition and employees’ loss as building inter-firm ties, thus enhancing company’s overall social capital. Negative binomial regression analyses at dyad-level test the significant impact of cluster affiliation (cluster firms vs non-cluster firms), industry affiliation (IT firms vs non-IT fims) and foreign affiliation (MNCs vs domestic firms) in shaping the uneven distribution of personnel mobility, and thus of knowledge flows, among companies.

Global scale investigation of cirrus clouds properties using active and passive sensors

A year of satellite-borne lidar CALIOP data is analyzed and statistics on occurrence and distribution of bulk properties of cirri are provided. The relationship between environmental and cloud physical parameters and the shape of the backscatter profile (BSP) is investigated. It is found that CALIOP BSP is mainly affected by cloud geometrical thickness while only minor impacts can be attributed to other quantities such as optical depth or temperature. To fit mean BSPs as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. It is demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile. The IWC parameterization is included into the RT-RET retrieval algorithm, that is exploited to analyze infrared radiance measurements in presence of cirrus clouds during the ECOWAR field campaign. Retrieved microphysical and optical properties of the observed cloud are used as input parameters in a forward RT simulation run over the 100-1100 cm-1 spectral interval and compared with interferometric data to test the ability of the current single scattering properties database of ice crystal to reproduce realistic optical features. Finally a global scale investigation of cirrus clouds is performed by developing a collocation algorithm that exploits satellite data from multiple sensors (AIRS, CALIOP, MODIS). The resulting data set is utilized to test a new infrared hyperspectral retrieval algorithm. Retrieval products are compared to data and in particular the cloud top height (CTH) product is considered for this purpose. A better agreement of the retrieval with the CALIOP CTH than MODIS is found, even if some cases of underestimation and overestimation are observed.

Generating vegetation-spectra as a basis for global monitoring of annual vegetation cycles using DOAS satellite observations

Vegetation-cycles are of general interest for many applications. Be it for harvest-predictions, global monitoring of climate-change or as input to atmospheric models.rnrnCommon Vegetation Indices use the fact that for vegetation the difference between Red and Near Infrared reflection is higher than in any other material on Earth’s surface. This gives a very high degree of confidence for vegetation-detection.rnrnThe spectrally resolving data from the GOME and SCIAMACHY satellite-instrumentsrnprovide the chance to analyse finer spectral features throughout the Red and Near Infrared spectrum using Differential Optical Absorption Spectroscopy (DOAS). Although originally developed to retrieve information on atmospheric trace gases, we use it to gain information on vegetation. Another advantage is that this method automatically corrects for changes in the atmosphere. This renders the vegetation-information easily comparable over long time-spans.rnThe first results using previously available reference spectra were encouraging, but also indicated substantial limitations of the available reflectance spectra of vegetation. This was the motivation to create new and more suitable vegetation reference spectra within this thesis.rnThe set of reference spectra obtained is unique in its extent and also with respect to its spectral resolution and the quality of the spectral calibration. For the first time, this allowed a comprehensive investigation of the high-frequency spectral structures of vegetation reflectance and of their dependence on the viewing geometry.rnrnThe results indicate that high-frequency reflectance from vegetation is very complex and highly variable. While this is an interesting finding in itself, it also complicates the application of the obtained reference spectra to the spectral analysis of satellite observations.rnrnThe new set of vegetation reference spectra created in this thesis opens new perspectives for research. Besides refined satellite analyses, these spectra might also be used for applications on other platforms such as aircraft. First promising studies have been presented in this thesis, but the full potential for the remote sensing of vegetation from satellite (or aircraft) could bernfurther exploited in future studies.

Geological and hydrogeological features affecting migration, multi-phase partitioning and degradation of chlorinated hydrocarbons through unconsolidated porous media.

Chlorinated solvents are the most ubiquitous organic contaminants found in groundwater since the last five decades. They generally reach groundwater as Dense Non-Aqueous Phase Liquid (DNAPL). This phase can migrate through aquifers, and also through aquitards, in ways that aqueous contaminants cannot. The complex phase partitioning to which chlorinated solvent DNAPLs can undergo (i.e. to the dissolved, vapor or sorbed phase), as well as their transformations (e.g. degradation), depend on the physico-chemical properties of the contaminants themselves and on features of the hydrogeological system. The main goal of the thesis is to provide new knowledge for the future investigations of sites contaminated by DNAPLs in alluvial settings, proposing innovative investigative approaches and emphasizing some of the key issues and main criticalities of this kind of contaminants in such a setting. To achieve this goal, the hydrogeologic setting below the city of Ferrara (Po plain, northern Italy), which is affected by scattered contamination by chlorinated solvents, has been investigated at different scales (regional and site specific), both from an intrinsic (i.e. groundwater flow systems) and specific (i.e. chlorinated solvent DNAPL behavior) point of view. Detailed investigations were carried out in particular in one selected test-site, known as “Caretti site”, where high-resolution vertical profiling of different kind of data were collected by means of multilevel monitoring systems and other innovative sampling and analytical techniques. This allowed to achieve a deep geological and hydrogeological knowledge of the system and to reconstruct in detail the architecture of contaminants in relationship to the features of the hosting porous medium. The results achieved in this thesis are useful not only at local scale, e.g. employable to interpret the origin of contamination in other sites of the Ferrara area, but also at global scale, in order to address future remediation and protection actions of similar hydrogeologic settings.