Model estimation of cerebral hemodynamics between blood flow and volume changes: A data-based modeling approach

It is well known that there is a dynamic relationship between cerebral blood flow (CBF) and cerebral blood volume (CBV). With increasing applications of functional MRI, where the blood oxygen-level-dependent signals are recorded, the understanding and accurate modeling of the hemodynamic relationship between CBF and CBV becomes increasingly important. This study presents an empirical and data-based modeling framework for model identification from CBF and CBV experimental data. It is shown that the relationship between the changes in CBF and CBV can be described using a parsimonious autoregressive with exogenous input model structure. It is observed that neither the ordinary least-squares (LS) method nor the classical total least-squares (TLS) method can produce accurate estimates from the original noisy CBF and CBV data. A regularized total least-squares (RTLS) method is thus introduced and extended to solve such an error-in-the-variables problem. Quantitative results show that the RTLS method works very well on the noisy CBF and CBV data. Finally, a combination of RTLS with a filtering method can lead to a parsimonious but very effective model that can characterize the relationship between the changes in CBF and CBV.

A new data set of soil mineralogy for dust-cycle modeling

The mineralogy of airborne dust affects the impact of dust particles on direct and indirect radiative forcing, on atmospheric chemistry and on biogeochemical cycling. It is determined partly by the mineralogy of the dust-source regions and partly by size-dependent fractionation during erosion and transport. Here we present a data set that characterizes the clay and silt-sized fractions of global soil units in terms of the abundance of 12 minerals that are important for dust–climate interactions: quartz, feldspars, illite, smectite, kaolinite, chlorite, vermiculite, mica, calcite, gypsum, hematite and goethite. The basic mineralogical information is derived from the literature, and is then expanded following explicit rules, in order to characterize as many soil units as possible. We present three alternative realizations of the mineralogical maps, taking the uncertainties in the mineralogical data into account. We examine the implications of the new database for calculations of the single scattering albedo of airborne dust and thus for dust radiative forcing.

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

Modeling grouped survival data with time-dependent covariates

In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.

Data information system to promote the organization data of collections - modeling considerations by the Unified Modelign Language (UML)

Pode-se afirmar que a evolução tecnológica (desenvolvimento de novos instrumentos de medição como, softwares, satélites e computadores, bem como, o barateamento das mídias de armazenamento) permite às Organizações produzirem e adquirirem grande quantidade de dados em curto espaço de tempo. Devido ao volume de dados, Organizações de pesquisa se tornam potencialmente vulneráveis aos impactos da explosão de informações. Uma solução adotada por algumas Organizações é a utilização de ferramentas de sistemas de informação para auxiliar na documentação, recuperação e análise dos dados. No âmbito científico, essas ferramentas são desenvolvidas para armazenar diferentes padrões de metadados (dados sobre dados). Durante o processo de desenvolvimento destas ferramentas, destaca-se a adoção de padrões como a Linguagem Unificada de Modelagem (UML, do Inglês Unified Modeling Language), cujos diagramas auxiliam na modelagem de diferentes aspectos do software. O objetivo deste estudo é apresentar uma ferramenta de sistemas de informação para auxiliar na documentação dos dados das Organizações por meio de metadados e destacar o processo de modelagem de software, por meio da UML. Será abordado o Padrão de Metadados Digitais Geoespaciais, amplamente utilizado na catalogação de dados por Organizações científicas de todo mundo, e os diagramas dinâmicos e estáticos da UML como casos de uso, sequências e classes. O desenvolvimento das ferramentas de sistemas de informação pode ser uma forma de promover a organização e a divulgação de dados científicos. No entanto, o processo de modelagem requer especial atenção para o desenvolvimento de interfaces que estimularão o uso das ferramentas de sistemas de informação.

Post-breakup tectonics in southeast Brazil from thermochronological data and combined inverse-forward thermal history modeling

The continental margin of southeast Brazil is elevated. Onshore Tertiary basins and Late Cretaceous/Paleogene intrusions are good evidence for post breakup tectono-magmatic activity. To constrain the impact of post-rift reactivation on the geological history of the area, we carried out a new thermochronological study. Apatite fission track ages range from 60.7 +/- 1.9 Ma to 129.3 +/- 4.3 Ma, mean track lengths from 11.41 +/- 0.23 mu m to 14.31 +/- 0.24 mu m and a subset of the (U-Th)/He ages range from 45.1 +/- 1.5 to 122.4 +/- 2.5 Ma. Results of inverse thermal history modeling generally support the conclusions from an earlier study for a Late Cretaceous phase of cooling. Around the onshore Taubate Basin, for a limited number of samples, the first detectable period of cooling occurred during the Early Tertiary. The inferred thermal histories for many samples also imply subsequent reheating followed by Neogene cooling. Given the uncertainty of the inversion results, we did deterministic forward modeling to assess the range of possibilities of this Tertiary part of the thermal history. The evidence for reheating seems to be robust around the Taubate Basin, but elsewhere the data cannot discriminate between this and a less complex thermal history. However, forward modeling results and geological information support the conclusion that the whole area underwent cooling during the Neogene. The synchronicity of the cooling phases with Andean tectonics and those in NE Brazil leads us to assume a plate-wide compressional stress that reactivated inherited structures. The present-day topographic relief of the margin reflects a contribution from post-breakup reactivation and uplift.

Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.

Multiproperty modeling for a set of binary systems. Evaluation of a model to correlate simultaneously several mixing properties of methyl ethanoate+alkanes and new experimental data

[EN] This work makes a theoretical–experimental contribution to the study of ester and alkane solutions. Experimental data of isobaric vapor–liquid equilibria (VLE) are presented at 101.3 kPa for binary systems of methyl ethanoate with six alkanes (from C5 to C10), and of volumes and mixing enthalpies, vE and hE.

Kinematics of the Sicily and Calabria Subduction System from Elastic Block Modeling of GPS Data

We use data from about 700 GPS stations in the EuroMediterranen region to investigate the present-day behavior of the the Calabrian subduction zone within the Mediterranean-scale plates kinematics and to perform local scale studies about the strain accumulation on active structures. We focus attenction on the Messina Straits and Crati Valley faults where GPS data show extentional velocity gradients of ∼3 mm/yr and ∼2 mm/yr, respectively. We use dislocation model and a non-linear constrained optimization algorithm to invert for fault geometric parameters and slip-rates and evaluate the associated uncertainties adopting a bootstrap approach. Our analysis suggest the presence of two partially locked normal faults. To investigate the impact of elastic strain contributes from other nearby active faults onto the observed velocity gradient we use a block modeling approach. Our models show that the inferred slip-rates on the two analyzed structures are strongly impacted by the assumed locking width of the Calabrian subduction thrust. In order to frame the observed local deformation features within the present- day central Mediterranean kinematics we realyze a statistical analysis testing the indipendent motion (w.r.t. the African and Eurasias plates) of the Adriatic, Cal- abrian and Sicilian blocks. Our preferred model confirms a microplate like behaviour for all the investigated blocks. Within these kinematic boundary conditions we fur- ther investigate the Calabrian Slab interface geometry using a combined approach of block modeling and χ2ν statistic. Almost no information is obtained using only the horizontal GPS velocities that prove to be a not sufficient dataset for a multi-parametric inversion approach. Trying to stronger constrain the slab geometry we estimate the predicted vertical velocities performing suites of forward models of elastic dislocations varying the fault locking depth. Comparison with the observed field suggest a maximum resolved locking depth of 25 km.