Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.

Oxygen-dependent hydroxylation by Factor Inhibiting HIF (FIH) regulates the TRPV3 ion channel

Factor Inhibiting HIF (FIH) is an oxygen-dependent asparaginyl hydroxylase that regulates the hypoxia-inducible factors (HIFs). Several proteins containing ankyrin repeat domains have been characterised as substrates of FIH, although there is little evidence for a functional consequence of hydroxylation on these substrates. This study demonstrates that the transient receptor potential vanilloid 3 (TRPV3) channel is hydroxylated by FIH on asparagine 242 within the cytoplasmic ankyrin repeat domain. Hypoxia, FIH inhibitors and mutation of asparagine 242 all potentiated TRPV3-mediated current, without altering TRPV3 protein levels, indicating that oxygen-dependent hydroxylation inhibits TRPV3 activity. This novel mechanism of channel regulation by oxygendependent asparaginyl hydroxylation is likely to extend to other ion channels.

Distribution of lipids in the grain of wheat (cv Hereward) determined by lipidomic analysis of milling and pearling fractions

Lipidomic analyses of milling and pearling fractions from wheat grain were carried out to determine differences in composition which could relate to the spatial distribution of lipids in the grain. Free fatty acids and triacylglycerols were major components in all fractions, but the relative contents of polar lipids varied, particularly lysophosphatidyl choline and digalactosyldiglyceride, which were enriched in flour fractions. By contrast, minor phospholipids were enriched in bran and offal fractions. The most abundant fatty acids in the analysed acyl lipids were C16:0 and C18:2 and their combinations, including C36:4 and C34:2. Phospholipids and galactolipids have been reported to have beneficial properties for bread making, while free fatty acids and triacylglycerols are considered detrimental. The subtle differences in the compositions of fractions determined in the present study could therefore underpin the production of flour fractions with optimised compositions for different end uses.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Statistical analysis of the Doppler broadening coincidence spectrum of electron-positron annihilation radiation in silicon

We report a statistical analysis of Doppler broadening coincidence data of electron-positron annihilation radiation in silicon using a (22)Na source. The Doppler broadening coincidence spectrum was fit using a model function that included positron annihilation at rest with 1s, 2s, 2p, and valence band electrons. In-flight positron annihilation was also fit. The response functions of the detectors accounted for backscattering, combinations of Compton effects, pileup, ballistic deficit, and pulse-shaping problems. The procedure allows the quantitative determination of positron annihilation with core and valence electron intensities as well as their standard deviations directly from the experimental spectrum. The results obtained for the core and valence band electron annihilation intensities were 2.56(9)% and 97.44(9)%, respectively. These intensities are consistent with published experimental data treated by conventional analysis methods. This new procedure has the advantage of allowing one to distinguish additional effects from those associated with the detection system response function. (C) 2009 Elsevier B.V. All rights reserved.

Characterizing magnetic interactions in Ni nanowires by FORC analysis

Polycrystalline Ni nanowires with different diameters were electrodeposited in nanoporous anodized alumina membranes. First-Order Reversal Curves (FORCs) were measured and FORC distributions were calculated. They clearly showed an asymmetric behavior with a strong maximum at negative interaction fields, evidencing the dominant demagnetizing interactions which depend on the geometry of the nanowires. (C) 2008 Elsevier B.V. All rights reserved.

Characterization of organic matter in sediment cores of the Todos os Santos Bay, Bahia, Brazil, by elemental analysis and (13)C NMR

The impact of human activity on the sediments of Todos os Santos Bay in Brazil was evaluated by elemental analysis and (13)C Nuclear Magnetic Resonance ((13)C NMR). This article reports a study of six sediment cores collected at different depths and regions of Todos os Santos Bay. The elemental profiles of cores collected on the eastern side of Frades Island suggest an abrupt change in the sedimentation regime. Auto-regressive Integrated Moving Average (ARIMA) analysis corroborates this result. The range of depths of the cores corresponds to about 50 years ago, coinciding with the implantation of major onshore industrial projects in the region. Principal Component Analysis of the (13)C NMR spectra clearly differentiates sediment samples closer to the Subae estuary, which have high contents of terrestrial organic matter, from those closer to a local oil refinery. The results presented in this article illustrate several important aspects of environmental impact of human activity on this bay. (C) 2011 Elsevier Ltd. All rights reserved.

Model for the Evaluation of Root Wear by Histometric Analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Cryptic hammerhead shark lineage occurrence in the western South Atlantic revealed by DNA analysis

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

Mapping soil pollution by spatial analysis and fuzzy classification

Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.

Production and body composition traits of broilers in relation to breast weight evaluated by path analysis

O peso do peito possui grande importância econômica na indústria de frangos, podendo estar associado a outras variáveis passíveis de seleção. Estimaram-se correlações fenotípicas entre características de desempenho (peso vivo aos 7, 28 dias e ao abate e profundidade de músculo peitoral por ultra-sonografia), carcaça (peso eviscerado e de pernas) e composição corporal (peso do coração, do fígado e da gordura abdominal), em uma linhagem de frangos, e quantificou-se a influência direta e indireta destas variáveis sobre o peso do peito. Para tanto, utilizou-se a análise de trilha, desdobrando-se a matriz de correlações parciais em coeficientes que forneceram a influência direta de uma variável sobre a outra, independentemente das demais. A manutenção das variáveis peso vivo ao abate e peso eviscerado na matriz de correlações pode ser prejudicial à análise estatística que envolve os sistemas de equações normais, como a análise de trilha, devido à multicolinearidade observada. O peso vivo ao abate e a profundidade do músculo peitoral por ultra-sonografia apresentaram efeitos diretos importantes sobre o peso de peito e foram identificadas como as principais responsáveis pela magnitude dos coeficientes de correlação obtidos. Assim, uma pré-seleção individual para estas características pode favorecer um aumento no peso de peito nesta linhagem, se mantidas as condições ambientais de criação dos frangos, uma vez que o peso vivo ao abate e a profundidade de músculo peitoral por ultra-sonografia afetam fenotipicamente e diretamente o peso de peito.

Stress induced ordering due to interstitial elements in Nb and Ta by frequency analysis

It is well known that the interstitial elements present in solid solution in metals interact with the matrix by a relaxation process known as stress induced ordering. Traditionally this relaxation process is observed in the internal friction measurements. It is a common practice that researchers present the results of the frequency together with internal friction without giving any analysis. In this work we apply an expression which relates the variation of frequency with temperature and analyse the experimental results cited in the literature of the relaxation process due to the stress induced ordering of oxygen and nitrogen present in niobium and tantalum.

Genetic variability in species of bats revealed by RAPD analysis

Random amplified polymorphic DNA molecular marker was utilized as a means of analyzing genetic variability in seven bat species: Molossus molossus, M. rufus, Eumops glaucinus, E. perotis, Myotis nigricans, Eptesicus furinalis, and Artibeus planirostris. The determination of genetic diversity was based on 741 bands produced by a 20-random primer set. Only eight bands were considered monomorphic to one species. The greatest number of bands and the most polymorphic condition were exhibited by M. molossus, followed by M. nigricans, A. planirostris, E. furinalis, E. glaucinus, M. rufus, and E. perotis. Nei's genetic diversity index in the seven species considering the 20 primers was not greater than 0.22, but some primers were capable of detecting values between 0.39 and 0.49. Nei's unbiased genetic distance values and the UPGMA clustering pattern show that M. molossus and M. rufus have a close genetic relationship, unlike that observed between E. perotis and E. glaucinus. The latter was clustered with A. planirostris and E. furinalis. The low values for genetic diversity and distance observed indicate a genetic conservatism in the seven species. The fluorescent in situ hybridization experiments did not confirm a monomorphic condition for the eight bands identified, demonstrating that the monomorphic bands obtained by random amplified polymorphic DNA are insufficient for the identification of bat species.

Rotor support stiffness estimation by sensitivity analysis

In the present work, a method for rotor support stiffness estimation via a model updating process using the sensitivity analysis is presented. This method consists in using the eigenvalues sensitivity analysis, relating to the rotor support stiffnesses variation to perform the adjustment of the model based on the minimization of the difference between eigenvalues of reference and eigenvalues obtained via mathematical model from previously adopted support bearing stiffness values. The mathematical model is developed by the finite element method and the method of adjustment should converge employing an iterative process. The performance and robustness of the method have been analyzed through a numerical example.