Wavelets And Adaptive Grids For The Discontinuous Galerkin Method

In this paper, space adaptivity is introduced to control the error in the numerical solution of hyperbolic systems of conservation laws. The reference numerical scheme is a new version of the discontinuous Galerkin method, which uses an implicit diffusive term in the direction of the streamlines, for stability purposes. The decision whether to refine or to unrefine the grid in a certain location is taken according to the magnitude of wavelet coefficients, which are indicators of local smoothness of the numerical solution. Numerical solutions of the nonlinear Euler equations illustrate the efficiency of the method. © Springer 2005.

Influence of Aluminum Oxide Sandblasting Associated with Nd:YAG or Er:YAG Lasers on Shear Bond Strength of a Feldspathic Ceramic to Resin Cements

Objective: This in vitro study evaluated the influence of the surface pretreatment of a feldspathic ceramic on the shear bond strength of two different resin cements. Background Data: Although several conventional surface treatments have been used on feldspathic ceramic, few studies have investigated the effects of an alternative surface treatment, the association of aluminum oxide sandblasting with Nd:YAG and Er:YAG lasers. Methods: Sixty samples made of a feldspathic ceramic were divided into three groups (n = 20) and treated with (1) controlled-air abrasion with Al(2)O(3) + 10% hydrofluoric acid (HF), (2) Al(2)O(3) + Er:YAG laser, and (3) Al(2)O(3) + Nd:YAG laser. Afterward, silane (Dentsply) was applied on each treated surface. Each of the three main groups was divided into two subgroups (n = 10), where a different resin cement was employed for each subgroup. It was built a cylinder with resin cement (RelyX Arc) in subgroup (A) and with self-adhesive cement (RelyX U100) in subgroup (B). After 24 h at 37 degrees C, the prepared specimens were submitted to shear bond strength test and stereoscopic evaluation to determine the type of failure. Results: Bond strength mean values were not statistically significant for the surface treatment methods or resin cements. Conclusion: The null surface treatment proposed with aluminum oxide sandblasting associated with the Er:YAG or Nd:YAG laser and using cementation with self-adhesive cement can be an alternative bonding technique for feldspathic ceramic, since it was as effective as the conventional treatment with aluminum oxide sandblasting and hydrofluoric acid using the conventional resin cement.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

Effects of bed materials on the performance of an anaerobic sequencing batch biofilm reactor treating domestic sewage

The objective of this study was to determine the best performance of an anaerobic sequencing batch biofilm reactor (AnSBBR) based on the use of four different bed materials as support for biomass immobilization. The bed materials utilized were Polyurethane foam (PU), vegetal carbon (VC), synthetic pumice (SP), and recycled low-density polyethylene (PE). The AnSBBR. with I total volume Of 7.2 L, was operated in 8-h batch cycles over 10 months, and fed with domestic sewage with an average influent chemical oxygen demand (COD) of 358 +/- 110 mg/L. The average effluent COD values were 121 +/- 31, 208 +/- 54, 233 +/- 52, and 227 +/- 51 mg/L. for PU, VC, SP, and PE, respectively. A modified first-order kinetic model was adjusted to temporal profiles of COD during a batch cycle, and the apparent kinetic constants were 0.52 +/- 0.05, 0.37 +/- 0.05, 0.80 +/- 0.04, and 0.30 +/- 0.021h(-1) for PU, VC, SP, and PE, respectively. Specific substrate utilization rates of 1.08, 0.11, and 0.86 mg COD/mg VS day were obtained for PU, VC, and PE, respectively. Although SP yielded the highest kinetic coefficient, PU was considered the best support, since SP presented loss of chemical constituents during the reactor`s operational phase. In addition, findings oil the microbial community were associated with the reactor`s performance data. Although PE did not show a satisfactory performance, an interesting microbial diversity was found oil its surface. Based oil the morphology and denaturing gradient gel electrophoresis (DGGE) results, PE showed the best capacity for promoting the attachment of methanogenic organisms, and is therefore a material that merits further analysis. PU was considered the Most suitable material showing the best performance in terms of efficiency of solids and COD removal. (C) 2007 Elsevier Ltd. All rights reserved.

Prediction of Crude Oil Properties and Chemical Composition by Means of Steady-State and Time-Resolved Fluorescence

Steady-state and time-resolved fluorescence measurements are reported for several crude oils and their saturates, aromatics, resins, and asphaltenes (SARA) fractions (saturates, aromatics and resins), isolated from maltene after pentane precipitation of the asphaltenes. There is a clear relationship between the American Petroleum Institute (API) grade of the crude oils and their fluorescence emission intensity and maxima. Dilution of the crude oil samples with cyclohexane results in a significant increase of emission intensity and a blue shift, which is a clear indication of the presence of energy-transfer processes between the emissive chromophores present in the crude oil. Both the fluorescence spectra and the mean fluorescence lifetimes of the three SARA fractions and their mixtures indicate that the aromatics and resins are the major contributors to the emission of crude oils. Total synchronous fluorescence scan (TSFS) spectral maps are preferable to steady-state fluorescence spectra for discriminating between the fractions, making TSFS maps a particularly interesting choice for the development of fluorescence-based methods for the characterization and classification of crude oils. More detailed studies, using a much wider range of excitation and emission wavelengths, are necessary to determine the utility of time-resolved fluorescence (TRF) data for this purpose. Preliminary models constructed using TSFS spectra from 21 crude oil samples show a very good correlation (R(2) > 0.88) between the calculated and measured values of API and the SARA fraction concentrations. The use of models based on a fast fluorescence measurement may thus be an alternative to tedious and time-consuming chemical analysis in refineries.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Observations of anti-winds in a deep alpine valley, Lake Tekapo, New Zealand

This paper presents observations of summertime anti-winds monitored under ideal conditions in the Lake Tekapo hydro-catchment situated in the central Southern Alps, New Zealand. Onset and cessation of anti-winds was observed to coincide with the change in phase of the surface limbs of thermally generated valley and mountain winds under settled anti-cyclonic conditions. Anti-winds were best developed in the early morning before surface heating and associated convective mixing of the valley atmosphere began to mask the boundaries between the surface based limb of the mountain-valley wind and the corresponding anti-wind. By mid-day, the anti-valley wind exceeded the height of the surrounding ridgeline and became embedded in the topographically channeled gradient wind. Observations presented here have both theoretical and applied implications with regard to the development of thermally generated wind systems in deep alpine valleys, and their role in the dispersion of air pollution.

Role of cytokine gene polymorphisms in acute rejection and renal impairment after liver transplantation

Although immunosuppressive regimens are effective, rejection occurs in up to 50% of patients after orthotopic liver transplantation (OLT), and there is concern about side effects from long-term therapy. Knowledge of clinical and immunogenetic variables may allow tailoring of immunosuppressive therapy to patients according to their potential risks. We studied the association between transforming growth factor-beta, interleukin-10, and tumor necrosis factor alpha (TNF-alpha) gene polymorphisms and graft rejection and renal impairment in 121 white liver transplant recipients. Clinical variables were collected retrospectively, and creatinine clearance was estimated using the formula of Cockcroft and Gault. Biallelic polymorphisms were detected using polymerase chain reaction-based methods. Thirty-seven of 121 patients (30.6%) developed at least 1 episode of rejection. Multivariate analysis showed that Child-Pugh score (P =.001), immune-mediated liver disease (P =.018), normal pre-OLT creatinine clearance (P =.037), and fewer HLA class 1 mismatches (P =.038) were independently associated with rejection, Renal impairment occurred in 80% of patients and was moderate or severe in 39%, Clinical variables independently associated with renal impairment were female sex (P =.001), pre-OLT renal dysfunction (P =.0001), and a diagnosis of viral hepatitis (P =.0008), There was a significant difference in the frequency of TNF-alpha -308 alleles among the primary liver diseases. After adjustment for potential confounders and a Bonferroni correction, the association between the TNF-alpha -308 polymorphism and graft rejection approached significance (P =.06). Recipient cytokine genotypes do not have a major independent role in graft rejection or renal impairment after OLT, Additional studies of immunogenetic factors require analysis of large numbers of patients with appropriate phenotypic information to avoid population stratification, which may lead to inappropriate conclusions.

Finite difference time domain (FDTD) method for modeling the effect of switched gradients on the human body in MRI

Numerical modeling of the eddy currents induced in the human body by the pulsed field gradients in MRI presents a difficult computational problem. It requires an efficient and accurate computational method for high spatial resolution analyses with a relatively low input frequency. In this article, a new technique is described which allows the finite difference time domain (FDTD) method to be efficiently applied over a very large frequency range, including low frequencies. This is not the case in conventional FDTD-based methods. A method of implementing streamline gradients in FDTD is presented, as well as comparative analyses which show that the correct source injection in the FDTD simulation plays a crucial rule in obtaining accurate solutions. In particular, making use of the derivative of the input source waveform is shown to provide distinct benefits in accuracy over direct source injection. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and the source injection method has been verified against examples with analytical solutions. Results are presented showing the spatial distribution of gradient-induced electric fields and eddy currents in a complete body model.

Biochemical and molecular studies using human autopsy brain tissue

The use of human brain tissue obtained at autopsy for neurochemical, pharmacological and physiological analyses is reviewed. RNA and protein samples have been found suitable for expression profiling by techniques that include RT-PCR, cDNA microarrays, western blotting, immunohistochemistry and proteomics. The rapid development of molecular biological techniques has increased the impetus for this work to be applied to studies of brain disease. It has been shown that most nucleic acids and proteins are reasonably stable post-mortem. However, their abundance and integrity can exhibit marked intra- and intercase variability, making comparisons between case-groups difficult. Variability can reveal important functional and biochemical information. The correct interpretation of neurochemical data must take into account such factors as age, gender, ethnicity, medicative history, immediate ante-mortem status, agonal state and post-mortem and post-autopsy intervals. Here we consider issues associated with the sampling of DNA, RNA and proteins using human autopsy brain tissue in relation to various ante- and post-mortem factors. We conclude that valid and practical measures of a variety of parameters may be made in human brain tissue, provided that specific factors are controlled.

Salt content in bread and dough from northern Portugal: method development and comparison

In the initial stage of this work, two potentiometric methods were used to determine the salt (sodium chloride) content in bread and dough samples from several cities in the north of Portugal. A reference method (potentiometric precipitation titration) and a newly developed ion-selective chloride electrode (ISE) were applied. Both methods determine the sodium chloride content through the quantification of chloride. To evaluate the accuracy of the ISE, bread and respective dough samples were analyzed by both methods. Statistical analysis (0.05 significance level) indicated that the results of these methods did not differ significantly. Therefore the ISE is an adequate alternative for the determination of chloride in the analyzed samples. To compare the results of these chloride-based methods with a sodium-based method, sodium was quantified in the same samples by a reference method (atomic absorption spectrometry). Significant differences between the results were verified. In several cases the sodium chloride content exceeded the legal limit when the chloride-based methods were used, but when the sodium-based method was applied this was not the case. This could lead to the erroneous application of fines and therefore the authorities should supply additional information regarding the analytical procedure for this particular control.

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Time domain design of fractional differintegrators using least-squares

In this paper we propose the use of the least-squares based methods for obtaining digital rational approximations (IIR filters) to fractional-order integrators and differentiators of type sα, α∈R. Adoption of the Padé, Prony and Shanks techniques is suggested. These techniques are usually applied in the signal modeling of deterministic signals. These methods yield suboptimal solutions to the problem which only requires finding the solution of a set of linear equations. The results reveal that the least-squares approach gives similar or superior approximations in comparison with other widely used methods. Their effectiveness is illustrated, both in the time and frequency domains, as well in the fractional differintegration of some standard time domain functions.

Multi-scale vegetation classification using earth observation data of the Sundarban mangrove forest, Bangladesh.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.