966 resultados para fast method


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The multi-dimensional classification problem is a generalisation of the recently-popularised task of multi-label classification, where each data instance is associated with multiple class variables. There has been relatively little research carried out specific to multi-dimensional classification and, although one of the core goals is similar (modelling dependencies among classes), there are important differences; namely a higher number of possible classifications. In this paper we present method for multi-dimensional classification, drawing from the most relevant multi-label research, and combining it with important novel developments. Using a fast method to model the conditional dependence between class variables, we form super-class partitions and use them to build multi-dimensional learners, learning each super-class as an ordinary class, and thus explicitly modelling class dependencies. Additionally, we present a mechanism to deal with the many class values inherent to super-classes, and thus make learning efficient. To investigate the effectiveness of this approach we carry out an empirical evaluation on a range of multi-dimensional datasets, under different evaluation metrics, and in comparison with high-performing existing multi-dimensional approaches from the literature. Analysis of results shows that our approach offers important performance gains over competing methods, while also exhibiting tractable running time.

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Foram estudadas trinta e uma cepas fúngicas não identificadas, as quais foram denominadasX1 a X31. O potencial fotoprotetor foi avaliado pela medida espectrofotométrica da absorçãodos extratos na região do UV (280-400 nm). Os extratos com os melhores perfis de absorção em cultura estacionária foram X1, X2, X6, X12, X13, X18, X19, X22, X24 e X31 e, em cultura agitada X4 e X17. A reprodutibilidade do processo foi avaliada e as cepas fúngicas que apresentaram coeficiente de variação menor que 15% foram selecionadas para o estudo de fotoestabilidade. A fotoestabilidade dos extratos foi avaliada pela medida da viabilidade celular de fibroblastos L929 tratados com extratos previamente irradiados sob radiação UVA (11,2 J/cm2) e UVB (3,43 J/cm2) e extratos não irradiados, bem como, pela comparação das áreas sob as curvas de absorção na região do UV dos extratos irradiados e não irradiados. Os extratos selecionados para o estudo de fotoestabilidade foram X4, X12, X19, X22, X24 e X31. Os extratos não irradiados apresentaram os seguintes valores deIC50 para viabilidade celular (citotoxidade): X4-130µg/ml, X19-20µg/ml, X22-10 µg/ml e X24-60µg/ml. Após a radiação UVA e UVB, os extratos apresentaram redução significativa da viabilidade celular em relação ao IC50 dos extratos não irradiados. Sob luz UVB, os extratos X12 (IC50 35µg/ml) e X31 (IC50 70µg/ml) mantiveram a mesma porcentagem de redução da viabilidade celular quando comparado ao IC50 dos extratos não irradiados. No entanto após exposição à luz UVA, o extrato X12 aumentou a viabilidade celular de 50% (quando não irradiado) para 75% (irradiado). Enquanto que o extrato X31, mesmo após a radiação UVA, manteve a mesma redução de 50% da viabilidade celular. Nessa etapa os extratos selecionados foram os X12 e X31. O espectro de absorção na região do UV obtido para o extrato X12 mostrou uma redução da absorbância de 28,3% sob radiação UVB e de 60% sob radiação UVA em relação ao extrato não irradiado. O extrato X31 apresentou uma redução da absorbância de 17,6% e30% sob radiação UVB e UVA respectivamente, em relação ao extrato não irradiado. Os fungos selecionados foram identificados por PCR, sugerindo que o fungo X12 seja o Aspergillus terreus e o X31 seja o Talaromyces pinophilus. Por fim, foi feita a identificação da substância ativa do extrato X12 empregando a técnica de desreplicação, a qual fez o uso da instrumentação analítica acoplada UHPLC-DAD-(ESI)-HRMS associada ao banco de dados Chapman& Hall\'s Dictionary of Natural Products (DNP). No extrato X12 o composto majoritário foi identificado como sendo a citreoviridina. Assim, os resultados do presente trabalho permitiu estabelecer um procedimento para a seleção de fungos produtores de compostos absorvedores de radiação UV, que poderia ser aplicado na obtenção de novos filtros orgânicos naturais para protetores solares.

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PURPOSE: To design and validate a vision-specific quality-of-life assessment tool to be used in a clinical setting to evaluate low-vision rehabilitation strategy and management. METHODS: Previous vision-related questionnaires were assessed by low-vision rehabilitation professionals and patients for relevance and coverage. The 74 items selected were pretested to ensure correct interpretation. One hundred and fifty patients with low vision completed the chosen questions on four occasions to allow the selection of the most appropriate items. The vision-specific quality of life of patients with low vision was compared with that of 70 age-matched and gender-matched patients with normal vision and before and after low-vision rehabilitation in 278 patients. RESULTS: Items that were unreliable, internally inconsistent, redundant, or not relevant were excluded, resulting in the 25-item Low Vision Quality-of-Life Questionnaire (LVQOL). Completion of the LVQOL results in a summed score between 0 (a low quality of life) and 125 (a high quality of life). The LVQOL has a high internal consistency (α = 0.88) and good reliability (0.72). The average LVQOL score for a population with low vision (60.9 ± 25.1) was significantly lower than the average score of those with normal vision (100.3 ± 20.8). Rehabilitation improved the LVQOL score of those with low vision by an average of 6.8 ± 15.6 (17%). CONCLUSIONS: The LVQOL was shown to be an internally consistent, reliable, and fast method for measuring the vision-specific quality of life of the visually impaired in a clinical setting. It is able to quantify the quality of life of those with low vision and is useful in determining the effects of low-vision rehabilitation. Copyright (C) 2000 Elsevier Science Inc.

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Geometric information relating to most engineering products is available in the form of orthographic drawings or 2D data files. For many recent computer based applications, such as Computer Integrated Manufacturing (CIM), these data are required in the form of a sophisticated model based on Constructive Solid Geometry (CSG) concepts. A recent novel technique in this area transfers 2D engineering drawings directly into a 3D solid model called `the first approximation'. In many cases, however, this does not represent the real object. In this thesis, a new method is proposed and developed to enhance this model. This method uses the notion of expanding an object in terms of other solid objects, which are either primitive or first approximation models. To achieve this goal, in addition to the prepared subroutine to calculate the first approximation model of input data, two other wireframe models are found for extraction of sub-objects. One is the wireframe representation on input, and the other is the wireframe of the first approximation model. A new fast method is developed for the latter special case wireframe, which is named the `first approximation wireframe model'. This method avoids the use of a solid modeller. Detailed descriptions of algorithms and implementation procedures are given. In these techniques utilisation of dashed line information is also considered in improving the model. Different practical examples are given to illustrate the functioning of the program. Finally, a recursive method is employed to automatically modify the output model towards the real object. Some suggestions for further work are made to increase the domain of objects covered, and provide a commercially usable package. It is concluded that the current method promises the production of accurate models for a large class of objects.

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The goal of my Ph.D. thesis is to enhance the visualization of the peripheral retina using wide-field optical coherence tomography (OCT) in a clinical setting.

OCT has gain widespread adoption in clinical ophthalmology due to its ability to visualize the diseases of the macula and central retina in three-dimensions, however, clinical OCT has a limited field-of-view of 300. There has been increasing interest to obtain high-resolution images outside of this narrow field-of-view, because three-dimensional imaging of the peripheral retina may prove to be important in the early detection of neurodegenerative diseases, such as Alzheimer's and dementia, and the monitoring of known ocular diseases, such as diabetic retinopathy, retinal vein occlusions, and choroid masses.

Before attempting to build a wide-field OCT system, we need to better understand the peripheral optics of the human eye. Shack-Hartmann wavefront sensors are commonly used tools for measuring the optical imperfections of the eye, but their acquisition speed is limited by their underlying camera hardware. The first aim of my thesis research is to create a fast method of ocular wavefront sensing such that we can measure the wavefront aberrations at numerous points across a wide visual field. In order to address aim one, we will develop a sparse Zernike reconstruction technique (SPARZER) that will enable Shack-Hartmann wavefront sensors to use as little as 1/10th of the data that would normally be required for an accurate wavefront reading. If less data needs to be acquired, then we can increase the speed at which wavefronts can be recorded.

For my second aim, we will create a sophisticated optical model that reproduces the measured aberrations of the human eye. If we know how the average eye's optics distort light, then we can engineer ophthalmic imaging systems that preemptively cancel inherent ocular aberrations. This invention will help the retinal imaging community to design systems that are capable of acquiring high resolution images across a wide visual field. The proposed model eye is also of interest to the field of vision science as it aids in the study of how anatomy affects visual performance in the peripheral retina.

Using the optical model from aim two, we will design and reduce to practice a clinical OCT system that is capable of imaging a large (800) field-of-view with enhanced visualization of the peripheral retina. A key aspect of this third and final aim is to make the imaging system compatible with standard clinical practices. To this end, we will incorporate sensorless adaptive optics in order to correct the inter- and intra- patient variability in ophthalmic aberrations. Sensorless adaptive optics will improve both the brightness (signal) and clarity (resolution) of features in the peripheral retina without affecting the size of the imaging system.

The proposed work should not only be a noteworthy contribution to the ophthalmic and engineering communities, but it should strengthen our existing collaborations with the Duke Eye Center by advancing their capability to diagnose pathologies of the peripheral retinal.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade UnB Planaltina, Mestrado em Ciências de Materias, 2016.

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Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

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The objective of this work was to develop and validate a rapid Reversed-Phase High-Performance Liquid Chromatography method for the quantification of 3,5,3 '-triiodothyroacetic acid (TRIAC) in nanoparticles delivery system prepared in different polymeric matrices. Special attention was given to developing a reliable reproductive technique for the pretreatment of the samples. Chromatographic runs were performed on an Agilent 1200 Series HPLC with a RP Phenomenex (R) Gemini C18 (150 x 4, 6 mm i.d., 5 mu m) column using acetonitrile and triethylamine buffer 0.1% (TEA) (40 : 60 v/v) as a mobile phase in an isocratic elution, pH 5.6 at a flow rate of 1 ml min(-1). TRIAC was detected at a wavelength of 220 nm. The injection volume was 20 mu l and the column temperature was maintained at 35 degrees C. The validation characteristics included accuracy, precision, specificity, linearity, recovery, and robustness. The standard curve was found to have a linear relationship (r(2) - 0.9996) over the analytical range of 5-100 mu g ml(-1) . The detection and quantitation limits were 1.3 and 3.8 mu g ml(-1), respectively. The recovery and loaded TRIAC in colloidal system delivery was nearly 100% and 98%, respectively. The method was successfully applied in polycaprolactone, polyhydroxybutyrate, and polymethylmethacrylate nanoparticles.

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A method was optimized for the analysis of omeprazole (OMZ) by ultra-high speed LC with diode array detection using a monolithic Chromolith Fast Gradient RP 18 endcapped column (50 x 2.0 mm id). The analyses were performed at 30 degrees C using a mobile phase consisting of 0.15% (v/v) trifluoroacetic acid (TFA) in water (solvent A) and 0.15% (v/v) TFA in acetonitrile (solvent B) under a linear gradient of 5 to 90% B in 1 min at a flow rate of 1.0 mL/min and detection at 220 nm. Under these conditions, OMZ retention time was approximately 0.74 min. Validation parameters, such as selectivity, linearity, precision, accuracy, and robustness, showed results within the acceptable criteria. The method developed was successfully applied to OMZ enteric-coated pellets, showing that this assay can be used in the pharmaceutical industry for routine QC analysis. Moreover, the analytical conditions established allow for the simultaneous analysis of OMZ metabolites, 5-hydroxyomeprazole and omeprazole sulfone, in the same run, showing that this method can be extended to other matrixes with adequate procedures for sample preparation.

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In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.

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Although the molecular typing of Pseudomonas aeruginosa is important to understand the local epidemiology of this opportunistic pathogen, it remains challenging. Our aim was to develop a simple typing method based on the sequencing of two highly variable loci. Single-strand sequencing of three highly variable loci (ms172, ms217, and oprD) was performed on a collection of 282 isolates recovered between 1994 and 2007 (from patients and the environment). As expected, the resolution of each locus alone [number of types (NT) = 35-64; index of discrimination (ID) = 0.816-0.964] was lower than the combination of two loci (NT = 78-97; ID = 0.966-0.971). As each pairwise combination of loci gave similar results, we selected the most robust combination with ms172 [reverse; R] and ms217 [R] to constitute the double-locus sequence typing (DLST) scheme for P. aeruginosa. This combination gave: (i) a complete genotype for 276/282 isolates (typability of 98%), (ii) 86 different types, and (iii) an ID of 0.968. Analysis of multiple isolates from the same patients or taps showed that DLST genotypes are generally stable over a period of several months. The high typability, discriminatory power, and ease of use of the proposed DLST scheme makes it a method of choice for local epidemiological analyses of P. aeruginosa. Moreover, the possibility to give unambiguous definition of types allowed to develop an Internet database ( http://www.dlst.org ) accessible by all.

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Currently, there is no simple direct screening method for the misuse of blood transfusions in sports. In this study, we investigated whether the measurement of iron in EDTA-plasma can serve as biomarker for such purpose. Our results revealed an increase of the plasma iron level up to 25-fold 6 h after blood re-infusion. The variable remained elevated 10-fold one day after the procedure. A specificity of 100% and a sensitivity of 93% were obtained with a proposed threshold at 45 µg/dL of plasma iron. Therefore, our test could be used as a simple, cost effective biomarker for the screening for blood transfusion misuse in sports. Copyright © 2014 John Wiley & Sons, Ltd.

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Very large molecular systems can be calculated with the so called CNDOL approximate Hamiltonians that have been developed by avoiding oversimplifications and only using a priori parameters and formulas from the simpler NDO methods. A new diagonal monoelectronic term named CNDOL/21 shows great consistency and easier SCF convergence when used together with an appropriate function for charge repulsion energies that is derived from traditional formulas. It is possible to obtain a priori molecular orbitals and electron excitation properties after the configuration interaction of single excited determinants with reliability, maintaining interpretative possibilities even being a simplified Hamiltonian. Tests with some unequivocal gas phase maxima of simple molecules (benzene, furfural, acetaldehyde, hexyl alcohol, methyl amine, 2,5 dimethyl 2,4 hexadiene, and ethyl sulfide) ratify the general quality of this approach in comparison with other methods. The calculation of large systems as porphine in gas phase and a model of the complete retinal binding pocket in rhodopsin with 622 basis functions on 280 atoms at the quantum mechanical level show reliability leading to a resulting first allowed transition in 483 nm, very similar to the known experimental value of 500 nm of "dark state." In this very important case, our model gives a central role in this excitation to a charge transfer from the neighboring Glu(-) counterion to the retinaldehyde polyene chain. Tests with gas phase maxima of some important molecules corroborate the reliability of CNDOL/2 Hamiltonians.

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This study shows the possibility offered by modern ultra-high performance supercritical fluid chromatography combined with tandem mass spectrometry in doping control analysis. A high throughput screening method was developed for 100 substances belonging to the challenging classes of anabolic agents, hormones and metabolic modulators, synthetic cannabinoids and glucocorticoids, which should be detected at low concentrations in urine. To selectively extract these doping agents from urine, a supported liquid extraction procedure was implemented in a 48-well plate format. At the tested concentration levels ranging from 0.5 to 5 ng/mL, the recoveries were better than 70% for 48-68% of the compounds and higher than 50% for 83-87% of the tested substances. Due to the numerous interferences related to isomers of steroids and ions produced by the loss of water in the electrospray source, the choice of SFC separation conditions was very challenging. After careful optimization, a Diol stationary phase was employed. The total analysis time for the screening assay was only 8 min, and interferences as well as susceptibility to matrix effect (ME) were minimized. With the developed method, about 70% of the compounds had relative ME within the range ±20%, at a concentration of 1 and 5 ng/mL. Finally, limits of detection achieved with the above-described strategy including 5-fold preconcentration were below 0.1 ng/mL for the majority of the tested compounds. Therefore, LODs were systematically better than the minimum required performance levels established by the World anti-doping agency, except for very few metabolites.

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Chromium(III) at the ng L-1 level was extracted using partially silylated MCM-41 modified by a tetraazamacrocyclic compound (TAMC) and determined by inductively coupled plasma optical emision spectrometry (ICP OES). The extraction time and efficiency, pH and flow rate, type and minimum amount of stripping acid, and break- through volume were investigated. The method's enrichment factor and detection limit are 300 and 45.5 pg mL-1, respectively. The maximum capacity of the 10 mg of modified silylated MCM-41 was found to be 400.5±4.7 µg for Cr(III). The method was applied to the determination of Cr(III) and Cr(VI) in the wastewater of the chromium electroplating industry and in environmental and biological samples (black tea, hot and black pepper).