986 resultados para Parallel methods
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Simulations provide a powerful means to help gain the understanding of crustal fault system physics required to progress towards the goal of earthquake forecasting. Cellular Automata are efficient enough to probe system dynamics but their simplifications render interpretations questionable. In contrast, sophisticated elasto-dynamic models yield more convincing results but are too computationally demanding to explore phase space. To help bridge this gap, we develop a simple 2D elastodynamic model of parallel fault systems. The model is discretised onto a triangular lattice and faults are specified as split nodes along horizontal rows in the lattice. A simple numerical approach is presented for calculating the forces at medium and split nodes such that general nonlinear frictional constitutive relations can be modeled along faults. Single and multi-fault simulation examples are presented using a nonlinear frictional relation that is slip and slip-rate dependent in order to illustrate the model.
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Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood, and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed. (C) 2003 International Life Sciences Institute.
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The apposition compound eyes of stomatopod crustaceans contain a morphologically distinct eye region specialized for color and polarization vision, called the mid-band. In two stomatopod superfamilies, the mid-band is constructed from six rows of enlarged ommatidia containing multiple photoreceptor classes for spectral and polarization vision. The aim of this study was to begin to analyze the underlying neuroarchitecture, the design of which might reveal clues how the visual system interprets and communicates to deeper levels of the brain the multiple channels of information supplied by the retina. Reduced silver methods were used to investigate the axon pathways from different retinal regions to the lamina ganglionaris and from there to the medulla externa, the medulla interna, and the medulla terminalis. A swollen band of neuropil-here termed the accessory lobe-projects across the equator of. the lamina ganglionaris, the medulla externa, and the medulla interna and represents, structurally, the retina's mid-band. Serial semithin and ultrathin resin sections were used to reconstruct the projection of photoreceptor axons from the retina to the lamina ganglionaris. The eight axons originating from one ommatidium project to the same lamina cartridge. Seven short visual fibers end at two distinct levels in each lamina cartridge, thus geometrically separating the two channels of polarization and spectral information. The eighth visual fiber runs axially through the cartridge and terminates in the medulla externa. We conclude that spatial, color, and polarization information is divided into three parallel data streams from the retina to the central nervous system. (C) 2003 Wiley-Liss, Inc.
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Taking functional programming to its extremities in search of simplicity still requires integration with other development (e.g. formal) methods. Induction is the key to deriving and verifying functional programs, but can be simplified through packaging proofs with functions, particularly folds, on data (structures). Totally Functional Programming avoids the complexities of interpretation by directly representing data (structures) as platonic combinators - the functions characteristic to the data. The link between the two simplifications is that platonic combinators are a kind of partially-applied fold, which means that platonic combinators inherit fold-theoretic properties, but with some apparent simplifications due to the platonic combinator representation. However, despite observable behaviour within functional programming that suggests that TFP is widely-applicable, significant work remains before TFP as such could be widely adopted.
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Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.
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Objective: The Assessing Cost-Effectiveness - Mental Health (ACE-MH) study aims to assess from a health sector perspective, whether there are options for change that could improve the effectiveness and efficiency of Australia's current mental health services by directing available resources toward 'best practice' cost-effective services. Method: The use of standardized evaluation methods addresses the reservations expressed by many economists about the simplistic use of League Tables based on economic studies confounded by differences in methods, context and setting. The cost-effectiveness ratio for each intervention is calculated using economic and epidemiological data. This includes systematic reviews and randomised controlled trials for efficacy, the Australian Surveys of Mental Health and Wellbeing for current practice and a combination of trials and longitudinal studies for adherence. The cost-effectiveness ratios are presented as cost (A$) per disability-adjusted life year (DALY) saved with a 95% uncertainty interval based on Monte Carlo simulation modelling. An assessment of interventions on 'second filter' criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') allows broader concepts of 'benefit' to be taken into account, as well as factors that might influence policy judgements in addition to cost-effectiveness ratios. Conclusions: The main limitation of the study is in the translation of the effect size from trials into a change in the DALY disability weight, which required the use of newly developed methods. While comparisons within disorders are valid, comparisons across disorders should be made with caution. A series of articles is planned to present the results.
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Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.
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Analytical and bioanalytical methods of high-performance liquid chromatography with fluorescence detection (HPLC-FLD) were developed and validated for the determination of chloroaluminum phthalocyanine in different formulations of polymeric nanocapsules, plasma and livers of mice. Plasma and homogenized liver samples were extracted with ethyl acetate, and zinc phthalocyanine was used as internal standard. The results indicated that the methods were linear and selective for all matrices studied. Analysis of accuracy and precision showed adequate values, with variations lower than 10% in biological samples and lower than 2% in analytical samples. The recoveries were as high as 96% and 99% in the plasma and livers, respectively. The quantification limit of the analytical method was 1.12 ng/ml, and the limits of quantification of the bioanalytical method were 15 ng/ml and 75 ng/g for plasma and liver samples, respectively. The bioanalytical method developed was sensitive in the ranges of 15-100 ng/ml in plasma and 75-500 ng/g in liver samples and was applied to studies of biodistribution and pharmacokinetics of AlClPc. (C) 2011 Elsevier B.V. All rights reserved.
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UV-VIS-Spectrophotometric and spectrofluorimetric methods have been developed and validated allowing the quantification of chloroaluminum phthalocyanine (CIAIPc) in nanocarriers. In order to validate the methods, the linearity, limit of detection (LOD), limit of quantification (LOQ), precision, accuracy, and selectivity were examined according to USP 30 and ICH guidelines. Linearities range were found between 0.50-3.00 mu g.mL(-1) (Y=0.3829 X [CIAIPc, mu g.mL(-1)] + 0.0126; r=0.9992) for spectrophotometry, and 0.05-1.00 mu g.mL(-1) (Y=2.24 x 10(6) X [CIAIPc, mu g.L(-1)] + 9.74 x 10(4); r=0.9978) for spectrofluorimetry. In addition, ANOVA and Lack-of-fit tests demonstrated that the regression equations were statistically significant (p<0.05), and the resulting linear model is fully adequate for both analytical methods. The LOD values were 0.09 and 0.01 mu g.mL(-1), while the LOCI were 0.27 and 0.04 mu g.mL(-1) for spectrophotometric and spectrofluorimetric methods, respectively. Repeatability and intermediate precision for proposed methods showed relative standard deviation (RSD) between 0.58% to 4.80%. The percent recovery ranged from 98.9% to 102.7% for spectrophotometric analyses and from 94.2% to 101.2% for spectrofluorimetry. No interferences from common excipients were detected and both methods were considered specific. Therefore, the methods are accurate, precise, specific, and reproducible and hence can be applied for quantification of CIAIPc in nanoemulsions (NE) and nanocapsules (NC).
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Background: A survey of pathology reporting of breast cancer in Western Australia in 1989 highlighted the need for improvement. The current study documents (1) changes in pathology reporting from 1989 to 1999 and (2) changes in patterns of histopathological prognostic indicators for breast cancer following introduction of mammographic screening in 1989. Methods: Data concerning all breast cancer cases reported in Western Australia in 1989, 1994 and 1999 were retrieved using the State Cancer Registry, Hospital Morbidity data system, and pathology laboratory records. Results: Pathology reports improved in quality during the decade surveyed. For invasive carcinoma, tumour size was not recorded in 1.2% of pathology reports in 1999 compared with 16.1% in 1989 (rho<0.001). Corresponding figures for other prognostic factors were: tumour grade 3.3% and 51.6% (rho<0.001), tumour type 0.2% and 4.1% (rho<0.001), vascular invasion 3.7% and 70.9% (rho<0.001), and lymph node status 1.9% and 4.5% (rho=0.023). In 1999, 5.9% of reports were not in a synoptic/checklist format, whereas all reports were descriptive in 1989 (rho<0.001). For the population as a whole, the proportion of invasive carcinomas <1 cm was 20.9% in 1999 compared with 14.5% in 1989 (rho<0.001); for tumours <2 cm the corresponding figures were 65.4% and 59.7% (rho=0.013). In 1999, 30.5% of tumours were histologically well-differentiated compared with 10.6% in 1989 (rho<0.001), and 61.7% were lymph node negative in 1999 compared with 57.1% in 1989 (rho=0.006). Pure ductal carcinoma in situ (DCIS) constituted 10.9% and 7.9% of total cases of breast carcinoma in 1999 and 1989, respectively (rho=0.01). Conclusions: Quality of pathology reporting improved markedly over the period, in parallel with adoption of stanclardised synoptic pathology reports. By 1999, recording of important prognostic information was almost complete. Frequency of favourable prognostic factors generally increased over time, reflecting expected effects of mammographic screening.
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Anemia screening before blood donation requires an accurate, quick, practical, and easy method with minimal discomfort for the donors. The aim of this study was to compare the accuracy of two quantitative methods of anemia screening: the HemoCue 201(+) (Aktiebolaget Leo Diagnostics) hemoglobin (Hb) and microhematocrit (micro-Hct) tests. Two blood samples of a single fingerstick were obtained from 969 unselected potential female donors to determine the Hb by HemoCue 201(+) and micro-Hct using HemataSTAT II (Separation Technology, Inc.), in alternating order. From each participant, a venous blood sample was drawn and run in an automatic hematology analyzer (ABX Pentra 60, ABX Diagnostics). Considering results of ABX Pentra 60 as true values, the sensitivity and specificity of HemoCue 201(+) and micro-Hct as screening methods were compared, using a venous Hb level of 12.0 g per dL as cutoff for anemia. The sensitivities of the HemoCue 201(+) and HemataSTAT II in detecting anemia were 56 percent (95% confidence interval [CI], 46.1%-65.5%) and 39.5 percent (95% CI, 30.2%-49.3%), respectively (p < 0.001). Analyzing only candidates with a venous Hb level lower than 11.0 g per dL, the deferral rate was 100 percent by HemoCue 201(+) and 77 percent by HemataSTAT II. The specificities of the methods were 93.5 and 93.2 percent, respectively. The HemoCue 201(+) showed greater discriminating power for detecting anemia in prospective blood donors than the micro-Hct method. Both presented equivalent deferral error rates of nonanemic potential donors. Compared to the micro-Hct, HemoCue 201(+) reduces the risk of anemic female donors giving blood, specially for those with lower Hb levels, without increasing the deferral of nonanemic potential donors.
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This special issue represents a further exploration of some issues raised at a symposium entitled “Functional magnetic resonance imaging: From methods to madness” presented during the 15th annual Theoretical and Experimental Neuropsychology (TENNET XV) meeting in Montreal, Canada in June, 2004. The special issue’s theme is methods and learning in functional magnetic resonance imaging (fMRI), and it comprises 6 articles (3 reviews and 3 empirical studies). The first (Amaro and Barker) provides a beginners guide to fMRI and the BOLD effect (perhaps an alternative title might have been “fMRI for dummies”). While fMRI is now commonplace, there are still researchers who have yet to employ it as an experimental method and need some basic questions answered before they venture into new territory. This article should serve them well. A key issue of interest at the symposium was how fMRI could be used to elucidate cerebral mechanisms responsible for new learning. The next 4 articles address this directly, with the first (Little and Thulborn) an overview of data from fMRI studies of category-learning, and the second from the same laboratory (Little, Shin, Siscol, and Thulborn) an empirical investigation of changes in brain activity occurring across different stages of learning. While a role for medial temporal lobe (MTL) structures in episodic memory encoding has been acknowledged for some time, the different experimental tasks and stimuli employed across neuroimaging studies have not surprisingly produced conflicting data in terms of the precise subregion(s) involved. The next paper (Parsons, Haut, Lemieux, Moran, and Leach) addresses this by examining effects of stimulus modality during verbal memory encoding. Typically, BOLD fMRI studies of learning are conducted over short time scales, however, the fourth paper in this series (Olson, Rao, Moore, Wang, Detre, and Aguirre) describes an empirical investigation of learning occurring over a longer than usual period, achieving this by employing a relatively novel technique called perfusion fMRI. This technique shows considerable promise for future studies. The final article in this special issue (de Zubicaray) represents a departure from the more familiar cognitive neuroscience applications of fMRI, instead describing how neuroimaging studies might be conducted to both inform and constrain information processing models of cognition.