991 resultados para predictor-corrector methods
Resumo:
In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.
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BACKGROUND. Sentinel lymph node (SLN) mapping and biopsy is emerging as an alternative to axillary lymph node dissection (ALND) in determining the lymph node status of patients with early-stage breast carcinoma. The hypothesis of the technique is that the SLN is the first lymph node in the regional lymphatic basin that drains the primary tumor. Non-SLN (NSLN) metastasis in the axilla is unlikely if the axillary SLN shows no tumor involvement, and, thus, further axillary interference may be avoided. However, the optimal treatment of the axilla in which an SLN metastasis is found requires ongoing evaluation. The objectives of this study were to evaluate the predictors for NSLN metastasis in the presence of a tumor-involved axillary SLN and to examine the treatment implications for patients with early-stage breast carcinoma. METHODS. Between June 1998 and May 2000, 167 patients participated in the pilot study of SLN mapping and biopsy at Westmead Hospital. SLNs were identified successfully and biopsied in 140 axillae. All study patients also underwent ALND. The incidence of NSLN metastasis in the 51 patients with a SLN metastasis was correlated with clinical and pathologic characteristics. RESULTS. Of 51 patients with a positive SLN, 24 patients (47%) had NSLN metastases. The primary tumor size was the only significant predictor for NSLN involvement. NSLN metastasis occurred in 25% of patients (95% confidence interval [95%CI], 10-47%) with a primary tumor size less than or equal to 20 mm and in 67% of patients (95%CI, 46-83%) with a primary tumor size > 20 mm (P = 0.005). The size of the SLN metastasis was not associated significantly with NSLN involvement. Three of 7 patients (43%) with an SLN micrometastasis (< 1 mm) had NSLN involvement compared with 38 of 44 patients (48%) with an SLN macrometastasis (greater than or equal to 1 mm). CONCLUSIONS. The current study did not identify a subgroup of SLN positive patients in whom the incidence of NSLN involvement was low enough to warrant no further axillary interference. At present, a full axillary dissection should be performed in patients with a positive SLN. (C) 2001 American Cancer Society.
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Background and Purpose-Few reliable estimates of the long-term functional outcome after stroke are available. This population-based study aimed to describe disability, dependency, and related independent prognostic factors at 5 years after,a first-ever stroke in patients in Perth, Western Australia. Methods-All individuals with a suspected acute stroke who were resident in a geographically defined region (population, 138 708) of Perth, Western Australia, were registered prospectively and assessed according to standardized diagnostic criteria over a period of 18 months in 1989 to 1990. Patients were followed up prospectively at 4 and 12 months and 5 years after the index event. Results-There were 370 cases of first-ever stroke, and 277 patients survived to 30 days. Of these early survivors, 152 (55%) were alive at 5 years, and among those who were neither institutionalized (n=146) nor disabled (n=129) at the time of their stroke, 21 (14%) were institutionalized in a nursing home, and 47 (36%) were disabled. The most important predictors of death or disability at 5 years were increasing age, baseline disability defined by a Barthel Index score of <20/20 (odds ratio [OR], 6.3; 95% confidence interval [CI], 2.7 to 14), moderate hemiparesis (OR, 2.7. 95% CI, 1.1 to 6.2), severe hemiparesis (OR, 4.5; 95% CI, 1.1 to 19), and recurrent stroke (OR, 9.4; 95% CI, 3.0 to 30). A low level of activity before the stroke was a significant predictor of institutionalization, and subsequent recurrent stroke was a consistent, independent predictor of institutionalization, disability, and death or institutionalization, increasing the odds of each of these 3 adverse outcomes by 5- to 15-fold. Conclusions-Among 30-day survivors of first-ever stroke, about half survive 5 years; of survivors, one third remain disabled, and I in 7 are in permanent institutional care. The major modifiable predictors of poor long-term outcome are a low level of activity before the stroke and subsequent recurrent stroke. Efforts to increase physical activity among the elderly and to prevent recurrent stroke in survivors of a first stroke are likely to reduce the long-term burden of cerebrovascular disease.
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Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.
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Two experiments examined whether a measure of implicit stereotyping based on the tendency to explain Black stereotype-incongruent events more often than Black stereotype-congruent events (Stereotypic Explanatory Bias or SEB) is predictive of behavior toward a partner in an interracial interaction. In Experiment I SEB predicted White males' choice to ask stereotypic questions of a Black female (but not a White male or White female) in an interview. In Experiment 2 the type of explanation (internal or external attribution) made for stereotype-inconsistency was examined. Results showed that White participants who made internal attributions for Black stereotype-incongruent behavior were rated more positively and those who made external attributions were rated more negatively by a Black male confederate. These results point to the potential of implicit stereotyping as an important predictor of behavior in an interracial interaction. (C) 2002 Elsevier Science (USA). All rights reserved.
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Recent attempts to explain the susceptibility of vertebrates to declines worldwide have largely focused on intrinsic factors such as body size, reproductive potential, ecological specialization, geographical range and phylogenetic longevity. Here, we use a database of 145 Australian marsupial species to test the effects of both intrinsic and extrinsic factors in a multivariate comparative approach. We model five intrinsic (body size, habitat specialization, diet, reproductive rate and range size) and four extrinsic (climate and range overlap with introduced foxes, sheep and rabbits) factors. We use quantitative measures of geographical range contraction as indices of decline. We also develop a new modelling approach of phylogenetically independent contrasts combined with imputation of missing values to deal simultaneously with phylogenetic structuring and missing data. One extrinsic variable-geographical range overlap with sheep-was the only consistent predictor of declines. Habitat specialization was independently but less consistently associated with declines. This suggests that extrinsic factors largely determine interspecific variation in extinction risk among Australian marsupials, and that the intrinsic factors that are consistently associated with extinction risk in other vertebrates are less important in this group. We conclude that recent anthropogenic changes have been profound enough to affect species on a continent-wide scale, regardless of their intrinsic biology.
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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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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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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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Background-C- reactive protein (CRP) levels have been shown to predict a number of cardiovascular outcomes. CRP levels have also been found to be elevated in patients with abdominal aortic aneurysms (AAAs). The aim of this study was to assess the relation between CRP levels and rates of expansion of small AAAs. Methods and Results-A cohort of men with small aneurysms was identified in a trial of screening with ultrasound scanning. After initial screening, men were rescanned at 6- to 12-month intervals. CRP levels were measured at the first follow-up visit. Rates of expansion and risk factors for expansion were assessed with the use of data from 545 men who attended for at least 1 scan after CRP levels were measured. These men were followed for a median of 48 (range, 5 to 69) months. The mean annual rate of expansion was 1.6 mm. The median CRP level was 2.6 mg/L in men with the smaller AAAs (30 to 39 mm, n=433) compared with 3.5 mg/L in men with larger AAAs (40 to 54 mm, n=112) (P=0.007). The multivariate age-adjusted logistic model confirmed initial aortic diameter to be the only factor associated with rapid expansion with an odds ratio of 7.2 (95% CI, 4.3,12.2) for an initial diameter of 40 to 54 mm relative to one of 30 to 39 mm. Conclusions-Most small aneurysms expand slowly. CRP levels are elevated in larger aneurysms but do not appear to be associated with rapid expansion. The most useful predictor of aneurysmal expansion in men is aortic diameter.
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Background-The importance of serum triglyceride levels as a risk factor for cardiovascular diseases is uncertain. Methods and Results-We performed an individual participant data meta-analysis of prospective studies conducted in the Asia-Pacific region. Cox models were applied to the combined data from 26 studies to estimate the overall and region-, sex-, and age-specific hazard ratios for major cardiovascular diseases by fifths of triglyceride values. During 796 671 person-years of follow-up among 96 224 individuals, 670 and 667 deaths as a result of coronary heart disease (CHD) and stroke, respectively, were recorded. After adjustment for major cardiovascular risk factors, participants grouped in the highest fifth of triglyceride levels had a 70% (95% CI, 47 to 96) greater risk of CHD death, an 80% (95% CI, 49 to 119) higher risk of fatal or nonfatal CHD, and a 50% (95% CI, 29% to 76%) increased risk of fatal or nonfatal stroke compared with those belonging to the lowest fifth. The association between triglycerides and CHD death was similar across subgroups defined by ethnicity, age, and sex. Conclusions-Serum triglycerides are an important and independent predictor of CHD and stroke risk in the Asia-Pacific region. These results may have clinical implications for cardiovascular risk prediction and the use of lipid-lowering therapy.
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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.