992 resultados para Aggregation methods


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PURPOSE: To determine whether hyperopia aggregates in families in an older mixed-race population. DESIGN: Cross-sectional familial aggregation study using sibships. METHODS: We recruited 759 subjects (mean age, 73.4 years) in 241 families through the population-based Salisbury Eye Evaluation study. Subjects underwent noncycloplegic refraction if best-corrected visual acuity (BCVA) was <or=20/40, had lensometry to measure their currently worn spectacles if BCVA was >20/40 with spectacles, or were considered to be plano (refraction of zero) if the BCVA was >20/40 without spectacles. Preoperative refraction from medical records was used for bilaterally pseudophakic subjects. RESULTS: Utilizing hyperopia cutoffs from 1.00 to 2.50 diopters, age-, race-, and gender-adjusted odds ratios for hyperopia with an affected sibling ranged from 2.72 (95% confidence interval [CI], 1.84-4.01) to 4.87 (95% CI, 2.54-9.30). The odds of hyperopia increased with age until 75 years, after which they remained relatively constant. Black men were significantly less likely to be hyperopic than white men, white women, or black women. CONCLUSIONS: Hyperopia appears to be under strong genetic control in this older population.

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PURPOSE: To determine the heritability of refractive error and the familial aggregation of myopia in an older population. METHODS: Seven hundred fifty-nine siblings (mean age, 73.4 years) in 241 families were recruited from the Salisbury Eye Evaluation (SEE) Study in eastern Maryland. Refractive error was determined by noncycloplegic subjective refraction (if presenting distance visual acuity was < or =20/40) or lensometry (if best corrected visual acuity was >20/40 with spectacles). Participants were considered plano (refractive error of zero) if uncorrected visual acuity was >20/40. Preoperative refraction from medical records was used for pseudophakic subjects. Heritability of refractive error was calculated with multivariate linear regression and was estimated as twice the residual between-sibling correlation after adjusting for age, gender, and race. Logistic regression models were used to estimate the odds ratio (OR) of myopia, given a myopic sibling relative to having a nonmyopic sibling. RESULTS: The estimated heritability of refractive error was 61% (95% confidence interval [CI]: 34%-88%) in this population. The age-, race-, and sex-adjusted ORs of myopia were 2.65 (95% CI: 1.67-4.19), 2.25 (95% CI: 1.31-3.87), 3.00 (95% CI: 1.56-5.79), and 2.98 (95% CI: 1.51-5.87) for myopia thresholds of -0.50, -1.00, -1.50, and -2.00 D, respectively. Neither race nor gender was significantly associated with an increased risk of myopia. CONCLUSIONS: Refractive error and myopia are highly heritable in this elderly population.

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KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.

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Background: Quercetin, a flavonoid present in the human diet, which is found in high levels in onions, apples, tea and wine, has been shown previously to inhibit platelet aggregation and signaling in vitro. Consequently, it has been proposed that quercetin may contribute to the protective effects against cardiovascular disease of a diet rich in fruit and vegetables. Objectives: A pilot human dietary intervention study was designed to investigate the relationship between the ingestion of dietary quercetin and platelet function. Methods: Human subjects ingested either 150 mg or 300 mg quercetin-4'-O-beta-D-glucoside Supplement to determine the systemic availability of quercetin. Platelets were isolated from subjects to analyse collagen-stimulated cell signaling and aggregation. Results: Plasma quercetin concentrations peaked at 4.66 mum (+/-0.77) and 9.72mum (+/-1.38) 30min after ingestion of 150-mg and 300-mg doses of quercefin-4'-O-beta-D-glucoside, respectively, demonstrating that quercetin was bioavailable, with plasma concentrations attained in the range known to affect platelet function in vitro. Platelet aggregation was inhibited 30 and 120 min after ingestion of both doses of quercetin-4'-O-beta-D-glucoside. Correspondingly, collagen-stimulated tyrosine phosphorylation of total platelet proteins was inhibited. This was accorripanied by reduced tyrosine phosphorylation of the tyrosine kinase Syk and phospholipase Cgamma2, components of the platelet glycoprotein VI collagen receptor signaling pathway. Conclusions: This study provides new evidence of the relatively high systemic availability of quercetin in the form of quercetin-4'-O-beta-D-glucoside by supplementation, and implicates quercetin as a dietary inhibitor of platelet cell signaling and thrombus formation.

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We focus this work on the theoretical investigation of the block-copolymer poly [oxyoctyleneoxy-(2,6-dimethoxy-1,4phenylene-1,2-ethinylene-phenanthrene-2,4diyl) named as LaPPS19, recently proposed for optoelectronic applications. We used for that a variety of methods, from molecular mechanics to quantum semiempirical techniques (AMI, ZINDO/S-CIS). Our results show that as expected isolated LaPPS19 chains present relevant electron localization over the phenanthrene group. We found, however, that LaPPS19 could assemble in a pi-stacked form, leading to impressive interchain interaction; the stacking induces electronic delocalization between neighbor chains and introduces new states below the phenanthrene-related absorption; these results allowed us to associate the red-shift of the absorption edge, seen in the experimental results, to spontaneous pi-stack aggregation of the chains. (C) 2009 Wiley Periodicals, Inc. Int J Quantum Chem 110: 885-892, 2010

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Asystematic study on the surface-enhanced Raman scattering (SERS) for 3,6-bi-2-pyridyl-1,2,4,5-tetrazine (bptz) adsorbed onto citrate-modified gold nanoparticles (cit-AuNps) was carried out based on electronic and vibrational spectroscopy and density functional methods. The citrate/bptz exchange was carefully controlled by the stepwise addition of bptz to the cit-AuNps, inducing flocculation and leading to the rise of a characteristic plasmon coupling band in the visible region. Such stepwise procedure led to a uniform decrease of the citrate SERS signals and to the rise of characteristic peaks of bptz, consistent with surface binding via the N heterocyclic atoms. In contrast, single addition of a large amount of bptz promoted complete aggregation of the nanoparticles, leading to a strong enhancement of the SERS signals. In this case, from the distinct Raman profiles involved, the formation of a new SERS environment became apparent, conjugating the influence of the local hot spots and charge-transfer (CT) effects. The most strongly enhanced vibrations belong to a(1) and b(2) representations, and were interpreted in terms of the electromagnetic and the CT mechanisms: the latter involving significant contribution of vibronic coupling in the system. Copyright (C) 2010 John Wiley & Sons, Ltd.

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Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision that are ever present in decision support and expert systems in many areas. The choice of aggregation operators is crucial to the behavior of the system that is intended to mimic human decision making. This paper discusses how aggregation operators can be selected and adjusted to fit empirical data—a series of test cases. Both parametric and nonparametric regression are considered and compared. A practical application of the proposed methods to electronic implementation of clinical guidelines is presented

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This paper treats the problem of fitting general aggregation operators with unfixed number of arguments to empirical data. We discuss methods applicable to associative operators (t-norms, t-conorms, uninorms and nullnorms), means and Choquet integral based operators with respect to a universal fuzzy measure. Special attention is paid to k-order additive symmetric fuzzy measures.

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This paper investigates the problem of obtaining the weights of the ordered weighted aggregation (OWA) operators from observations. The problem is formulated as a restricted least squares and uniform approximation problems. We take full advantage of the linearity of the problem. In the former case, a well known technique of non-negative least squares is used. In a case of uniform approximation, we employ a recently developed cutting angle method of global optimisation. Both presented methods give results superior to earlier approaches, and do not require complicated nonlinear constructions. Additional restrictions, such as degree of orness of the operator, can be easily introduced

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This paper examines methods of point wise construction of aggregation operators via optimal interpolation. It is shown that several types of application-specific requirements lead to interpolatory type constraints on the aggregation function. These constraints are translated into global optimization problems, which are the focus of this paper. We present several methods of reduction of the number of variables, and formulate suitable numerical algorithms based on Lipschitz optimization.

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We address the issue of identifying various classes of aggregation operators from empirical data, which also preserves the ordering of the outputs. It is argued that the ordering of the outputs is more important than the numerical values, however the usual data fitting methods are only concerned with fitting the values. We will formulate preservation of the ordering problem as a standard mathematical programming problem, solved by standard numerical methods.

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Theoretical advances in modelling aggregation of information produced a wide range of aggregation operators, applicable to almost every practical problem. The most important classes of aggregation operators include triangular norms, uninorms, generalised means and OWA operators.
With such a variety, an important practical problem has emerged: how to fit the parameters/ weights of these families of aggregation operators to observed data? How to estimate quantitatively whether a given class of operators is suitable as a model in a given practical setting? Aggregation operators are rather special classes of functions, and thus they require specialised regression techniques, which would enforce important theoretical properties, like commutativity or associativity. My presentation will address this issue in detail, and will discuss various regression methods applicable specifically to t-norms, uninorms and generalised means. I will also demonstrate software implementing these regression techniques, which would allow practitioners to paste their data and obtain optimal parameters of the chosen family of operators.

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In this chapter we examine a number of methods to construct aggregation operators of interpolatory type for specific applications. The construction is based on the desired values of the aggregation operator at certain prototypical points, and on other desired properties, such as, conjuctive, disjunctive or averaging behaviour, symmetry and marginals.

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Background and Aims : Increased platelet aggregation is a major risk factor for heart attacks, stroke and thrombosis. Long chain omega-3 polyunsaturated fatty acids (LCn-3PUFA; eicosapentaenoic acid, EPA; docosahexaenoic acid, DHA) reduce platelet aggregation; however studies in the published literature involving EPA and/or DHA supplementation have yielded equivocal results. Recent in vitro studies have demonstrated that inhibition of platelet aggregation by LCn-3PUFA is gender specific. We examined the acute effects of dietary supplementation with EPA or DHA rich oils on platelet aggregation in healthy male and females.

Methods and Results :
A blinded placebo controlled trial involving 15 male and 15 female subjects. Platelet aggregation was measured at 0, 2, 5 and 24 h post-supplementation with a single dose of either a placebo or EPA or DHA rich oil capsules. The relationship between LCn-3PUFA and platelet activity at each time point was examined according to gender vs. treatment. EPA was significantly the most effective in reducing platelet aggregation in males at 2, 5 and 24 h post-supplementation (−11%, −10.6%, −20.5% respectively) whereas DHA was not effective relative to placebo. In contrast, in females, DHA significantly reduced platelet aggregation at 24 h (−13.7%) while EPA was not effective. An inverse relationship between testosterone levels and platelet aggregation following EPA supplementation was observed.

Conclusion : Interactions between sex hormones and omega-3 fatty acids exist to differentially reduce platelet aggregation. For healthy individuals, males may benefit more from EPA supplementation while females are more responsive to DHA.

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The web is a rich resource for information discovery, as a result web mining is a hot topic. However, a reliable mining result depends on the reliability of the data set. For every single second, the web generate huge amount of data, such as web page requests, file transportation. The data reflect human behavior in the cyber space and therefore valuable for our analysis in various disciplines, e.g. social science, network security. How to deposit the data is a challenge. An usual strategy is to save the abstract of the data, such as using aggregation functions to preserve the features of the original data with much smaller space. A key problem, however is that such information can be distorted by the presence of illegitimate traffic, e.g. botnet recruitment scanning, DDoS attack traffic, etc. An important consideration in web related knowledge discovery then is the robustness of the aggregation method , which in turn may be affected by the reliability of network traffic data. In this chapter, we first present the methods of aggregation functions, and then we employe information distances to filter out anomaly data as a preparation for web data mining.