973 resultados para MISSING VALUE ESTIMATION
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This article reports on a search for dark matter pair production in association with bottom or top quarks in 20.3fb−1 of pp collisions collected at s√=8 TeV by the ATLAS detector at the LHC. Events with large missing transverse momentum are selected when produced in association with high-momentum jets of which one or more are identified as jets containing b-quarks. Final states with top quarks are selected by requiring a high jet multiplicity and in some cases a single lepton. The data are found to be consistent with the Standard Model expectations and limits are set on the mass scale of effective field theories that describe scalar and tensor interactions between dark matter and Standard Model particles. Limits on the dark-matter--nucleon cross-section for spin-independent and spin-dependent interactions are also provided. These limits are particularly strong for low-mass dark matter. Using a simplified model, constraints are set on the mass of dark matter and of a coloured mediator suitable to explain a possible signal of annihilating dark matter.
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Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of s√=8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT>120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between EmissT>150 GeV and EmissT>700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with large extra spatial dimensions, pair production of weakly interacting dark matter candidates, and production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presented.
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The results of a search for supersymmetry in final states containing at least one isolated lepton (electron or muon), jets and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider (LHC) are reported. The search is based on proton-proton collision data at a centre-of-mass energy s√=8 TeV collected in 2012, corresponding to an integrated luminosity of 20 fb−1. No significant excess above the Standard Model expectation is observed. Limits are set on the parameters of a minimal universal extra dimensions model, excluding a compactification radius of 1/Rc=950 GeV for a cut-off scale times radius (ΛRc) of approximately 30, as well as on sparticle masses for various supersymmetric models. Depending on the model, the search excludes gluino masses up to 1.32 TeV and squark masses up to 840 GeV.
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Extreme value theory (EVT) deals with the occurrence of extreme phenomena. The tail index is a very important parameter appearing in the estimation of the probability of rare events. Under a semiparametric framework, inference requires the choice of a number k of upper order statistics to be considered. This is the crux of the matter and there is no definite formula to do it, since a small k leads to high variance and large values of k tend to increase the bias. Several methodologies have emerged in literature, specially concerning the most popular Hill estimator (Hill, 1975). In this work we compare through simulation well-known procedures presented in Drees and Kaufmann (1998), Matthys and Beirlant (2000), Beirlant et al. (2002) and de Sousa and Michailidis (2004), with a heuristic scheme considered in Frahm et al. (2005) within the estimation of a different tail measure but with a similar context. We will see that the new method may be an interesting alternative.
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The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.
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In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.
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Mycotoxins are toxic secondary metabolites produced by filamentous fungi that occur naturally in agricultural commodities worldwide. Aflatoxins, ochratoxin A, patulin, fumonisins, zearalenone, trichothecenes and ergot alkaloids are presently the most important for food and feed safety. These compounds are produced by several species that belong to the Aspergillus, Penicillium, Fusarium and Claviceps genera and can be carcinogenic, mutagenic, teratogenic, cytotoxic, neurotoxic, nephrotoxic, estrogenic and immunosuppressant. Human and animal exposure to mycotoxins is generally assessed by taking into account data on the occurrence of mycotoxins in food and feed as well as data on the consumption patterns of the concerned population. This evaluation is crucial to support measures to reduce consumer exposure to mycotoxins. This work reviews the occurrence and levels of mycotoxins in Portuguese food and feed to provide a global overview of this issue in Portugal. With the information collected, the exposure of the Portuguese population to those mycotoxins is assessed, and the estimated dietary intakes are presented.
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Proceedings da AUTEX 2015, Bucareste, Roménia.
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Results of a search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton--proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb−1 have been collected with the ATLAS detector at the LHC. The observed data are well described by the expected Standard Model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyond the Standard Model featuring dark-matter candidates.
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Mushrooms contain a multitude of biomolecules with nutritional and/or biological activity. Among the bioactive molecules, phenolic compounds and tocopherols are the most responsible for their antioxidant activity. In the present work, Boletus edulis, Lentinus edodes and Xerocomus badius, three edible mushroom species originated from Poland, were analyzed for their chemical composition and antioxidant activity. Carbohydrates were the most abundant macronutrients, followed by proteins and ash. Fructose, mannitol and trehalose were the prevalent sugars, but glucose was only found in B. edulis. Polyunsaturated fatty acids predominated over mono and saturated fatty acids. Palmitic, oleic and linoleic acids were abundant in the three samples. α- and β- Tocopherols were quantified in all the samples, but γ-tocopherol was only identified in X. badius. Oxalic and fumaric acids were quantified in the three samples; quinic acid was only present in L. edodes, and malic and citric acids were only found in X. badius. p-Hydroxybenzoic, protocatechuic and cinnamic acids were quantified in all the species, while p-coumaric acid was only found in B. edulis. This species and X. badius revealed the highest antioxidant properties, being B. edulis more effective in radicals scavenging activity and reducing power, and X. badius in lipid peroxidation inhibition, which is related with the highest amounts in phenolic compounds and tocopherols, respectively.
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)
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In this study, a mathematical model for the production of Fructo-oligosaccharides (FOS) by Aureobasidium pullulans is developed. This model contains a relatively large set of unknown parameters, and the identification problem is analyzed using simulation data, as well as experimental data. Batch experiments were not sufficiently informative to uniquely estimate all the unknown parameters, thus, additional experiments have to be achieved in fed-batch mode to supplement the missing information. © 2015 IEEE.
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Background and aims: Small bowel capsule endoscopy (SBCE) allows mapping of small bowel inflammation in Crohn’s disease (CD). We aimed to assess the prognostic value of the severity of inflammatory lesions, quantified by the Lewis score (LS), in patients with isolated small bowel CD. Methods: A retrospective study was performed in which 53 patients with isolated small bowel CD were submitted to SBCE at the time of diagnosis. The Lewis score was calculated and patients had at least 12 months of follow-up after diagnosis. As adverse events we defined disease flare requiring systemic corticosteroid therapy, hospitalization and/or surgery during follow-up. We compared the incidence of adverse events in 2 patient subgroups, i.e. those with moderate or severe inflammatory activity (LS =790) and those with mild inflammatory activity (135 = LS < 790). Results: The LS was =790 in 22 patients (41.5%), while 58.5% presented with LS between 135 and 790. Patients with a higher LS were more frequently smokers (p = 0.01), males (p = 0017) and under immunosuppressive therapy (p = 0.004). In multivariate analysis, moderate to severe disease at SBCE was independently associated with corticosteroid therapy during follow-up, with a relative risk (RR) of 5 (p = 0.011; 95% confidence interval [CI] 1.5–17.8), and for hospitalization, with an RR of 13.7 (p = 0 .028; 95% CI 1.3–141.9). Conclusion: In patients with moderate to severe inflammatory activity there were higher prevalences of corticosteroid therapy demand and hospitalization during follow-up. Thus, stratifying the degree of small bowel inflammatory activity with SBCE and LS calculation at the time of diagnosis provided relevant prognostic value in patients with isolated small bowel CD.
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A precise estimation of the postmortem interval (PMI) is one of the most important topics in forensic pathology. However, the PMI estimation is based mainly on the visual observation of cadaverous pheno- mena (e.g. algor, livor and rigor mortis) and on alternative methods such as thanatochemistry that remain relatively imprecise. The aim of this in vitro study was to evaluate the kinetic alterations of several bio- chemical parameters (i.e. proteins, enzymes, substrates, electrolytes and lipids) during putrefaction of human blood. For this purpose, we performed kinetic biochemical analysis during a 264 hour period. The results showed a significant linear correlation between total and direct bilirubin, urea, uric acid, transferrin, immunoglobulin M (IgM), creatine kinase (CK), aspartate transaminase (AST), calcium and iron with the time of blood putrefaction. These parameters allowed us to develop two mathematical models that may have predictive values and become important complementary tools of traditional methods to achieve a more accurate PMI estimation
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OBJECTIVE: To determine if abnormal laboratory findings are more common in individuals with hypertension and in those with other risk factors, such as obesity, smoking and alcohol ingestion. METHODS: A study was carried out in the general outpatient clinics of a university hospital (145 individuals without previous diagnosis of hypertension) and the following variables were assessed: high blood pressure (as defined by the VI Joint National Committee on Prevention, Detection and Treatment of High Blood Pressure - VI JNC), obesity [calculated using body mass index (BMI)], tobacco use, and alcoholic ingestion. The laboratory examinations consisted of the following tests: hemogram, glycemia, uric acid, potassium, total/HDL-fraction cholesterol, triglycerides, calcium and creatinine. RESULTS: High blood pressure was not associated with a higher number of abnormal laboratory tests. Hypertensive individuals with a BMI > or = 25kg/m² or normotensive obese individuals, however, had a higher frequency of diabetes (12X), hypertriglyceridemia (3X), and hypercholesterolemia (2X), as compared with hypertensive individuals with BMI <25kg/m² and preobese/normal weight normotensive individuals. CONCLUSION: High blood pressure is not associated with a higher frequency of abnormal laboratory tests. The association of high blood pressure and obesity, however, increases the detection of diabetes and dyslipidemias.