729 resultados para NORMALIZATION


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Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied appropriately. In this study we carried out simulation experiments and also analysed real microarray data to investigate the suitability of RMA when it is applied to dataset with different groups of biological samples. From our experiments, we showed that RMA with QN does not preserve the biological signal included in each group, but rather it would mix the signals between the groups. We also showed that the Median Polish method in the summarization step of RMA has similar mixing effect. RMA is one of the most widely used methods in microarray data processing and has been applied to a vast volume of data in biomedical research. The problematic behaviour of this method suggests that previous studies employing RMA could have been misadvised or adversely affected. Therefore we think it is crucially important that the research community recognizes the issue and starts to address it. The two core elements of the RMA method, quantile normalization and Median Polish, both have the undesirable effects of mixing biological signals between different sample groups, which can be detrimental to drawing valid biological conclusions and to any subsequent analyses. Based on the evidence presented here and that in the literature, we recommend exercising caution when using RMA as a method of processing microarray gene expression data, particularly in situations where there are likely to be unknown subgroups of samples.

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Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extractions. Simple, complex and end-stopped cells tuned to different spatial frequencies (scales) and/or orientations provide input for line, edge and keypoint detection. This yields a rich, multi-scale object representation that can be stored in memory in order to identify objects. The multi-scale, keypoint-based saliency maps for Focus-of-Attention can be explored to obtain face detection and normalization, after which face recognition can be achieved using the line/edge representation. In this paper, we focus only on face normalization, showing that multi-scale keypoints can be used to construct canonical representations of faces in memory.

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Fluctuations in ammonium (NH4+), measured as NH4-N loads using an ion-selective electrode installed at the inlet of a sewage treatment plant, showed a distinctive pattern which was associated to weekly (i.e., commuters) and seasonal (i.e., holidays) fluctuations of the population. Moreover, population size estimates based on NH4-N loads were lower compared to census data. Diurnal profiles of benzoylecgonine (BE) and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) were shown to be strongly correlated to NH4-N. Characteristic patterns, which reflect the prolonged nocturnal activity of people during the weekend, could be observed for BE, cocaine, and a major metabolite of MDMA (i.e., 4-hydroxy-3-methoxymethamphetamine). Additional 24 h composite samples were collected between February and September 2013. Per-capita loads (i.e., grams per day per 1000 inhabitants) were computed using census data and NH4-N measurements. Normalization with NH4-N did not modify the overall pattern, suggesting that the magnitude of fluctuations in the size of the population is negligible compared to those of illicit drug loads. Results show that fluctuations in the size of the population over longer periods of time or during major events can be monitored using NH4-N loads: either using raw NH4-N loads or population size estimates based on NH4-N loads, if information about site-specific NH4-N population equivalents is available.

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We critically discuss relaxation experiments in magnetic systems that can be characterized in terms of an energy barrier distribution, showing that proper normalization of the relaxation data is needed whenever curves corresponding to different temperatures are to be compared. We show how these normalization factors can be obtained from experimental data by using the Tln (t/t0) scaling method without making any assumptions about the nature of the energy barrier distribution. The validity of the procedure is tested using a ferrofluid of Fe3O4 particles.

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Regarding the standardization of psychological assessment instruments, that is, the construction of referential interpretations of a test, we can find different procedures performed both by Classical Test Theory (CTT) and the Theory of Item Response (IRT). Especially in this case (IRT), we can admit one test as a default, so to use its standardization and transfer the cut-off point to another instrument. Based on this information, the present study aimed to provide a cutoff score for the Baptista Depression Scale - Adult Version (EBADEP-A) through procedures of norms-transfer based on the Center for Epidemiologic Studies – Depression Scale (CES-D). The EBADEP-A presented good distribution and ability to discriminate depressive symptoms, and the sample, consisting of Brazilian College students, received a cutoff score of 32 points. It is emphasized that this is an exploratory and preliminary study, and it is suggested further analyzes to be performed with clinical samples for which results can be corroborated or confronted.

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We argue that impulsiveness is characterized by compromised timing functions such as premature motor timing, decreased tolerance to delays, poor temporal foresight and steeper temporal discounting. A model illustration for the association between impulsiveness and timing deficits is the impulsiveness disorder of attention-deficit hyperactivity disorder (ADHD). Children with ADHD have deficits in timing processes of several temporal domains and the neural substrates of these compromised timing functions are strikingly similar to the neuropathology of ADHD. We review our published and present novel functional magnetic resonance imaging data to demonstrate that ADHD children show dysfunctions in key timing regions of prefrontal, cingulate, striatal and cerebellar location during temporal processes of several time domains including time discrimination of milliseconds, motor timing to seconds and temporal discounting of longer time intervals. Given that impulsiveness, timing abnormalities and more specifically ADHD have been related to dopamine dysregulation, we tested for and demonstrated a normalization effect of all brain dysfunctions in ADHD children during time discrimination with the dopamine agonist and treatment of choice, methylphenidate. This review together with the new empirical findings demonstrates that neurocognitive dysfunctions in temporal processes are crucial to the impulsiveness disorder of ADHD and provides first evidence for normalization with a dopamine reuptake inhibitor.

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The current study aims to assess the applicability of direct or indirect normalization for the analysis of fractional anisotropy (FA) maps in the context of diffusion-weighted images (DWIs) contaminated by ghosting artifacts. We found that FA maps acquired by direct normalization showed generally higher anisotropy than indirect normalization, and the disparities were aggravated by the presence of ghosting artifacts in DWIs. The voxel-wise statistical comparisons demonstrated that indirect normalization reduced the influence of artifacts and enhanced the sensitivity of detecting anisotropy differences between groups. This suggested that images contaminated with ghosting artifacts can be sensibly analyzed using indirect normalization.

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We present a method to determine the magnitude of the uncorrelated background distribution obtained with the event mixing technique, through the simultaneous observation of the projectile elastic scattering in different detectors, which correspond to random coincidences. The procedure is tested with alpha-d angular correlation data from the (6)Li + (59)Co reaction at E(lab) = 29.6 MeV. We also show that the method can be applied using the product of singles events, when singles measurements are available. (C) 2009 Elsevier B.V. All rights reserved.

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In this work we present new coupled channel calculations with the Sao Paulo potential (SPP) as the bare interaction, and an imaginary potential with system and energy independent normalization that has been developed to take into account dissipative processes in heavy-ion reactions. This imaginary potential is based on high-energy nucleon interaction in nuclear medium. Our theoretical predictions for energies up to approximate to 100 MeV/nucleon agree very well with the experimental data for the p, n + nucleus, (16)O + (27)Al, (16)O + (60)Ni, (58)Ni + (124)Sn, and weakly bound projectile (7)Li + (120)Sn systems. (C) 2008 Elsevier B.V. All rights reserved.

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NMR quantum information processing studies rely on the reconstruction of the density matrix representing the so-called pseudo-pure states (PPS). An initially pure part of a PPS state undergoes unitary and non-unitary (relaxation) transformations during a computation process, causing a ""loss of purity"" until the equilibrium is reached. Besides, upon relaxation, the nuclear polarization varies in time, a fact which must be taken into account when comparing density matrices at different instants. Attempting to use time-fixed normalization procedures when relaxation is present, leads to various anomalies on matrices populations. On this paper we propose a method which takes into account the time-dependence of the normalization factor. From a generic form for the deviation density matrix an expression for the relaxing initial pure state is deduced. The method is exemplified with an experiment of relaxation of the concurrence of a pseudo-entangled state, which exhibits the phenomenon of sudden death, and the relaxation of the Wigner function of a pseudo-cat state.

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Important words, which usually exist in part of Title, Subject and Keywords, can briefly reflect the main topic of a document. In recent years, it is a common practice to exploit the semantic topic of documents and utilize important words to achieve document clustering, especially for short texts such as news articles. This paper proposes a novel method to extract important words from Subject and Keywords of articles, and then partition documents only with those important words. Considering the fact that frequencies of important words are usually low and the scale matrix dataset for important words is small, a normalization method is then proposed to normalize the scale dataset so that more accurate results can be achieved by sufficiently exploiting the limited information. The experiments validate the effectiveness of our method.