29 resultados para Antepartum non-stress test

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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We present a new method for constructing exact distribution-free tests (and confidence intervals) for variables that can generate more than two possible outcomes.This method separates the search for an exact test from the goal to create a non-randomized test. Randomization is used to extend any exact test relating to meansof variables with finitely many outcomes to variables with outcomes belonging to agiven bounded set. Tests in terms of variance and covariance are reduced to testsrelating to means. Randomness is then eliminated in a separate step.This method is used to create confidence intervals for the difference between twomeans (or variances) and tests of stochastic inequality and correlation.

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Evaluar una arquitectura de la información en un sitio web ya desplegado no resulta una tarea sencilla. La mayoría de las técnicas se centran en examinar la usabilidad del sistema que, aunque afecta a la arquitectura de la información, no es el único factor que influye en ella. La principal técnica que se utiliza es el test de estrés de navegación. Se muestra un aporte metodológico para hacer dicha técnica más informativa, llevándola más allá de la simple anotación en papel por parte del usuario de respuestas a las preguntas de navegación planteadas. Se propone la combinación de ésta con otras técnicas de evaluación de la usabilidad: la técnica de pensar en voz alta o thinking aloud y un cuestionario de usabilidad. Se ha utilizado un sistema de seguimiento de la mirada o eye tracking para complementar la información obtenida mediante las técnicas aplicadas. El enfoque metodológico planteado se ha puesto a prueba analizando una serie de sitios web de bibliotecas de universidades públicas españolas. Se muestra en los resultados la validez del enfoque empleado, así como el valor que dicho enfoque y el uso del eye tracking aportan al análisis de la arquitectura de la información respecto al test de estrés de navegación tradicional.

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Human Immunodeficiency Virus continues to be a pandemic. Spain is one of the European countries with the highest incidence of HIV. Within Catalonia, Spain many projects have been implemented with the intention of improving HIV knowledge and lowering the incidence. HIV knowledge is also known to have a positive effect on lowering stigma and discrimination of the people living with HIV. However, few studies study the distribution of HIV knowledge and its association to HIV status, age, sex, geographical zone of origin and level of education within the same study. Objectives: To identify if HIV knowledge is associated with HIV status, age, sex, geographical zone of origin and level of education. Method: Quantitative, cross-sectional, centre-based study comprising of people receiving an HIV test in Catalonia, Spain. Data will be collected from the 11 HIV Non-Governmental Organisations in Catalonia, Spain. The Brief HIV Knowledge Scale will be used to assess HIV knowledge; information from the HIV test session will be used to assess HIV status, age, sex, geographic zone of origin and level of education. The association between HIV knowledge and the afore mentioned variables will then be calculated.

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This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.

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This note describes ParallelKnoppix, a bootable CD that allows econometricians with average knowledge of computers to create and begin using a high performance computing cluster for parallel computing in very little time. The computers used may be heterogeneous machines, and clusters of up to 200 nodes are supported. When the cluster is shut down, all machines are in their original state, so their temporary use in the cluster does not interfere with their normal uses. An example shows how a Monte Carlo study of a bootstrap test procedure may be done in parallel. Using a cluster of 20 nodes, the example runs approximately 20 times faster than it does on a single computer.

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Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

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• Quercus ilex L., the dominant species in Mediterranean forests and one with a great capacity for resprouting after disturbances, is threatened by the expected increase in fire frequency and drought associated with climate change. • The aim of this study was to determine the contribution of photosynthesis limitants, especially mesophyll conductance (gmes ) during this species’ resprouting and under summer drought. • Resprouts showed 5.3-fold increased gmes and 3.8-fold increased stomatal conductance (gs) atmidday with respect to leaves of undisturbed individuals. With increased drought, structural changes (decreased density and increased thickness) in resprouts contributed to the observed higher photosynthesis and increased gmes. However, gmes only partially depended on leaf structure, and was also under physiological control. Resprouts also showed lower non-stomatal limitations (around 50% higher carboxylation velocity (Vc,max) and capacity for ribulose-1,5-bisphosphate regeneration (Jmax)). A significant contribution of gmes to leaf carbon isotope discrimination values was observed. • gmes exhibits a dominant role in photosynthesis limitation in Q. ilex and is regulated by factors other than morphology. During resprouting after disturbances, greater capacity to withstand drought, as evidenced by higher gmes , gs and lower non-stomatal limitants, enables increased photosynthesis and rapid growth.

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Dietary fatty acid supply can affect stress response in fish during early development. Although knowledge on the mechanisms involved in fatty acid regulation of stress tolerance is scarce, it has often been hypothesised that eicosanoid profiles can influence cortisol production. Genomic cortisol actions are mediated by cytosolic receptors which may respond to cellular fatty acid signalling. An experiment was designed to test the effects of feeding gilthead sea-bream larvae with four microdiets, containing graded arachidonic acid (ARA) levels (0·4, 0·8, 1·5 and 3·0 %), on the expression of genes involved in stress response (steroidogenic acute regulatory protein, glucocorticoid receptor and phosphoenolpyruvate carboxykinase), lipid and, particularly, eicosanoid metabolism (hormone-sensitive lipase, PPARα, phospholipase A2, cyclo-oxygenase-2 and 5-lipoxygenase), as determined by real-time quantitative PCR. Fish fatty acid phenotypes reflected dietary fatty acid profiles. Growth performance, survival after acute stress and similar whole-body basal cortisol levels suggested that sea-bream larvae could tolerate a wide range of dietary ARA levels. Transcription of all genes analysed was significantly reduced at dietary ARA levels above 0·4 %. Nonetheless, despite practical suppression of phospholipase A2 transcription, higher leukotriene B4 levels were detected in larvae fed 3·0 % ARA, whereas a similar trend was observed regarding PGE2 production. The present study demonstrates that adaptation to a wide range of dietary ARA levels in gilthead sea-bream larvae involves the modulation of the expression of genes related to eicosanoid synthesis, lipid metabolism and stress response. The roles of ARA, other polyunsaturates and eicosanoids as signals in this process are discussed.

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Background: Non-invasive monitoring of respiratory muscle function is an area of increasing research interest, resulting in the appearance of new monitoring devices, one of these being piezoelectric contact sensors. The present study was designed to test whether the use of piezoelectric contact (non-invasive) sensors could be useful in respiratory monitoring, in particular in measuring the timing of diaphragmatic contraction.Methods: Experiments were performed in an animal model: three pentobarbital anesthetized mongrel dogs. The motion of the thoracic cage was acquired by means of a piezoelectric contact sensor placed on the costal wall. This signal is compared with direct measurements of the diaphragmatic muscle length, made by sonomicrometry. Furthermore, to assess the diaphragmatic function other respiratory signals were acquired: respiratory airflow and transdiaphragmatic pressure. Diaphragm contraction time was estimated with these four signals. Using diaphragm length signal as reference, contraction times estimated with the other three signals were compared with the contraction time estimated with diaphragm length signal.Results: The contraction time estimated with the TM signal tends to give a reading 0.06 seconds lower than the measure made with the DL signal (-0.21 and 0.00 for FL and DP signals, respectively), with a standard deviation of 0.05 seconds (0.08 and 0.06 for FL and DP signals, respectively). Correlation coefficients indicated a close link between time contraction estimated with TM signal and contraction time estimated with DL signal (a Pearson correlation coefficient of 0.98, a reliability coefficient of 0.95, a slope of 1.01 and a Spearman's rank-order coefficient of 0.98). In general, correlation coefficients and mean and standard deviation of the difference were better in the inspiratory load respiratory test than in spontaneous ventilation tests.Conclusion: The technique presented in this work provides a non-invasive method to assess the timing of diaphragmatic contraction in canines, using a piezoelectric contact sensor placed on the costal wall.

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Under the Dynamic Model of Multilingualism multilinguals are especially vulnerable to language attrition. It was the aim of the present study to verify if this was the case and to observe whether the different linguistic skills (receptive vs. descriptive) and the different linguistic levels (syntactic, lexical, morphological, etc.) would be affected equally.Data were gathered longitudinally by means of a language test for the subject’s reading, writing, listening and speaking skills as well as her knowledge of grammar and vocabulary. Although the overall accuracy remained intact and no proof for attrition in the receptive skills was found, the productive skills - mainly fluency - were shown to have suffered from language attrition. This was demonstrated by an increase in the number of pauses, hesitations, repetitions and self-corrections among others and decrease in the percentage of error-free clauses and decrease in the clause length, in oral and written fluency respectively.

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This paper argues that low-stakes test scores, available in surveys, may be partially determined by test-taking motivation, which is associated with personality traits but not with cognitive ability. Therefore, such test score distributions may not be informative regarding cognitive ability distributions. Moreover, correlations, found in survey data, between high test scores and economic success may be partially caused by favorable personality traits. To demonstrate these points, I use the coding speed test that was administered without incentives to National Longitudinal Survey of Youth 1979 (NLSY) participants. I suggest that due to its simplicity its scores may especially depend on individuals' test-taking motivation. I show that controlling for conventional measures of cognitive skills, the coding speed scores are correlated with future earnings of male NLSY participants. Moreover, the coding speed scores of highly motivated, though less educated, population (potential enlists to the armed forces) are higher than NLSY participants' scores. I then use controlled experiments to show that when no performance-based incentives are provided, participants' characteristics, but not their cognitive skills, affect effort invested in the coding speed test. Thus, participants with the same ability (measured by their scores on an incentivized test) have significantly different scores on tests without performance- based incentives.

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Hierarchical clustering is a popular method for finding structure in multivariate data,resulting in a binary tree constructed on the particular objects of the study, usually samplingunits. The user faces the decision where to cut the binary tree in order to determine the numberof clusters to interpret and there are various ad hoc rules for arriving at a decision. A simplepermutation test is presented that diagnoses whether non-random levels of clustering are presentin the set of objects and, if so, indicates the specific level at which the tree can be cut. The test isvalidated against random matrices to verify the type I error probability and a power study isperformed on data sets with known clusteredness to study the type II error.

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This paper argues that low-stakes test scores, available in surveys, may be partially determinedby test-taking motivation, which is associated with personality traits but not with cognitiveability. Therefore, such test score distributions may not be informative regarding cognitiveability distributions. Moreover, correlations, found in survey data, between high test scoresand economic success may be partially caused by favorable personality traits. To demonstratethese points, I use the coding speed test that was administered without incentives to NationalLongitudinal Survey of Youth 1979 (NLSY) participants. I suggest that due to its simplicityits scores may especially depend on individuals' test-taking motivation. I show that controllingfor conventional measures of cognitive skills, the coding speed scores are correlated with futureearnings of male NLSY participants. Moreover, the coding speed scores of highly motivated,though less educated, population (potential enlists to the armed forces) are higher than NLSYparticipants' scores. I then use controlled experiments to show that when no performance-basedincentives are provided, participants' characteristics, but not their cognitive skills, affect effortinvested in the coding speed test. Thus, participants with the same ability (measured by theirscores on an incentivized test) have significantly different scores on tests without performance-based incentives.

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A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.

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Although it is commonly accepted that most macroeconomic variables are nonstationary, it is often difficult to identify the source of the non-stationarity. In particular, it is well-known that integrated and short memory models containing trending components that may display sudden changes in their parameters share some statistical properties that make their identification a hard task. The goal of this paper is to extend the classical testing framework for I(1) versus I(0)+ breaks by considering a a more general class of models under the null hypothesis: non-stationary fractionally integrated (FI) processes. A similar identification problem holds in this broader setting which is shown to be a relevant issue from both a statistical and an economic perspective. The proposed test is developed in the time domain and is very simple to compute. The asymptotic properties of the new technique are derived and it is shown by simulation that it is very well-behaved in finite samples. To illustrate the usefulness of the proposed technique, an application using inflation data is also provided.