949 resultados para INTERVAL METHOD


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Background: Results from clinical trials are usually summarized in the form of sampling distributions. When full information (mean, SEM) about these distributions is given, performing meta-analysis is straightforward. However, when some of the sampling distributions only have mean values, a challenging issue is to decide how to use such distributions in meta-analysis. Currently, the most common approaches are either ignoring such trials or for each trial with a missing SEM, finding a similar trial and taking its SEM value as the missing SEM. Both approaches have drawbacks. As an alternative, this paper develops and tests two new methods, the first being the prognostic method and the second being the interval method, to estimate any missing SEMs from a set of sampling distributions with full information. A merging method is also proposed to handle clinical trials with partial information to simulate meta-analysis.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The present study compared the expression of cytokeratins CK6, CK16 and CK19 and pan-cytokeratin (PAN) in oral mucosa cells between smokers and nonsmokers in order to determine the stage of cell differentiation and to consequently infer proliferative activity and expressions indicative of a potential for malignant differentiation. Thirty smokers and 30 non-smokers seen at the clinics of FOSJC-UNESP were screened. Smears were obtained from the left lateral border of the tongue with a cytobrush and slides were processed for immunohistochemistry using the antibodies reported Conventional microscopy was used for qualitative analysis. The results were analyzed statistically by the Z test, Fisher's exact test and comparison of two proportions (plus-4 confidence interval method). The expression of CK6 (p=0.002), CK16 (p=0.003), CK19 (p=0.0001) and PAN (p=0.008) was higher in oral mucosa smears from smokers compared to non- smokers. ln conclusion, increased epithelial proliferation is observed in the oral mucosa of smokers as demonstrated by the increased expression of CK6 and CKJ6, and these cells present alterations in epithelial maturation

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Exact results on particle densities as well as correlators in two models of immobile particles, containing either a single species or else two distinct species, are derived. The models evolve following a descent dynamics through pair annihilation where each particle interacts once at most throughout its entire history. The resulting large number of stationary states leads to a non-vanishing configurational entropy. Our results are established for arbitrary initial conditions and are derived via a generating function method. The single-species model is the dual of the 1D zero-temperature kinetic Ising model with Kimball-Deker-Haake dynamics. In this way, both in finite and semi-infinite chains and also the Bethe lattice can be analysed. The relationship with the random sequential adsorption of dimers and weakly tapped granular materials is discussed.

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Using second-order autocorrelation conception, a novel method and instrument for accurately measuring interval between two linearly polarized ultrashort pulses with real time were presented. The experiment demonstrated that the measuring method and instrument were simple and accurate (the measurement error <5 fs). During measuring, there was no moving element resulting in dynamic measurement error.

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Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models.

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The increasing prevalence of obesity in society has been associated with a number of atherogenic risk factors such as insulin resistance. Aerobic training is often recommended as a strategy to induce weight loss, with a greater impact of high-intensity levels on cardiovascular function and insulin sensitivity, and a greater impact of moderate-intensity levels on fat oxidation. Anaerobic high-intensity (supramaximal) interval training has been advocated to improve cardiovascular function, insulin sensitivity and fat oxidation. However, obese individuals tend to have a lower tolerance of high-intensity exercise due to discomfort. Furthermore, some obese individuals may compensate for the increased energy expenditure by eating more and/or becoming less active. Recently, both moderate- and high-intensity aerobic interval training have been advocated as alternative approaches. However, it is still uncertain as to which approach is more effective in terms of increasing fat oxidation given the issues with levels of fitness and motivation, and compensatory behaviours. Accordingly, the objectives of this thesis were to compare the influence of moderate- and high-intensity interval training on fat oxidation and eating behaviour in overweight/obese men. Two exercise interventions were undertaken by 10-12 overweight/obese men to compare their responses to study variables, including fat oxidation and eating behaviour during moderate- and high-intensity interval training (MIIT and HIIT). The acute training intervention was a methodological study designed to examine the validity of using exercise intensity from the graded exercise test (GXT) - which measured the intensity that elicits maximal fat oxidation (FATmax) - to prescribe interval training during 30-min MIIT. The 30-min MIIT session involved 5-min repetitions of workloads 20% below and 20% above the FATmax. The acute intervention was extended to involve HIIT in a cross-over design to compare the influence of MIIT and HIIT on eating behaviour using subjective appetite sensation and food preference through the liking and wanting test. The HIIT consisted of 15-sec interval training at 85 %VO2peak interspersed by 15-sec unloaded recovery, with a total mechanical work equal to MIIT. The medium term training intervention was a cross-over 4-week (12 sessions) MIIT and HIIT exercise training with a 6-week detraining washout period. The MIIT sessions consisted of 5-min cycling stages at ±20% of mechanical work at 45 %VO2peak, and the HIIT sessions consisted of repetitive 30-sec work at 90 %VO2peak and 30-sec interval rests, during identical exercise sessions of between 30 and 45 mins. Assessments included a constant-load test (45 %VO2peak for 45 mins) followed by 60-min recovery at baseline and the end of 4-week training, to determine fat oxidation rate. Participants’ responses to exercise were measured using blood lactate (BLa), heart rate (HR) and rating of perceived exertion (RPE) and were measured during the constant-load test and in the first intervention training session of every week during training. Eating behaviour responses were assessed by measuring subjective appetite sensations, liking and wanting and ad libitum energy intake. Results of the acute intervention showed that FATmax is a valid method to estimate VO2 and BLa, but is not valid to estimate HR and RPE in the MIIT session. While the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax (0.16 ±0.09 and 0.14 ±0.08 g/min, respectively), fat oxidation was significantly higher at minute 25 of MIIT (P≤0.01). In addition, there was no significant difference between MIIT and HIIT in the rate of appetite sensations after exercise, but there was a tendency towards a lower rate of hunger after HIIT. Different intensities of interval exercise also did not affect explicit liking or implicit wanting. Results of the medium-term intervention indicated that current interval training levels did not affect body composition, fasting insulin and fasting glucose. Maximal aerobic capacity significantly increased (P≤0.01) (2.8 and 7.0% after MIIT and HIIT respectively) during GXT, and fat oxidation significantly increased (P≤0.01) (96 and 43% after MIIT and HIIT respectively) during the acute constant-load exercise test. RPE significantly decreased after HIIT greater than MIIT (P≤0.05), and the decrease in BLa was greater during the constant-load test after HIIT than MIIT, but this difference did not reach statistical significance (P=0.09). In addition, following constant-load exercise, exercise-induced hunger and desire to eat decreased after HIIT greater than MIIT but were not significant (p value for desire to eat was 0.07). Exercise-induced liking of high-fat sweet (HFSW) and high-fat non-sweet (HFNS) foods increased after MIIT and decreased after HIIT (p value for HFNS was 0.09). The intervention explained 12.4% of the change in fat intake (p = 0.07). This research is significant in that it confirmed two points in the acute study. While the rate of fat oxidation increased during MIIT, the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax. In addition, manipulating the intensity of acute interval exercise did not affect appetite sensations and liking and wanting. In the medium-term intervention, constant-load exercise-induced fat oxidation significantly increased after interval training, independent of exercise intensity. In addition, desire to eat, explicit liking for HFNS and fat intake collectively confirmed that MIIT is accompanied by a greater compensation of eating behaviour than HIIT. Findings from this research will assist in developing exercise strategies to provide obese men with various training options. In addition, the finding that overweight/obese men expressed a lower RPE and decreased BLa after HIIT compared with MIIT is contrary to the view that obese individuals may not tolerate high-intensity interval training. Therefore, high-intensity interval training can be advocated among the obese adult male population. Future studies may extend this work by using a longer-term intervention.

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Purpose To develop a signal processing paradigm for extracting ERG responses to temporal sinusoidal modulation with contrasts ranging from below perceptual threshold to suprathreshold contrasts. To estimate the magnitude of intrinsic noise in ERG signals at different stimulus contrasts. Methods Photopic test stimuli were generated using a 4-primary Maxwellian view optical system. The 4-primary lights were sinusoidally temporally modulated in-phase (36 Hz; 2.5 - 50% Michelson). The stimuli were presented in 1 s epochs separated by a 1 ms blank interval and repeated 160 times (160.16 s duration) during the recording of the continuous flicker ERG from the right eye using DTL fiber electrodes. After artefact rejection, the ERG signal was extracted using Fourier methods in each of the 1 s epochs where a stimulus was presented. The signal processing allows for computation of the intrinsic noise distribution in addition to the signal to noise (SNR) ratio. Results We provide the initial report that the ERG intrinsic noise distribution is independent of stimulus contrast whereas SNR decreases linearly with decreasing contrast until the noise limit at ~2.5%. The 1ms blank intervals between epochs de-correlated the ERG signal at the line frequency (50 Hz) and thus increased the SNR of the averaged response. We confirm that response amplitude increases linearly with stimulus contrast. The phase response shows a shallow positive relationship with stimulus contrast. Conclusions This new technique will enable recording of intrinsic noise in ERG signals above and below perceptual visual threshold and is suitable for measurement of continuous rod and cone ERGs across a range of temporal frequencies, and post-receptoral processing in the primary retinogeniculate pathways at low stimulus contrasts. The intrinsic noise distribution may have application as a biomarker for detecting changes in disease progression or treatment efficacy.

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Background: Smoking and physical inactivity are major risk factors for heart disease. Linking strategies that promote improvements in fitness and assist quitting smoking has potential to address both these risk factors simultaneously. The objective of this study is to compare the effects of two exercise interventions (high intensity interval training (HIIT) and lifestyle physical activity) on smoking cessation in female smokers. Method/design: This study will use a randomised controlled trial design. Participants: Women aged 18–55 years who smoke ≥ 5 cigarettes/day, and want to quit smoking. Intervention: all participants will receive usual care for quitting smoking. Group 1 - will complete two gym-based supervised HIIT sessions/week and one home-based HIIT session/week. At each training session participants will be asked to complete four 4-min (4 × 4 min) intervals at approximately 90 % of maximum heart rate interspersed with 3- min recovery periods. Group 2 - participants will receive a resource pack and pedometer, and will be asked to use the 10,000 steps log book to record steps and other physical activities. The aim will be to increase daily steps to 10,000 steps/day. Analysis will be intention to treat and measures will include smoking cessation, withdrawal and cravings, fitness, physical activity, and well-being. Discussion: The study builds on previous research suggesting that exercise intensity may influence the efficacy of exercise as a smoking cessation intervention. The hypothesis is that HIIT will improve fitness and assist women to quit smoking.

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Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.

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In voiced speech analysis epochal information is useful in accurate estimation of pitch periods and the frequency response of the vocal tract system. Ideally, linear prediction (LP) residual should give impulses at epochs. However, there are often ambiguities in the direct use of LP residual since samples of either polarity occur around epochs. Further, since the digital inverse filter does not compensate the phase response of the vocal tract system exactly, there is an uncertainty in the estimated epoch position. In this paper we present an interpretation of LP residual by considering the effect of the following factors: 1) the shape of glottal pulses, 2) inaccurate estimation of formants and bandwidths, 3) phase angles of formants at the instants of excitation, and 4) zeros in the vocal tract system. A method for the unambiguous identification of epochs from LP residual is then presented. The accuracy of the method is tested by comparing the results with the epochs obtained from the estimated glottal pulse shapes for several vowel segments. The method is used to identify the closed glottis interval for the estimation of the true frequency response of the vocal tract system.

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Routing of floods is essential to control the flood flow at the flood control station such that it is within the specified safe limit. In this paper, the applicability of the extended Muskingum method is examined for routing of floods for a case study of Hirakud reservoir, Mahanadi river basin, India. The inflows to the flood control station are of two types-one controllable which comprises of reservoir releases for power and spill and the other is uncontrollable which comprises of inflow from lower tributaries and intermediate catchment between the reservoir and the flood control station. Muskingum model is improved to incorporate multiple sources of inflows and single outflow to route the flood in the reach. Instead of time lag and prismoidal flow parameters, suitable coefficients for various types of inflows were derived using Linear Programming. Presently, the decisions about operation of gates of Hirakud dam are being taken once in 12 h during floods. However, four time intervals of 24, 18, 12 and 6 h are examined to test the sensitivity of the routing time interval on the computed flood flow at the flood control station. It is observed that mean relative error decreases with decrease in routing interval both for calibration and testing phase. It is concluded that the extended Muskingum method can be explored for similar reservoir configurations such as Hirakud reservoir with suitable modifications. (C) 2010 International Association of Hydro-environment Engineering and Research. Asia Pacific Division. Published by Elsevier By. All rights reserved.

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Wavelet Variable Interval Time Average (WVITA) is introduced as a method incorporating burst event detection in wall turbulence. Wavelet transform is performed to unfold the longitudinal fluctuating velocity time series measured in the near wall region of a turbulent boundary layer using hot-film anemometer. This unfolding is both in time and in space simultaneously. The splitted kinetic of the longitudinal fluctuating velocity time series among different scales is obtained by integrating the square of wavelet coefficient modulus over temporal space. The time scale that related to burst events in wall turbulence passing through the fixed probe is ascertained by maximum criterion of the kinetic energy evolution across scales. Wavelet transformed localized variance of the fluctuating velocity time series at the maximum kinetic scale is put forward instead of localized short time average variance in Variable Interval Time Average (VITA) scheme. The burst event detection result shows that WVITA scheme can avoid erroneous judgement and solve the grouping problem more effectively which is caused by VITA scheme itself and can not be avoided by adjusting the threshold level or changing the short time average interval.