12 resultados para Response prediction
em University of Queensland eSpace - Australia
Resumo:
Statistical tests of Load-Unload Response Ratio (LURR) signals are carried in order to verify statistical robustness of the previous studies using the Lattice Solid Model (MORA et al., 2002b). In each case 24 groups of samples with the same macroscopic parameters (tidal perturbation amplitude A, period T and tectonic loading rate k) but different particle arrangements are employed. Results of uni-axial compression experiments show that before the normalized time of catastrophic failure, the ensemble average LURR value rises significantly, in agreement with the observations of high LURR prior to the large earthquakes. In shearing tests, two parameters are found to control the correlation between earthquake occurrence and tidal stress. One is, A/(kT) controlling the phase shift between the peak seismicity rate and the peak amplitude of the perturbation stress. With an increase of this parameter, the phase shift is found to decrease. Another parameter, AT/k, controls the height of the probability density function (Pdf) of modeled seismicity. As this parameter increases, the Pdf becomes sharper and narrower, indicating a strong triggering. Statistical studies of LURR signals in shearing tests also suggest that except in strong triggering cases, where LURR cannot be calculated due to poor data in unloading cycles, the larger events are more likely to occur in higher LURR periods than the smaller ones, supporting the LURR hypothesis.
Resumo:
Numerous studies in the last 60 years have investigated the relationship between land slope and soil erosion rates. However, relatively few of these have investigated slope gradient responses: ( a) for steep slopes, (b) for specific erosion processes, and ( c) as a function of soil properties. Simulated rainfall was applied in the laboratory on 16 soils and 16 overburdens at 100 mm/h to 3 replicates of unconsolidated flume plots 3 m long by 0.8 m wide and 0.15 m deep at slopes of 20, 5, 10, 15, and 30% slope in that order. Sediment delivery at each slope was measured to determine the relationship between slope steepness and erosion rate. Data from this study were evaluated alongside data and existing slope adjustment functions from more than 55 other studies from the literature. Data and the literature strongly support a logistic slope adjustment function of the form S = A + B/[1 + exp (C - D sin theta)] where S is the slope adjustment factor and A, B, C, and D are coefficients that depend on the dominant detachment and transport processes. Average coefficient values when interill-only processes are active are A - 1.50, B 6.51, C 0.94, and D 5.30 (r(2) = 0.99). When rill erosion is also potentially active, the average slope response is greater and coefficient values are A - 1.12, B 16.05, C 2.61, and D 8.32 (r(2) = 0.93). The interill-only function predicts increases in sediment delivery rates from 5 to 30% slope that are approximately double the predictions based on existing published interill functions. The rill + interill function is similar to a previously reported value. The above relationships represent a mean slope response for all soils, yet the response of individual soils varied substantially from a 2.5-fold to a 50-fold increase over the range of slopes studied. The magnitude of the slope response was found to be inversely related ( log - log linear) to the dispersed silt and clay content of the soil, and 3 slope adjustment equations are proposed that provide a better estimate of slope response when this soil property is known. Evaluation of the slope adjustment equations proposed in this paper using independent datasets showed that the new equations can improve soil erosion predictions.
Resumo:
Field observations on an unconfined coastal aquifer showed that a groundwater pulse, generated by it moderate (significant wave height, H-sig similar to 4.5 m) wave/storm event, induced significant oscillations in the salt-freshwater interface of the order of several metres in the horizontal direction. A dynamic sharp-interface model is developed to quantify the mechanism of these interface oscillations. The model uses the 50% seawater salinity contour as the location of the equivalent sharp-interface. The model was calibrated against the observed groundwater table fluctuations. It predicted reasonably well the interface oscillations with a slight over-prediction of the oscillation magnitude and a steepening of the interface. The neglect of mixing in the salt-freshwater mixing zone by the sharp-interface model is suggested as a possible contributor to the discrepancies between the model predictions and observations. In contrast with the significant wave effects, there was no observable response of the interface to diurnal or semidiurnal tides. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
Gray's Reinforcement Sensitivity Theory (RST) consists of the Behavioural Activation System (BAS) which is the basis of Impulsivity, and Behavioural Inhibition System (BIS) which is the basis of Anxiety. In this study, Impulsivity and Anxiety were used as distal predictors of attitudes to religion in the prediction of three religious dependent variables (Church attendance, Amount of prayer, and Importance of church). We hypothesised that Impulsivity would independently predict a Rewarding attitude to the Church and that Anxiety would independently predict an Anxious attitude to the church, and that these attitudes would be proximal predictors of our dependent variables. Moreover, we predicted that interactions between predictors would be proximal. Using structural equation modelling, data from 400 participants supported the hypotheses. We also tested Eysenck's personality scales of Extraversion and Neuroticism and found a key path of the structural equation model to be non-significant. (C) 2003 Elsevier Ltd. All rights reserved.
Resumo:
Background There is a substantial discrepancy between in vitro and in vivo experiments. The purpose of the present work was development of a theoretical framework to enable improved prediction of in vivo response from in vitro bioassay results. Results For dose-response curve reaches a plateau in vitro we demonstrated that the in vivo response has only one maximum. For biphasic patterns of biological response in vitro both the bimodal and biphasic in vivo responses might be observed. Conclusion As the main result of this work we have demonstrated that in vivo responses might be predicted from dose-effect curves measured in vitro.
Resumo:
The Appetitive Motivation Scale (Jackson & Smillie, 2004) is a new trait conceptualisation of Gray's (I 970 199 1) Behavioural Activation System. In this experiment we explore relationships that the Appetitive Motivation Scale and other measures of Gray's model have with Approach and Active Avoidance responses. Using a sample of 144 undergraduate students, both Appetitive Motivation and Sensitivity to Reward (from the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, SPSRQ; Torrubia, Avila, Molto, & Ceseras, 2001), were found to be significant predictors of Approach and Active Avoidance response latency. This confirms previous experimental validations of the SPSRQ (e.g., Avila, 2001) and provides the first experimental evidence for the validity of the Appetitive Motivation scale. Consistent with interactive views of Gray's model (e.g., Corr, 2001), high SPSRQ Sensitivity to Punishment diminished the relationship between Sensitivity to Reward and our BAS criteria. Measures of BIS did not however interact in this way with the appetitive motivation scale. A surprising result was the failure for any of Carver and White's (1994) BAS scales to correlate with RST criteria. Implications of these findings and potential future directions are discussed. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
Motivation: While processing of MHC class II antigens for presentation to helper T-cells is essential for normal immune response, it is also implicated in the pathogenesis of autoimmune disorders and hypersensitivity reactions. Sequence-based computational techniques for predicting HLA-DQ binding peptides have encountered limited success, with few prediction techniques developed using three-dimensional models. Methods: We describe a structure-based prediction model for modeling peptide-DQ3.2 beta complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2 beta receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2 beta binding and non-binding peptides obtained from biochemical and functional studies. Results: Our model predicts DQ3.2 beta binding peptides with high accuracy [area under the receiver operating characteristic (ROC) curve A(ROC) > 0.90], compared with experimental data. We investigated the binding patterns of DQ3.2 beta peptides and illustrate that several registers exist within a candidate binding peptide. Further analysis reveals that peptides with multiple registers occur predominantly for high-affinity binders.
Resumo:
Background. Exercise therapy improves functional capacity in CHF, but selection and individualization of training would be helped by a simple non-invasive marker of peak VO2. Peak VO2 in these pts is difficult to predict without direct measurement, and LV ejection fraction is a poor predictor. Myocardial tissue velocities are less load-dependent, and may be predictive of the exercise response in CHF pts. We sought to use tissue velocity as a predictor of peak VO2 in CHF pts. Methods. Resting 2D-echocardiography and tissue Doppler imaging were performed in 182 CHF pts (159 male, age 62±10 years) before and after metabolic exercise testing. The majority of these patients (129, 71%) had an ischemic cardiomyopathy, with resting EF of 35±13% and a peak VO2 of 13.5±4.7 ml/kg/min. Results. Neither resting EF (r=0.15) nor peak EF (r=0.18, both p=NS) were correlated with peak VO2. However, peak VO2 correlated with peak systolic velocity in septal (Vss, r=0.31) and lateral walls (Vsl, r=0.26, both p=0.01). In a general linear model (r2 = 0.25), peak VO2 was calculated from the following equation: 9.6 + 0.68*Vss - 0.09*age + 0.06*maximum HR. This model proved to be a superior predictor of peak VO2 (r=0.51, p=0.01) than the standard prediction equations of Wasserman (r= -0.12, p=0.01). Conclusions. Resting tissue Doppler, age and maximum heart rate may be used to predict functional capacity in CHF patients. This may be of use in selecting and following the response to therapy, including for exercise training.