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Predicted Response (predicted + response)
Selected AbstractsPredictive instantaneous optimal control of elastic structures during earthquakesEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 14 2003Kevin K. F. Wong Abstract A predictive instantaneous optimal control (PIOC) algorithm is proposed for controlling the seismic responses of elastic structures. This algorithm compensates for the time delay that happens in practical control applications by predicting the structural response over a period that equals the time delay, and by substituting the predicted response in the instantaneous optimal control (IOC) algorithm. The unique feature of this proposed PIOC algorithm is that it is simple and at the same time compensates for the time delay very effectively. Numerical examples of single degree of freedom structures are presented to compare the performance of PIOC and IOC systems for various time delay magnitudes. Results show that a time delay always causes degradation of control efficiency, but PIOC can greatly reduce this degradation compared to IOC. The effects of the structure's natural periods and the choice of control gains on the degradation induced by the time delay are also analyzed. Results show that shorter natural periods and larger control gains are both more sensitive and more serious to the degradation of control efficiency. Finally, a practical application of PIOC is performed on a six-story moment-resisting steel frame. It is demonstrated that PIOC contributes significantly to maintain stability in multiple degree of freedom structures, and at the same time PIOC has a satisfactory control performance. Copyright © 2003 John Wiley & Sons, Ltd. [source] Whole ecosystem metabolic pulses following precipitation eventsFUNCTIONAL ECOLOGY, Issue 5 2008G. D. Jenerette Summary 1Ecosystem respiration varies substantially at short temporal intervals and identifying the role of coupled temperature- and precipitation-induced changes has been an ongoing challenge. To address this challenge we applied a metabolic ecological theory to identify pulses in ecosystem respiration following rain events. Using this metabolic framework, precipitation-induced pulses were described as a reduction in metabolic activation energy after individual precipitation events. 2We used this approach to estimate the responses of 237 individual events recorded over 2 years at four eddy-covariance sites in southern AZ, USA. The sites varied in both community type (woody and grass dominated) and landscape position (riparian and upland). We used a nonlinear inversion procedure to identify both the parameters for the pre-event temperature sensitivity and the predicted response of the temperature sensitivity to precipitation. By examining multiple events we evaluated the consistency of pulses between sites and discriminated between hypotheses regarding landscape position, event distributions, and pre-event ecosystem metabolism rates. 3Over the 5-day post-event period across all sites the mean precipitation effect was attributed to 6·1 g CO2 m,2 of carbon release, which represented a 21% increase in respiration over the pre-event steady state trajectory of carbon loss. Differences in vegetation community were associated with differences in the integrated magnitude of pulse responses, while differences in topographic position were associated with the initial peak pulse rate. In conjunction with the differences between sites, the individual total pulse response was positively related to the drying time interval and metabolic rates prior to the event. The quantitative theory presented provides an approach for understanding ecosystem pulse dynamics and helps characterized the dependence of ecosystem metabolism on both temperature and precipitation. [source] Modelling the behaviour of an embankment on soft clay with different constitutive modelsINTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 10 2006M. Karstunen Abstract The paper investigates the effect of constitutive models on the predicted response of a simplified benchmark problem, an embankment on soft soil. The soft soil is assumed to have the properties of POKO clay from Finland and five different constitutive models are used to model the deposit. Two of the models are isotropic models, i.e. the Modified Cam Clay model and the Soft-Soil model. The other models are recently proposed constitutive models that account for plastic anisotropy. The S-CLAY1 and S-CLAY1S models are embedded in a standard elasto-plastic framework and account for anisotropy via a rotational hardening law. In addition, the S-CLAY1S model accounts for bonding and destructuration. In contrast, the Multilaminate Model for Clay (MMC) accounts for plastic anisotropy by utilizing so-called multilaminate framework. The results of numerical simulations show that accounting for anisotropy results in notable differences in the predicted settlements and horizontal movements compared to the predictions using the isotropic models. There are also significant differences in the K0 predictions by the different constitutive models and this has a significant impact on the results. Copyright © 2006 John Wiley & Sons, Ltd. [source] Application of SIC (simple interval calculation) for object status classification and outlier detection,comparison with regression approachJOURNAL OF CHEMOMETRICS, Issue 9 2004Oxana Ye. Abstract We introduce a novel approach termed simple interval calculation (SIC) for classification of object status in linear multivariate calibration (MVC) and other data analytical contexts. SIC is a method that directly constructs an interval estimator for the predicted response. SIC is based on the single assumption that all errors involved in MVC are limited. We present the theory of the SIC method and explain its realization by linear programming techniques. The primary SIC consequence is a radically new object classification that can be interpreted using a two-dimensional object status plot (OSP), ,SIC residual vs SIC leverage'. These two new measures of prediction quality are introduced in the traditional chemometric MVC context. Simple straight demarcations divide the OSP into areas which quantitatively discriminate all objects involved in modeling and prediction into four different types: boundary samples, which are the significant objects (for generating the entire data structure) within the training subset; insiders, which are samples that comply with the model; outsiders, which are samples that have large prediction errors; and finally outliers, which are those samples that cannot be predicted at all with respect to a given model. We also present detailed comparisons of the new SIC approach with traditional chemometric methods applied for MVC, classification and outlier detection. These comparisons employ four real-world data sets, selected for their particular complexities, which serve as showcases of SIC application on intricate training and test set data structures. Copyright © 2005 John Wiley & Sons, Ltd. [source] Response to hepatitis A vaccine in HIV-positive patients,JOURNAL OF VIRAL HEPATITIS, Issue 2 2006S. Weissman Summary., The USPHS/IDSA guidelines for Prevention of Opportunistic Infections in Persons with human immunodeficiency virus (HIV) recommends that all susceptible HIV+ patients at increased risk for hepatitis A virus (HAV) or with chronic liver disease, be vaccinated against HAV. Immune response to HAV vaccine has not been well studied in HIV+ patients. In particular, there is little information in the literature regarding the effect and relationship of the CD4 count and the immune response in HIV patients. A retrospective analysis of HIV+ patients who received HAV vaccine was performed, and the antibody response to HAV (anti-HAV) measured. Univariate and multivariate analyses were performed to determine predictors of response to vaccine administration. Of the 503 patients evaluated, 138 patients completed their HAV vaccination series and 48% of them had postvaccine anti-HAV positive results (responders). There was no difference in age, race, antiretroviral therapy use, or hepatitis C virus exposure between responders and nonresponders. In univariate analysis, responders were more likely to be female (40.3%vs 21.1%, P = 0.01), have a higher CD4 count at vaccine (508.6 cells/mm3vs 344.3 cells/mm3, P = 0.001) and marginally lower viral load at vaccine (2.65 log copies vs 2.94 log copies, P = 0.07). Multivariate analysis showed that female gender and higher CD4 count at vaccine were independent predictors of response to vaccine. Forty-eight per cent of our HIV+ patients responded to HAV vaccine administration. This is much lower than reported rates of 100% in HIV-negative patients. Female gender and CD4 count at vaccine, but not CD4 nadir, predicted response to vaccine. [source] Logic of experiments in ecology: is pseudoreplication a pseudoissue?OIKOS, Issue 1 2001Lauri Oksanen Hurlbert divides experimental ecologist into ,those who do not see any need for dispersion (of replicated treatments and controls), and those who do recognize its importance and take whatever measures are necessary to achieve a good dose of it'. Experimental ecologists could also be divided into those who do not see any problems with sacrificing spatial and temporal scales in order to obtain replication, and those who understand that appropriate scale must always have priority over replication. If an experiment is conducted in a spatial or temporal scale, where the predictions of contesting hypotheses are convergent or ambiguous, no amount of technical impeccability can make the work instructive. Conversely, replication can always be obtained afterwards, by conducting more experiments with basically similar design in different areas and by using meta-analysis. This approach even reduces the sampling bias obtained if resources are allocated to a small number of well-replicated experiments. For a strict advocate of the hypothetico-deductive method, replication is unnecessary even as a matter of principle, unless the predicted response is so weak that random background noise is a plausible excuse for a discrepancy between predictions and results. By definition, a prediction is an ,all-statement', referring to all systems within a well-defined category. What applies to all must apply to any. Hence, choosing two systems and assigning them randomly to a treatment and a control is normally an adequate design for a deductive experiment. The strength of such experiments depends on the firmness of the predictions and their a priori probability of corroboration. Replication is but one of many ways of reducing this probability. Whether the experiment is replicated or not, inferential statistics should always be used, to enable the reader to judge how well the apparent patterns in samples reflect real patterns in statistical populations. The concept ,pseudoreplication' amounts to entirely unwarranted stigmatization of a reasonable way to test predictions referring to large-scale systems. [source] Water availability controls microbial temperature responses in frozen soil CO2 productionGLOBAL CHANGE BIOLOGY, Issue 11 2009MATS G. ÖQUIST Abstract Soil processes in high-latitude regions during winter are important contributors to global carbon circulation, but our understanding of the mechanisms controlling these processes is poor and observed temperature response coefficients of CO2 production in frozen soils deviate markedly from thermodynamically predicted responses (sometimes by several orders of magnitude). We investigated the temperature response of CO2 production in 23 unfrozen and frozen surface soil samples from various types of boreal forests and peatland ecosystems and also measured changes in water content in them after freezing. We demonstrate that deviations in temperature responses at subzero temperatures primarily emanates from water deficiency caused by freezing of the soil water, and that the amount of unfrozen water is mainly determined by the quality of the soil organic matter, which is linked to the vegetation cover. Factoring out the contribution of water limitation to the CO2 temperature responses yields response coefficients that agree well with expectations based on thermodynamic theory concerning biochemical temperature responses. This partitioning between a pure temperature response and the effect of water availability on the response of soil CO2 production at low temperatures is crucial for a thorough understanding of low-temperature soil processes and for accurate predictions of C-balances in northern terrestrial ecosystems. [source] Temporal variability of phytoplankton in a salt wedge estuary, the Swan,Canning Estuary, Western AustraliaHYDROLOGICAL PROCESSES, Issue 13 2001Peter A. Thompson Abstract The temporal cycles of variation in salinity, temperature and river flow in the Swan,Canning Estuary plus rainfall in the vicinity are examined. A ,normal' pattern is defined for rainfall and river flow based on long-term median monthly values from available historical data. Long-term monthly median rainfall and median monthly river flow were highly correlated. Deviations from the ,normal' patterns of rainfall and river flow are documented. Three years of detailed data on the temporal distribution of the algal biomass and phytoplankton community composition from the Swan,Canning Estuary are presented and discussed. Significant interannual variability in the phytoplankton biomass was observed with 1996 having a significantly lower median chlorophyll a concentration than 1995 or 1997. Different years also had pronounced differences in the timing, persistence and occurrence of algal blooms. Links with, and between, rainfall, river flow, nutrient concentrations and phytoplankton biomass are made by careful examination of the temporal patterns. Deviations from the proposed ,normal' temporal pattern of physical and chemical environmental factors relevant to the growth of phytoplankton biomass are assessed. Deviations from ,normal' rainfall and river flow, depending upon their timing and intensity, appear to be associated with occurrence of algal blooms. For example, the lack of a dinoflagellate bloom in December 1996 or January 1997 appears to be associated with a wetter than normal spring. Based upon the observed data, published reports and basic principles of algal ecology a set of predicted responses to variation in the major environmental variables (rainfall and river flow) are tabulated. The tabulated predictions are proposed as a useful tool for resource managers. Copyright © 2001 John Wiley & Sons, Ltd. [source] A mixture of seven antiandrogens induces reproductive malformations in ratsINTERNATIONAL JOURNAL OF ANDROLOGY, Issue 2 2008Cynthia V. Rider Summary To date, regulatory agencies have not considered conducting cumulative risk assessments for mixtures of chemicals with diverse mechanisms of toxicity because it is assumed that the chemicals will act independently and the individual chemical doses are not additive. However, this assumption is not supported by new research addressing the joint effects of chemicals that disrupt reproductive tract development in the male rat by disrupting the androgen signalling pathway via diverse mechanisms of toxicity [i.e. androgen receptor (AR) antagonism in the reproductive tract vs. inhibition of androgen synthesis in the foetal testis]. In this study, pregnant rats were exposed to four dilutions of a mixture containing vinclozolin, procymidone, linuron, prochloraz, benzyl butyl phthalate, dibutyl phthalate and diethylhexyl phthalate during the period of sexual differentiation and male offspring were assessed for effects on hormone sensitive endpoints including: anogenital distance, infant areolae retention and reproductive tract tissue weights and malformations. The ratio of the chemicals in the mixture was based upon each chemical's ED50 for inducing reproductive tract malformations (hypospadias or epididymal agenesis). The observed responses from the mixture were compared with predicted responses generated with a toxic equivalency approach and models of dose addition, response addition or integrated addition. As hypothesized, we found that the mixture of chemicals that alter the androgen signalling pathway via diverse mechanisms disrupted male rat reproductive tract differentiation and induced malformations in a cumulative, dose-additive manner. The toxic equivalency and dose addition models provided the best fit to observed responses even though the chemicals do not act via a common cellular mechanism of action. The current regulatory framework for conducting cumulative risk assessments needs to consider the results, including those presented herein, which indicate that chemicals that disrupt foetal tissues during sexual differentiation act in a cumulative, dose-additive manner irrespective of the specific cellular mechanism of toxicity. [source] Theory of net analyte signal vectors in inverse regressionJOURNAL OF CHEMOMETRICS, Issue 12 2003Rasmus Bro Abstract The net analyte signal and the net analyte signal vector are useful measures in building and optimizing multivariate calibration models. In this paper a theory for their use in inverse regression is developed. The theory of net analyte signal was originally derived from classical least squares in spectral calibration where the responses of all pure analytes and interferents are assumed to be known. However, in chemometrics, inverse calibration models such as partial least squares regression are more abundant and several tools for calculating the net analyte signal in inverse regression models have been proposed. These methods yield different results and most do not provide results that are in accordance with the chosen calibration model. In this paper a thorough development of a calibration-specific net analyte signal vector is given. This definition turns out to be almost identical to the one recently suggested by Faber (Anal. Chem. 1998; 70: 5108,5110). A required correction of the net analyte signal in situations with negative predicted responses is also discussed. Copyright © 2004 John Wiley & Sons, Ltd. [source] A backoff strategy for model-based experiment design under parametric uncertaintyAICHE JOURNAL, Issue 8 2010Federico Galvanin Abstract Model-based experiment design techniques are an effective tool for the rapid development and assessment of dynamic deterministic models, yielding the most informative process data to be used for the estimation of the process model parameters. A particular advantage of the model-based approach is that it permits the definition of a set of constraints on the experiment design variables and on the predicted responses. However, uncertainty in the model parameters can lead the constrained design procedure to predict experiments that turn out to be, in practice, suboptimal, thus decreasing the effectiveness of the experiment design session. Additionally, in the presence of parametric mismatch, the feasibility constraints may well turn out to be violated when that optimally designed experiment is performed, leading in the best case to less informative data sets or, in the worst case, to an infeasible or unsafe experiment. In this article, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure both feasibility and optimality of the planned experiment. A prediction of the system responses for the given parameter distribution is used to evaluate and update suitable backoffs from the nominal constraints, which are used in the design session to keep the system within a feasible region with specified probability. This approach is particularly useful when designing optimal experiments starting from limited preliminary knowledge of the parameter set, with great improvement in terms of design efficiency and flexibility of the overall iterative model development scheme. The effectiveness of the proposed methodology is demonstrated and discussed by simulation through two illustrative case studies concerning the parameter identification of physiological models related to diabetes and cancer care. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] | |||||||||||||||||||