77 resultados para Auto-Regressive and Moving-Average Model with exogenous inputs


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In this paper a new structural model is presented to describe the evolution of porosity of char during the gasification process. The model assumes the char structure to be composed of bundles of parallel graphite layers, and the reactivities of each layer with the gasification agent are assumed to be different to represent the different degree of heterogeneity of each layer (i.e. each layer will react with the gasification agent at a different rate). It is this difference in the reactivity that allows micropores to be created during the course of gasification. This simple structural model enables the evolution of pore volume, pore geometrical surface area and the pore size distribution to be described with respect to the extent of char burn-off. The model is tested against the experimental data of gasification of longan seed-derived char with carbon dioxide and it is found that the agreement between the model and the data is reasonably satisfactory, especially the evolution of surface area and pore volume with burn-off.

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A model drug release study on the ingress of water and Kokubo simulated body fluid (SBF) into poly(2-hydroxyethyl methacrylate) (THFMA) and its copolymers with tetrahydrofurfuryl methacrylate (THFMA) loaded with vitamin B-12 was undertaken over the temperature range 298-318 K. The polymers were studied as cylinders and were loaded with either 5 or 10 wt-% of the drug. The drug release from the polymers was found to follow a Fickian diffusion mechanism in the early stages of the drug release, with higher normalized release rates at higher temperatures and higher drug loadings. The normalized release rates were also found to be higher for the SBF solution than for water. The copolymer composition was found to have a significant effect on the rate of release of the drug, with the rate falling rapidly between HEMA mole fractions of 1.0 and 0.8, but for lower mole fractions of HEMA the normalized release rate decreased more slowly. This behaviour followed the trend found for the changes in the equilibrium penetrant contents for the copolymers.

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This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

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Genotype, sulphur (S) nutrition and soil-type effects on spring onion quality were assessed using a 32-conducting polymer sensor E-nose. Relative changes in sensor resistance ratio (% dR/R) varied among eight spring onion genotypes. The % dR/R was reduced by S application in four of the eight genotypes. For the other four genotypes, S application gave no change in % dR/R in three, and increased % dR/R in the other. E-nose classification of headspace volatiles by a two-dimensional principal component analysis (PCA) plot for spring onion genotypes differed for S fertilisation vs. no S fertilisation. Headspace volatiles data set clusters for cv. 'White Lisbon' grown on clay or on sandy loam overlapped when 2.9 [Mahalanobis distance value (D2) = 1.6], or 5.8-(D2 = 0.3) kg S ha-1 was added. In contrast, clear separation (D2 = 7.5) was recorded for headspace volatile clusters for 0 kg S hd-1 on clay vs. sandy loam. Addition of 5.8 kg S ha-1 increased pyruvic acid content (mmole g-1 fresh weight) by 1.7-fold on average across the eight genotypes. However, increased S from 2.9 to 5.8 kg ha-1 did not significantly (P > 0.05) influence % dR/R, % dry matter (DM) or total soluble solids (TSS) contents, but significantly (P < 0.05) increased pyruvic acid content. TSS was significantly (P < 0.05) reduced by S addition, while % DM was unaffected. In conclusion, the 32-conducting polymer E-nose discerned differences in spring onion quality that were attributable to genotype and to variations in growing conditions as shown by the significant (P < 0.05) interaction effects for % dR/R.

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Genetic screening of women from multiple-case breast cancer families and other research-based endeavors have identified an extensive collection of germline variations of BRCA1 and BRCA2 that can be classified as deleterious and have clinical relevance. For some variants, such as those in the conserved intronic splice site regions which are highly likely to alter splicing, it is not possible to classify them based on the identified DNA sequence variation alone. We studied 11 multiple-case breast cancer families carrying seven distinct splice site region genetic alterations in BRCA1 or BRCA2 (BRCA1, c.IVS6-2delA, c.IVS9-2A>C, c.IVS4-1G>T, c.IVS20+1G>A and BRCA2, c.IVS17-1G>C, c.IVS20+1G>A, c.IVS7-1G>A) and applied SpliceSiteFinder to predict possible changes in efficiency of splice donor and acceptor sites, characterized the transcripts, and estimated the average age-specific cumulative risk (penetrance) using a modified segregation analysis. SpliceSiteFinder predicted and we identified transcipts that illustrated that all variants caused exon skipping, and all but two led to frameshifts. The risks of breast cancer to age 70 yrs, averaged over all variants, over BRCA1 variants alone, and over BRCA2 variants alone, were 73% (95% confidence interval 47-93), 64% (95%CI 28-96) and 79% (95%CI 48-98) respectively (all P

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The A(n-1) Gaudin model with integrable boundaries specified by non-diagonal K-matrices is studied. The commuting families of Gaudin operators are diagonalized by the algebraic Bethe ansatz method. The eigenvalues and the corresponding Bethe ansatz equations are obtained. (c) 2005 Elsevier B.V. All rights reserved.

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The mechanical behavior of the vertebrate skull is often modeled using free-body analysis of simple geometric structures and, more recently, finite-element (FE) analysis. In this study, we compare experimentally collected in vivo bone strain orientations and magnitudes from the cranium of the American alligator with those extrapolated from a beam model and extracted from an FE model. The strain magnitudes predicted from beam and FE skull models bear little similarity to relative and absolute strain magnitudes recorded during in vivo biting experiments. However, quantitative differences between principal strain orientations extracted from the FE skull model and recorded during the in vivo experiments were smaller, and both generally matched expectations from the beam model. The differences in strain magnitude between the data sets may be attributable to the level of resolution of the models, the material properties used in the FE model, and the loading conditions (i.e., external forces and constraints). This study indicates that FE models and modeling of skulls as simple engineering structures may give a preliminary idea of how these structures are loaded, but whenever possible, modeling results should be verified with either in vitro or preferably in vivo testing, especially if precise knowledge of strain magnitudes is desired. (c) 2005 Wiley-Liss, Inc.

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The water retention curve (WRC) is a hydraulic characteristic of concrete required for advanced modeling of water (and thus solute) transport in variably saturated, heterogeneous concrete. Unfortunately, determination by a direct experimental method (for example, measuring equilibrium moisture levels of large samples stored in constant humidity cells) is a lengthy process, taking over 2 years for large samples. A surrogate approach is presented in which the WRC is conveniently estimated from mercury intrusion porosimetry (MIP) and validated by water sorption isotherms: The well-known Barrett, Joyner and Halenda (BJH) method of estimating the pore size distribution (PSD) from the water sorption isotherm is shown to complement the PSD derived from conventional MIP. This provides a basis for predicting the complete WRC from MIP data alone. The van Genuchten equation is used to model the combined water sorption and MIP results. It is a convenient tool for describing water retention characteristics over the full moisture content range. The van Genuchten parameter estimation based solely on MIP is shown to give a satisfactory approximation to the WRC, with a simple restriction on one. of the parameters.

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Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

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Background: Oral itraconazole (ITRA) is used for the treatment of allergic bronchopulmonary aspergillosis in patients with cystic fibrosis (CF) because of its antifungal activity against Aspergillus species. ITRA has an active hydroxy-metabolite (OH-ITRA) which has similar antifungal activity. ITRA is a highly lipophilic drug which is available in two different oral formulations, a capsule and an oral solution. It is reported that the oral solution has a 60% higher relative bioavailability. The influence of altered gastric physiology associated with CF on the pharmacokinetics (PK) of ITRA and its metabolite has not been previously evaluated. Objectives: 1) To estimate the population (pop) PK parameters for ITRA and its active metabolite OH-ITRA including relative bioavailability of the parent after administration of the parent by both capsule and solution and 2) to assess the performance of the optimal design. Methods: The study was a cross-over design in which 30 patients received the capsule on the first occasion and 3 days later the solution formulation. The design was constrained to have a maximum of 4 blood samples per occasion for estimation of the popPK of both ITRA and OH-ITRA. The sampling times for the population model were optimized previously using POPT v.2.0.[1] POPT is a series of applications that run under MATLAB and provide an evaluation of the information matrix for a nonlinear mixed effects model given a particular design. In addition it can be used to optimize the design based on evaluation of the determinant of the information matrix. The model details for the design were based on prior information obtained from the literature, which suggested that ITRA may have either linear or non-linear elimination. The optimal sampling times were evaluated to provide information for both competing models for the parent and metabolite and for both capsule and solution simultaneously. Blood samples were assayed by validated HPLC.[2] PopPK modelling was performed using FOCE with interaction under NONMEM, version 5 (level 1.1; GloboMax LLC, Hanover, MD, USA). The PK of ITRA and OH‑ITRA was modelled simultaneously using ADVAN 5. Subsequently three methods were assessed for modelling concentrations less than the LOD (limit of detection). These methods (corresponding to methods 5, 6 & 4 from Beal[3], respectively) were (a) where all values less than LOD were assigned to half of LOD, (b) where the closest missing value that is less than LOD was assigned to half the LOD and all previous (if during absorption) or subsequent (if during elimination) missing samples were deleted, and (c) where the contribution of the expectation of each missing concentration to the likelihood is estimated. The LOD was 0.04 mg/L. The final model evaluation was performed via bootstrap with re-sampling and a visual predictive check. The optimal design and the sampling windows of the study were evaluated for execution errors and for agreement between the observed and predicted standard errors. Dosing regimens were simulated for the capsules and the oral solution to assess their ability to achieve ITRA target trough concentration (Cmin,ss of 0.5-2 mg/L) or a combined Cmin,ss for ITRA and OH-ITRA above 1.5mg/L. Results and Discussion: A total of 241 blood samples were collected and analysed, 94% of them were taken within the defined optimal sampling windows, of which 31% where taken within 5 min of the exact optimal times. Forty six per cent of the ITRA values and 28% of the OH-ITRA values were below LOD. The entire profile after administration of the capsule for five patients was below LOD and therefore the data from this occasion was omitted from estimation. A 2-compartment model with 1st order absorption and elimination best described ITRA PK, with 1st order metabolism of the parent to OH-ITRA. For ITRA the clearance (ClItra/F) was 31.5 L/h; apparent volumes of central and peripheral compartments were 56.7 L and 2090 L, respectively. Absorption rate constants for capsule (kacap) and solution (kasol) were 0.0315 h-1 and 0.125 h-1, respectively. Comparative bioavailability of the capsule was 0.82. There was no evidence of nonlinearity in the popPK of ITRA. No screened covariate significantly improved the fit to the data. The results of the parameter estimates from the final model were comparable between the different methods for accounting for missing data, (M4,5,6)[3] and provided similar parameter estimates. The prospective application of an optimal design was found to be successful. Due to the sampling windows, most of the samples could be collected within the daily hospital routine, but still at times that were near optimal for estimating the popPK parameters. The final model was one of the potential competing models considered in the original design. The asymptotic standard errors provided by NONMEM for the final model and empirical values from bootstrap were similar in magnitude to those predicted from the Fisher Information matrix associated with the D-optimal design. Simulations from the final model showed that the current dosing regimen of 200 mg twice daily (bd) would provide a target Cmin,ss (0.5-2 mg/L) for only 35% of patients when administered as the solution and 31% when administered as capsules. The optimal dosing schedule was 500mg bd for both formulations. The target success for this dosing regimen was 87% for the solution with an NNT=4 compared to capsules. This means, for every 4 patients treated with the solution one additional patient will achieve a target success compared to capsule but at an additional cost of AUD $220 per day. The therapeutic target however is still doubtful and potential risks of these dosing schedules need to be assessed on an individual basis. Conclusion: A model was developed which described the popPK of ITRA and its main active metabolite OH-ITRA in adult CF after administration of both capsule and solution. The relative bioavailability of ITRA from the capsule was 82% that of the solution, but considerably more variable. To incorporate missing data, using the simple Beal method 5 (using half LOD for all samples below LOD) provided comparable results to the more complex but theoretically better Beal method 4 (integration method). The optimal sparse design performed well for estimation of model parameters and provided a good fit to the data.

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Although IL-6 has been shown to predict onset of disability in older persons and both IL-6 and CRP are associated with motality risk, these markers of inflammation have only limited associations with physical performance, except for walking measures and grip strength at baseline, and do not predict change in performance 7 years later in a high-functioning subset of older adults.

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Febrile seizures affect approximately 3% of all children under six years of age and are by far the most common seizure disorder(1). A small proportion of children with febrile seizures later develop ongoing epilepsy with afebrile seizures(2). Segregation analysis suggests the majority of cases have complex inheritance(3) but rare families show apparent autosomal dominant: inheritance. Two putative loci have been mapped (FEB1 and FEB2), but specific genes have not yet been identified(4,5). We recently described a clinical subset, termed generalized epilepsy with febrile seizures plus (GEFS(+)), in which many family members have seizures with fever that may persist beyond six years of age or be associated with afebrile generalized seizures(6). We now report linkage, in another large GEFS(+) family, to chromosome region 19q13.1 and identification of a mutation in the voltage-gated sodium (Na+)-channel beta 1 subunit gene (SCN1B). The mutation changes a conserved cysteine residue disrupting a putative disulfide bridge which normally maintains an extracellular immunoglobulin-like fold. Go-expression of the mutant pr subunit with a brain Na+-channel alpha subunit in Xenopus laevis oocytes demonstrates that the mutation interferes with the ability of the subunit to modulate channel-gating kinetics consistent with a loss-of-function allele. This observation develops the theme that idiopathic epilepsies are a family of channelopathies and raises the possibility of involvement of other Na+-channel subunit genes in febrile seizures and generalized epilepsies with complex inheritance patterns.

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Carbohydrate-deficient transferrin (CDT) has emerged as the best new marker for alcohol abuse. Recently plasma immunoglobulin A (IgA) reactivity with acetaldehyde (AcH)-modified proteins, or the modified proteins per se, have been proposed as a markers for high levels of alcohol consumption. In this study, we have compared CDT, IgA reactivity with AcH adducts (IgA ASR), and AcH-modified albumin with conventional markers of high alcohol intake in groups with well-defined drinking histories, The plasma activity of ALT, AST, and gamma-glutamyltransferase increased steadily with increasing alcohol consumption, CDT and AcH-modified albumin showed a similar pattern, whereas IgA ASR appeared only to be elevated after a threshold level of consumption had been reached, Neither CDT IgA ASR or AcH-modified albumin correlated strongly with any of the conventional markers or each other. This study shows that CDT, IgA ASR, AcH-modified albumin, and the conventional markers are not related, but suggests that the concurrent use of CDT and IgA ASR may lead to better identification of high alcohol intake.