948 resultados para Random Coefficient Autoregressive Model{ RCAR (1)}
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Includes index.
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The granulocyte colony-stimulating factor (G-CSF) and Fit-3 receptor agonist progenipoietin-1 (ProGP-1) has potent effects on dendritic cell (DC) expansion and may be an alternative to G-CSF for the mobilization of stem cells for allogeneic stem cell transplantation (SCT). We studied the ability of stem cell grafts mobilized with this agent to induce graft-versus-host disease (GVHD) to minor and major histocompatibility antigens in the well-described B6 --> B6D2F1 SCT model. ProGP-1, G-CSIF, or control diluent was administered to donor B6 mice. ProGP-1 expanded all cell lineages in the spleen, and unseparated splenocytes from these animals produced large amounts of interleukin 10 (IL-10) and transforming growth factor beta (TGFbeta) whereas the expression of T-cell adhesion molecules was diminished. Transplantation survival was 0%, 50%, and 90% in recipients of control-, G-CSF-, and ProGP-1-treated allogeneic donor splenocytes, respectively (P < .0001). Donor pretreatment with ProGP-1 allowed a 4-fold escalation in T-cell dose over that possible with G-CSF. Donor CD4 T cells from allogeneic SCT recipients of ProGP-1 splenocytes demonstrated an anergic response to host antigen, and cytokine production (interferon gamma [IFNγ], IL-4, and IL-10) was also reduced while CD8 T-cell cytotoxicity to host antigens remained intact. Neither CD11c(hi) DCs nor CD11c(dim)/B220(hi) DCs from ProGP-1-treated animals conferred protection from GVHD when added to control spleen. Conversely, when equal numbers of purified T cells from control-, G-CSF-, or ProGP-1-treated allogeneic donors were added to allogeneic T-cell-depleted control spleen, survival at day 60 was 0%, 15%, and 90%, respectively (P < .0001). The improved survival in recipients of ProGP-1 T cells was associated with reductions in systemic tumor necrosis factor alpha generation and GVHD of the gastrointestinal tract. We conclude that donor pretreatment with ProGP-1 is superior to G-CSIF for the prevention of GVHD after allogeneic SCT, primarily due to incremental affects on T-cell phenotype and function
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We previously reported that bacterial products such as LPS and CpG DNA down-modulated cell surface levels of the Colony Stimulating Factor (CSF)-1 receptor (CSF-1R) on primary murine macrophages in an all-or-nothing manner. Here we show that the ability of bacterial products to down-modulate the CSF-IR rendered bone marrow-derived macrophages (BMM) unresponsive to CSF-1 as assessed by Akt and ERK 1/2 phosphorylation. Using toll-like receptor (th-)9 as a model CSF-1-repressed gene, we show that LPS induced tlr9 expression in BMM only when CSF-1 was present, suggesting that LPS relieves CSF-1-mediated inhibition to induce gene expression. Using cDNA microarrays, we identified a cluster of similarly CSF-1 repressed genes in BMM. By real time PCR we confirmed that the expression of a selection of these genes, including integral membrane protein 2B (itm2b), receptor activity-modifying protein 2 (ramp2) and macrophage-specific gene 1 (mpg-1), were repressed by CSF-1 and were induced by LPS only in the presence of CSF-1. This pattern of gene regulation was also apparent in thioglycollate-elicited peritoneal macrophages (TEPM). LPS also counteracted CSF-1 action to induce mRNA expression of a number of transcription factors including interferon consensus sequence binding protein 1 (Icsbp1), suggesting that this mechanism leads to transcriptional reprogramming in macrophages. Since the majority of in vitro studies on macrophage biology do not include CSF-1, these genes represent a set of previously uncharacterised LPS-inducible genes. This study identifies a new mechanism of macrophage activation, in which LPS (and other toll-like receptor agonists) regulate gene expression by switching off the CSF-1R signal. This finding also provides a biological relevance to the well-documented ability of macrophage activators to down-modulate surface expression of the CSF-1R. (C) 2005 Elsevier GmbH. All rights reserved.
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The ingress of water and Kokubo simulated body fluid (SBF) into poly (2-hydroxyethyl methacrylate) (PHEMA), and its co-polymers with tetrahydrofurduryl methacrylate (THFMA), loaded with either one of two model drugs, vitamin 1312 or aspirin, was studied by mass uptake over the temperature range 298-318 K. The polymers were studied as cylinders and were loaded with either 5 wt% or 10 wt% of the drugs. From DSC studies it was observed that vitamin B-12 behaved as a physical cross-linker restricting chain segmental mobility, and so had a small anti-plasticisation effect on PHEMA and the co-polymers rich in HEMA, but almost no effect on the T-g of co-polymers rich in THFMA. On the other hand, aspirin exhibited a plasticising effect on PHEMA and the copolymers. All of the polymers were found to absorb water and SBF according to a Fickian diffusion mechanism. The polymers were all found to swell to a greater extent in SBF than in water, which was attributed to the presence of Tris buffer in the SBF. The sorptions of the two penetrants were found to follow Fickian kinetics in all cases and the diffusion coefficients at 310 K for SBF were found to be smaller than those for water, except for the polymers containing aspirin where the diffusion coefficients were higher than for the other systems. For example, for sorption into PHEMA the diffusion coefficient for water was 1.41 X 10(-11) m(2)/s and for SBF was 0.79 x 10-11 m(2)/s, but in the presence of 5 wt% aspirin the corresponding values were 1.27 x 10(-1)1 m(2)/s and 1.25 x 10(-11) m(2)/s, respectively. The corresponding values for PHEMA loaded with 5 wt% B-12 were 1.25 x 10(-11) m(2)/s and 0.74 x 10(-11) m(2)/s, respectively.
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The pharmacokinetic disposition of metformin in late pregnancy was studied together with the level of fetal exposure at birth. Blood samples were obtained in the third trimester of pregnancy from women with gestational diabetes or type 2 diabetes, 5 had a previous diagnosis of polycystic ovary syndrome. A cord blood sample also was obtained at the delivery of some of these women, and also at delivery of others who had been taking metformin during pregnancy but from whom no blood had been taken. Plasma metformin concentrations were assayed by a new, validated, reverse-phase HPLC method, A 2-compartment, extravascular maternal model with transplacental partitioning of drug to a fetal compartment was fitted to the data. Nonlinear mixed-effects modeling was performed in'NONMEM using FOCE with INTERACTION. Variability was estimated using logarithmic interindividual and additive residual variance models; the covariance between clearance and volume was modeled simultaneously. Mean (range) metformin concentrations in cord plasma and in maternal plasma were 0.81 (range, 0.1-2.6) mg/L and 1.2 (range, 0. 1-2.9) mg/L, respectively. Typical population values (interindividual variability, CV%) for allometrically scaled maternal clearance and volume of distribution were 28 L/h/70 kg (17.1%) and 190 L/70 ka (46.3%), giving a derived population-wide half-life of 5.1 hours. The placental partition coefficient for metformin was 1.07 (36.3%). Neither maternal age nor weight significantly influenced the pharmacokinetics. The variability (SD) of observed concentrations about model-predicted concentrations was 0.32 mg/L. The pharmacokinetics were similar to those in nonpregnant patients and, therefore, no dosage adjustment is warranted. Metformin readily crosses the placenta, exposing the fetus to concentrations approaching those in the maternal circulation. The sequelae to such exposure, ea, effects on neonatal obesity and insulin resistance, remain unknown.
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This thesis, set within an Action Research framework, details the development and validation of a writer-centred model of the writing process. The model was synthesised within the boundaries of a writers’ group for MA students. The initial data collected, and analysed using the principles of grounded theory, were retrospective descriptions of group members’ writing processes. After initial analysis, additional data, from group members’ writing, and from audio recordings, were used for further analysis, and to form a model of the writing process. To ascertain whether the model had value outside the specific context in which it was made, it was validated from three different perspectives. Firstly, the retrospective descriptions of other writers were collected and analysed, using the model as a framework. Secondly, the model was presented at academic conferences; comments about the model, made by members of the audience, were collected and analysed. Finally, the model was used in writing courses for PhD students. Comments from these students, along with questionnaire responses, were collected and the content analysed. Upon examination of all data sources, the model was updated to reflect additional insights arising from the analysis. Analysis of the data also indicated that the model is useable outside its original context. Potential uses for the model are 1) raising awareness of the process of writing, 2) putting writers at ease, 3) serving as a starting point for individuals or groups to design their own models of the writing process, and 4) as a tool to help writers take control of their writing processes.
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This paper compares the UK/US exchange rate forecasting performance of linear and nonlinear models based on monetary fundamentals, to a random walk (RW) model. Structural breaks are identified and taken into account. The exchange rate forecasting framework is also used for assessing the relative merits of the official Simple Sum and the weighted Divisia measures of money. Overall, there are four main findings. First, the majority of the models with fundamentals are able to beat the RW model in forecasting the UK/US exchange rate. Second, the most accurate forecasts of the UK/US exchange rate are obtained with a nonlinear model. Third, taking into account structural breaks reveals that the Divisia aggregate performs better than its Simple Sum counterpart. Finally, Divisia-based models provide more accurate forecasts than Simple Sum-based models provided they are constructed within a nonlinear framework.
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We examine the empirical evidence for an environmental Kuznets curve using a semiparametric smooth coefficient regression model that allows us to incorporate flexibility in the parameter estimates, while maintaining the basic econometric structure that is typically used to estimate the pollution-income relationship. This allows us to assess the sensitivity to parameter heterogeneity of typical parametric models used to estimate the relationship between pollution and income, as well as identify why the results from such models are seldom found to be robust. Our results confirm that the resulting relationship between pollution and income is fragile; we show that the estimated pollution-income relationship depends substantially on the heterogeneity of the slope coefficients and the parameter values at which the relationship is evaluated. Different sets of parameters obtained from the semiparametric model give rise to many different shapes for the pollution-income relationship that are commonly found in the literature.
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While many offline retailers have developed informational websites that offer information on products and prices, the key question for such informational websites is whether they can increase revenues via web-to-store shopping. The current paper draws on the information search literature to specify and test hypotheses regarding the offline revenue impact of adding an informational website. Explicitly considering marketing efforts, a latent class model distinguishes consumer segments with different short-term revenue effects, while a Vector Autoregressive model on these segments reveals different long-term marketing response. We find that the offline revenue impact of the informational website critically depends on the product category and customer segment. The lower online search costs are especially beneficial for sensory products and for customers distant from the store. Moreover, offline revenues increase most for customers with high web visit frequency. We find that customers in some segments buy more and more expensive products, suggesting that online search and offline purchases are complements. In contrast, customers in a particular segment reduce their shopping trips, suggesting their online activities partially substitute for experiential shopping in the physical store. Hence, offline retailers should use specific online activities to target specific product categories and customer segments.
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A range of physical and engineering systems exhibit an irregular complex dynamics featuring alternation of quiet and burst time intervals called the intermittency. The intermittent dynamics most popular in laser science is the on-off intermittency [1]. The on-off intermittency can be understood as a conversion of the noise in a system close to an instability threshold into effective time-dependent fluctuations which result in the alternation of stable and unstable periods. The on-off intermittency has been recently demonstrated in semiconductor, Erbium doped and Raman lasers [2-5]. Recently demonstrated random distributed feedback (random DFB) fiber laser has an irregular dynamics near the generation threshold [6,7]. Here we show the intermittency in the cascaded random DFB fiber laser. We study intensity fluctuations in a random DFB fiber laser based on nitrogen doped fiber. The laser generates first and second Stokes components 1120 nm and 1180 nm respectively under an appropriate pumping. We study the intermittency in the radiation of the second Stokes wave. The typical time trace near the generation threshold of the second Stokes wave (Pth) is shown at Fig. 1a. From the number of long enough time-traces we calculate statistical distribution between major spikes in time dynamics, Fig. 1b. To eliminate contribution of high frequency components of spikes we use a low pass filter along with the reference value of the output power. Experimental data is fitted by power law,
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Setting out from the database of Operophtera brumata, L. in between 1973 and 2000 due to the Light Trap Network in Hungary, we introduce a simple theta-logistic population dynamical model based on endogenous and exogenous factors, only. We create an indicator set from which we can choose some elements with which we can improve the fitting results the most effectively. Than we extend the basic simple model with additive climatic factors. The parameter optimization is based on the minimized root mean square error. The best model is chosen according to the Akaike Information Criterion. Finally we run the calibrated extended model with daily outputs of the regional climate model RegCM3.1, regarding 1961-1990 as reference period and 2021-2050 with 2071-2100 as future predictions. The results of the three time intervals are fitted with Beta distributions and compared statistically. The expected changes are discussed.
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In this thesis, research for tsunami remote sensing using the Global Navigation Satellite System-Reflectometry (GNSS-R) delay-Doppler maps (DDMs) is presented. Firstly, a process for simulating GNSS-R DDMs of a tsunami-dominated sea sur- face is described. In this method, the bistatic scattering Zavorotny-Voronovich (Z-V) model, the sea surface mean square slope model of Cox and Munk, and the tsunami- induced wind perturbation model are employed. The feasibility of the Cox and Munk model under a tsunami scenario is examined by comparing the Cox and Munk model- based scattering coefficient with the Jason-1 measurement. A good consistency be- tween these two results is obtained with a correlation coefficient of 0.93. After con- firming the applicability of the Cox and Munk model for a tsunami-dominated sea, this work provides the simulations of the scattering coefficient distribution and the corresponding DDMs of a fixed region of interest before and during the tsunami. Fur- thermore, by subtracting the simulation results that are free of tsunami from those with presence of tsunami, the tsunami-induced variations in scattering coefficients and DDMs can be clearly observed. Secondly, a scheme to detect tsunamis and estimate tsunami parameters from such tsunami-dominant sea surface DDMs is developed. As a first step, a procedure to de- termine tsunami-induced sea surface height anomalies (SSHAs) from DDMs is demon- strated and a tsunami detection precept is proposed. Subsequently, the tsunami parameters (wave amplitude, direction and speed of propagation, wavelength, and the tsunami source location) are estimated based upon the detected tsunami-induced SSHAs. In application, the sea surface scattering coefficients are unambiguously re- trieved by employing the spatial integration approach (SIA) and the dual-antenna technique. Next, the effective wind speed distribution can be restored from the scat- tering coefficients. Assuming all DDMs are of a tsunami-dominated sea surface, the tsunami-induced SSHAs can be derived with the knowledge of background wind speed distribution. In addition, the SSHA distribution resulting from the tsunami-free DDM (which is supposed to be zero) is considered as an error map introduced during the overall retrieving stage and is utilized to mitigate such errors from influencing sub- sequent SSHA results. In particular, a tsunami detection procedure is conducted to judge the SSHAs to be truly tsunami-induced or not through a fitting process, which makes it possible to decrease the false alarm. After this step, tsunami parameter estimation is proceeded based upon the fitted results in the former tsunami detec- tion procedure. Moreover, an additional method is proposed for estimating tsunami propagation velocity and is believed to be more desirable in real-world scenarios. The above-mentioned tsunami-dominated sea surface DDM simulation, tsunami detection precept and parameter estimation have been tested with simulated data based on the 2004 Sumatra-Andaman tsunami event.
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This paper presents the results of a combined study, using cosmogenic 36Cl exposure dating and terrestrial digital photogrammetry, of the Palliser Rockslide located in the southeastern Canadian Rocky Mountains. This site is particularly well-suited to demonstrate how this multi-disciplinary approach can be used to differentiate distinct rocksliding events, estimate their volume, and establish their chronology and recurrence interval. Observations suggest that rocksliding has been ongoing since the late Pleistocene deglaciation. Two major rockslide events have been dated at 10.0 ± 1.2 kyr and 7.7 ± 0.8 kyr before present, with failure volumes of 40 Mm3 and 8 Mm3, respectively. The results have important implications concerning our understanding of the temporal distribution of paraglacial rockslides and rock avalanches; they provide a better understanding of the volumes and failure mechanisms of recurrent failure events; and they represent the first absolute ages of a prehistoric high magnitude event in the Canadian Rocky Mountains.
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The achievement and measurement of improvements and innovations is not often an overt practice in the design and delivery of government services other than in health services. There is a need for specific mechanisms proven to increase the rate and scale of improvements and innovations in organisations, communities, regions and industries. This paper describes a model for the design, measurement and management of projects and services as systems for achieving and sustaining outcomes, improvements and innovations.The development of the model involved the practice of continuous improvement and innovation within and across a number of agricultural development projects in Australia and nternationally. Key learnings from the development and use of the model are: (1) all elements and factors critical for success can be implemented, measured and managed; (2) the design of a meaningful systemic measurement framework is possible; (3) all project partners can achieve and sustain rapid improvements and innovations; (4) outcomes can be achieved from early in the life of projects; and (5) significant spill-over benefits can be achieved beyond the scope, scale and timeframe of projects
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We introduce a new class of integer-valued self-exciting threshold models, which is based on the binomial autoregressive model of order one as introduced by McKenzie (Water Resour Bull 21:645–650, 1985. doi:10.1111/j.1752-1688.1985. tb05379.x). Basic probabilistic and statistical properties of this class of models are discussed. Moreover, parameter estimation and forecasting are addressed. Finally, the performance of these models is illustrated through a simulation study and an empirical application to a set of measle cases in Germany.