Time course analysis of hypoxia, granulation tissue and blood vessel growth, and remodeling in healing rat cutaneous incisional primary intention wounds

Hypoxia and the development and remodeling of blood vessels and connective tissue in granulation tissue that forms in a wound gap following full-thickness skin incision in the rat were examined as a function of time. A 1.5 cm-long incisional wound was created in rat groin skin and the opposed edges sutured together. Wounds were harvested between 3 days and 16 weeks and hypoxia, percent vascular volume, cell proliferation and apoptosis, α-smooth muscle actin, vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 expression in granulation tissue were then assessed. Hypoxia was evident between 3 and 7 days while maximal cell proliferation at 3 days (123.6 ± 22.2 cells/mm 2, p < 0.001 when compared with normal skin) preceded the peak percent vascular volume that occurred at 7 days (15.83 ± 1.10%, p < 0.001 when compared with normal skin). The peak in cell apoptosis occurred at 3 weeks (12.1 ± 1.3 cells/mm 2, p < 0.001 when compared with normal skin). Intense α-smooth muscle actin labeling in myofibroblasts was evident at 7 and 10 days. Vascular endothelial growth factor receptor-2 and vascular endothelial growth factor-A were detectable until 2 and 3 weeks, respectively, while transforming growth factor-β 1 protein was detectable in endothelial cells and myofibroblasts until 3-4 weeks and in the extracellular matrix for 16 weeks. Incisional wound granulation tissue largely developed within 3-7 days in the presence of hypoxia. Remodeling, marked by a decline in the percent vascular volume and increased cellular apoptosis, occurred largely in the absence of detectable hypoxia. The expression of vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 is evident prior, during, and after the peak of vascular volume reflecting multiple roles for these factors during wound healing.

Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods

In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.

Multifractal analyses of daily rainfall time series in Pearl River basin of China

The multifractal properties of daily rainfall time series at the stations in Pearl River basin of China over periods of up to 45 years are examined using the universal multifractal approach based on the multiplicative cascade model and the multifractal detrended fluctuation analysis (MF-DFA). The results from these two kinds of multifractal analyses show that the daily rainfall time series in this basin have multifractal behavior in two different time scale ranges. It is found that the empirical multifractal moment function K(q)K(q) of the daily rainfall time series can be fitted very well by the universal multifractal model (UMM). The estimated values of the conservation parameter HH from UMM for these daily rainfall data are close to zero indicating that they correspond to conserved fields. After removing the seasonal trend in the rainfall data, the estimated values of the exponent h(2)h(2) from MF-DFA indicate that the daily rainfall time series in Pearl River basin exhibit no long-term correlations. It is also found that K(2)K(2) and elevation series are negatively correlated. It shows a relationship between topography and rainfall variability.

Monitoring the Performance of Complex Projects from Multiple Perspectives over Multiple Time Frames

When complex projects go wrong they can go horribly wrong with severe financial consequences. We are undertaking research to develop leading performance indicators for complex projects, metrics to provide early warning of potential difficulties. The assessment of success of complex projects can be made by a range of stakeholders over different time scales, against different levels of project results: the project’s outputs at the end of the project; the project’s outcomes in the months following project completion; and the project’s impact in the years following completion. We aim to identify leading performance indicators, which may include both success criteria and success factors, and which can be measured by the project team during project delivery to forecast success as assessed by key stakeholders in the days, months and years following the project. The hope is the leading performance indicators will act as alarm bells to show if a project is diverting from plan so early corrective action can be taken. It may be that different combinations of the leading performance indicators will be appropriate depending on the nature of project complexity. In this paper we develop a new model of project success, whereby success is assessed by different stakeholders over different time frames against different levels of project results. We then relate this to measurements that can be taken during project delivery. A methodology is described to evaluate the early parts of this model. Its implications and limitations are described. This paper describes work in progress.

Econometric analysis of stuctural systems with permanent and transitory shocks

This paper considers the implications of the permanent/transitory decomposition of shocks for identification of structural models in the general case where the model might contain more than one permanent structural shock. It provides a simple and intuitive generalization of the influential work of Blanchard and Quah [1989. The dynamic effects of aggregate demand and supply disturbances. The American Economic Review 79, 655–673], and shows that structural equations with known permanent shocks cannot contain error correction terms, thereby freeing up the latter to be used as instruments in estimating their parameters. The approach is illustrated by a re-examination of the identification schemes used by Wickens and Motto [2001. Estimating shocks and impulse response functions. Journal of Applied Econometrics 16, 371–387], Shapiro and Watson [1988. Sources of business cycle fluctuations. NBER Macroeconomics Annual 3, 111–148], King et al. [1991. Stochastic trends and economic fluctuations. American Economic Review 81, 819–840], Gali [1992. How well does the ISLM model fit postwar US data? Quarterly Journal of Economics 107, 709–735; 1999. Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review 89, 249–271] and Fisher [2006. The dynamic effects of neutral and investment-specific technology shocks. Journal of Political Economy 114, 413–451].