Estimating equations for parameters in stochastic growth models from tag-recapture data

James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.

Effect of individual variability on estimation of population parameters from length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock when there is individual variability in the von Bertalanffy growth parameter L-infinity and investigate the possible bias in the estimates when the individual variability is ignored. Three methods are examined: (i) the regression method based on the Beverton and Holt's (1956, Rapp. P.V. Reun. Cons. Int. Explor. Mer, 140: 67-83) equation; (ii) the moment method of Powell (1979, Rapp. PV. Reun. Int. Explor. Mer, 175: 167-169); and (iii) a generalization of Powell's method that estimates the individual variability to be incorporated into the estimation. It is found that the biases in the estimates from the existing methods are, in general, substantial, even when individual variability in growth is small and recruitment is uniform, and the generalized method performs better in terms of bias but is subject to a larger variation. There is a need to develop robust and flexible methods to deal with individual variability in the analysis of length-frequency data.

An improved Fabens method for estimation of growth parameters in the vonBertalanffy model with individual asymptotes

In the analysis of tagging data, it has been found that the least-squares method, based on the increment function known as the Fabens method, produces biased estimates because individual variability in growth is not allowed for. This paper modifies the Fabens method to account for individual variability in the length asymptote. Significance tests using t-statistics or log-likelihood ratio statistics may be applied to show the level of individual variability. Simulation results indicate that the modified method reduces the biases in the estimates to negligible proportions. Tagging data from tiger prawns (Penaeus esculentus and Penaeus semisulcatus) and rock lobster (Panulirus ornatus) are analysed as an illustration.

Direct shear testing on unsaturated silty soils to investigate the effects of drying and wetting on shear strength parameters at low suction

A modified conventional direct shear device was used to measure unsaturated shear strength of two silty soils at low suction values (0 ~ 50 kPa) that were achieved by following drying and wetting paths of soil water characteristic curves (SWCCs). The results revealed that the internal friction angle of the soils was not significantly affected by either the suction or the drying wetting SWCCs. The apparent cohesion of soil increased with a decreasing rate as suction increased. Shear stress-shear displacement curves obtained from soil specimens subjected to the same net normal stress and different suction values showed a higher initial stiffness and a greater peak stress as suction increased. A soil in wetting exhibited slightly higher peak shear stress and more contractive volume change behavior than that of soil in drying at the same net normal stress and suction.

Organosolv pretreatment of plant biomass for enhanced enzymatic saccharification

The combination of dwindling petroleum reserves and population growth make the development of renewable energy and chemical resources more pressing than ever before. Plant biomass is the most abundant renewable source for energy and chemicals. Enzymes can selectively convert the polysaccharides in plant biomass into simple sugars which can then be upgraded to liquid fuels and platform chemicals using biological and/or chemical processes. Pretreatment is essential for efficient enzymatic saccharification of plant biomass and this article provides an overview of how organic solvent (organosolv) pretreatments affect the structure and chemistry of plant biomass, and how these changes enhance enzymatic saccharification. A comparison between organosolv pretreatments utilizing broadly different classes of solvents (i.e., low boiling point, high boiling point, and biphasic) is presented, with a focus on solvent recovery and formation of by-products. The reaction mechanisms that give rise to these by-products are investigated and strategies to minimize by-product formation are suggested. Finally, process simulations of organosolv pretreatments are compared and contrasted, and discussed in the context of an industrial-scale plant biomass to fermentable sugar process.

Product-library-derived specification parameters in building information models augmentation

This paper conceptualizes a framework for bridging the BIM (building information modelling)-specifications divide through augmenting objects within BIM with specification parameters derived from a product library. We demonstrate how model information, enriched with data at various LODs (levels of development), can evolve simultaneously with design and construction using different representation of a window object embedded in a wall as lifecycle phase exemplars at different levels of granularity. The conceptual standpoint is informed by the need for exploring a methodological approach which extends beyond current limitations of current modelling platforms in enhancing the information content of BIM models. Therefore, this work demonstrates that BIM objects can be augmented with construction specification parameters leveraging product libraries.

Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Effects of glycerol on enzymatic hydrolysis and ethanol production using sugarcane bagasse pretreated by acidified glycerol solution

In this study, for the first time the effects of glycerol on enzymatic hydrolysis and ethanol fermentation were investigated. Enzymatic hydrolysis was inhibited slightly with 2.0 wt% glycerol, leading to reduction in glucan digestibility from 84.9% without glycerol to 82.9% (72 h). With 5.0 wt% and 10.0 wt% glycerol, glucan digestibility reduced by 4.5% and11.0%, respectively. However, glycerol appeared not detrimental to cellulase enzymes. Ethanol fermentation was not affected with glycerol up to 5.0 wt%, and was inhibited slightly with 10.0 wt% glycerol, which resulted in reduction in ethanol yield from 86.0% without glycerol to 83.7% (20 h). Based on laboratory and pilot scale enzymatic hydrolysis and ethanol production results, it was estimated that 0.142 kg ethanol could be produced from 1.0 kg dry bagasse (a glucan content of 38.0%) after pretreatment with acidified glycerol solution.