995 resultados para Growth Estimation
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Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length-frequency-based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length-frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time-dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length-frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub-step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.
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The development of large-scale solid-stale fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation. (C) 2000 John Wiley & Sons, Inc.
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The main objective of the present work is to acquire information regarding the growth responses of P. monodon larvae (from PZ1 upto PL1) to various mono specific and mixed diets. Evaluate the nutritional quality of selected species of micro algae viz. Chaetoceros calcitrans, Dunaliella salina, Isochrysis galbana and Nannochloropsis salina, larvae at three cell concentrations 10x104 cells/ml, 25x104 cells/ml and 50x104 cells/ml. The P. monodon larvae were transported, at the Nauplius stage, to the laboratory. The larvae were stocked at density of 150 larvae per litre in 5 litre FRP tanks with 3 litres of sea water. The algal cell density given to the larvae varied. The larval stages were fed with increasing densities of algae to evaluate the relationship between the food densities, ingestion rates, development and growth of the larvae. The water quality parameters, the percentage of survival rate, the growth estimation and the algal cell count were done. Each experiment was carried out in triplicate with a control group of larvae fed with Chaetoceros calcitrans. For the estimation standard procedures were used.to P. monodon
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The nineteenth symposium was held at the University of Missouri–Columbia on April 22, 1989. A total of eighteen papers were scheduled for presentation, of which nine were in poster session. Finally, fifteen papers were presented and sixteen were submitted for this proceedings. It was attended by 53 participants from five institutions. A sixth group (from Colorado State University) was kept from attending the symposium due to mechanical problems on the road and we missed them. Since they worked hard at their presentations, I requested CSU-group to submit their papers for the proceedings and I am happy that they did. ContentsMathematical modelling of a flour milling system. K. Takahashi, Y. Chen, J. Hosokoschi, and L. T. Fan. Kansas State University A novel solution to the problem of plasmid segregation in continuous bacterial fermentations. K.L. Henry, R. H. Davis, and A. L. Taylor. University of Colorado Modelling of embryonic growth in avian and reptile Eggs. C.L. Krause, R. C. Seagrave, and R. A. Ackerman. Iowa State University Mathematical modeling of in situ biodegradation processes. J.C. Wu, L. T. Fan, and L. E. Erickson. Kansas State University Effect of molecular changes on starch viscosity. C.H. Rosane and V. G. Murphy. Colorado State University Analysis of two stage recombinant bacterial fermentations using a structured kinetic model. F. Miao and D. S. Kampala. University of Colorado Lactic acid fermentation from enzyme-thinned starch by Lactobacillus amylovorus. P.S. Cheng, E. L. Iannotti, R. K. Bajpai, R. Mueller, and s. Yaeger. University of Missouri–Columbia Solubilization of preoxidized Texas lignite by cell-free broths of Penicillium strains. R. Moolick, M. N. Karim, J. C. Linden, and B. L. Burback. Colorado State University Separation of proteins from polyelectrolytes by ultrafiltration. A.G. Bazzano and C. E. Glatz. Iowa State University Growth estimation and modelling of Rhizopus oligosporus in solid state fermentations. D.-H. Ryoo, V. G. Murphy, M. N. Karim, and R. P. Tengerdy. Colorado State University Simulation of ethanol fermentations from sugars in cheese whey. C.J. Wang and R. K. Bajpai. University of Missouri–Columbia Studies on protoplast fusion of B. licheniformis. B. Shi, Kansas State University Cell separations of non-dividing and dividing yeasts using an inclined settler. C.-Y. Lee, R. H. Davis, and R. A. Sclafani. University of Colorado Effect of·serum upon local hydrodynamics within an airlift column. G.T. Jones, L. E. Erickson, and L. A. Glasgow. Kansas State University Optimization of heterologous protein secretion in continuous culture. A. Chatterjee, W. F. Remirez, and R. H. Davis. University of Colorado An improved model for lactic acid fermentation. P. Yeh, R. K. Bajpai, and E. L. Iannotti. University of Missouri–Columbia
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This study addresses the issue of the presence of a unit root on the growth rate estimation by the least-squares approach. We argue that when the log of a variable contains a unit root, i.e., it is not stationary then the growth rate estimate from the log-linear trend model is not a valid representation of the actual growth of the series. In fact, under such a situation, we show that the growth of the series is the cumulative impact of a stochastic process. As such the growth estimate from such a model is just a spurious representation of the actual growth of the series, which we refer to as a “pseudo growth rate”. Hence such an estimate should be interpreted with caution. On the other hand, we highlight that the statistical representation of a series as containing a unit root is not easy to separate from an alternative description which represents the series as fundamentally deterministic (no unit root) but containing a structural break. In search of a way around this, our study presents a survey of both the theoretical and empirical literature on unit root tests that takes into account possible structural breaks. We show that when a series is trendstationary with breaks, it is possible to use the log-linear trend model to obtain well defined estimates of growth rates for sub-periods which are valid representations of the actual growth of the series. Finally, to highlight the above issues, we carry out an empirical application whereby we estimate meaningful growth rates of real wages per worker for 51 industries from the organised manufacturing sector in India for the period 1973-2003, which are not only unbiased but also asymptotically efficient. We use these growth rate estimates to highlight the evolving inter-industry wage structure in India.
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Growing concerns about toxicity and development of resistance against synthetic herbicides have demanded looking for alternative weed management approaches. Allelopathy has gained sufficient support and potential for sustainable weed management. Aqueous extracts of six plant species (sunflower, rice, mulberry, maize, brassica and sorghum) in different combinations alone or in mixture with 75% reduced dose of herbicides were evaluated for two consecutive years under field conditions. A weedy check and S-metolachlor with atrazine (pre emergence) and atrazine alone (post emergence) at recommended rates was included for comparison. Weed dynamics, maize growth indices and yield estimation were done by following standard procedures. All aqueous plant extract combinations suppressed weed growth and biomass. Moreover, the suppressive effect was more pronounced when aqueous plant extracts were supplemented with reduced doses of herbicides. Brassica-sunflower-sorghum combination suppressed weeds by 74-80, 78-70, 65-68% during both years of study that was similar with S-metolachlor along half dose of atrazine and full dose of atrazine alone. Crop growth rate and dry matter accumulation attained peak values of 32.68 and 1,502 g m-2 d-1 for brassica-sunflower-sorghum combination at 60 and 75 days after sowing. Curve fitting regression for growth and yield traits predicted strong positive correlation to grain yield and negative correlation to weed dry biomass under allelopathic weed management in maize crop.
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This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.
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Identifying a periodic time-series model from environmental records, without imposing the positivity of the growth rate, does not necessarily respect the time order of the data observations. Consequently, subsequent observations, sampled in the environmental archive, can be inversed on the time axis, resulting in a non-physical signal model. In this paper an optimization technique with linear constraints on the signal model parameters is proposed that prevents time inversions. The activation conditions for this constrained optimization are based upon the physical constraint of the growth rate, namely, that it cannot take values smaller than zero. The actual constraints are defined for polynomials and first-order splines as basis functions for the nonlinear contribution in the distance-time relationship. The method is compared with an existing method that eliminates the time inversions, and its noise sensitivity is tested by means of Monte Carlo simulations. Finally, the usefulness of the method is demonstrated on the measurements of the vessel density, in a mangrove tree, Rhizophora mucronata, and the measurement of Mg/Ca ratios, in a bivalve, Mytilus trossulus.
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The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 Elsevier B.V. All rights reserved.
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OBJECTIVE: This study was undertaken to assess whether fine needle aspirates from non-Hodgkins lymphoma (NHL) could be used for growth fraction analysis with proliferating cell nuclear antigen (PCNA) staining and if there was a relationship between the growth fraction and cytomorphologic classification according to the Kiel classification.STUDY DESIGN: the study group consisted of 40 patients with NHL diagnosed by fine needle aspiration (FNA) cytology. The cytologic classification of the lymphomas was made by two cytopathologists on May-Grunwald-Giemsa-stained slides using the Kiel classification. There were 27 cases of low and 13 of high grade lymphoma. The estimation of the growth fraction was made by PCNA immunoreactivity. The PCNA index was quantitated in smears by counting an average of 1,000 cells, and the count teas correlated with the cytomorphologic classification.RESULTS: There was It strong correlation between the PCNA index and lymphoma grading. High grade lymphomas exhibited a mean PCNA positivity of 74.0%, which was significantly higher (P <.001) than that of low grade lymphomas (17.6%).CONCLUSION: Our study showed that PCNA evalua tion is suitable for smears obtained by FNA on NHL, correlates with increasing grades of lymphoma according to the Kiel classification and may offer a method of monitoring treatment of lymphoma.
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Includes bibliography
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Includes bibliography
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The motivating problem concerns the estimation of the growth curve of solitary corals that follow the nonlinear Von Bertalanffy Growth Function (VBGF). The most common parameterization of the VBGF for corals is based on two parameters: the ultimate length L∞ and the growth rate k. One aim was to find a more reliable method for estimating these parameters, which can capture the influence of environmental covariates. The main issue with current methods is that they force the linearization of VBGF and neglect intra-individual variability. The idea was to use the hierarchical nonlinear model which has the appealing features of taking into account the influence of collection sites, possible intra-site measurement correlation and variance heterogeneity, and that can handle the influence of environmental factors and all the reliable information that might influence coral growth. This method was used on two databases of different solitary corals i.e. Balanophyllia europaea and Leptopsammia pruvoti, collected in six different sites in different environmental conditions, which introduced a decisive improvement in the results. Nevertheless, the theory of the energy balance in growth ascertains the linear correlation of the two parameters and the independence of the ultimate length L∞ from the influence of environmental covariates, so a further aim of the thesis was to propose a new parameterization based on the ultimate length and parameter c which explicitly describes the part of growth ascribable to site-specific conditions such as environmental factors. We explored the possibility of estimating these parameters characterizing the VBGF new parameterization via the nonlinear hierarchical model. Again there was a general improvement with respect to traditional methods. The results of the two parameterizations were similar, although a very slight improvement was observed in the new one. This is, nevertheless, more suitable from a theoretical point of view when considering environmental covariates.