'Neighbourhood' size, dispersal and density estimates in the prickly forest skink (Gnypetoscincus queenslandiae) using individual genetic and demographic methods

Dispersal, or the amount of dispersion between an individual's birthplace and that of its offspring, is of great importance in population biology, behavioural ecology and conservation, however, obtaining direct estimates from field data on natural populations can be problematic. The prickly forest skink, Gnypetoscincus queenslandiae, is a rainforest endemic skink from the wet tropics of Australia. Because of its log-dwelling habits and lack of definite nesting sites, a demographic estimate of dispersal distance is difficult to obtain. Neighbourhood size, defined as 4 piD sigma (2) (where D is the population density and sigma (2) the mean axial squared parent-offspring dispersal rate), dispersal and density were estimated directly and indirectly for this species using mark-recapture and microsatellite data, respectively, on lizards captured at a local geographical scale of 3 ha. Mark-recapture data gave a dispersal rate of 843 m(2)/generation (assuming a generation time of 6.5 years), a time-scaled density of 13 635 individuals * generation/km(2) and, hence, a neighbourhood size of 144 individuals. A genetic method based on the multilocus (10 loci) microsatellite genotypes of individuals and their geographical location indicated that there is a significant isolation by distance pattern, and gave a neighbourhood size of 69 individuals, with a 95% confidence interval between 48 and 184. This translates into a dispersal rate of 404 m(2)/generation when using the mark-recapture density estimation, or an estimate of time-scaled population density of 6520 individuals * generation/km(2) when using the mark-recapture dispersal rate estimate. The relationship between the two categories of neighbourhood size, dispersal and density estimates and reasons for any disparities are discussed.

Reconciling value estimates from the discounted cash flow model and the residual income model

This paper examines why practitioners and researchers get different estimates of equity value when they use a discounted cash flow (CF) model versus a residual income (RI) model. Both models are derived from the same underlying assumption -- that price is the present value of expected future net dividends discounted at the cost of equity capital -- but in practice and in research they frequently yield different estimates. We argue that the research literature devoted to comparing the accuracy of these two models is misguided; properly implemented, both models yield identical valuations for all firms in all years. We identify how prior research has applied inconsistent assumptions to the two models and show how these seemingly small errors cause surprisingly large differences in the value estimates. [ABSTRACT FROM AUTHOR]

Population balance modelling of granulation with a physically based coalescence kernel

It was previously published by the authors that granules can either coalesce through Type I (when granules coalesce by viscous dissipation in the surface liquid layer before their surfaces touch) or Type II (when granules are slowed to a halt during rebound, after their surfaces have made contact) (AIChE J. 46 (3) (2000) 529). Based on this coalescence mechanism, a new coalescence kernel for population balance modelling of granule growth is presented. The kernel is constant such that only collisions satisfying the conditions for one of the two coalescence types are successful. One constant rate is assigned to each type of coalescence and zero is for the case of rebound. As the conditions for Types I and II coalescence are dependent on granule and binder properties, the coalescence kernel is thus physically based. Simulation results of a variety of binder and granule materials show good agreement with experimental data. (C) 2002 Elsevier Science Ltd. All rights reserved.

The effect of water, brine and ethanol flotation on the quality and shelf life of macadamia kernels 2. Kernel pieces

Raw macadamia kernel pieces were immersed in water (specific gravity 1.00 g/cm(3)), brine (SG 1.02 g/cm(3)) or ethanol solution (SG 0.97 g/cm(3)) for 30 or 60 s, then re-dried to below 1.5% moisture (wet basis) and stored under vacuum for 0, 4 and 12 months. Flotation in water had no effect on the quality or shelf life of the kernel pieces over 12 months storage, as measured by sensory evaluation of the kernels and chemical analysis of the kernel oil. Immersion in a salt solution caused unacceptable changes in quality during storage, increasing as storage time increased. Flotation in dilute ethanol also caused unacceptable quality changes during storage. Therefore, only flotation of macadamia kernel pieces in water can be recommended for commercial operations. Microbiological concerns with such a process still need to be addressed.

Effect of changing data collection parameters on statistical motor unit number estimates

The effect of number of samples and selection of data for analysis on the calculation of surface motor unit potential (SMUP) size in the statistical method of motor unit number estimates (MUNE) was determined in 10 normal subjects and 10 with amyotrophic lateral sclerosis (ALS). We recorded 500 sequential compound muscle action potentials (CMAPs) at three different stable stimulus intensities (10–50% of maximal CMAP). Estimated mean SMUP sizes were calculated using Poisson statistical assumptions from the variance of 500 sequential CMAP obtained at each stimulus intensity. The results with the 500 data points were compared with smaller subsets from the same data set. The results using a range of 50–80% of the 500 data points were compared with the full 500. The effect of restricting analysis to data between 5–20% of the CMAP and to standard deviation limits was also assessed. No differences in mean SMUP size were found with stimulus intensity or use of different ranges of data. Consistency was improved with a greater sample number. Data within 5% of CMAP size gave both increased consistency and reduced mean SMUP size in many subjects, but excluded valid responses present at that stimulus intensity. These changes were more prominent in ALS patients in whom the presence of isolated SMUP responses was a striking difference from normal subjects. Noise, spurious data, and large SMUP limited the Poisson assumptions. When these factors are considered, consistent statistical MUNE can be calculated from a continuous sequence of data points. A 2 to 2.5 SD or 10% window are reasonable methods of limiting data for analysis. Muscle Nerve 27: 320–331, 2003

Estimates of global and regional potential health gains from reducing multiple major risk factors

Background Estimates of the disease burden due to multiple risk factors can show the potential gain from combined preventive measures. But few such investigations have been attempted, and none on a global scale. Our aim was to estimate the potential health benefits from removal of multiple major risk factors. Methods We assessed the burden of disease and injury attributable to the joint effects of 20 selected leading risk factors in 14 epidemiological subregions of the world. We estimated population attributable fractions, defined as the proportional reduction in disease or mortality that would occur if exposure to a risk factor were reduced to an alternative level, from data for risk factor prevalence and hazard size. For every disease, we estimated joint population attributable fractions, for multiple risk factors, by age and sex, from the direct contributions of individual risk factors. To obtain the direct hazards, we reviewed publications and re-analysed cohort data to account for that part of hazard that is mediated through other risks. Results Globally, an estimated 47% of premature deaths and 39% of total disease burden in 2000 resulted from the joint effects of the risk factors considered. These risks caused a substantial proportion of important diseases, including diarrhoea (92%-94%), lower respiratory infections (55-62%), lung cancer (72%), chronic obstructive pulmonary disease (60%), ischaemic heart disease (83-89%), and stroke (70-76%). Removal of these risks would have increased global healthy life expectancy by 9.3 years (17%) ranging from 4.4 years (6%) in the developed countries of the western Pacific to 16.1 years (43%) in parts of sub-Saharan Africa. Interpretation Removal of major risk factors would not only increase healthy life expectancy in every region, but also reduce some of the differences between regions, The potential for disease prevention and health gain from tackling major known risks simultaneously would be substantial.

Measuring the accumulated hazards of smoking: global and regional estimates for 2000

Objective: Current prevalence of smoking, even where data are available, is a poor proxy for cumulative hazards of smoking, which depend on several factors including the age at which smoking began, duration of smoking, number of cigarettes smoked per day, degree of inhalation, and cigarette characteristics such as tar and nicotine content or filter type. Methods: We extended the Peto-Lopez smoking impact ratio method to estimate accumulated hazards of smoking for different regions of the world. Lung cancer mortality data were obtained from the Global Burden of Disease mortality database. The American Cancer Society Cancer Prevention Study, phase 11 (CPS-II) with follow up for the years 1982 to 1988 was the reference population. For the global application of the method, never-smoker lung cancer mortality rates were chosen based on the estimated use of coal for household energy in each region. Results: Men in industrialised countries of Europe, North America, and the Western Pacific had the largest accumulated hazards of smoking. Young and middle age males in many regions of the developing world also had large smoking risks. The accumulated hazards of smoking for women were highest in North America followed by Europe. Conclusions: In the absence of detailed data on smoking prevalence and history, lung cancer mortality provides a robust indicator of the accumulated hazards of smoking. These hazards in developing countries are currently more concentrated among young and middle aged males.

Estimates of global mortality attributable to smoking in 2000

Background Smoking is a risk factor for several diseases and has been increasing in many developing countries. Our aim was to estimate global and regional mortality in 2000 caused by smoking, including an analysis of uncertainty. Methods Following the methods of Peto and colleagues, we used lung-cancer mortality as an indirect marker for accumulated smoking risk. Never-smoker lung-cancer mortality was estimated based on the household use of coal with poor ventilation. Relative risks were taken from the American Cancer Society Cancer Prevention Study, phase II, and the retrospective proportional mortality analysis of Liu and colleagues in China. Relative risks were corrected for confounding and extrapolation to other regions. Results We estimated that in 2000, 4.83 (uncertainty range 3.94-5.93) million premature deaths in the world were attributable to smoking; 2.41 (1.80-3.15) million in developing countries and 2.43 (2.13-2.78) million in industrialised countries. 3.84 million of these deaths were in men. The leading causes of death from smoking were cardiovascular diseases (1.69 million deaths), chronic obstructive pulmonary disease (0.97 million deaths), and lung cancer (0.85 million deaths). Interpretation Smoking was an important cause of global mortality in 2000. In view of the expected demographic and epidemiological transitions and current smoking patterns in the developing world, the health loss due to smoking will grow even larger unless effective interventions and policies that reduce smoking among men and prevent increases among women in developing countries are implemented.