An extravariation model for improving confidence intervals of population size estimates from removal data

We propose a new model for estimating the size of a population from successive catches taken during a removal experiment. The data from these experiments often have excessive variation, known as overdispersion, as compared with that predicted by the multinomial model. The new model allows catchability to vary randomly among samplings, which accounts for overdispersion. When the catchability is assumed to have a beta distribution, the likelihood function, which is refered to as beta-multinomial, is derived, and hence the maximum likelihood estimates can be evaluated. Simulations show that in the presence of extravariation in the data, the confidence intervals have been substantially underestimated in previous models (Leslie-DeLury, Moran) and that the new model provides more reliable confidence intervals. The performance of these methods was also demonstrated using two real data sets: one with overdispersion, from smallmouth bass (Micropterus dolomieu), and the other without overdispersion, from rat (Rattus rattus).

Size-dependent natural mortality of juvenile banana prawns Penaeus merguiensis in the Gulf of Carpentaria, Australia

Natural mortality of marine invertebrates is often very high in the early life history stages and decreases in later stages. The possible size-dependent mortality of juvenile banana prawns, P. merguiensis (2-15 mm carapace length) in the Gulf of Carpentaria was investigated. The analysis was based on the data collected at 2-weekly intervals by beam trawls at four sites over a period of six years (between September 1986 and March 1992). It was assumed that mortality was a parametric function of size, rather than a constant. Another complication in estimating mortality for juvenile banana prawns is that a significant proportion of the population emigrates from the study area each year. This effect was accounted for by incorporating the size-frequency pattern of the emigrants in the analysis. Both the extra parameter in the model required to describe the size dependence of mortality, and that used to account for emigration were found to be significantly different from zero, and the instantaneous mortality rate declined from 0.89 week(-1) for 2 mm prawns to 0.02 week(-1) for 15 mm prawns.

Does the size of subsamples taken from multispecies trawl catches affect estimates of catch composition and abundance?

Although subsampling is a common method for describing the composition of large and diverse trawl catches, the accuracy of these techniques is often unknown. We determined the sampling errors generated from estimating the percentage of the total number of species recorded in catches, as well as the abundance of each species, at each increase in the proportion of the sorted catch. We completely partitioned twenty prawn trawl catches from tropical northern Australia into subsamples of about 10 kg each. All subsamples were then sorted, and species numbers recorded. Catch weights ranged from 71 to 445 kg, and the number of fish species in trawls ranged from 60 to 138, and invertebrate species from 18 to 63. Almost 70% of the species recorded in catches were "rare" in subsamples (less than one individual per 10 kg subsample or less than one in every 389 individuals). A matrix was used to show the increase in the total number of species that were recorded in each catch as the percentage of the sorted catch increased. Simulation modelling showed that sorting small subsamples (about 10% of catch weights) identified about 50% of the total number of species caught in a trawl. Larger subsamples (50% of catch weight on average) identified about 80% of the total species caught in a trawl. The accuracy of estimating the abundance of each species also increased with increasing subsample size. For the "rare" species, sampling error was around 80% after sorting 10% of catch weight and was just less than 50% after 40% of catch weight had been sorted. For the "abundant" species (five or more individuals per 10 kg subsample or five or more in every 389 individuals), sampling error was around 25% after sorting 10% of catch weight, but was reduced to around 10% after 40% of catch weight had been sorted.

Community-based social marketing: Effects on social norms

Purpose This research investigates whether application of a community-based social marketing principle, namely increasing the visibility of a target behaviour in the community, can change social norms surrounding the behaviour. Design/methodology/approach A repeated measures quasi-experimental design was employed to evaluate the Victorian Health Promotion Foundation’s Walk to School 2013 programme, which increases the visibility of walking to and from school through programme participation to promote active transportation for primary school children. The target population for the survey were caregivers of primary school children aged between 5-12 years old. The final sample size across the three online surveys administered was 102 respondents. Findings The results suggest that the programme increased caregivers’ perceptions that children in their community walked to and from school and that walking to and from school is socially acceptable. Originality/value The study contributes to addressing the recent call for research examining the relationship between community-based social marketing principles and programme outcomes. Further, the results provide insight for enhancing the social norms approach, which has traditionally relied on changing social norms exclusively through media campaigns.

Mandatory nap times and group napping patterns in child care: An observational study

Policy provision for naps is typical in child care settings, but there is variability in the practices employed. One practice that might modify children’s early sleep patterns is the allocation of a mandatory nap time in which all children are required to lie on their beds without alternate activity permitted. There is currently limited evidence of the effects of such practices on children’s napping patterns. This study examined the association between duration of mandatory nap times and group-level napping patterns in child care settings. Observations were undertaken in a community sample of 113 preschool rooms with a scheduled nap time (N = 2,114 children). Results showed that 83.5% of child care settings implemented a mandatory nap time (range = 15–145 min) while 14.2% provided alternate activities for children throughout the nap time period. Overall, 31% of children napped during nap times. Compared to rooms with ≤ 30 min of mandatory nap time, rooms with 31–60 min and > 60 min of mandatory nap time had a two-and-a-half and fourfold increase, respectively, in the proportion of children napping. Nap onset latency did not significantly differ across groups. Among preschool children, exposure to longer mandatory nap times in child care may increase incidence of napping.

A Bayesian decision approach for sample size determination in phase II trials

Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.

Analysis of human immunodeficiency virus type 1 drug resistance in children receiving nucleoside analogue reverse-transcriptase inhibitors plus nevirapine, nelfinavir, or ritonavir (Pediatric AIDS Clinical Trials Group 377)

In Pediatric AIDS Clinical Trials Group 377, antiretroviral therapy-experienced children were randomized to 4 treatment arms that included different combinations of stavudine, lamivudine (3TC), nevirapine (Nvp), nelfinavir (Nfv), and ritonavir (Rtv). Previous treatment with zidovudine (Zdv), didanosine (ddI), or zalcitabine (ddC) was acceptable. Drug resistance ((R)) mutations were assessed before study treatment (baseline) and at virologic failure. Zdv(R), ddI(R), and ddC(R) mutations were detected frequently at baseline but were not associated with virologic failure. Children with drug resistance mutations at baseline had greater reductions in virus load over time than did children who did not. Nvp(R) and 3TC(R) mutations were detected frequently at virologic failure, and Nvp(R) mutations were more common among children receiving 3-drug versus 4-drug Nvp-containing regimens. Children who were maintained on their study regimen after virologic failure accumulated additional Nvp(R) and 3TC(R) mutations plus Rtv(R) and Nfv(R) mutations. However, Rtv(R) and Nfv(R) mutations were detected at unexpectedly low rates.

Variable Size Population NSGA-II: VPNSGA-II

Multi-objective optimization is an active field of research with broad applicability in aeronautics. This report details a variant of the original NSGA-II software aimed to improve the performances of such a widely used Genetic Algorithm in finding the optimal Pareto-front of a Multi-Objective optimization problem for the use of UAV and aircraft design and optimsaiton. Original NSGA-II works on a population of predetermined constant size and its computational cost to evaluate one generation is O(mn^2 ), being m the number of objective functions and n the population size. The basic idea encouraging this work is that of reduce the computational cost of the NSGA-II algorithm by making it work on a population of variable size, in order to obtain better convergence towards the Pareto-front in less time. In this work some test functions will be tested with both original NSGA-II and VPNSGA-II algorithms; each test will be timed in order to get a measure of the computational cost of each trial and the results will be compared.

Size-dependent melting of nanoparticles: Hundred years of thermodynamic model

Thermodynamic model first published in 1909, is being used extensively to understand the size-dependent melting of nanoparticles. Pawlow deduced an expression for the size-dependent melting temperature of small particles based on the thermodynamic model which was then modified and applied to different nanostructures such as nanowires, prism-shaped nanoparticles, etc. The model has also been modified to understand the melting of supported nanoparticles and superheating of embedded nanoparticles. In this article, we have reviewed the melting behaviour of nanostructures reported in the literature since 1909.

Systematic stability analysis of the renormalization group flow for the normal-superconductor-normal junction of Luttinger liquid wires

We study the renormalization group flows of the two terminal conductance of a superconducting junction of two Luttinger liquid wires. We compute the power laws associated with the renormalization group flow around the various fixed points of this system using the generators of the SU(4) group to generate the appropriate parametrization of an matrix representing small deviations from a given fixed point matrix [obtained earlier in S. Das, S. Rao, and A. Saha, Phys. Rev. B 77, 155418 (2008)], and we then perform a comprehensive stability analysis. In particular, for the nontrivial fixed point which has intermediate values of transmission, reflection, Andreev reflection, and crossed Andreev reflection, we show that there are eleven independent directions in which the system can be perturbed, which are relevant or irrelevant, and five directions which are marginal. We obtain power laws associated with these relevant and irrelevant perturbations. Unlike the case of the two-wire charge-conserving junction, here we show that there are power laws which are nonlinear functions of V(0) and V(2kF) [where V(k) represents the Fourier transform of the interelectron interaction potential at momentum k]. We also obtain the power law dependence of linear response conductance on voltage bias or temperature around this fixed point.