Two-dimensional balanced sampling plans excluding contiguous units

A balanced sampling plan excluding contiguous units (or BSEC for short) was first introduced by Hedayat, Rao and Stufken in 1988. These designs can be used for survey sampling when the units are arranged in one-dimensional ordering and the contiguous units in this ordering provide similar information. In this paper, we generalize the concept of a BSEC to the two-dimensional situation and give constructions of two-dimensional BSECs with block size 3. The existence problem is completely solved in the case where lambda = 1.

Evaluation of line-transect sampling for estimating koala abundance in the Pine Rivers Shire, south-east Queensland

Distance sampling using line transects has not been previously used or tested for estimating koala abundance. In July 2001, a pilot survey was conducted to compare the use of line transects with strip transects for estimating koala abundance. Both methods provided a similar estimate of density. On the basis of the results of the pilot survey, the distribution and abundance of koalas in the Pine Rivers Shire, south-east Queensland, was determined using line-transect sampling. In total, 134 lines (length 64 km) were used to sample bushland areas. Eighty-two independent koalas were sighted. Analysis of the frequency distribution of sighting distances using the software program DISTANCE enabled a global detection function to be estimated for survey sites in bushland areas across the Shire. Abundance in urban parts of the Shire was estimated from densities obtained from total counts at eight urban sites that ranged from 26 to 51 ha in size. Koala abundance in the Pine Rivers Shire was estimated at 4584 (95% confidence interval, 4040-5247). Line-transect sampling is a useful method for estimating koala abundance provided experienced koala observers are used when conducting surveys.

Parathyroid hormone venous sampling prior to reoperation for primary hyperparathyroidism

Background: The surgical cure rate for primary hyperparathyroidism is greater than 95%. For those who have recurrent or persistent disease, preoperative localization improves reoperation success rates. Selective parathyroid venous sampling (SPVS) for intact parathyroid hormone is particularly useful when non-invasive localization techniques are negative or inconclusive. Methods: We present all known cases (n = 13) between 1994 and 2002 who had venous sampling for localization at our institution prior to reoperation for recurrent or persistent primary hyperparathyroidism. Comparison was made with non-invasive localization procedures. Results of invasive and non-invasive localization were correlated with surgical findings. Results: Of the nine reoperated cases, eight had positive correlations between SPVS and operative findings and histopathology. SPVS did not reveal the parathyroid hormone source in one case with negative non-invasive localization procedures. Comparisons between SPVS, computerized tomography (CT), and parathyroid scintigraphy (MIBI) as expressed in terms of true positive (TP), false positive (FP) and false negative (FN) were: SPVS - TP 88.8%, FP 0%, FN 11.1%; CT - TP 22.2%, FP 22.2%, FN 55.5%; and MIBI - TP 33.3%, FP 0%, FN 66.6%. At least seven of the nine operated cases have been cured; another remained normocalcaemic 2 weeks after subtotal parathyroidectomy. Conclusion: In our institution SPVS has proven to be a valuable tool in cases with recurrent or persistent primary hyperparathyroidism and negative non-invasive localization procedures.

A baseline study of importance of bovines for human Schistosoma Japonicum infections around Poyang Lake, China: Villages studied and snail sampling strategy

An epidemiologic survey among four administrative villages around Poyang Lake, in Jiangxi Province, China (two experimental and two controls) is being conducted to determine if bovine infections are responsible for the persistence of human schistosomiasis transmission on Yangtze River marshlands. A previously published paper presented the experimental design and baseline data for humans and bovines. This paper presents basic data for the four villages using remote sensing, and baseline data for snails that includes geographic information systems and remote sensing technology to classify the areas of bovine grazing ranges and habitats suitable for snails. A new method for sampling Oncomelania snails in China is used to determine the distribution, density, and infection rates of snails throughout the grazing ranges from season to season over a four-year period. Hypothetically, treating bovines should reduce infection rates in snails to below the critical number necessary to maintain infections in man and bovines.

A generalized Markov sampler

A recent development of the Markov chain Monte Carlo (MCMC) technique is the emergence of MCMC samplers that allow transitions between different models. Such samplers make possible a range of computational tasks involving models, including model selection, model evaluation, model averaging and hypothesis testing. An example of this type of sampler is the reversible jump MCMC sampler, which is a generalization of the Metropolis-Hastings algorithm. Here, we present a new MCMC sampler of this type. The new sampler is a generalization of the Gibbs sampler, but somewhat surprisingly, it also turns out to encompass as particular cases all of the well-known MCMC samplers, including those of Metropolis, Barker, and Hastings. Moreover, the new sampler generalizes the reversible jump MCMC. It therefore appears to be a very general framework for MCMC sampling. This paper describes the new sampler and illustrates its use in three applications in Computational Biology, specifically determination of consensus sequences, phylogenetic inference and delineation of isochores via multiple change-point analysis.

A method of sampling blood from Australian freshwater turtles

Blood sampling is an essential technique in many herpetological studies. This paper describes a quick and humane technique to collect blood samples from three species of Australian chelid turtles ( Order Pleurodira): Chelodina expansa, Elseya latisternum, and Emydura macquarii signata.

Consequences of incorrect sampling procedures in resonance-based radar target identification

Radar target identification based on complex natural resonances is sometimes achieved by convolving a linear time-domain filter with a received target signature. The filter is constructed from measured or pre-calculated target resonances. The performance of the target identification procedure is degraded if the difference between the sampling rates of the target signature and the filter is ignored. The problem is investigated for the natural extinction pulse technique (E-pulse) for the case of identifying stick models of aircraft.

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.

Passive air sampling theory for semivolatile organic compounds

The mathematical modelling underlying passive air sampling theory can be based on mass transfer coefficients or rate constants. Generally, these models have not been inter-related. Starting with basic models, the exchange of chemicals between the gaseous phase and the sampler is developed using mass transfer coefficients and rate constants. Importantly, the inter-relationships between the approaches are demonstrated by relating uptake rate constants and loss rate constants to mass transfer coefficients when either sampler-side or air-side resistance is dominating chemical exchange. The influence of sampler area and sampler volume on chemical exchange is discussed in general terms and as they relate to frequently used parameters such as sampling rates and time to equilibrium. Where air-side or sampler-side resistance dominates, an increase in the surface area of the sampler will increase sampling rates. Sampling rates are not related to the sampler/air partition coefficient (K-SV) when air-side resistance dominates and increase with K-SV when sampler-side resistance dominates.

Heavy tails, importance sampling and cross-entropy

We consider the problem of estimating P(Yi + (...) + Y-n > x) by importance sampling when the Yi are i.i.d. and heavy-tailed. The idea is to exploit the cross-entropy method as a toot for choosing good parameters in the importance sampling distribution; in doing so, we use the asymptotic description that given P(Y-1 + (...) + Y-n > x), n - 1 of the Yi have distribution F and one the conditional distribution of Y given Y > x. We show in some specific parametric examples (Pareto and Weibull) how this leads to precise answers which, as demonstrated numerically, are close to being variance minimal within the parametric class under consideration. Related problems for M/G/l and GI/G/l queues are also discussed.