Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

Beherrschung stark korrelierter Logistik- und Produktions-Prozesse

Bei der Simulation von Logistik- und Produktionssystem werden Zufallszahlengeneratoren verwendet, um stochastische Einflüsse zu modellieren. Ein wichtiges Qualitätsmerkmal dieser Generatoren ist die Er-zeugung möglichst unabhängiger Zufallszahlen. Werden jedoch reale Prozesse betrachtet, so sind die Daten im Allgemeinen nicht unabhängig. Diese Arbeit befasst sich mit der Analyse von Praxisdaten bezüglich des Auftretens von Abhängigkeiten. Dazu werden Korrelationsstrukturen gesucht. Außerdem wird gezeigt, dass unabhängige Zufallszahlen in der Regel ungeeignet sind, um stochastische Prozesse mit ausgeprägten Abhängigkeiten zu modellieren.

Optical quantum random number generator

A physical random number generator based on the intrinsic randomness of quantum mechanics is described. The random events are realized by the choice of single photons between the two outputs of a beamsplitter. We present a simple device, which minimizes the impact of the photon counters’ noise, dead-time and after pulses.

In vitro differentiation of near-unlimited numbers of functional mouse basophils using conditional Hoxb8

Background: Basophils constitute a rare leukocyte population known for their effector functions in inflammation and allergy, as well as more recently described immunoregulatory roles. Besides their low frequency, functional analysis of basophils is hindered by a short life span, inefficient ex vivo differentiation protocols, and lack of suitable cell models. A method to produce large quantities of basophils in vitro would facilitate basophil research and constitute a sought-after tool for diagnostic and drug testing purposes. Methods: A method is described to massively expand bone marrow–derived basophils in vitro. Myeloid progenitors are conditionally immortalized using Hoxb8 in the presence of interleukin-3 (IL-3) and outgrowing cell lines selected for their potential to differentiate into basophils upon shutdown of Hoxb8 expression. Results: IL-3-dependent, conditional Hoxb8-immortalized progenitor cell lines can be expanded and maintained in culture for prolonged periods. Upon shutdown of Hoxb8 expression, near-unlimited numbers of mature functional basophils can be differentiated in vitro within six days. The cells are end-differentiated and short-lived and express basophil-specific surface markers and proteases. Upon IgE- as well as C5a-mediated activation, differentiated basophils release granule enzymes and histamine and secrete Th2-type cytokines (IL-4, IL-13) and leukotriene C4. IL-3-deprivation induces apoptosis correlating with upregulation of the BH3-only proteins BCL-2-interacting mediator of cell death (BIM) and p53 upregulated modulator of apoptosis (PUMA) and downregulation of proviral integration site for Moloney murine leukemia virus 1 kinase (PIM-1). Conclusion: A novel method is presented to generate quantitative amounts of mouse basophils in vitro, which moreover allows genetic manipulation of conditionally immortalized progenitors. This approach may represent a useful alternative method to isolating primary basophils.

Reporting quality of abstracts of randomized controlled trials published in dental specialty journals

OBJECTIVES A widespread assessment of the reporting of RCT abstracts published in dental journals is lacking. Our aim was to investigate the quality of reporting of abstracts published in leading dental specialty journals using, as a guide, the CONSORT for abstracts checklist. METHODS Electronic and supplementary hand searching were undertaken to identify RCTs published in seven dental specialty journals. The quality of abstract reporting was evaluated using a modified checklist based on the CONSORT for abstracts checklist. Descriptive statistics followed by univariate and multivariate analyses were conducted. RESULTS 228 RCT abstracts were identified. Reporting of interventions, objectives and conclusions within abstracts were adequate. Inadequately reported items included: title, participants, outcomes, random number generation, numbers randomized and effect size estimate. Randomization restrictions, allocation concealment, blinding, numbers analyzed, confidence intervals, intention-to-treat analysis, harms, registration and funding were rarely described. CONCLUSIONS The mean overall reporting quality score was suboptimal at 62.5% (95% CI: 61.9, 63.0). Significantly better abstract reporting was noted in certain specialty journals and in multicenter trials.

Efficiency of risk-based vs . random sampling for the monitoring of tetracycline residues in slaughtered calves in Switzerland

In all European Union countries, chemical residues are required to be routinely monitored in meat. Good farming and veterinary practice can prevent the contamination of meat with pharmaceutical substances, resulting in a low detection of drug residues through random sampling. An alternative approach is to target-monitor farms suspected of treating their animals with antimicrobials. The objective of this project was to assess, using a stochastic model, the efficiency of these two sampling strategies. The model integrated data on Swiss livestock as well as expert opinion and results from studies conducted in Switzerland. Risk-based sampling showed an increase in detection efficiency of up to 100% depending on the prevalence of contaminated herds. Sensitivity analysis of this model showed the importance of the accuracy of prior assumptions for conducting risk-based sampling. The resources gained by changing from random to risk-based sampling should be transferred to improving the quality of prior information.

Choosing a random distribution with prescribed risks

We describe several simulation algorithms that yield random probability distributions with given values of risk measures. In case of vanilla risk measures, the algorithms involve combining and transforming random cumulative distribution functions or random Lorenz curves obtained by simulating rather general random probability distributions on the unit interval. A new algorithm based on the simulation of a weighted barycentres array is suggested to generate random probability distributions with a given value of the spectral risk measure.

Stereological Modelling of Random Particles

Stochastic models for three-dimensional particles have many applications in applied sciences. Lévy–based particle models are a flexible approach to particle modelling. The structure of the random particles is given by a kernel smoothing of a Lévy basis. The models are easy to simulate but statistical inference procedures have not yet received much attention in the literature. The kernel is not always identifiable and we suggest one approach to remedy this problem. We propose a method to draw inference about the kernel from data often used in local stereology and study the performance of our approach in a simulation study.

Case and partnership reproduction numbers for a curable sexually transmitted infection

Sexually transmitted infections (STIs) are, by definition, transmitted between sexual partners. For curable STIs an infected index case can potentially re-infect the same partner multiple times. Thus, R0, the average number of secondary infections one typical infected individual will produce during his or her infectious period is not necessarily the same as the average number of secondary cases (infected persons). Here we introduce the new concept of the case reproduction number (Rc). In addition, we define the partnership reproduction number (Rp) as the average number of secondary partnerships consisting of two infected individuals one typical infected individual will produce over his or her infectious lifetime. Rp takes into account clearance and re-infection within partnerships, which results in a prolongation of the duration of the infectious period. The two new reproduction numbers were derived for a deterministic pair model with serial monogamous partnerships using infection parameters for Chlamydia trachomatis, an example of a curable STI. We showed that re-infection within partnerships means that curable STIs can be sustained endemically even when the average number of secondary cases a person produces during his or her infectious period is below one.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

Evidence for distinct modes of solar activity

The Sun shows strong variability in its magnetic activity, from Grand minima to Grand maxima, but the nature of the variability is not fully understood, mostly because of the insufficient length of the directly observed solar activity records and of uncertainties related to long-term reconstructions. Here we present a new adjustment-free reconstruction of solar activity over three millennia and study its different modes. Methods. We present a new adjustment-free, physical reconstruction of solar activity over the past three millennia, using the latest verified carbon cycle, 14C production, and archeomagnetic field models. This great improvement allowed us to study different modes of solar activity at an unprecedented level of details. Results. The distribution of solar activity is clearly bi-modal, implying the existence of distinct modes of activity. The main regular activity mode corresponds to moderate activity that varies in a relatively narrow band between sunspot numbers 20 and 67. The existence of a separate Grand minimum mode with reduced solar activity, which cannot be explained by random fluctuations of the regular mode, is confirmed at a high confidence level. The possible existence of a separate Grand maximum mode is also suggested, but the statistics is too low to reach a confident conclusion. Conclusions. The Sun is shown to operate in distinct modes – a main general mode, a Grand minimum mode corresponding to an inactive Sun, and a possible Grand maximum mode corresponding to an unusually active Sun. These results provide important constraints for both dynamo models of Sun-like stars and investigations of possible solar influence on Earth’s climate.