Bayesian Inference for ARFIMA Models

This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations. These methods utilize sequentially adaptive Bayesian learning, a sequential Monte Carlo algorithm that can exploit massively parallel desktop computing with graphics processing units (GPUs). The article identifies and solves several problems in the computation of the likelihood function that apparently have not been addressed in the literature. Four applications illustrate the utility of the approach. The most ambitious is an ARFIMA(2,d,2) model for the Campito tree ring time series (length 5405), for which the methods developed in the article provide an essentially uncorrelated sample of size 16,384 from the exact posterior distribution in under four hours. Less ambitious applications take as little as 4 minutes without exploiting GPUs.     

Statistical analysis of manual segmentations of structures in medical images

The problem of extracting anatomical structures from medical images is both very important and difficult. In this paper we are motivated by a new paradigm in medical image segmentation, termed Citizen Science, which involves a volunteer effort from multiple, possibly non-expert, human participants. These contributors observe 2D images and generate their estimates of anatomical boundaries in the form of planar closed curves. The challenge, of course, is to combine these different estimates in a coherent fashion and to develop an overall estimate of the underlying structure. Treating these curves as random samples, we use statistical shape theory to generate joint inferences and analyze this data generated by the citizen scientists. The specific goals in this analysis are: (1) to find a robust estimate of the representative curve that provides an overall segmentation, (2) to quantify the level of agreement between segmentations, both globally (full contours) and locally (parts of contours), and (3) to automatically detect outliers and help reduce their influence in the estimation. We demonstrate these ideas using a number of artificial examples and real applications in medical imaging, and summarize their potential use in future scenarios.     

Relationships among HIV risk beliefs, attitudes, and behaviors in sexually active, seronegative gay men

Safer-sex guidelines established during the early days of the HIV/AIDS epidemic have undergone very little revision despite some controversy. Although these guidelines have been widely disseminated in the gay community, many gay men continue to engage in behaviors that are believed to put them at high risk for transmission of HIV. This suggests either that they have not accepted safer-sex guidelines as accurate or that other factors override personal implementation of the guidelines. The study examined seronegative gay men's beliefs about the accuracy of safer sex guidelines and the men's participation in behaviors risky for transmitting HIV. The greatest disagreement between the men's beliefs and behaviors centered on the risk of oral intercourse; this suggests a need for clarification of the safer sex message about this behavior. The findings of this study support the need to reformulate safer-sex guidelines. When unprotected oral and anal sex are classified at the same level of risk, those who engage in unprotected oral sex may proceed to unprotected anal sex with less reservation.     

NIST micronutrients measurement quality assurance program: characterizing individual participant measurement performance over time

The mission of the Micronutrients Measurement Quality Assurance Program (M2QAP) at the National Institute of Standards and Technology is enhanced interlaboratory measurement comparability for fat-soluble vitamin-related measurands in human serum. We recently described improved tools for evaluating individual participant measurement performance in single interlaboratory comparison exercises; we here apply and extend these tools to the evaluation of participant performance over the entire 15-year history of the M2QAP. We describe and illustrate a set of interconnected graphical reporting tools for identifying long-term trends and single-exercise events. We document and discuss recurrent patterns we observe in the measurement performance characteristics for M2QAP participants. The graphical analysis techniques utilized may be applicable to other interlaboratory comparison programs.     

A Microcomputer-Based Laboratory Aid for Visually Impaired Students

Built with high-performance industrial boards, this portable microcomputer functions both as a CP/M-based data acquisition and analysis system with voice output and as a talking scientific calculator.     

Delivery method and supplement consumption by grazing ruminants: a review

The effectiveness of supplementation programs is affected by the ability to reduce intake variation and to meet target supplement consumption. A review was made of factors affecting variation in individual animal consumption of supplement by grazing cattle and sheep, including supplement type and feeding method, animal dominance and social interactions, and forage availability. The effects of palatability were not included. The proportion of animals not consuming supplement is increased by limited trough space, small supplement allowance, self-fed supplements, neophobia to feed or feed delivery devices, and group feeding situations. Variation in individual animal supplement intake is increased by excessive trough space, limited supplement allowance, self-fed supplements, feed and feed delivery equipment neophobia, and individual feeding of supplements. Factors influencing the percentage of animals consuming the target amount of supplement need to be more clearly identified. There seems to be an optimum level of feeding competition that reduces intake variation and improves the proportion of animals consuming adequate amounts of supplement, but this optimum varies with the feeding situation.     

In vitro evaluation of a series of N-dodecanoyl-L-amino acid methyl esters as dermal penetration enhancers

A series of N-dodecanoyl-L-amino acid methyl esters (1-10) and n-pentyl N-acetylprolinate (11) were evaluated for dermal enhancement properties using an in vitro diffusion cell technique. Methods of synthesis of these compounds were described. Enhancers were applied 1 h prior to drug treatment. Hydrocortisone was used as the model drug and was applied to excised hairless mouse skin as a saturated suspension in propylene glycol. Enhancement ratios (ER) were determined for permeability coefficient, 24 h diffusion cell receptor concentration (Q24), and 24 h full-thickness skin steroid content. Controls received no enhancer pretreatment of the skin. N-Dodecanoyl-L-proline (10) showed the highest Q24 value for total steroid (ER 13.7) while N-dodecanoyl-L-phenylalanine (5) showed the highest total steroid skin retention (ER 16.5).     

Quantitative comparison and analysis of brain image registrationusing frequency-adaptive wavelet shrinkage

In the field of template-based medical image analysis, image registration and normalization are frequently used to evaluate and interpret data in a standard template or reference atlas space. Despite the large number of image-registration (warping) techniques developed recently in the literature, only a few studies have been undertaken to numerically characterize and compare various alignment methods. In this paper, we introduce a new approach for analyzing image registration based on a selective-wavelet reconstruction technique using a frequency-adaptive wavelet shrinkage. We study four polynomial-based and two higher complexity nonaffine warping methods applied to groups of stereotaxic human brain structural (magnetic resonance imaging) and functional (positron emission tomography) data. Depending upon the aim of the image registration, we present several warp classification schemes. Our method uses a concise representation of the native and resliced (pre- and post-warp) data in compressed wavelet space to assess quality of registration. This technique is computationally inexpensive and utilizes the image compression, image enhancement, and denoising characteristics of the wavelet-based function representation, as well as the optimality properties of frequency-dependent wavelet shrinkage