Influence of sample type and collection method on Streptococcus mutans and Lactobacillus spp. counts in the oral cavity

Objectives: This study compared three methods of Streptococcus mutans and Lactobacillus spp. detection in the oral cavity: saliva swab (SS)-sample of stimulated saliva collected with swab; whole saliva (WS)-sample of 2 ml of stimulated saliva; and the dental plaque method (DP)-plaque sample of all dental surfaces.Methods: Thirty children were included in this study. In the first 15 children, the SS and WS methods were carried out before the dental plaque collection, and in the following 15, the sequence was inverted to evaluate possible interference of the methods sequence. The samples were diluted and inoculated in SB20 and Rogosa agar, respectively for S. mutans and Lactobacillus spp., at 37 degrees C for 48 h.Results: the results (cfu/mL) of S. mutans were analysed by the statistical Friedman's test. The levels of Lactobacillus spp. were analysed by descriptive statistics due to the high proportion of zero counts in the culture. In the first sequence of methods, the number of S. mutans counted for the SS method was inferior to DP and WS (P < 0.05), and the results for the WS and DP methods were similar. The detection of Lactobacillus spp. was observed just by the WS (100 %) and SS (14.3 %) methods. However, in the second experimental set the number of S. mutans detected by the DP method was similar to those of the SS and WS, however, the WS method showed higher values than SS (P < 0.05). A greater number of Lactobacillus spp. was detected by the WS method (100 %), followed by SS (55.5 %) and DP (33.3 %).Conclusions: the dental plaque collection and the sample of stimulated whole saliva presented similar results in the S. mutans count. The most suitable method to detect the Lactobacillus spp. level in the oral cavity is the stimulated whole saliva method. (c) 2004 Elsevier Ltd. All rights reserved.

Multivariate models for correlated count data

In this study, we deal with the problem of overdispersion beyond extra zeros for a collection of counts that can be correlated. Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial distributions have been considered. First, we propose a multivariate count model in which all counts follow the same distribution and are correlated. Then we extend this model in a sense that correlated counts may follow different distributions. To accommodate correlation among counts, we have considered correlated random effects for each individual in the mean structure, thus inducing dependency among common observations to an individual. The method is applied to real data to investigate variation in food resources use in a species of marsupial in a locality of the Brazilian Cerrado biome. © 2013 Copyright Taylor and Francis Group, LLC.

Analyzing Panel Count Data with Informative Observation Times

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying recurrent event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the recurrent event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximizing a conditional likelihood function of observed event counts and solving estimation equations. Large sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumor study is presented to illustrate the use of the proposed methods.

Effects of ground semen collection on weight bearing on hindquarters, libido, and semen parameters in stallions

Collection of semen on the ground from the standing stallion represents an alternative method to dummy mount semen collection and is of increasing popularity for sport stallions, males suffering from health problems, or in studs without a dummy or suitable mare at disposal. Our aim was to collect and compare spermatological and physiological data associated with traditional and ground semen collection. Twelve of 23 Franches-Montagnes stallions were selected to carry out semen collection on a dummy and while standing in a crossed experimental protocol. Semen quantity and quality parameters, weight bearing on hindquarters, and behavioral and libido data were recorded. Ground versus dummy mount semen collection was accompanied by lower seminal volume (15.9 ± 14.6 vs. 22.0 ± 13.3 mL; P < 0.01) and lower total sperm count (4.913 ± 2.721 × 10(9) vs. 6.544 ± 2.856 × 10(9) sperm; P < 0.001). No significant differences were found concerning sperm motility and viability. Time to ejaculation was longer, and the number of attempts to ejaculation was higher (P = 0.053) in the standing position compared with the mount on the dummy. A higher (P < 0.01) amount of tail flagging was manifested by the stallions during ejaculation on the dummy compared to when standing. There was no difference in weight bearing on hindquarters when comparing dummy collection (51.2 ± 2.5%) and standing collection (48.9 ± 5.5%). Ground semen collection can be considered as a viable option for stallions that cannot mount a dummy or a mare. However, it requires training and may be not easily accepted by all stallions. Owners should be advised that ground semen collection is associated with significantly lower sperm numbers than with dummy mount semen collection.

Electronic toll collection systems.

Texas Department of Transportation, Austin

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates

Garbage collection optimization for non uniform memory access architectures

Cache-coherent non uniform memory access (ccNUMA) architecture is a standard design pattern for contemporary multicore processors, and future generations of architectures are likely to be NUMA. NUMA architectures create new challenges for managed runtime systems. Memory-intensive applications use the system’s distributed memory banks to allocate data, and the automatic memory manager collects garbage left in these memory banks. The garbage collector may need to access remote memory banks, which entails access latency overhead and potential bandwidth saturation for the interconnection between memory banks. This dissertation makes five significant contributions to garbage collection on NUMA systems, with a case study implementation using the Hotspot Java Virtual Machine. It empirically studies data locality for a Stop-The-World garbage collector when tracing connected objects in NUMA heaps. First, it identifies a locality richness which exists naturally in connected objects that contain a root object and its reachable set— ‘rooted sub-graphs’. Second, this dissertation leverages the locality characteristic of rooted sub-graphs to develop a new NUMA-aware garbage collection mechanism. A garbage collector thread processes a local root and its reachable set, which is likely to have a large number of objects in the same NUMA node. Third, a garbage collector thread steals references from sibling threads that run on the same NUMA node to improve data locality. This research evaluates the new NUMA-aware garbage collector using seven benchmarks of an established real-world DaCapo benchmark suite. In addition, evaluation involves a widely used SPECjbb benchmark and Neo4J graph database Java benchmark, as well as an artificial benchmark. The results of the NUMA-aware garbage collector on a multi-hop NUMA architecture show an average of 15% performance improvement. Furthermore, this performance gain is shown to be as a result of an improved NUMA memory access in a ccNUMA system. Fourth, the existing Hotspot JVM adaptive policy for configuring the number of garbage collection threads is shown to be suboptimal for current NUMA machines. The policy uses outdated assumptions and it generates a constant thread count. In fact, the Hotspot JVM still uses this policy in the production version. This research shows that the optimal number of garbage collection threads is application-specific and configuring the optimal number of garbage collection threads yields better collection throughput than the default policy. Fifth, this dissertation designs and implements a runtime technique, which involves heuristics from dynamic collection behavior to calculate an optimal number of garbage collector threads for each collection cycle. The results show an average of 21% improvements to the garbage collection performance for DaCapo benchmarks.