Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Effectiveness of a new toothbrush design versus a conventional tongue scraper in improving breath odor and reducing tongue microbiota

For centuries, specific instruments or regular toothbrushes have routinely been used to remove tongue biofilm and improve breath odor. Toothbrushes with a tongue scraper on the back of their head have recently been introduced to the market. The present study compared the effectiveness of a manual toothbrush with this new design, i.e., possessing a tongue scraper, and a commercial tongue scraper in improving breath odor and reducing the aerobic and anaerobic microbiota of tongue surface. The evaluations occurred at 4 moments, when the participants (n=30) had their halitosis quantified with a halimeter and scored according to a 4-point scoring system corresponding to different levels of intensity. Saliva was collected for counts of aerobic and anaerobic microorganisms. Data were analyzed statistically by Friedman's test (p<0.05). When differences were detected, the Wilcoxon test adjusted for Bonferroni correction was used for multiple comparisons (group to group). The results confirmed the importance of mechanical cleaning of the tongue, since this procedure provided an improvement in halitosis and reduction of aerobe and anaerobe counts. Regarding the evaluated methods, the toothbrush's tongue scraper and conventional tongue scraper had a similar performance in terms of breath improvement and reduction of tongue microbiota, and may be indicated as effective methods for tongue cleaning.

Influence of specimens' design and manufacturing process on microtensile bond strength to enamel: laboratory and FEA comparison

This study evaluated the effect of specimens' design and manufacturing process on microtensile bond strength, internal stress distributions (Finite Element Analysis - FEA) and specimens' integrity by means of Scanning Electron Microscopy (SEM) and Laser Scanning Confocal Microscopy (LCM). Excite was applied to flat enamel surface and a resin composite build-ups were made incrementally with 1-mm increments of Tetric Ceram. Teeth were cut using a diamond disc or a diamond wire, obtaining 0.8 mm² stick-shaped specimens, or were shaped with a Micro Specimen Former, obtaining dumbbell-shaped specimens (n = 10). Samples were randomly selected for SEM and LCM analysis. Remaining samples underwent microtensile test, and results were analyzed with ANOVA and Tukey test. FEA dumbbell-shaped model resulted in a more homogeneous stress distribution. Nonetheless, they failed under lower bond strengths (21.83 ± 5.44 MPa)c than stick-shaped specimens (sectioned with wire: 42.93 ± 4.77 MPaª; sectioned with disc: 36.62 ± 3.63 MPa b), due to geometric irregularities related to manufacturing process, as noted in microscopic analyzes. It could be concluded that stick-shaped, nontrimmed specimens, sectioned with diamond wire, are preferred for enamel specimens as they can be prepared in a less destructive, easier, and more precise way.

Design, construction and evaluation of a simple pressurized solvent extraction system

This work describes the construction and testing of a simple pressurized solvent extraction (PSE) system. A mixture of acetone:water (80:20), 80 ºC and 103.5 bar, was used to extract two herbicides (Diuron and Bromacil) from a sample of polluted soil, followed by identification and quantification by high-performance liquid chromatography coupled with diode array detector (HPLC-DAD). The system was also used to extract soybean oil (70 ºC and 69 bar) using pentane. The extracted oil was weighed and characterized through the fatty acid methyl ester analysis (myristic (< 0.3%), palmitic (16.3%), stearic (2.8%), oleic (24.5%), linoleic (46.3%), linolenic (9.6%), araquidic (0.3%), gadoleic (< 0.3%), and behenic (0.3%) acids) using high-resolution gas chromatography with flame ionization detection (HRGC-FID). PSE results were compared with those obtained using classical procedures: Soxhlet extraction for the soybean oil and solid-liquid extraction followed by solid-phase extraction (SLE-SPE) for the herbicides. The results showed: 21.25 ± 0.36% (m/m) of oil in the soybeans using the PSE system and 21.55 ± 0.65% (m/m) using the soxhlet extraction system; extraction efficiency (recovery) of herbicides Diuron and Bromacil of 88.7 ± 4.5% and 106.6 ± 8.1%, respectively, using the PSE system, and 96.8 ± 1.0% and 94.2 ± 3.9%, respectively, with the SLP-SPE system; limit of detection (LOD) and limit of quantification (LOQ) for Diuron of 0.012 mg kg-1 and 0.040 mg kg-1, respectively; LOD and LOQ for Bromacil of 0.025 mg kg-1 and 0.083 mg kg-1, respectively. The linearity used ranged from 0.04 to 1.50 mg L-1 for Diuron and from 0.08 to 1.50 mg L-1 for Bromacil. In conclusion, using the PSE system, due to high pressure and temperature, it is possible to make efficient, fast extractions with reduced solvent consumption in an inert atmosphere, which prevents sample and analyte decomposition.

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Design and characterization of bridged loop-gap resonators for use in electron paramagnetic resonance measurements

This paper revisits the design of L and S band bridged loop-gap resonators (BLGRs) for electron paramagnetic resonance applications. A novel configuration is described and extensively characterized for resonance frequency and quality factor as a function of the geometrical parameters of the device. The obtained experimental results indicate higher values of the quality factor (Q) than previously reported in the literature, and the experimental analysis data should provide useful guidelines for BLGR design.

Design methodology for multi-pumped discrete Raman amplifiers: case-study employing photonic crystal fibers

This paper proposes a new design methodology for discrete multi-pumped Raman amplifier. In a multi-objective optimization scenario, in a first step the whole solution-space is inspected by a CW analytical formulation. Then, the most promising solutions are fully investigated by a rigorous numerical treatment and the Raman amplification performance is thus determined by the combination of analytical and numerical approaches. As an application of our methodology we designed an photonic crystal fiber Raman amplifier configuration which provides low ripple, high gain, clear eye opening and a low power penalty. The amplifier configuration also enables to fully compensate the dispersion introduced by a 70-km singlemode fiber in a 10 Gbit/s system. We have successfully obtained a configuration with 8.5 dB average gain over the C-band and 0.71 dB ripple with almost zero eye-penalty using only two pump lasers with relatively low pump power. (C) 2009 Optical Society of America

Analysis of the effects of conical indentation variables on the indentation response of elastic-plastic materials through factorial design of experiment

In this work, the effects of conical indentation variables on the load-depth indentation curves were analyzed using finite element modeling and dimensional analysis. A factorial design 2(6) was used with the aim of quantifying the effects of the mechanical properties of the indented material and of the indenter geometry. Analysis was based on the input variables Y/E, R/h(max), n, theta, E, and h(max). The dimensional variables E and h(max) were used such that each value of dimensionless Y/E was obtained with two different values of E and each value of dimensionless R/h(max) was obtained with two different h(max) values. A set of dimensionless functions was defined to analyze the effect of the input variables: Pi(1) = P(1)/Eh(2), Pi(2) = h(c)/h, Pi(3) = H/Y, Pi(4) = S/Eh(max), Pi(6) = h(max)/h(f) and Pi(7) = W(P)/W(T). These six functions were found to depend only on the dimensionless variables studied (Y/E, R/h(max), n, theta). Another dimension less function, Pi(5) = beta, was not well defined for most of the dimensionless variables and the only variable that provided a significant effect on beta was theta. However, beta showed a strong dependence on the fraction of the data selected to fit the unloading curve, which means that beta is especially Susceptible to the error in the Calculation of the initial unloading slope.

Multidisciplinary optimization of a catamaran's hydrofoil design with dynamic response surface and distributive processing

This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.

Hypotheses, rationale, design, and methods for prognostic evaluation in type 2 diabetic patients with angiographically normal coronary arteries. The MASS IV-DM Trial

Background: The MASS IV-DM Trial is a large project from a single institution, the Heart Institute (InCor), University of Sao Paulo Medical School, Brazil to study ventricular function and coronary arteries in patients with type 2 diabetes mellitus. Methods/Design: The study will enroll 600 patients with type 2 diabetes who have angiographically normal ventricular function and coronary arteries. The goal of the MASS IV-DM Trial is to achieve a long-term evaluation of the development of coronary atherosclerosis by using angiograms and coronary-artery calcium scan by electron-beam computed tomography at baseline and after 5 years of follow-up. In addition, the incidence of major cardiovascular events, the dysfunction of various organs involved in this disease, particularly microalbuminuria and renal function, will be analyzed through clinical evaluation. In addition, an effort will be made to investigate in depth the presence of major cardiovascular risk factors, especially the biochemical profile, metabolic syndrome inflammatory activity, oxidative stress, endothelial function, prothrombotic factors, and profibrinolytic and platelet activity. An evaluation will be made of the polymorphism as a determinant of disease and its possible role in the genesis of micro- and macrovascular damage. Discussion: The MASS IV-DM trial is designed to include diabetic patients with clinically suspected myocardial ischemia in whom conventional angiography shows angiographically normal coronary arteries. The result of extensive investigation including angiographic follow-up by several methods, vascular reactivity, pro-thrombotic mechanisms, genetic and biochemical studies may facilitate the understanding of so-called micro- and macrovascular disease of DM.

Disequilibrium Coefficient: A Bayesian Perspective

Hardy-Weinberg Equilibrium (HWE) is an important genetic property that populations should have whenever they are not observing adverse situations as complete lack of panmixia, excess of mutations, excess of selection pressure, etc. HWE for decades has been evaluated; both frequentist and Bayesian methods are in use today. While historically the HWE formula was developed to examine the transmission of alleles in a population from one generation to the next, use of HWE concepts has expanded in human diseases studies to detect genotyping error and disease susceptibility (association); Ryckman and Williams (2008). Most analyses focus on trying to answer the question of whether a population is in HWE. They do not try to quantify how far from the equilibrium the population is. In this paper, we propose the use of a simple disequilibrium coefficient to a locus with two alleles. Based on the posterior density of this disequilibrium coefficient, we show how one can conduct a Bayesian analysis to verify how far from HWE a population is. There are other coefficients introduced in the literature and the advantage of the one introduced in this paper is the fact that, just like the standard correlation coefficients, its range is bounded and it is symmetric around zero (equilibrium) when comparing the positive and the negative values. To test the hypothesis of equilibrium, we use a simple Bayesian significance test, the Full Bayesian Significance Test (FBST); see Pereira, Stern andWechsler (2008) for a complete review. The disequilibrium coefficient proposed provides an easy and efficient way to make the analyses, especially if one uses Bayesian statistics. A routine in R programs (R Development Core Team, 2009) that implements the calculations is provided for the readers.

Design and fabrication of microcavity-array superhydrophobic surfaces

We have modeled, fabricated, and characterized superhydrophobic surfaces with a morphology formed of periodic microstructures which are cavities. This surface morphology is the inverse of that generally reported in the literature when the surface is formed of pillars or protrusions, and has the advantage that when immersed in water the confined air inside the cavities tends to expel the invading water. This differs from the case of a surface morphology formed of pillars or protrusions, for which water can penetrate irreversibly among the microstructures, necessitating complete drying of the surface in order to again recover its superhydrophobic character. We have developed a theoretical model that allows calculation of the microcavity dimensions needed to obtain superhydrophobic surfaces composed of patterns of such microcavities, and that provides estimates of the advancing and receding contact angle as a function of microcavity parameters. The model predicts that the cavity aspect ratio (depth-to-diameter ratio) can be much less than unity, indicating that the microcavities do not need to be deep in order to obtain a surface with enhanced superhydrophobic character. Specific microcavity patterns have been fabricated in polydimethylsiloxane and characterized by scanning electron microscopy, atomic force microscopy, and contact angle measurements. The measured advancing and receding contact angles are in good agreement with the predictions of the model. (C) 2010 American Institute of Physics. [doi:10.1063/1.3466979]

Design and fabrication of superhydrophobic surfaces formed of microcavities

We have developed a theoretical model for superhydrophobic surfaces that are formed from an extended array of microcavities, and have fabricated specific microcavity patterns to form superhydrophobic surfaces of the kind modeled. The model shows that the cavity aspect ratio can be significantly less than unity, indicating that the microcavities do not need to be deep in order to enhance the superhydrophobic character of the surface. We have fabricated surfaces of this kind and measured advancing contact angle as high as 153 degrees, in agreement with predictions of the model.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.