Comparison of Neck Skin Excision and Whole Carcass Rinse Sampling Methods for Microbiological Evaluation of Broiler Carcasses before and after Immersion Chilling

Sampling protocols for detecting Salmonella on poultry differ among various countries. In the United States, the U.S. Department of Agriculture Food Safety and Inspection Service dictates that whole broiler carcasses should be rinsed with 400 ml of 1% buffered peptone water, whereas in the European Union 25-g samples composed of neck skin from three carcasses are evaluated. The purpose of this study was to evaluate a whole carcass rinse (WCR) and a neck skin excision (NS) procedure for Salmonella and Escherichia coli isolation from the same broiler carcass. Carcasses were obtained from three broiler processing plants. The skin around the neck area was aseptically removed and bagged separately from the carcass, and microbiological analysis was performed. The corresponding carcass was bagged and a WCR sample was evaluated. No significant difference (alpha <= 0.05) in Salmonella prevalence was found between the samples processed by the two methods, but both procedures produced many false-negative Salmonella results. Prechill, 37% (66 carcasses), 28% (50 carcasses), and 51% (91 carcasses) of the 180 carcasses examined were positive for Salmonella by WCR, NS, and both procedures combined, respectively. Postchill, 3% (5 carcasses), 7% (12 carcasses), and 10% (17 carcasses) of the 177 carcasses examined were positive for Salmonella by the WCR, NS, and combination of both procedures, respectively. Prechill, E. coli plus coliform counts were 3.0 and 2.6 log CFU/ml by the WCR and NS methods, respectively. Postchill. E. coli plus coliform counts were 1.7 and 1.4 log CFU/ml by the WCR and NS methods, respectively.

Development and calibration of a portable radon sampling system for groundwater (222)Rn activity concentration measurements

The assembling of a system for field sampling and activity concentration measurement of radon dissolved in groundwater is described. Special attention is given in presenting the calibration procedure to obtain the radon activity concentration in groundwater from the raw counting rate registered in a portable scintillation detector and in establishing the precision of the activity concentration measurements. A field procedure was established and the system tested during one year of monthly observations of (222)Rn activity concentration in groundwater drawn from two wells drilled on metamorphic rocks exposed at Eastern Sao Paulo State, Brazil. The observed mean (222)Rn activity concentrations are 374 Bq/dm(3) in one well and about 1275 Bq/dm(3) in the other one. In both wells the (222)Rn activity concentrations showed a seasonal variation similar to variations previously reported in the literature for the same region. (C) 2009 Elsevier Ltd. All rights reserved.

Temporal Diversity Patterns and Phenology in Fruit-feeding Butterflies in the Atlantic Forest

The Atlantic Forest deserves special attention due to its high level of species endemism and degree of threat. As in other tropical biomes, there is little information about the ecology of the organisms that occur there. The objectives of this study were to verify how fruit-feeding butterflies are distributed through time, and the relation with meteorological conditions. Species richness and Shannon index were partitioned additively at the monthly level, and beta diversity, used as a hierarchical measure of temporal species turnover, was calculated among months, trimesters, and semesters. Circular analysis was used to verify how butterflies are distributed along seasons and its relation with meteorological conditions. We sampled 6488 individuals of 73 species. Temporal diversity of butterflies was more grouped than expected by chance among the months of each trimester. Circular analyses revealed that diversity is concentrated in hot months (September-March), with the subfamily Brassolinae strongly concentrated in February-March. Average temperature was correlated with total abundance of butterflies, abundance of Biblidinae, Brassolinae and Morphinae, and richness of Satyrinae. The present results show that 3mo of sampling between September and March is enough to produce a nonbiased sample of the local assemblage of butterflies, containing at least 70 percent of the richness and 25 percent of abundance. The influence of temperature on sampling is probably related to butterfly physiology. Moreover, temperature affects resource availability for larvae and adults, which is higher in hot months. The difference in seasonality patterns among subfamilies is probably a consequence of different evolutionary pressures through time.

Comparing methods for sampling large- and medium-sized mammals: camera traps and track plots

Activities involving fauna monitoring are usually limited by the lack of resources; therefore, the choice of a proper and efficient methodology is fundamental to maximize the cost-benefit ratio. Both direct and indirect methods can be used to survey mammals, but the latter are preferred due to the difficulty to come in sight of and/or to capture the individuals, besides being cheaper. We compared the performance of two methods to survey medium and large-sized mammal: track plot recording and camera trapping, and their costs were assessed. At Jatai Ecological Station (S21 degrees 31`15 ``- W47 degrees 34`42 ``-Brazil) we installed ten camera traps along a dirt road directly in front of ten track plots, and monitored them for 10 days. We cleaned the plots, adjusted the cameras, and noted down the recorded species daily. Records taken by both methods showed they sample the local richness in different ways (Wilcoxon, T=231; p;;0.01). The track plot method performed better on registering individuals whereas camera trapping provided records which permitted more accurate species identification. The type of infra-red sensor camera used showed a strong bias towards individual body mass (R(2)=0.70; p=0.017), and the variable expenses of this method in a 10-day survey were estimated about 2.04 times higher compared to track plot method; however, in a long run camera trapping becomes cheaper than track plot recording. Concluding, track plot recording is good enough for quick surveys under a limited budget, and camera trapping is best for precise species identification and the investigation of species details, performing better for large animals. When used together, these methods can be complementary.

The Prospective and Retrospective Memory Questionnaire: A population-based random sampling study

The Prospective and Retrospective Memory Questionnaire (PRMQ) has been shown to have acceptable reliability and factorial, predictive, and concurrent validity. However, the PRMQ has never been administered to a probability sample survey representative of all ages in adulthood, nor have previous studies controlled for factors that are known to influence metamemory, such as affective status. Here, the PRMQ was applied in a survey adopting a probabilistic three-stage cluster sample representative of the population of Sao Paulo, Brazil, according to gender, age (20-80 years), and economic status (n=1042). After excluding participants who had conditions that impair memory (depression, anxiety, used psychotropics, and/or had neurological/psychiatric disorders), in the remaining 664 individuals we (a) used confirmatory factor analyses to test competing models of the latent structure of the PRMQ, and (b) studied effects of gender, age, schooling, and economic status on prospective and retrospective memory complaints. The model with the best fit confirmed the same tripartite structure (general memory factor and two orthogonal prospective and retrospective memory factors) previously reported. Women complained more of general memory slips, especially those in the first 5 years after menopause, and there were more complaints of prospective than retrospective memory, except in participants with lower family income.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of Document Collections

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.

HIERARCHICAL DECOMPOSITION OF MULTICLASS PROBLEMS

Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.

Aerosol inorganic composition at a tropical site: Discrepancies between filter-based sampling and a semi-continuous method

The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.

Numerical analysis of an incremented statistical sampling procedure in MCNP

MCNP has stood so far as one of the main Monte Carlo radiation transport codes. Its use, as any other Monte Carlo based code, has increased as computers perform calculations faster and become more affordable along time. However, the use of Monte Carlo method to tally events in volumes which represent a small fraction of the whole system may turn to be unfeasible, if a straight analogue transport procedure (no use of variance reduction techniques) is employed and precise results are demanded. Calculations of reaction rates in activation foils placed in critical systems turn to be one of the mentioned cases. The present work takes advantage of the fixed source representation from MCNP to perform the above mentioned task in a more effective sampling way (characterizing neutron population in the vicinity of the tallying region and using it in a geometric reduced coupled simulation). An extended analysis of source dependent parameters is studied in order to understand their influence on simulation performance and on validity of results. Although discrepant results have been observed for small enveloping regions, the procedure presents itself as very efficient, giving adequate and precise results in shorter times than the standard analogue procedure. (C) 2007 Elsevier Ltd. All rights reserved.

Hierarchical spherical model from a geometric point of view

A continuous version of the hierarchical spherical model at dimension d=4 is investigated. Two limit distributions of the block spin variable X(gamma), normalized with exponents gamma = d + 2 and gamma=d at and above the critical temperature, are established. These results are proven by solving certain evolution equations corresponding to the renormalization group (RG) transformation of the O(N) hierarchical spin model of block size L(d) in the limit L down arrow 1 and N ->infinity. Starting far away from the stationary Gaussian fixed point the trajectories of these dynamical system pass through two different regimes with distinguishable crossover behavior. An interpretation of this trajectories is given by the geometric theory of functions which describe precisely the motion of the Lee-Yang zeroes. The large-N limit of RG transformation with L(d) fixed equal to 2, at the criticality, has recently been investigated in both weak and strong (coupling) regimes by Watanabe (J. Stat. Phys. 115:1669-1713, 2004) . Although our analysis deals only with N = infinity case, it complements various aspects of that work.

Hierarchical spatial organization of geographical networks

In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

Hierarchical Assembly of CaMoO(4) Nano-Octahedrons and Their Photoluminescence Properties

Hierarchical assemblies of CaMoO4 (CM) nano-octahedrons were obtained by microwave-assisted hydrothemial synthesis at 120 degrees C for different times. These structures were structurally, morphologically and optically characterized by X-ray diffraction, micro-Raman spectroscopy, field-emission gun scanning electron microscopy, ultraviolet-visible absorption spectroscopy and photoluminescence measurements. First-principle calculations have been carried out to understand the structural and electronic order-disorder effects as a function of the particle/region size. Supercells of different dimensions were constructed to simulate the geometric distortions along both they and z planes of the scheelite structure. Based on these experimental results and with the help of detailed structural simulations, we were able to model the nature of the order-disorder in this important class of materials and discuss the consequent implications on its physical properties, in particular, the photoluminescence properties of CM nanocrystals.

Insights into the dynamics and sources of atmospheric lead and particulate matter in Sao Paulo, Brazil, from high temporal resolution sampling

We present the first results of a study investigating the processes that control concentrations and sources of Pb and particulate matter in the atmosphere of Sao Paulo City Brazil Aerosols were collected with high temporal resolution (3 hours) during a four-day period in July 2005 The highest Pb concentrations measured coincided with large fireworks during celebration events and associated to high traffic occurrence Our high-resolution data highlights the impact that a singular transient event can have on air quality even in a megacity Under meteorological conditions non-conducive to pollutant dispersion Pb and particulate matter concentrations accumulated during the night leading to the highest concentrations in aerosols collected early in the morning of the following day The stable isotopes of Pb suggest that emissions from traffic remain an Important source of Pb in Sao Paulo City due to the large traffic fleet despite low Pb concentrations in fuels (C) 2010 Elsevier BV All rights reserved

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.