Culturable Bacterial Diversity From A Feed Water Of A Reverse Osmosis System, Evaluation Of Biofilm Formation And Biocontrol Using Phages.

Biofilm formation on reverse osmosis (RO) systems represents a drawback in the application of this technology by different industries, including oil refineries. In RO systems the feed water maybe a source of microbial contamination and thus contributes for the formation of biofilm and consequent biofouling. In this study the planktonic culturable bacterial community was characterized from a feed water of a RO system and their capacities were evaluated to form biofilm in vitro. Bacterial motility and biofilm control were also analysed using phages. As results, diverse Protobacteria, Actinobacteria and Bacteroidetes were identified. Alphaproteobacteria was the predominant group and Brevundimonas, Pseudomonas and Mycobacterium the most abundant genera. Among the 30 isolates, 11 showed at least one type of motility and 11 were classified as good biofilm formers. Additionally, the influence of non-specific bacteriophage in the bacterial biofilms formed in vitro was investigated by action of phages enzymes or phage infection. The vB_AspP-UFV1 (Podoviridae) interfered in biofilm formation of most tested bacteria and may represent a good alternative in biofilm control. These findings provide important information about the bacterial community from the feed water of a RO system that may be used for the development of strategies for biofilm prevention and control in such systems.

Partitioning The Net Effect Of Host Diversity On An Emerging Amphibian Pathogen.

The 'dilution effect' (DE) hypothesis predicts that diverse host communities will show reduced disease. The underlying causes of pathogen dilution are complex, because they involve non-additive (driven by host interactions and differential habitat use) and additive (controlled by host species composition) mechanisms. Here, we used measures of complementarity and selection traditionally employed in the field of biodiversity-ecosystem function (BEF) to quantify the net effect of host diversity on disease dynamics of the amphibian-killing fungus Batrachochytrium dendrobatidis (Bd). Complementarity occurs when average infection load in diverse host assemblages departs from that of each component species in uniform populations. Selection measures the disproportionate impact of a particular species in diverse assemblages compared with its performance in uniform populations, and therefore has strong additive and non-additive properties. We experimentally infected tropical amphibian species of varying life histories, in single- and multi-host treatments, and measured individual Bd infection loads. Host diversity reduced Bd infection in amphibians through a mechanism analogous to complementarity (sensu BEF), potentially by reducing shared habitat use and transmission among hosts. Additionally, the selection component indicated that one particular terrestrial species showed reduced infection loads in diverse assemblages at the expense of neighbouring aquatic hosts becoming heavily infected. By partitioning components of diversity, our findings underscore the importance of additive and non-additive mechanisms underlying the DE.

Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

Análise do investimento em climatização para bovinos de leite em sistema de alojamento free-stall

The difficulty in adapting European dairy cows breeds in Brazil affect considerably the milk production sector. Brazilian climatic conditions are not totally favorable and the development of new tecnologies is needed for the animals express their genetic potential, as well as their best feed conversion. An economical analysis of the applied investment in the free-stall climatization equipment in dairy housing, for estimating studies related to profit, possibility of return investment as well as time for this return is necessary. The objective of this research was to evaluate the influence of climatization investment in the milk production process and analyze the economical aspect of this investment. There were used 470 high productive dairy cows with genetic and morphologic homogeneous characteristics, and analyzed in two similar periods. Investment calculations were done using Excell®. The results were satisfactory and the invested capital was proved to return to the producer in a short term, 57 days.

Uso de redes neurais artificiais na identificação de vocalização de suínos

Animal welfare has been an important research topic in animal production mainly in its ways of assessment. Vocalization is found to be an interesting tool for evaluating welfare as it provides data in a non-invasive way as well as it allows easy automation of process. The present research had as objective the implementation of an algorithm based on artificial neural network that had the potential of identifying vocalization related to welfare pattern indicatives. The research was done in two parts, the first was the development of the algorithm, and the second its validation with data from the field. Previous records allowed the development of the algorithm from behaviors observed in sows housed in farrowing cages. Matlab® software was used for implementing the network. It was selected a retropropagation gradient algorithm for training the network with the following stop criteria: maximum of 5,000 interactions or error quadratic addition smaller than 0.1. Validation was done with sows and piglets housed in commercial farm. Among the usual behaviors the ones that deserved enhancement were: the feed dispute at farrowing and the eventual risk of involuntary aggression between the piglets or between those and the sow. The algorithm was able to identify through the noise intensity the inherent risk situation of piglets welfare reduction.

Análise bayesiana do modelo de herança monogênica no melhoramento vegetal: um exemplo com abobrinha

A common breeding strategy is to carry out basic studies to investigate the hypothesis of a single gene controlling the trait (major gene) with or without polygenes of minor effect. In this study we used Bayesian inference to fit genetic additive-dominance models of inheritance to plant breeding experiments with multiple generations. Normal densities with different means, according to the major gene genotype, were considered in a linear model in which the design matrix of the genetic effects had unknown coefficients (which were estimated in individual basis). An actual data set from an inheritance study of partenocarpy in zucchini (Cucurbita pepo L.) was used for illustration. Model fitting included posterior probabilities for all individual genotypes. Analysis agrees with results in the literature but this approach was far more efficient than previous alternatives assuming that design matrix was known for the generations. Partenocarpy in zucchini is controlled by a major gene with important additive effect and partial dominance.

Gluttonous predators: how to estimate prey size when there are too many prey

Prey size is an important factor in food consumption. In studies of feeding ecology, prey items are usually measured individually using calipers or ocular micrometers. Among amphibians and reptiles, there are species that feed on large numbers of small prey items (e.g. ants, termites). This high intake makes it difficult to estimate prey size consumed by these animals. We addressed this problem by developing and evaluating a procedure for subsampling the stomach contents of such predators in order to estimate prey size. Specifically, we developed a protocol based on a bootstrap procedure to obtain a subsample with a precision error of at the most 5%, with a confidence level of at least 95%. This guideline should reduce the sampling effort and facilitate future studies on the feeding habits of amphibians and reptiles, and also provide a means of obtaining precise estimates of prey size.

Brincando no ambiente natural : uma contribuição para o desenvolvimento sensorio-motor da criança portadora de paralisia cerebral

Universidade Estadual de Campinas . Faculdade de Educação Física