Genomic blueprints of sponge-prokaryote symbiosis are shared by low abundant and cultivatable Alphaproteobacteria

Marine sponges are early-branching, filter-feeding metazoans that usually host complex microbiomes comprised of several, currently uncultivatable symbiotic lineages. Here, we use a low-carbon based strategy to cultivate low-abundance bacteria from Spongia officinalis. This approach favoured the growth of Alphaproteobacteria strains in the genera Anderseniella, Erythrobacter, Labrenzia, Loktanella, Ruegeria, Sphingorhabdus, Tateyamaria and Pseudovibrio, besides two likely new genera in the Rhodobacteraceae family. Mapping of complete genomes against the metagenomes of S. officinalis, seawater, and sediments confirmed the rare status of all the above-mentioned lineages in the marine realm. Remarkably, this community of low-abundance Alphaproteobacteria possesses several genomic attributes common to dominant, presently uncultivatable sponge symbionts, potentially contributing to host fitness through detoxification mechanisms (e.g. heavy metal and metabolic waste removal, degradation of aromatic compounds), provision of essential vitamins (e.g. B6 and B12 biosynthesis), nutritional exchange (especially regarding the processing of organic sulphur and nitrogen) and chemical defence (e.g. polyketide and terpenoid biosynthesis). None of the studied taxa displayed signs of genome reduction, indicative of obligate mutualism. Instead, versatile nutrient metabolisms along with motility, chemotaxis, and tight-adherence capacities - also known to confer environmental hardiness - were inferred, underlying dual host-associated and free-living life strategies adopted by these diverse sponge-associated Alphaproteobacteria.PTDC/MAR-BIO/1547/2014; full PhD scholarship from the Erasmus Mundus Programme/SALAM EMA2 lot7/SALA1206422info:eu-repo/semantics/publishedVersio

Composição e abundância de peixes da interface entre as águas abertas e bancos de macrófitas e sua dinâmica nos períodos de crepúsculos matutino e vespertino, no lago Catalão, Amazonas, Brasil (Composition and abundance of fishes in the interface between open water and macrophyte banks, and the dynamics of this interface during morning and evening twilight, in lake Catalao, Amazonas, Brazil)

This work studied the composition and abundance of the fishes that move between macrophyte banks and open water during the morning twilight (CM) and afternoon twilight (CV). The collections were made using gillnets, along banks of Paspalum repens, at Catalão lake, in Amazonas, Brazil. A total of 222 individuals and 37 species were collected. Of these, 130 individuals were collected during the CM and 92 during the CV; 80 individuals were leaving during the CM and 40 individuals were leaving during the CV. Auchenipterus nuchalis, Pellona castelnaeana, Triportheus angulatus and T. albus were the most common and concentrated species collected in the CM and Pimelodus blochii was the most common species collected in the CV

A cana-de-açúcar na Transamazônica, PA: resultados de 8 anos de pesquisa, 1974/82.

bitstream/item/57751/1/Altamira-Doc5.pd

Optimization of filament antennas using the Gauss-Newton method

The project of the Yagi-Uda antenna was optimized using the Gauss-Newton method. The optimization consisted of specifying value interval for directivity, front-to-back ratio and beamwidth and, starting from a pre-defined initial model, the best values for the length and spacing of the elements were determined. For the direct modeling, the method of moments on the integral Pocklington equation was used, which consisted of obtaining the values of directivity, front-to-back ratio and beamwidth from the length and spacing between known elements. The procedure was applied to the synthesis of Yagi-Uda antennas with five and six elements and the results were found to be as good as those obtained in the literature using other optimization methods

2D cloud template matching - a comparison between iterative closest point and perfect match

Self-localization of mobile robots in the environment is one of the most fundamental problems in the robotics field. It is a complex and challenging problem due to the high requirements of autonomous mobile vehicles, particularly with regard to algorithms accuracy, robustness and computational efficiency. In this paper we present the comparison of two of the most used map-matching algorithm, which are the Iterative Closest Point and the Perfect Match. This category of algorithms are normally applied in localization based on natural landmarks. They were compared using an extensive collection of metrics, such as accuracy, computational efficiency, convergence speed, maximum admissible initialization error and robustness to outliers in the robots sensors data. The test results were performed in both simulated and real world environments.info:eu-repo/semantics/publishedVersio

A comparison of the Normal and Laplace distributions in the models of fuzzy probability distribution for portfolio selection

The propose of this work is applied the fuzzy Laplace distribution on a possibilistic mean-variance model presented by Li et al which appliehe fuzzy normal distribution. The theorem necessary to introduce the Laplace distribution in the model was demonstrated. It was made an analysis of the behavior of the fuzzy normal and fuzzy Laplace distributions on the portfolio selection with VaR constraint and risk-free investment considering real data. The results showns that were not difference in assets selection and in return rate, however, There was a change in the risk rate, which was higher in the Laplace distribution than in the normal distribution

An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method

This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed convergence to an ϵ-global minimizer of a constrained nonlinear optimization problem. The bound constrained subproblems that emerge at each iteration k of the framework are solved by an improved artificial fish swarm algorithm. Convergence to an ϵk-global minimizer of the HAL function is guaranteed with probability one, where ϵk→ϵ as k→∞. Preliminary numerical experiments show that the proposed paradigm compares favorably with other penalty-type methods.Fundação para a Ciência e a Tecnologia (FCT

On a hyperbolic augmented lagrangian artificial fish swarm based method: convergence issues

Fundação para a Ciência e a Tecnologia (FCT

AFSFilter: artificial fish swarm filter-based algorithm for global optimization

A fish swarm intelligence algorithm based on the filter set concept to accept, at each iteration, a population of trial solutions whenever they improve constraint violation or objective function, relative to the current solutions, is proposed for constrained global continuous optimization problems. Preliminary numerical results are provided.Fundação para a Ciência e a Tecnologia (FCT