Sanitary conditions of a colony of urban feral cats (Felis catus Linnaeus, 1758) in a zoological garden of Rio de Janeiro, Brazil

The colony of urban stray cats living in the Rio de Janeiro zoological garden was studied in order to develop a population and health control program. As many cats as possible were captured during two months (47 animals) and were classified according to gender, age, weight and coat markings. They were submitted to a general health evaluation, examined for the presence of ectoparasites and sent to a surgical neutering program. All animals had a blood sample drawn for CBC, platelet count, heartworm and retroviruses detection. Capillary blood smears were made for hemoparasites detection. Coat marking and colors were tabby (59.7%), followed by solid black (17%); torbie (10.6%); bicolor (10.6%) and harlequin (2.1%). The only ectoparasites found were fleas, which infested 28% of the animals. The hemoparasites found were Haemobartonella felis (38%) and piroplasmas that could not be differentiated between Cytauxzoon spp. and Babesia spp. (47%). No cat was found infected by Dirofilaria immitis or FeLV (Feline Leukemia Virus), although FIV (Feline Immunodeficiency Virus) antibodies could be detected (21%). There was no correlation between hemoparasites and FIV infections. The estimated total cat population (mark-recapture method) was 59; 68% female and 32% male, suggesting that a neutering program is in fact needed.

Models for pheromone evaluation in Ant Systems for Mobile Ad-hoc networks

On a mobile ad-hoc network environment, where the resources are scarce, the knowledge about the network's link state is essential to optimize the routing procedures. This paper presents a study about different pheromone evaluation models and how they react to possible changes in traffic rate. Observing how the pheromone value on a link changes, it could be possible to identify certain patterns which can indicate the path status. For this study, the behavior of the Ant System evaluation model was compared with a Temporal Active Pheromone model (a biological approach) and a Progressive Pheromone Reduction model with and without a maximum pheromone limit.

Sensitivity of an immunoenzymatic test for detection of ant-L. brasiliensis antibodies compared to other tests used for the diagnosis of American cutaneous leishmaniasis

The diagnosis of American cutaneous leishmaniasis (ACL) is frequently based on clinical and epidemiological data associated with the results of laboratory tests. Some laboratory methods are currently being applied for the diagnosis of ACL, among them the indirect immunofluorescence reaction (IIFR), the Montenegro skin test (MST), histopathological examination, and the polymerase chain reaction (PCR). The performance of these methods varies in a considerable proportion of patients. After the standardization of an immunoenzymatic test (ELISA) for the detection of IgG in the serum of patients with ACL using a crude Leishmania braziliensis antigen, the results obtained were compared to those of other tests routinely used for the diagnosis. The tests revealed the following sensitivity, when analyzed separately: 85% for ELISA IgG, 81% for PCR, 64.4% for MST, 58.1% for IIFR, and 34% for the presence of parasites in the biopsy. ELISA was positive in 75% of patients with ACL presenting a negative MST, in 84.8% of ACL patients with negative skin or mucous biopsies for the presence of the parasite, and in 100% of cases with a negative PCR. Thus, ELISA presented a higher sensitivity than the other tests and was useful as a complementary method for the diagnosis of ACL.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

Characterization of rabies virus isolated from a colony of Eptesicus furinalis bats in Brazil

Some bat species have adapted to the expanding human population by acquiring the ability to roost in urban buildings, increasing the exposure risk for people and domestic animals, and consequently, the likelihood of transmitting rabies. Three dead bats were found in the yard of a house in an urban area of Jundiaí city in the state of São Paulo in southeast Brazil. Two of the three bats tested positive for rabies, using Fluorescent Antibody and Mouse Inoculation techniques. A large colony of Eptesicus furinalis was found in the house's attic, and of the 119 bats captured, four more tested positive for rabies. The objectives of this study were to report the rabies diagnosis, characterize the isolated virus antigenically and genetically, and study the epidemiology of the colony.

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Chagas' disease: an algorithm for donor screening and positive donor counseling

Classical serological screening assays for Chagas' disease are time consuming and subjective. The objective of the present work is to evaluate the enzyme immuno-assay (ELISA) methodology and to propose an algorithm for blood banks to be applied to Chagas' disease. Seven thousand, nine hundred and ninety nine blood donor samples were screened by both reverse passive hemagglutination (RPHA) and indirect immunofluorescence assay (IFA). Samples reactive on RPHA and/or IFA were submitted to supplementary RPHA, IFA and complement fixation (CFA) tests. This strategy allowed us to create a panel of 60 samples to evaluate the ELISA methodology from 3 different manufacturers. The sensitivity of the screening by IFA and the 3 different ELISA's was 100%. The specificity was better on ELISA methodology. For Chagas disease, ELISA seems to be the best test for blood donor screening, because it showed high sensitivity and specificity, it is not subjective and can be automated. Therefore, it was possible to propose an algorithm to screen samples and confirm donor results at the blood bank.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Local diversity of tropical and temperature ant faunas (Hymenoptera, Formicidae)

Qualitative and quantitative collections of ants made in the region of Manaus, Brazil (evergreen tropical humid forest), and in western North Carolina, USA (deciduous temperate/wet forest), were undertaken to investigate. latitudinal patterns of ant diversity and community organization on regional and local scales. We have found to date 307 ant species in the Municipality of Manaus. Totals ranging from 134 to 270+ species have been reported in the literature for other tropical regions of less than 10,000km2. In contrast, temperate ant surveys generally report only SO to 150 species in similar or larger areas. Sampling at sardine baits set 10m apart on square grids, we found forest ecosystems near Manaus to be much richer and more diverse in ants than those sampled in North Carolina: 28 species vs. 5-10 species in 50 collections and 16 vs. 3 previously unrecorded species discovered with each doubling of sample size. Room's (1975a) results from climatically simllar Papua New Guinea forest agree closely with those from Manaus. We suggest that one important factor contributing to the increased diversity of tropical, omnivorous ants may be greater variety of nest sites available for specialization.

The persistence of ant-following birds in small amazonian forest fragments

SUMMARYMist-net captures of army ant-following bird were monitored during the isolation of central Amazonian forest fragments of 1 ha (n = 5), 10 ha (n = 4) and 100 ha (n = 1). Post-isolation captures of the three obligate ant-following birds Dendrocinela merula, Pithys albifrons, and Gymnopithys rufigula decreased significantly in all fragments. post-isolation captures of four facultative ant-following species were not significantly different in forest fragments of 1 ha and 10 ha, although two species decreased significantly in the 100 ha fragment. Experimental introductions of obligate species into small forest fragments in the absence and presence of introduced Eciton burchelli army ant colonies resulted in significantly greater recaptures of introduced birds when active army ant colonies were present. Of the 105 birds introduced, 58 ' 55%) crossed 100-320 m od dedorested area an were recaptured in continuous forest.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.