Caracterização genética de leiteira (Euphorbia heterophylla) com tolerância ao glyphosate.

2016

Genetic analysis of the gametophytes of Undaria pinnatifida (Phaeophyceae) with ISSR method

Inter-simple sequence repeat (ISSR) analysis was used to assess eleven pairs of Undaria pinnatifida (Harv.) Suringar male and female gametophytes. After screening fifty primers, 18 ISSR primers were selected for final analysis. A total of 104 loci were obtained, of which 77 were polymorphic, among the gametophytes studied. Genetic relationships were analyzed with simple matching (S), Jaccard's (J) and Dice's (D) distance coefficients. Little genetic variations were found among the selected Undaria gametophytes, for instance, the genetic distances ranging from 0.010 to 0.125 with Dice coefficients. UPGMA dendrograms showed that 11 pairs of Undaria gametophytes were distributed into five groups. Most Undaria strains cultivated in China exhibited closely genetic relationships with the strains from Japan. However, gametophytes from Qingdao appeared as distinct clades from other Undaria strains with all three distance coefficients used. Mantel test showed that the three distance measurements generated congruent clustering patterns on the same data. Our results demonstrated the feasibility of applying ISSR markers for genetic analysis of Undaria gametophytes. (c) 2006 Elsevier B.V. All rights reserved.

Identification and assessing the cultivars of Laminaria Lamx. (phaeophyceae) with molecular markers

Molecular markers were used to identify and assess cultivars of Laminaria Lamx. and to delineate their phylogenetic relationships. Random amplified polymorphic DNA (RAPD) analysis was used for detection. After screening, 11 primers were selected and they yielded 133 bands in all, of which approximately 99.2% were polymorphic. The genetic distances between gametophytes ranged from 0.412 to 0.956. Two clusters were formed with the unweighted pair group method with arithmetic mean (UPGMA) dendrogram based on the simple matching coefficient. All cultivars of Laminaria japonica Aresch. used for breeding in China fell into one cluster. L. japonica from Japan, L. saccharina (L.) Lam., and L. angustata Kjellm. formed the other cluster and showed higher genetic variation than L. japonica from China. Nuclear ribosomal DNA (rDNA) sequences, including internal transcribed spacers (ITS1 and ITS2) were studied and aligned. The nucleotides of the sequences ranged from 634 to 668, with a total of 692 positions including TTS1, ITS2, and the 5.8S coding region. The phylogenetic tree obtained by the neighbor-joining method favored, to some extent, the results revealed by RAPD analysis. The present study indicates that RAPD and ITS analyses could be used to identify and assess Laminaria germplasm and to distinguish some species and, even intraspecies, in Laminaria.

Polyclonal endemicity of Pseudomonas aeruginosa in a teaching hospital from Brazil: molecular typing of decade-old strains

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Assessment of genetic relationship between Klebsiella pneumoniae and Klebsiella oxytoca samples isolated from a dental office

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

PHYLOGENETIC STUDIES OF SOME SPECIES OF THE GENUS COFFEA .1. NUMERICAL-ANALYSIS OF FLAVONOID COMPOUNDS

Flavonoid compounds were analyzed in ripe fruit pulp of ten species of Coffea, including two cultivars of C. arabica and two of C. canephora. Three coefficients of similarity: Simple-Matching, Jaccard and Ochiai and three different clustering methods, Single Linkage, Complete Linkage and Unweighted Pair Group, Using Arithmetic Averages (UPGMA), were used to analyze the data.Jaccard and Ochiai's coefficients of association showed a more coherent result, when compared with taxonomic and hybridization studies. Inclusion of Psilanthopsis kapakata in the genus Coffea, as C. kapakata, is justified by the similarity of this species with other studied species, and clusters clearly approximate the species C. arabica and C. eugenioides. The latter is one of the possible parents of the allotetraploid species C. arabica, C. congensis is the only species whose position remains ambiguous, probably due to the fact that the plants of this species that were introduced into the Campinas collections, were hybrids and not typical of C. congensis.

PHYLOGENETIC STUDIES OF SOME SPECIES OF THE GENUS COFFEA .2. NUMERICAL-ANALYSIS OF ISOENZYMATIC DATA

Thirteen species of Coffea were studied for five enzymes systems, including alpha and beta esterase, alkaline phosphatase, acid phosphatase, malate dehydrogenase and acid dehydrogenase. Three coefficients of similarity: Simple Matching, Jaccard and Ochiai and three different clustering methods: Single Linkage, Complete Linkage and Unweighted Pair Group, using Arithmetic Averages (UPGMA) were used to analyse the data.The phylogenetic relationships among the twelve diploid species and between them and the tetraploid species C. arabica showed that similarity among species of the same subsection is not always greater than among species of different subsections. In addition, although there are several similarity groups in common, established by isoenzymatic polymorphism, morphological characteristics, chemical data, crossability and geographic distribution, there is no common trend among the phylogenetic relationships as indicated by all these different evaluating procedures.

Essays on labor economics.

Doctor of Philosophy in subject of Economics

SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases

The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the efficient alignment of large-scale knowledge bases still poses a considerable challenge. Here, we present Simple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts. SiGMa is an iterative propagation algorithm which leverages both the structural information from the relationship graph as well as flexible similarity measures between entity properties in a greedy local search, thus making it scalable. Despite its greedy nature, our experiments indicate that SiGMa can efficiently match some of the world's largest knowledge bases with high precision. We provide additional experiments on benchmark datasets which demonstrate that SiGMa can outperform state-of-the-art approaches both in accuracy and efficiency.

CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

Edge-to-edge matching and its applications - Part I. Application to the simple HCP/BCC system

The edge-to-edge matching crystallographic model has been used to predict all the orientation relationships (OR) between crystals that have simple hexagonal close packed (HCP) and body-centered cubic (BCC) structures. Using the critical values for the interatomic spacing misfit along the matching directions and the cl-value mismatch between matching planes, the model predicted all the four common ORs, namely the Burgers OR, the Potter OR, the Pitsch-Schrader OR and the Rong Dunlop OR, together with the corresponding habit planes. Taking the c(H)/a(H) and a(H)/a(B) ratios as variables, where H and B denote the HCP and BCC structures respectively, the model also predicted the relationship between these variables and the four ORs. These predictions are perfectly consistent with the published experimental results. As was the case in the FCC/BCC system, the edge-to-edge matching model has been shown to be a powerful tool for predicting the crystallographic features of diffusion-controlled phase transformations. (C) 2004 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The role of sensation seeking and need for cognition on web-site evaluations : a resource-matching perspective

The Internet theoretically enables marketers to personalize a Website to an individual consumer. This article examines optimal Website design from the perspective of personality trait theory and resource-matching theory. The influence of two traits relevant to Internet Web-site processing—sensation seeking and need for cognition— were studied in the context of resource matching and different levels of Web-site complexity. Data were collected at two points of time: personality-trait data and a laboratory experiment using constructed Web sites. Results reveal that (a) subjects prefer Web sites of a medium level of complexity, rather than high or low complexity; (b)high sensation seekers prefer complex visual designs, and low sensation seekers simple visual designs, both in Web sites of medium complexity; and (c) high need-for-cognition subjects evaluated Web sites with high verbal and low visual complexity more favourably.

Wide-baseline keypoint detection and matching with wide-angle images for vision based localisation

This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.