Estudo lipidômico em folhas de cultivares de cana-de-açúcar e avaliação do papel desses metabólicos na ferrugem alaranjada

Pós-graduação em Química - IQ

Ação do extrato de glândulas salivares de fêmeas do carrapato Rhipicephalus sanguineus (Latreille, 1806) sobre a inibição da proliferação de células de linhagem tumoral

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

Evaluation of pH effects on genomic integrity in adipose-derived mesenchymal stem cells using the comet assay

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Diagnóstico laboratorial de Mycobacterium spp. em Botucatu e região, utilizando a técnica Reação em Cadeia da Polimerase (PCR) em material biológico e avaliação de condições associadas

Pós-graduação em Saúde Coletiva - FMB

Aplicação de um jogo digital e análise de conceitos da teoria cinética dos gases

Pós-graduação em Educação para a Ciência - FC

Diversity and genetic structure in natural populations of Hancornia speciosa var. speciosa Gomes in northeastern Brazil

Hancornia speciosa Gomes is a fruit tree native from Brazil that belongs to Apocinaceae family, and is popularly known as Mangabeira. Its fruits are widely consumed raw or processed as fruit jam, juices and ice creams, which have made it a target of intense exploitation. The extractive activities and intense human activity on the environment of natural occurrence of H. speciosa has caused genetic erosion in the species and little is known about the ecology or genetic structure of natural populations. The objective of this research was the evaluation of the genetic diversity and genetic structure of H. speciosa var. speciosa. The genetic variability was assessed using 11 allozyme loci with a sample of 164 individuals distributed in six natural populations located in the States of Pernambuco and Alagoas, Northeastern Brazil. The results showed a high level of genetic diversity within the species (e= 0.36) seeing that the most of the genetic variability of H. speciosa var. speciosa is within its natural populations with low difference among populations ( or = 0.081). The inbreeding values within ( = -0.555) and among populations ( =-0.428) were low showing lacking of endogamy and a surplus of heterozygotes. The estimated gene flow ( m ) was high, ranging from 2.20 to 13.18, indicating to be enough to prevent the effects of genetic drift and genetic differentiation among populations. The multivariate analyses indicated that there is a relationship between genetic and geographical distances, which was confirmed by a spatial pattern analysis using Mantel test (r = 0.3598; p = 0.0920) with 1000 random permutations. The high genetic diversity index in these populations indicates potential for in situ genetic conservation.

Nano-engineering of composite material via reactive mechanical alloying/milling (RMA/M)

Attempts to strengthen a chromium-modified titanium trialuminide by a combination of grain size refinement and dispersoid strengthening led to a new means to synthesize such materials. This Reactive Mechanical Alloying/Milling process uses in situ reactions between the metallic powders and elements from a process control agent and/or a gaseous environment to assemble a dispersed small hard particle phase within the matrix by a bottom-up approach. In the current research milled powders of the trialuminide alloy along with titanium carbide were produced. The amount of the carbide can be varied widely with simple processing changes and in this case the milling process created trialuminide grain sizes and carbide particles that are the smallest known from such a process. Characterization of these materials required the development of x-ray diffraction means to determine particle sizes by deconvoluting and synthesizing components of the complex multiphase diffraction patterns and to carry out whole pattern analysis to analyze the diffuse scattering that developed from larger than usual highly defective grain boundary regions. These identified regions provide an important mass transport capability in the processing and not only facilitate the alloy development, but add to the understanding of the mechanical alloying process. Consolidation of the milled powder that consisted of small crystallites of the alloy and dispersed carbide particles two nanometers in size formed a unique, somewhat coarsened, microstructure producing an ultra-high strength solid material composed of the chromium-modified titanium trialuminide alloy matrix with small platelets of the complex carbides Ti2AlC and Ti3AlC2. This synthesis process provides the unique ability to nano-engineer a wide variety of composite materials, or special alloys, and has shown the ability to be extended to a wide variety of metallic materials.

Active Testing for Face Detection and Localization

We provide a novel search technique which uses a hierarchical model and a mutual information gain heuristic to efficiently prune the search space when localizing faces in images. We show exponential gains in computation over traditional sliding window approaches, while keeping similar performance levels.

Unified detection and tracking of instruments during retinal microsurgery

Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not naturally take advantage of target motion continuity during detection. The advantage of local optimization is efficiency and accuracy, but it requires additional algorithms to initialize tracking when the target is lost. To bridge these two approaches, we propose a framework for unified detection and tracking as a time-series Bayesian estimation problem. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a target in each frame. To do this we integrate the Active Testing (AT) paradigm with Bayesian filtering, and this results in a framework capable of both detecting and tracking robustly in situations where the target object enters and leaves the field of view regularly. We demonstrate our approach on a retinal tool tracking problem and show through extensive experiments that our method provides an efficient and robust tracking solution.

Design, development and field evaluation of a Spanish into sign language translation system

This paper describes the design, development and field evaluation of a machine translation system from Spanish to Spanish Sign Language (LSE: Lengua de Signos Española). The developed system focuses on helping Deaf people when they want to renew their Driver’s License. The system is made up of a speech recognizer (for decoding the spoken utterance into a word sequence), a natural language translator (for converting a word sequence into a sequence of signs belonging to the sign language), and a 3D avatar animation module (for playing back the signs). For the natural language translator, three technological approaches have been implemented and evaluated: an example-based strategy, a rule-based translation method and a statistical translator. For the final version, the implemented language translator combines all the alternatives into a hierarchical structure. This paper includes a detailed description of the field evaluation. This evaluation was carried out in the Local Traffic Office in Toledo involving real government employees and Deaf people. The evaluation includes objective measurements from the system and subjective information from questionnaires. The paper details the main problems found and a discussion on how to solve them (some of them specific for LSE).

Camera localization using trajectories and maps

We propose a new Bayesian framework for automatically determining the position (location and orientation) of an uncalibrated camera using the observations of moving objects and a schematic map of the passable areas of the environment. Our approach takes advantage of static and dynamic information on the scene structures through prior probability distributions for object dynamics. The proposed approach restricts plausible positions where the sensor can be located while taking into account the inherent ambiguity of the given setting. The proposed framework samples from the posterior probability distribution for the camera position via data driven MCMC, guided by an initial geometric analysis that restricts the search space. A Kullback-Leibler divergence analysis is then used that yields the final camera position estimate, while explicitly isolating ambiguous settings. The proposed approach is evaluated in synthetic and real environments, showing its satisfactory performance in both ambiguous and unambiguous settings.