Métodos quantitativos para determinação de características bioquímicas e fisiológicas associadas com bactérias promotoras do crescimento vegetal.

Metodologia para as análises em laboratório; Produção de sideróforos; Produção de ácido indol acético (AIA); Produção de citocininas e giberelinas; Fixação assimbiotica de N2; Produção de quitinase; Producao de B-1,3-glucanase; Produção de 1-aminociclopropano-1-carboxylato deaminase; Produção de ácido cianidrico; Solubilizacao de fosfatos; Produção de pectinase; Produção de celulase; Antagonismo direto a fungos; Antagonismo indireto a fungos (compostos volateis); Antagonismo entre bacterias.

Marcadores moleculares: princípios básicos e uso em programas de melhoramento genético vegetal.

2000

Variabilidade e diversidade genética vegetal: requisito fundamental em um programa de melhoramento.

2002

Citogenética vegetal: da era clássica à molecular.

2007

Carbon nanotubes as adsorbent of solid-phase extraction and matrix for laser desorption/ionization mass spectrometry

A method with carbon nanotubes functioning both as the adsorbent of solid-phase extraction (SPE) and the matrix for matrix assisted laser desorption/ ionization mass spectrometry (MALDI-MS) to analyze small molecules in solution has been developed. In this method, 10 muL suspensions of carbon nanotubes in 50% (vol/vol) methanol were added to the sample solution to extract analytes onto surface of carbon nanotubes because of their dramatic hydrophobicity. Carbon nanotubes in solution are deposited onto the bottom of tube with centrifugation. After removing the supernatant fluid, carbon nanotubes are suspended again with dispersant and pipetted directly onto the sample target of the MALDI-MS to perform a mass spectrometric analysis. It was demonstrated by analysis of a variety of small molecules that the resolution of peaks and the efficiency of desorption/ ionization on the carbon nanotubes are better than those on the activated carbon. It is found that with the addition of glycerol and sucrose to the dispersant, the intensity, the ratio of signal to noise (S/N), and the resolution of peaks for analytes by mass spectrometry increased greatly. Compared with the previously reported method by depositing sample solution onto thin layer of carbon nanotubes, it is observed that the detection limit for analytes can be enhanced about 10 to 100 times due to solid-phase extraction of analytes in solution by carbon nanotubes. An acceptable result of simultaneously quantitative analysis of three analytes in solution has been achieved. The application in determining drugs spiked into urine has also been realized. (C) 2004 American Society for Mass Spectrometry.

Determination of organophosphorus pesticides in cucumber and potato by stir bar sorptive extraction

Organophosphorus pesticides (OPPs) in vegetables were determined by stir bar sorptive extraction (SBSE) and capillary gas chromatography with thermionic specific detection (TSD). Hydroxy-terminated polydimethylsioxane (PDMS) prepared by sol-gel method was used as extraction phase. The effects of extraction temperature, salting out, extraction time on extraction efficiency were studied. The detection limits of OPPs in water were <= 1.2 ng/l. This method was also applied to the analysis of OPPs in vegetable samples and matrix effect was studied. Linear ranges of OPPs in vegetable samples were 0.05-50 ng/g with detection limits <= 0. 15 ng/g and the repeatability of the method was less than 20% relative standard deviation. (c) 2005 Elsevier B.V. All rights reserved.

Irrigação na cultura da bucha vegetal.

2013

Visual Segmentation-Based Data Record Extraction From Web Documents

Li, Longzhuang, Liu, Yonghuai, Obregon, A., Weatherston, M. Visual Segmentation-Based Data Record Extraction From Web Documents. Proceedings of IEEE International Conference on Information Reuse and Integration, 2007, pp. 502-507. Sponsorship: IEEE

A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

Petacas tradicionales elaboradas en fibra vegetal de yaré por los indígenas Nukak Makú, y diversificación desarrollada por otras comunidades Guaviare.

15 hojas : ilustraciones, fotografías a color.

C 167 INST-D 2013. 348 Muestra de diversificación del diseño de sombreros elaborados en fibras de diferentes palmas e ilustraciones de sombreros tradicionales elaborados en fibra vegetal de palma sará.

15 fotografías a color.

Extraction of Caffeine from Energy Drinks

A simple procedure for the isolation of caffeine from energy drinks by solid phase extraction on a C18 cartridge. Quantitative analysis of the amount of caffeine by LC/MS is determined by referencing a standard curve.

Extraction and Clustering of Motion Trajectories in Video

A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clusters of similar trajectories in the video dataset. Objects' motion trajectories are extracted via an EKF formulation that provides each object's 3D trajectory up to a constant factor. To increase accuracy when occlusions occur, multiple tracking hypotheses are followed. For trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence (LCSS) is employed. Similarities are computed between projections of trajectories on coordinate axes. Trajectories are grouped based, using an agglomerative clustering algorithm. To check the validity of the approach, experiments using real data were performed.

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

Rule Extraction, Fuzzy ARTMAP, and Medical Databases

This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those recognition nodes whose confidence index falls below a selected threshold; and quantization of continuous learned weights allows the final system state to be translated into a usable set of rules. Simulations on a medical prediction problem, the Pima Indian Diabetes (PID) database, illustrate the method. In the simulations, pruned networks about 1/3 the size of the original actually show improved performance. Quantization yields comprehensible rules with only slight degradation in test set prediction performance.