Two Pine Endo-β-1,4-Glucanases Are Associated with Rapidly Growing Reproductive Structures

Two cDNA clones encoding endo-β-1,4-glucanases (EGases) were isolated from a radiata pine (Pinus radiata) cDNA library prepared from immature female strobili. The cDNAs PrCel1 (Pinus radiata cellulase 1) and PrCel2 encode proteins 509 and 515 amino acids in length, respectively, including putative signal peptides. Both proteins contain domains conserved in plant and bacterial EGases. The proteins PRCEL1 and PRCEL2 showed strong similarity to each other (76% amino acid identity), and higher similarity to TPP18 (73 and 67%, respectively), an EGase cloned from tomato (Lycopersicon esculentum) pistils, than to any other reported EGases. Northern-blot analyses indicated that both genes displayed a similar pattern of expression. The only significant difference was in the level of expression. In situ hybridizations were used to demonstrate that, within differentiating pine reproductive structures, PrCel1 expression was greatest in microsporangia in pollen strobili and near the developing ovule in the seed strobili. Expression was also found in vegetative tissues, especially in regions experiencing cell elongation, such as the elongating region of root tips. Both proteins have an ability to degrade carboxymethylcellulose in vitro. Genomic-blot analysis indicated the presence of a family of EGase genes in the radiata pine genome, and that PrCel1 and PrCel2 are transcribed from distinct one-copy genes.

Molecular Cloning of Vacuolar H+-Pyrophosphatase and Its Developmental Expression in Growing Hypocotyl of Mung Bean1

Vacuolar proton-translocating inorganic pyrophosphatase and H+-ATPase acidify the vacuoles and power the vacuolar secondary active transport systems in plants. Developmental changes in the transcription of the pyrophosphatase in growing hypocotyls of mung bean (Vigna radiata) were investigated. The cDNA clone for the mung bean enzyme contains an uninterrupted open reading frame of 2298 bp, coding for a polypeptide of 766 amino acids. Hypocotyls were divided into elongating and mature regions. RNA analysis revealed that the transcript level of the pyrophosphatase was high in the elongating region of the 3-d-old hypocotyl but was extremely low in the mature region of the 5-d-old hypocotyl. The level of transcript of the 68-kD subunit of H+-ATPase also decreased after cell maturation. In the elongating region, the proton-pumping activity of pyrophosphatase on the basis of membrane protein was 3 times higher than that of H+-ATPase. After cell maturation, the pyrophosphatase activity decreased to 30% of that in the elongating region. The decline in the pyrophosphatase activity was in parallel with a decrease in the enzyme protein content. These findings indicate that the level of the pyrophosphatase, a main vacuolar proton pump in growing cells, is negatively regulated after cell maturation at the transcriptional level.

Circadian gating of cell division in cyanobacteria growing with average doubling times of less than 24 hours.

To ascertain whether the circadian oscillator in the prokaryotic cyanobacterium Synechococcus PCC 7942 regulates the timing of cell division in rapidly growing cultures, we measured the rate of cell division, DNA content, cell size, and gene expression (monitored by luminescence of the PpsbAI::luxAB reporter) in cultures that were continuously diluted to maintain an approximately equal cell density. We found that populations dividing at rates as rapid as once per 10 h manifest circadian gating of cell division, since phases in which cell division slows or stops recur with a circadian periodicity. The data clearly show that Synechococcus cells growing with doubling times that are considerably faster than once per 24 h nonetheless express robust circadian rhythms of cell division and gene expression. Apparently Synechococcus cells are able to simultaneously sustain two timing circuits that express significantly different periods.

Location of light-repressible, small GTP-binding protein of the YPT/rab family in the growing zone of etiolated pea stems.

YPT/rab proteins are ras-like small GTP-binding proteins that serve as key regulators of vesicular transport. The mRNA levels of two YPT/rab genes in pea plants are repressed by light, with the process mediated by phytochrome. Here, we examined the mRNA expression and the location of the two proteins, pra2- and pra3-encoded proteins, using monoclonal antibodies. The pra2 and pra3 mRNA levels were highest in the stems of dark-grown seedlings. The corresponding proteins were found in the cytosol and the membranes of the stems. Most of the pra2 protein was in the growing internodes, especially in the growing region, but the pra3 protein was widespread. These results suggest that the pra2 protein is important for vesicular transport in stems, possibly contributing to stem growth in the dark, and that the pra3 protein is important for general vesicular transport. The amounts of pra2 and pra3 proteins decreased with illumination. The decrease in these proteins may be related to the phytochrome-dependent inhibition of stem growth that occurs in etiolated pea seedlings.

Mulheres motoristas de caminhão: realidades, estereótipos e desafios

Introdução A presença de mulheres no transporte rodoviário de cargas tem sido cada vez mais crescente e as repercussões do trabalho na vida das motoristas de caminhão ainda são desconhecidas pela comunidade científica. Objetivo - Caracterizar e analisar o trabalho de mulheres motoristas de caminhão e suas repercussões sobre sua saúde, a partir do relato de homens e mulheres motoristas de caminhão. Metodologia - O estudo com abordagem qualitativa utilizou a técnica do grupo focal, entrevistas individuais e observação não participante. Os grupos focais foram realizados em uma empresa transportadora localizada no estado de São Paulo e as entrevistas individuais em evento realizado na cidade de Itupeva/SP. Em oito encontros, grupos de motoristas de caminhão, discutiram a temática trabalho e saúde conduzida por meio de questões semiabertas. As mesmas questões foram utilizadas para as entrevistas individuais. Os relatos foram gravados, sendo o conteúdo das gravações transcrito e analisado por meio da metodologia Análise de Conteúdo de Bardin. A partir dos dados obtidos, construíram-se as seguintes categorias: A trajetória profissional de motoristas de caminhão; As mulheres no Transporte Rodoviário de Cargas; O trabalho; Um momento inesquecível na profissão e A saúde das mulheres motoristas na estrada. Resultados Tornar-se motorista de caminhão, para a maioria das mulheres, ocorreu por acaso, ou devido à uma necessidade financeira, ou a falta de perspectiva de emprego. Para as mulheres no Transporte Rodoviário de Cargas, o cotidiano de trabalho das profissionais está atravessado por aspectos como: a força física; dúvidas e preconceitos quanto à sua orientação sexual; o desafio em conciliar a vida dentro e fora do caminhão; conflitos na vida conjugal decorrentes da vida profissional; a discriminação sexual e a necessidade do reconhecimento no trabalho, bem como a falta de infraestrutura dedicada às trabalhadoras nas empresas e postos de parada nas rodovias brasileiras. O momento inesquecível nesta profissão, considerado por homens e mulheres, foi a primeira viagem. Os impactos do trabalho sobre a saúde das trabalhadoras recaíram sobre dores lombares e na coluna; problemas relacionados ao sono; necessidade de recorrer ao uso de drogas como anfetaminas e cocaína para manterem-se acordadas durante o trabalho; estresse; infecção urinária e uso ininterrupto de anticoncepcionais. Conclusões - A inserção das mulheres no transporte rodoviário de cargas desafia empresas e a infraestrutura existente nas rodovias do país a acompanharem as transformações sociais no mundo do trabalho, incluindo as demandas de um novo perfil de trabalhadoras. Descritores: trabalho, gênero, saúde, motoristas de caminhão.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes

The Growing Neural Gas model is used widely in artificial neural networks. However, its application is limited in some contexts by the proliferation of nodes in dense areas of the input space. In this study, we introduce some modifications to address this problem by imposing three restrictions on the insertion of new nodes. Each restriction aims to maintain the homogeneous values of selected criteria. One criterion is related to the square error of classification and an alternative approach is proposed for avoiding additional computational costs. Three parameters are added that allow the regulation of the restriction criteria. The resulting algorithm allows models to be obtained that suit specific needs by specifying meaningful parameters.

Combining visual features and Growing Neural Gas networks for robotic 3D SLAM

The use of 3D data in mobile robotics provides valuable information about the robot’s environment. Traditionally, stereo cameras have been used as a low-cost 3D sensor. However, the lack of precision and texture for some surfaces suggests that the use of other 3D sensors could be more suitable. In this work, we examine the use of two sensors: an infrared SR4000 and a Kinect camera. We use a combination of 3D data obtained by these cameras, along with features obtained from 2D images acquired from these cameras, using a Growing Neural Gas (GNG) network applied to the 3D data. The goal is to obtain a robust egomotion technique. The GNG network is used to reduce the camera error. To calculate the egomotion, we test two methods for 3D registration. One is based on an iterative closest points algorithm, and the other employs random sample consensus. Finally, a simultaneous localization and mapping method is applied to the complete sequence to reduce the global error. The error from each sensor and the mapping results from the proposed method are examined.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

3D reconstruction of medical images from slices automatically landmarked with growing neural models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

An history of fungusses, growing about Halifax ... By James Bolton.

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An history of fungusses, growing about Halifax ... By James Bolton.

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A flora of North America :containing abridged descriptions of all the known indigenous and naturalized plants growing north of Mexico, arranged according to the natural system /by John Torrey and Asa Gray.

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Ageing Modernity: Growing old in the EU in the 21st Century. EU Centre in Singapore Background Brief No. 7, December 2012

How do urban growth and an ageing population affect or inform planning at the national and regional level in the European Union? At a time when economic stagnation, environmental concerns and demographic changes are affecting social and political discourses, they are also influencing urban form and development. Furthermore, as people are living longer, they still have much to contribute in their later years to their communities and to the economy. As a result, the policy and urban design paradigm is shifting as the relative importance of older people grows. By looking at the connections between ageing, design and the environment, and the role of policy and planning strategies, this brief seeks to understand how the EU plans for an ageing population and attempts to reshape communities in an increasingly challenging socioeconomic context. This brief looks at some of the regional initiatives and guidelines and highlights the role the EU is playing in influencing some of the development trends, particularly those in urban centres.