Ultra light vertical array remote data acquisition system

SiPLAB Report 03/05, FCT, University of Algarve,2005.In the framework of the ATOMS project, a project devoted to study uppwelling processes off the S. Vicente Cape, Portugal, by oceanographic and acoustic means, it was requested to adapt an existent underwater acoustic acquisition system named Ultra Light Vertical Array (ULVA) to fulfil the project requirements. The ULVA system was a vertical instrumented with up to 16 hydrophones and various non-acoustic sensors (thermistors, tiltmeters and pressure gauges). The ULVA system was used during the INTIFANTE project sea trial, where the acquired data were transmitted through a radio link to a remote PC station located in a vessel for storage, monitoring and online processing. In order to overcome data loses due to radio link fails, identified during the INTIFANTE sea trial, and improve the mobility of the vessel where the PC station is located, a must for the ATOMS project, it was decided to transform the ULVA system into an autonomous acquisition system with local storage facilities, lower power consumption, capability of on line remote quality control of the acquired data and positioning information. The first version of this new system, named Ultra Light Vertical Array/Remote Data Acquisition System (ULVA/RDAS), was described in the report. During the sea trial MREA'04 it was found that an auxiliary UHF radio link used to send some commands to the ULVA, like switch on/off the power or switch on/off the array electronics, remains a source of problems in the ULVA/RDAS. Thus, it was decided to remove the UHF link from the system, emulating its facilities by new developed hardware. In this new version (second) of the ULVA/RDAS system, it was also introduced a new monitoring software, in order to improve its robustness and share a common user interface with other SiPLAB acquisition systems. This report describes the actual ULVA/RDAS system (version 2) and is intended as a system reference and user guide.FC

Problemas atuais da juticultura amazônica.

No presente trabalho, os autores procuraram expor os problemas atuais que entravam o desenvolvimento da juticultura amazônica, ressaltando a importância marcante da produção das fibras desta tiliácea como fonte da manutenção do mercado interno brasileiro de matéria prima necessária ao abastecimento do parque nacional de aniagem. Os problemas considerados, no trabalho em questão, foram: 1) problemas de ordem agrícola, 2) problemas de ordem sócio-econômica. Procurou-se, também, de forma sintética, expor a situação do mercado nacional e as possibilidades de exportação. Como conclusão, os autores admitem a necessidade urgente e prioritária de se estimular econômicamente o juticultor a fim de que se possa posteriormente mostrar que a quantidade e qualidade do produto depende em grande parte dos problemas culturais e tecnológicos.Separata da Pesquisa Agropecuária Brasileira, v. 1, p. 1-6, 1966

The Mass-to-Light Ratio of Binary Galaxies

We report on the mass-to-light ratio determination based on a newly selected binary galaxy sample, which includes a large number of pairs whose separations exceed a few hundred kpc. The probability distributions of the projected separation and the velocity difference have been calculated considering the contamination of optical pairs, and the mass-to-light ratio has been determined based on the maximum likelihood method. The best estimate of $M/L$ in the B band for 57 pairs is found to be 28 $\sim$ 36 depending on the orbital parameters and the distribution of optical pairs (solar unit, $H_0=50$ km s$^{-1}$ Mpc$^{-1}$). The best estimate of $M/L$ for 30 pure spiral pairs is found to be 12 $\sim$ 16. These results are relatively smaller than those obtained in previous studies, but consistent with each other within the errors. Although the number of pairs with large separation is significantly increased compared to previous samples, $M/L$ does not show any tendency of increase, but found to be almost independent of the separation of pairs beyond 100 kpc. The constancy of $M/L$ beyond 100 kpc may indicate that the typical halo size of spiral galaxies is less than $\sim 100$ kpc.Comment: 18 pages + 8 figures, to appear in ApJ Vol. 516 (May 10

Genetic gain in an improvement program of irrigated rice in Minas Gerais.

An evaluation of the genetic improvement programme of irrigated rice of Minas Gerais (Brazil) estimated the genetic gain obtained in the 90s. Grain yield data of the advanced comparative trials of cultivars and lines of continuously flooded rice, conducted from 1990-91 to 2000-01, were used. The estimate of the genetic gain was obtained by the methodology of the adjusted means proposed by Breseghello (1998). The mean annual genetic gain in the 90s was 42.45+or-17.89 kg ha-1 (0.7% per year). The improvement programme proved auspicious for the development of lines that outmatched the controls. The mean of the cultivars released in the 90s did however not outstrip the mean of the elite lines, which were the genotypes with the highest means in this study and will be further evaluated in the ongoing programme

Ubiquitin-specific proteases: Players in cancer cellular processes

Ubiquitination represents a post-translational modification (PTM) essential for the maintenance of cellular homeostasis. Ubiquitination is involved in the regulation of protein function, localization and turnover through the attachment of a ubiquitin molecule(s) to a target protein. Ubiquitination can be reversed through the action of deubiquitinating enzymes (DUBs). The DUB enzymes have the ability to remove the mono-or poly-ubiquitination signals and are involved in the maturation, recycling, editing and rearrangement of ubiquitin(s). Ubiquitin-specific proteases (USPs) are the biggest family of DUBs, responsible for numerous cellular functions through interactions with different cellular targets. Over the past few years, several studies have focused on the role of USPs in carcinogenesis, which has led to an increasing development of therapies based on USP inhibitors. In this review, we intend to describe different cellular functions, such as the cell cycle, DNA damage repair, chromatin remodeling and several signaling pathways, in which USPs are involved in the development or progression of cancer. In addition, we describe existing therapies that target the inhibition of USPs.This work was funded (in part) by the Programa Operacional Regional do Norte and co-funded by the European Regional Development Fund under the project “The Porto Comprehensive Cancer Center” with the reference NORTE-01-0145-FEDER-072678—Consórcio PORTO.CCC— Porto.Comprehensive Cancer Center. The authors acknowledge the support from the Portuguese Foundation for Science and Technology (FCT) that funded the contract to MC through the project PTDC/MED-ONC/31438/2017 (The Other Faces of Telomerase: Looking beyond Tumor Immortalization). The project is supported by NORTE 2020 under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF)/COMPETE 2020?Operacional Program for Competitiveness and Internationalization (POCI) and by Portuguese funds through FCT

A spatiotemporal deep learning approach for automatic pathological Gait classification

Human motion analysis provides useful information for the diagnosis and recovery assessment of people suffering from pathologies, such as those affecting the way of walking, i.e., gait. With recent developments in deep learning, state-of-the-art performance can now be achieved using a single 2D-RGB-camera-based gait analysis system, offering an objective assessment of gait-related pathologies. Such systems provide a valuable complement/alternative to the current standard practice of subjective assessment. Most 2D-RGB-camera-based gait analysis approaches rely on compact gait representations, such as the gait energy image, which summarize the characteristics of a walking sequence into one single image. However, such compact representations do not fully capture the temporal information and dependencies between successive gait movements. This limitation is addressed by proposing a spatiotemporal deep learning approach that uses a selection of key frames to represent a gait cycle. Convolutional and recurrent deep neural networks were combined, processing each gait cycle as a collection of silhouette key frames, allowing the system to learn temporal patterns among the spatial features extracted at individual time instants. Trained with gait sequences from the GAIT-IT dataset, the proposed system is able to improve gait pathology classification accuracy, outperforming state-of-the-art solutions and achieving improved generalization on cross-dataset tests.info:eu-repo/semantics/publishedVersio