936 resultados para Embedded module


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Paraffin-embedded samples commonly stored at educational and research institutions constitute tissues banks for follow-up or epidemiological studies; however, the paraffin inclusion process involves the use of substances that can cause DNA degradation. In this study, a PCR protocol was applied to identify Leishmania strains in 33 paraffin-embedded skin samples of patients with American cutaneous leishmaniasis. DNA was obtained by the phenol-chloroform protocol following paraffin removal and then used in PCR or nested PCR based on the nucleotide sequence of the small subunit ribosomal RNA (SSU rDNA). The amplicons obtained were cloned and sequenced to determine the single nucleotide polymorphism that distinguishes between different Leishmania species or groups. This assay allowed to distinguish organisms belonging to the subgenus Viannia and identify L. (Leishmania) amazonensis and L. (L.) chagasi of the Leishmania subgenus. Of the 33 samples, PCR and nested PCR identified 91% of samples. After sequencing the PCR product of 26 samples, 16 were identified as L. (L.) amazonensis, the other 10 contain organisms belonging to the L. (Viannia) sub-genus. These results open a huge opportunity to study stored samples and promote relevant contributions to epidemiological studies.

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Objective: Micro RNA (miRNA) is a class of small noncoding RNA that plays a major role in the regulation of gene expression, which has been related to cancer behavior. The possibility of analyzing miRNA from the archives of pathology laboratories is exciting, as it allows for large retrospective studies. Formalin is the most common fixative used in the surgical pathology routine, and its promotion of nucleic acid degradation is well known. Our aim is to compare miRNA profiles from formalin-fixed paraffin embedded (FFPE) tissues with fresh-frozen prostate cancer tissues. Methods: The expression of 14 miRNAs was determined by quantitative real time polymerase chain reaction (qRT-PCR) in 5 paired fresh-frozen and FFPE tissues, which were representative of prostate carcinoma. Results: There was a very good correlation of the miRNA expression of miR-let7c and miR-32 between the fresh-frozen and FFPE tissues, with Pearson`s correlation coefficients of 0.927 (P = 0.023) and 0.960 (P = 0.010), respectively. For the remaining miRNAs, the correlation was good with Spearman correlation coefficient of 0.638 (P < 0.001). Conclusion: Analysis of miRNAs from routinely processed and stored FFPE prostate tissue is feasible for some miRNAs using qRT-PCR. Further studies should be conducted to confirm the reliability of using stock tissues for miRNA expression determination. (C) 2011 Elsevier Inc. All rights reserved.

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At present, there is a variety of formalisms for modeling and analyzing the communication behavior of components. Due to a tremendous increase in size and complexity of embedded systems accompanied by shorter time to market cycles and cost reduction, so called behavioral type systems become more and more important. This chapter presents an overview and a taxonomy of behavioral types. The intentions of this taxonomy are to provide a guidance for software engineers and to form the basis for future research.

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This paper is concerned with the design of a Ku-band active transmit-array module of transistor amplifiers excited by either a pyramidal horn or a patch array Optimal distances between the active transmit array and the signal-launching:receiving device, which is either a passive corporate-fed array or a horn, are determined to maximise the power gain at a design frequency: Having established these conditions, the complete structure is investigated in terms of operational bandwidth and near-field and far-field distributions measured at the output side of the transmit array, The experimental results show that the use of a corporate-fed array as an illuminating/receiving device gives higher gain and significantly larger operational bandwidth, An explanation for this behavior is sought.

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Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.

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This paper proposes a wireless EEG acquisition platform based on Open Multimedia Architecture Platform (OMAP) embedded system. A high-impedance active dry electrode was tested for improving the scalp- electrode interface. It was used the sigma-delta ADS1298 analog-to-digital converter, and developed a “kernelspace” character driver to manage the communications between the converter unit and the OMAP’s ARM core. The acquired EEG signal data is processed by a “userspace” application, which accesses the driver’s memory, saves the data to a SD-card and transmits them through a wireless TCP/IP-socket to a PC. The electrodes were tested through the alpha wave replacement phenomenon. The experimental results presented the expected alpha rhythm (8-13 Hz) reactiveness to the eyes opening task. The driver spends about 725 μs to acquire and store the data samples. The application takes about 244 μs to get the data from the driver and 1.4 ms to save it in the SD-card. A WiFi throughput of 12.8Mbps was measured which results in a transmission time of 5 ms for 512 kb of data. The embedded system consumes about 200 mAh when wireless off and 400 mAh when it is on. The system exhibits a reliable performance to record EEG signals and transmit them wirelessly. Besides the microcontroller-based architectures, the proposed platform demonstrates that powerful ARM processors running embedded operating systems can be programmed with real-time constrains at the kernel level in order to control hardware, while maintaining their parallel processing abilities in high level software applications.