922 resultados para Signal generators


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This masters thesis describes the development of signal processing and patternrecognition in monitoring Parkison’s disease. It involves the development of a signalprocess algorithm and passing it into a pattern recogniton algorithm also. Thesealgorithms are used to determine , predict and make a conclusion on the study ofparkison’s disease. We get to understand the nature of how the parkinson’s disease isin humans.

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Speech perception runs smoothly and automatically when there is silence in the background, but when the speech signal is degraded by background noise or by reverberation, effortful cognitive processing is needed to compensate for the signal distortion. Previous research has typically investigated the effects of signal-to-noise ratio (SNR) and reverberation time in isolation, whilst few have looked at their interaction. In this study, we probed how reverberation time and SNR influence recall of words presented in participants' first- (L1) and second-language (L2). A total of 72 children (10 years old) participated in this study. The to-be-recalled wordlists were played back with two different reverberation times (0.3 and 1.2 s) crossed with two different SNRs (+3 dBA and +12 dBA). Children recalled fewer words when the spoken words were presented in L2 in comparison with recall of spoken words presented in L1. Words that were presented with a high SNR (+12 dBA) improved recall compared to a low SNR (+3 dBA). Reverberation time interacted with SNR to the effect that at +12 dB the shorter reverberation time improved recall, but at +3 dB it impaired recall. The effects of the physical sound variables (SNR and reverberation time) did not interact with language. © 2016 Hurtig, Keus van de Poll, Pekkola, Hygge, Ljung and Sörqvist.

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The mixed-signal and analog design on a pre-diffused array is a challenging task, given that the digital array is a linear matrix arrangement of minimum-length transistors. To surmount this drawback a specific discipline for designing analog circuits over such array is required. An important novel technique proposed is the use of TAT (Trapezoidal Associations of Transistors) composite transistors on the semi-custom Sea-Of-Transistors (SOT) array. The analysis and advantages of TAT arrangement are extensively analyzed and demonstrated, with simulation and measurement comparisons to equivalent single transistors. Basic analog cells were also designed as well in full-custom and TAT versions in 1.0mm and 0.5mm digital CMOS technologies. Most of the circuits were prototyped in full-custom and TAT-based on pre-diffused SOT arrays. An innovative demonstration of the TAT technique is shown with the design and implementation of a mixed-signal analog system, i. e., a fully differential 2nd order Sigma-Delta Analog-to-Digital (A/D) modulator, fabricated in both full-custom and SOT array methodologies in 0.5mm CMOS technology from MOSIS foundry. Three test-chips were designed and fabricated in 0.5mm. Two of them are IC chips containing the full-custom and SOT array versions of a 2nd-Order Sigma-Delta A/D modulator. The third IC contains a transistors-structure (TAT and single) and analog cells placed side-by-side, block components (Comparator and Folded-cascode OTA) of the Sigma-Delta modulator.

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Signaling models have contributed to the corporate finance literature by formalizing "the informational content of dividends" hypothesis. However, these models are under criticism of empirical literature, as weak evidences were found supporting one of the main predicitions: the positive relation between changes in dividends and changes in earnings. We claim thaht the failure to verify this prediction does not invalidate the signaling approach. The models developed up to now assume or derive utility functions with the single-crossing property. We show thaht signaling is possible in the absence of this property and, in this case, changes in dividend and changes in earnings can be positively or negatively related.

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The focus of this thesis is to discuss the development and modeling of an interface architecture to be employed for interfacing analog signals in mixed-signal SOC. We claim that the approach that is going to be presented is able to achieve wide frequency range, and covers a large range of applications with constant performance, allied to digital configuration compatibility. Our primary assumptions are to use a fixed analog block and to promote application configurability in the digital domain, which leads to a mixed-signal interface. The use of a fixed analog block avoids the performance loss common to configurable analog blocks. The usage of configurability on the digital domain makes possible the use of all existing tools for high level design, simulation and synthesis to implement the target application, with very good performance prediction. The proposed approach utilizes the concept of frequency translation (mixing) of the input signal followed by its conversion to the ΣΔ domain, which makes possible the use of a fairly constant analog block, and also, a uniform treatment of input signal from DC to high frequencies. The programmability is performed in the ΣΔ digital domain where performance can be closely achieved according to application specification. The interface performance theoretical and simulation model are developed for design space exploration and for physical design support. Two prototypes are built and characterized to validate the proposed model and to implement some application examples. The usage of this interface as a multi-band parametric ADC and as a two channels analog multiplier and adder are shown. The multi-channel analog interface architecture is also presented. The characterization measurements support the main advantages of the approach proposed.

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This work analyzes the entry problem in the hydroelectric generation industry. The operation of a generator upstream regularizes the river flow for generators located downstream on the same river, increasing the production capacity of the latter. This positive externality increases the attractiveness of the locations downstream whenever a generator decides to enter upstream. Therefore, the entry decision of a generator in a given location may affect all entry decisions in potential locations for plants downstream. I first model the problem of generators located in cascade on the same river to show the positive effect of the externality. Next, I develop a method to estimate an entry model specific to the hydro generation industry which takes into account the externality of the entry decisions. Finally, I use a data set on investment decisions of Brazilian hydro-generators to estimate the model. The results show a positive incentive to locate downstream from existing plants and from locations where entry is likely to occur. An interesting by-product of the analysis is that the year effects’ estimates show an increase one year before the energy crisis of 2001, providing evidence that the market anticipated the crisis. It contradicts the governmental version that the crisis was due to an unexpected drought.

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The signaling models have contributed to the literature of corporate finance by the formalization of "the informational content of dividends hypothesis". However, these models are under criticism of empirical works, as weak evidences were found supporting one of the main predictions: the positive relation between changes in dividends and changes in earnings. We claim that the failure to verify this prediction does not invalidate the signaling approach. The mo deIs developed up to now assume or derive utility functions with the single-crossing property. We show that signaling is possible in the absence of this property and, in this case, changes in dividend and changes in earnings can be positively or negatively related.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Background: Sugarcane is an increasingly economically and environmentally important C4 grass, used for the production of sugar and bioethanol, a low-carbon emission fuel. Sugarcane originated from crosses of Saccharum species and is noted for its unique capacity to accumulate high amounts of sucrose in its stems. Environmental stresses limit enormously sugarcane productivity worldwide. To investigate transcriptome changes in response to environmental inputs that alter yield we used cDNA microarrays to profile expression of 1,545 genes in plants submitted to drought, phosphate starvation, herbivory and N-2-fixing endophytic bacteria. We also investigated the response to phytohormones (abscisic acid and methyl jasmonate). The arrayed elements correspond mostly to genes involved in signal transduction, hormone biosynthesis, transcription factors, novel genes and genes corresponding to unknown proteins.Results: Adopting an outliers searching method 179 genes with strikingly different expression levels were identified as differentially expressed in at least one of the treatments analysed. Self Organizing Maps were used to cluster the expression profiles of 695 genes that showed a highly correlated expression pattern among replicates. The expression data for 22 genes was evaluated for 36 experimental data points by quantitative RT-PCR indicating a validation rate of 80.5% using three biological experimental replicates. The SUCAST Database was created that provides public access to the data described in this work, linked to tissue expression profiling and the SUCAST gene category and sequence analysis. The SUCAST database also includes a categorization of the sugarcane kinome based on a phylogenetic grouping that included 182 undefined kinases.Conclusion: An extensive study on the sugarcane transcriptome was performed. Sugarcane genes responsive to phytohormones and to challenges sugarcane commonly deals with in the field were identified. Additionally, the protein kinases were annotated based on a phylogenetic approach. The experimental design and statistical analysis applied proved robust to unravel genes associated with a diverse array of conditions attributing novel functions to previously unknown or undefined genes. The data consolidated in the SUCAST database resource can guide further studies and be useful for the development of improved sugarcane varieties.

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A collection of 237,954 sugarcane ESTs was examined in search of signal transduction genes. Over 3,500 components involved in several aspects of signal transduction, transcription, development, cell cycle, stress responses and pathogen interaction were compiled into the Sugarcane Signal Transduction (SUCAST) Catalogue. Sequence comparisons and protein domain analysis revealed 477 receptors, 510 protein kinases, 107 protein phosphatases, 75 small GTPases, 17 G-proteins, 114 calcium and inositol metabolism proteins, and over 600 transcription factors. The elements were distributed into 29 main categories subdivided into 409 sub-categories. Genes with no matches in the public databases and of unknown function were also catalogued. A cDNA microarray was constructed to profile individual variation of plants cultivated in the field and transcript abundance in six plant organs (flowers, roots, leaves, lateral buds, and 1(st) and 4(th) internodes). From 1280 distinct elements analyzed, 217 (17%) presented differential expression in two biological samples of at least one of the tissues tested. A total of 153 genes (12%) presented highly similar expression levels in all tissues. A virtual profile matrix was constructed and the expression profiles were validated by real-time PCR. The expression data presented can aid in assigning function for the sugarcane genes and be useful for promoter characterization of this and other economically important grasses.

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During pregnancy, the maternal endocrine pancreas undergoes, as a consequence of placental lactogens and prolactin (PR,L) action, functional changes that are characterized by increased glucose-induced insulin secretion. After delivery, the maternal endocrine pancreas rapidly returns to nonpregnant state, which is mainly attributed to the increased serum levels of glucocorticoids (GCs). Although GCs are known to decrease insulin secretion and counteract PRL action, the mechanisms for these effects are poorly understood. We have previously demonstrated that signal transducer and activator of transcription 3 (STAT3) is increased in islets treated with PRL. In the present study, we show that STAT3 expression and serine phosphorylation are increased in pancreatic islets at the end of pregnancy (P19). STAT3 serine phosphorylation rapidly returned to basal levels 3 days after delivery (U). The expression of the sarcoendoplasmic reticulum Ca2+-ATPase 2 (SERCA2), a crucial protein involved in the regulation of calcium handling in P-cells, was also increased in P19, returning to basal levels at L3. PRL increased SERCA2 and STAT3 expressions and STAT3 serine phosphorylation in RINm5F cells. The upregulation of SERCA2 by PRL was abolished after STAT3 knockdown. Moreover, PRL-induced STAT3 serine phosphorylation and SERCA2 expression were inhibited by dexamethasone (DEX). Insulin secretion from islets of PI 9 rats pre-incubated with thapsigargin and L3 rats showed a dramatic suppression of first phase of insulin release. The present results indicate that PRL regulates SERCA2 expression by a STAT3-dependent mechanism. PRL effect is counteracted by DEX and might contribute to the adaptation of maternal endocrine pancreas during the peripartum period.

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Block diagrams and signal-flow graphs are used to represent and to obtain the transfer function of interconnected systems. The reduction of signal-flow graphs is considered simpler than the reduction of block diagrams for systems with complex interrelationships. Signal-flow graphs reduction can be made without graphic manipulations of diagrams, and it is attractive for a computational implementation. In this paper the authors propose a computational method for direct reduction of signal-flow graphs. This method uses results presented in this paper about the calculation of literal determinants without symbolic mathematics tools. The Cramer's rule is applied for the solution of a set of linear equations, A program in MATLAB language for reduction of signal-flow graphs with the proposed method is presented.