1000 resultados para Automatization, VI coding, calibration, hot wire anemometry
Resumo:
Pavements are subjected to different stresses during their design lives. A properly designed pavement will perform adequately during its design life, and the distresses will not exceed the allowable limits; however, there are several factors that can lead to premature pavement failure. One such factor is moisture sensitivity. AASHTO T 283 is the standard test used in the moisture susceptibility evaluation of asphalt mixtures, but the results of the test are not very representative of the expected behavior of asphalt mixtures. The dynamic modulus test measures a fundamental property of the mixture. The results of the dynamic modulus test can be used directly in the Mechanistic-Empirical Pavement Design Guide (MEPDG) and are considered a very good representation of the expected field performance of the mixture. Further research is still needed to study how the dynamic modulus results are affected by moisture. The flow number test was studied in previous research as a candidate test for moisture-susceptibility evaluation, but the results of that research were not favorable. This research has four main objectives. The first objective of this research is to evaluate the usefulness of the dynamic modulus and flow number tests in moisture-susceptibility evaluation. The second objective is to compare the results to those achieved using the AASHTO T 283 test. The third objective is to study the effect of different methods of sample conditioning and testing conditions. The fourth objective of the research is to study the variability in the test results.
Resumo:
In the previous study, moisture loss indices were developed based on the field measurements from one CIR-foam and one CIR-emulsion construction sites. To calibrate these moisture loss indices, additional CIR construction sites were monitored using embedded moisture and temperature sensors. In addition, to determine the optimum timing of an HMA overlay on the CIR layer, the potential of using the stiffness of CIR layer measured by geo-gauge instead of the moisture measurement by a nuclear gauge was explored. Based on the monitoring the moisture and stiffness from seven CIR project sites, the following conclusions are derived: 1. In some cases, the in-situ stiffness remained constant and, in other cases, despite some rainfalls, stiffness of the CIR layers steadily increased during the curing time. 2. The stiffness measured by geo-gauge was affected by a significant amount of rainfall. 3. The moisture indices developed for CIR sites can be used for predicting moisture level in a typical CIR project. The initial moisture content and temperature were the most significant factors in predicting the future moisture content in the CIR layer. 4. The stiffness of a CIR layer is an extremely useful tool for contractors to use for timing their HMA overlay. To determine the optimal timing of an HMA overlay, it is recommended that the moisture loss index should be used in conjunction with the stiffness of the CIR layer.
Resumo:
Collection : Bibliothèque contemporaine
Hot spots for diversity of Magnaporthe oryzae physiological races in irrigated rice fields in Brazil
Resumo:
The objective of this work was to evaluate the Magnaporthe oryzae pathotype diversity in new commercial irrigated rice fields in the Araguaia River Valley, state of Tocantins, Brazil. The causal agent of rice blast has heavily affected rice production in the region. Despite the efforts of breeding programs, blast resistance breakdown has been recorded shortly after the release of new resistant cultivars developed for the region. Among the causes of resistance breakage is the capacity of the fungus to rapidly develop new pathotypes. A sample of 479 M. oryzae monosporic isolates was obtained and tested using the international rice blast differential set. Isolate collections were made in small areas designed as trap nurseries and in scattered sites in their vicinity. Analysis of 250 M. oryzae isolates from three trap nurseries indicated the presence of 45 international M. oryzae races belonging to seven pathotype groups (IA-IG). In the isolates tested, 61 M. oryzae pathotypes belonging to all but the IH group were detected. The new areas of irrigated rice in the Araguaia River Valley have the highest diversity of M. oryzae pathotypes reported so far in Brazil.
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Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as “phase-of-firing coding” (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (~10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.
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The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models.
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INTRODUCTION: Intrauterine Growth Restriction (IUGR) is a multifactorial disease defined by an inability of the fetus to reach its growth potential. IUGR not only increases the risk of neonatal mortality/morbidity, but also the risk of metabolic syndrome during adulthood. Certain placental proteins have been shown to be implicated in IUGR development, such as proteins from the GH/IGF axis and angiogenesis/apoptosis processes. METHODS: Twelve patients with term IUGR pregnancy (birth weight < 10th percentile) and 12 CTRLs were included. mRNA was extracted from the fetal part of the placenta and submitted to a subtraction method (Clontech PCR-Select cDNA Subtraction). RESULTS: One candidate gene identified was the long non-coding RNA NEAT1 (nuclear paraspeckle assembly transcript 1). NEAT1 is the core component of a subnuclear structure called paraspeckle. This structure is responsible for the retention of hyperedited mRNAs in the nucleus. Overall, NEAT1 mRNA expression was 4.14 (±1.16)-fold increased in IUGR vs. CTRL placentas (P = 0.009). NEAT1 was exclusively localized in the nuclei of the villous trophoblasts and was expressed in more nuclei and with greater intensity in IUGR placentas than in CTRLs. PSPC1, one of the three main proteins of the paraspeckle, co-localized with NEAT1 in the villous trophoblasts. The expression of NEAT1_2 mRNA, the long isoform of NEAT1, was only modestly increased in IUGR vs. CTRL placentas. DISCUSSION/CONCLUSION: The increase in NEAT1 and its co-localization with PSPC1 suggests an increase in paraspeckles in IUGR villous trophoblasts. This could lead to an increased retention of important mRNAs in villous trophoblasts nuclei. Given that the villous trophoblasts are crucial for the barrier function of the placenta, this could in part explain placental dysfunction in idiopathic IUGR fetuses.
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When certain control parameters of nervous cell models are varied, complex bifurcation structures develop in which the dynamical behaviors available appear classified in blocks, according to criteria of dynamical likelihood. This block structured dynamics may be a clue to understand how activated neurons encode information by firing spike trains of their action potentials.
