110 resultados para Closed cracks


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Wave-induced fluid flow at microscopic and mesoscopic scales arguably constitutes the major cause of intrinsic seismic attenuation throughout the exploration seismic and sonic frequency ranges. The quantitative analysis of these phenomena is, however, complicated by the fact that the governing physical processes may be dependent. The reason for this is that the presence of microscopic heterogeneities, such as micro-cracks or broken grain contacts, causes the stiffness of the so-called modified dry frame to be complex-valued and frequency-dependent, which in turn may affect the viscoelastic behaviour in response to fluid flow at mesoscopic scales. In this work, we propose a simple but effective procedure to estimate the seismic attenuation and velocity dispersion behaviour associated with wave-induced fluid flow due to both microscopic and mesoscopic heterogeneities and discuss the results obtained for a range of pertinent scenarios.

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BACKGROUND: Neoadjuvant trials conducted using a double HER2 blockade with lapatinib and trastuzumab, combined with different paclitaxel-containing chemotherapy regimens, have shown high pathological complete response (pCR) rates, but at the cost of important toxicity. We hypothesised that this toxicity might be due to a specific interaction between paclitaxel and lapatinib. This trial assesses the toxicity and activity of the combination of docetaxel with lapatinib and trastuzumab. PATIENTS AND METHODS: Patients with stage IIA to IIIC HER2-positive breast cancer received six cycles of chemotherapy (three cycles of docetaxel followed by three cycles of fluorouracil, epirubicin, cyclophosphamide). They were randomised 1 : 1 : 1 to receive during the first three cycles either lapatinib (1000 mg orally daily), trastuzumab (4 mg/kg loading dose followed by 2 mg/kg weekly), or trastuzumab + lapatinib at the same dose. The primary end point was pCR rate defined as ypT0/is. Secondary end points included safety and toxicity. pCR rate defined as ypT0/is ypN0 was assessed as an exploratory analysis. In June 2012, arm A was closed for futility based on the results from other studies. RESULTS: From October 2010 to January 2013, 128 patients were included in 14 centres. The percentage of the 122 assessable patients with pCR in the breast, and pCR in the breast and nodes, was numerically highest in the lapatinib + trastuzumab group (60% and 56%, respectively), intermediate in the trastuzumab group (52% and 52%), and lowest in the lapatinib group (46% and 36%). Frequency (%) of the most common grade 3-4 toxicities in the lapatinib /trastuzumab/lapatinib + trastuzumab arms were: febrile neutropenia 23/15/10, diarrhoea 9/2/18, infection (other) 9/4/8, and hepatic toxicity 0/2/8. CONCLUSIONS: This study demonstrates a numerically modest pCR rate increase with double anti-HER2 blockade plus chemotherapy, but suggests that the use of docetaxel rather than paclitaxel may not reduce toxicity. CLINICALTRIALSGOV: NCT00450892.

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SNARE protein-driven secretion of neurotransmitters from synaptic vesicles is at the center of neuronal communication. In the absence of the cytosolic protein Munc18-1, synaptic secretion comes to a halt. Although it is believed that Munc18-1 orchestrates SNARE complexes, its mode of action is still a matter of debate. In particular, it has been challenging to clarify the role of a tight Munc18/syntaxin 1 complex, because this interaction interferes strongly with syntaxin's ability to form a SNARE complex. In this complex, two regions of syntaxin, the N-peptide and the remainder in closed conformation, bind to Munc18 simultaneously. Until now, this binary complex has been reported for neuronal tissues only, leading to the hypothesis that it might be a specialization of the neuronal secretion apparatus. Here we aimed, by comparing the core secretion machinery of the unicellular choanoflagellate Monosiga brevicollis with that of animals, to reconstruct the ancestral function of the Munc18/syntaxin1 complex. We found that the Munc18/syntaxin 1 complex from M. brevicollis is structurally and functionally highly similar to the vertebrate complex, suggesting that it constitutes a fundamental step in the reaction pathway toward SNARE assembly. We thus propose that the primordial secretion machinery of the common ancestor of choanoflagellates and animals has been co-opted for synaptic roles during the rise of animals.

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Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

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The use of urinary hexane diamine (HDA) as a biomarker to assess human respiratory exposure to hexamethylene diisocyanate (HDI) aerosol was evaluated. Twenty-three auto body shop workers were exposed to HDI biuret aerosol for two hours using a closed exposure apparatus. HDI exposures were quantified using both a direct-reading instrument and a treated-filter method. Urine samples collected at baseline, immediately post exposure, and every four to five hours for up to 20 hours were analyzed for HDA using gas chromatography and mass spectrometry. Mean urinary HDA (microg/g creatinine) sharply increased from the baseline value of 0.7 to 18.1 immediately post exposure and decreased rapidly to 4.7, 1.9 and 1.1, respectively, at 4, 9, and 18 hours post exposure. Considerable individual variability was found. Urinary HDA can assess acute respiratory exposure to HDI aerosol, but may have limited use as a biomarker of exposure in the workplace. [Authors]