990 resultados para Limit State Functions
Resumo:
Knowledge of the soil water retention curve (SWRC) is essential for understanding and modeling hydraulic processes in the soil. However, direct determination of the SWRC is time consuming and costly. In addition, it requires a large number of samples, due to the high spatial and temporal variability of soil hydraulic properties. An alternative is the use of models, called pedotransfer functions (PTFs), which estimate the SWRC from easy-to-measure properties. The aim of this paper was to test the accuracy of 16 point or parametric PTFs reported in the literature on different soils from the south and southeast of the State of Pará, Brazil. The PTFs tested were proposed by Pidgeon (1972), Lal (1979), Aina & Periaswamy (1985), Arruda et al. (1987), Dijkerman (1988), Vereecken et al. (1989), Batjes (1996), van den Berg et al. (1997), Tomasella et al. (2000), Hodnett & Tomasella (2002), Oliveira et al. (2002), and Barros (2010). We used a database that includes soil texture (sand, silt, and clay), bulk density, soil organic carbon, soil pH, cation exchange capacity, and the SWRC. Most of the PTFs tested did not show good performance in estimating the SWRC. The parametric PTFs, however, performed better than the point PTFs in assessing the SWRC in the tested region. Among the parametric PTFs, those proposed by Tomasella et al. (2000) achieved the best accuracy in estimating the empirical parameters of the van Genuchten (1980) model, especially when tested in the top soil layer.
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Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland) forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2) and Akaike information criterion (AIC) and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.
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We derive a simple closed analytical expression for the total entropy production along a single stochastic trajectory of a Brownian particle diffusing on a periodic potential under an external constant force. By numerical simulations we compute the probability distribution functions of the entropy and satisfactorily test many of the predictions based on Seiferts integral fluctuation theorem. The results presented for this simple model clearly illustrate the practical features and implications derived from such a result of nonequilibrium statistical mechanics.
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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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What we do: Since 1892, the Iowa Geological and Water Survey (IGWS) has provided earth, water, and mapping science to all Iowans. We collect and interpret information on subsurface geologic conditions, groundwater and surface water quantity and quality, and the natural and built features of our landscape. This information is critical for: Predicting the future availability of economic water supplies and mineral resources. Assuring proper function of waste disposal facilities. Delineation of geologic hazards that may jeopardize property and public safety. Assessing trends and providing protection of water quality and soil resources. Applied technical assistance for economic development and environmental stewardship. Our goal: Providing the tools for good decision making to assure the long-term vitality of Iowa’s communities, businesses, and quality of life. Information and technical assistance are provided through web-based databases, comprehensive Geographic Information System (GIS) tools, predictive groundwater models, and watershed assessments and improvement grants. The key service we provide is direct assistance from our technical staff, working with Iowans to overcome real-world challenges. This report describes the basic functions of IGWS program areas and highlights major activities and accomplishments during calendar year 2011. More information on IGWS is available at http://www.igsb.uiowa.edu/.
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Rigorous quantum dynamics calculations of reaction rates and initial state-selected reaction probabilities of polyatomic reactions can be efficiently performed within the quantum transition state concept employing flux correlation functions and wave packet propagation utilizing the multi-configurational time-dependent Hartree approach. Here, analytical formulas and a numerical scheme extending this approach to the calculation of state-to-state reaction probabilities are presented. The formulas derived facilitate the use of three different dividing surfaces: two dividing surfaces located in the product and reactant asymptotic region facilitate full state resolution while a third dividing surface placed in the transition state region can be used to define an additional flux operator. The eigenstates of the corresponding thermal flux operator then correspond to vibrational states of the activated complex. Transforming these states to reactant and product coordinates and propagating them into the respective asymptotic region, the full scattering matrix can be obtained. To illustrate the new approach, test calculations study the D + H2(ν, j) → HD(ν′, j′) + H reaction for J = 0.
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The effect of aging on steady-state plasma concentrations of citalopram (CIT) and desmethylcitalopram (DCIT) was investigated in 128 depressive patients treated with 10-80 mg/day CIT. They were separated into three groups, with age up to 64 years (mean age+/-S.D.: 47+/-12 years; n=48), between 65 and 79 years (72+/-1 years; n=57), and from 80 years or older (84+/-1 years; n=23). Body mass index (BMI), renal and hepatic functions were similar in the three groups. A large interindividual variability of plasma levels of CIT (16-fold) and DCIT (12-fold) was measured for a given dose. The mean plasma levels of CIT corrected for a 20 mg daily dose were 55% higher in the very elderly (>=80 years) patients (65+/-30 ng/ml; p<0.001) and 38% higher in the elderly (65-79 years) patients (58+/-24 ng/ml; p<0.001) when compared to the adult patients (42+/-17 ng/ml). DCIT mean plasma level was 38% higher (p<0.05) in the group of very elderly patients (22+/-10 ng/ml) when compared to the adult patients (16+/-9 ng/ml). As a consequence, the mean plasma concentration of CIT+DCIT was 48% higher in the very elderly patients (86+/-36 ng/ml; p<0.001) and 33% higher in the elderly patients (77+/-28 ng/ml; p<0.001) when compared to the adult patients (58+/-21 ng/ml). Age correlated significantly with CIT (r=0.43, p<0.001), DCIT (r=0.28, p<0.01), and CIT+DCIT plasma levels (r=0.44, p<0.001), and thus accounts for 18% of the variability of CIT plasma levels, with no influence of gender. The recommended dose reduction of CIT in elderly patients seems therefore justified.
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Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.
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Iowa's county road system serves many critical functions in a changing environment. Many counties with very different social, economic, and demographic circumstances do not have adequate resources to provide the desired level of service on their secondary road systems. How the state's Road Use Tax Fund (RUTF) is distributed among counties is therefore of great importance. This report presents the results of a year-long study of how to distribute RUTF resources among Iowa's 99 counties. The project was undertaken at the request of county engineers who wish to replace the current method of allocation with one that is more stable, comprehensible, and predictable. This report describes the current allocation method, examines how other states distribute road funds to counties, and discusses potential allocation factors that could be included in a revised procedure. The process undertaken to narrow the range of possible formulas and determine the one to recommend is summarized. Finally, the report presents the allocation formula recommended by the project advisory committee, along with how it would operate.
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During the last two decades, endoscopic endonasal approach has completed the minimally invasive skull base surgery armamentarium. Endoscopic endonasal skull base surgery (EESBS) was initially developed in the field of pituitary adenomas, and gained an increasing place for the treatment of a wide variety of skull base pathologies, extending on the midline from crista galli process to the occipitocervical junction and laterally to the parasellar areas and petroclival apex. Until now, most studies are retrospective and lack sufficient methodological quality to confirm whether the endoscopic endonasal pituitary surgery has better results than the microsurgical trans-sphenoidal classical approach. The impressions of the expert teams show a trend toward better results for some pituitary adenomas with the endoscopic endonasal route, in terms of gross total resection rate and probably more comfortable postoperative course for the patient. Excepting intra- and suprasellar pituitary adenomas, EESBS seems useful for selected lesions extending onto the cavernous sinus and Meckel's cave but also for clival pathologies. Nevertheless, this infatuation toward endoscopic endonasal approaches has to be balanced with the critical issue of cerebrospinal fluid leaks, which constitutes actually the main limit of this approach. Through their experience and a review of the literature, the authors aim to present the state of the art of this approach as well as its limits.
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Adult mammalian central nervous system (CNS) axons have a limited regrowth capacity following injury. Myelin-associated inhibitors (MAIs) limit axonal outgrowth and their blockage improves the regeneration of damaged fiber tracts. Three of these proteins, Nogo-A, MAG and OMgp, share two common neuronal receptors: NgR1, together with its co-receptors (p75(NTR), TROY and Lingo-1), and the recently described paired immunoglobulin-like receptor B (PirB). These proteins impair neuronal regeneration by limiting axonal sprouting. Some of the elements involved in the myelin inhibitory pathways may still be unknown, but the discovery that blocking both PirB and NgR1 activities leads to near-complete release from myelin inhibition, sheds light on one of the most competitive and intense fields of neuroregeneration study during in recent decades. In parallel with the identification and characterization of the roles and functions of these inhibitory molecules in axonal regeneration, data gathered in the field strongly suggest that most of these proteins have roles other than axonal growth inhibition. The discovery of a new group of interacting partners for myelin-associated receptors and ligands, as well as functional studies within or outside the CNS environment, highlights the potential new physiological roles for these proteins in processes such as development, neuronal homeostasis, plasticity and neurodegeneration.
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The Caulobacter DNA methyltransferase CcrM is one of five master cell-cycle regulators. CcrM is transiently present near the end of DNA replication when it rapidly methylates the adenine in hemimethylated GANTC sequences. The timing of transcription of two master regulator genes and two cell division genes is controlled by the methylation state of GANTC sites in their promoters. To explore the global extent of this regulatory mechanism, we determined the methylation state of the entire chromosome at every base pair at five time points in the cell cycle using single-molecule, real-time sequencing. The methylation state of 4,515 GANTC sites, preferentially positioned in intergenic regions, changed progressively from full to hemimethylation as the replication forks advanced. However, 27 GANTC sites remained unmethylated throughout the cell cycle, suggesting that these protected sites could participate in epigenetic regulatory functions. An analysis of the time of activation of every cell-cycle regulatory transcription start site, coupled to both the position of a GANTC site in their promoter regions and the time in the cell cycle when the GANTC site transitions from full to hemimethylation, allowed the identification of 59 genes as candidates for epigenetic regulation. In addition, we identified two previously unidentified N(6)-methyladenine motifs and showed that they maintained a constant methylation state throughout the cell cycle. The cognate methyltransferase was identified for one of these motifs as well as for one of two 5-methylcytosine motifs.
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On July 1, 2005, the State of Iowa implemented a 70 mile per hour (mph) speed limit on most rural Interstates. This document reports on a study of the safety effect of this change. Changes in speeds, traffic volume on and off the rural Interstate system (diversion), and safety (crashes) for on- and off-system roads were studied. After the change, mean and 85th percentile speeds increased by about 2 mph on rural Interstates, but speeding was reduced (the number of drivers exceeding the speed limit by 10 mph decreased from 20 per cent to about 8 per cent). Daytime and nighttime serious crashes were studied for a period of 14 and a half years prior to the change and 2 and a half years afterwards. Simple descriptive statistics reveal increases in all crash severity categories for the 2 and a half year period following the speed limit increase when compared to the most recent comparable 2 and a half year period prior to the increase. When compared to longer term trends, the increases were less pronounced in some severity levels and types, and for a few severity levels the average crash frequencies were observed to decrease. However, fatal and other serious cross-median crashes increased by relatively larger amounts as compared to expected random variation. The study also analyzed crash frequencies grouped into six-month periods, revealing similar findings.
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Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is considered a multifunctional protein with defined functions in numerous mammalian cellular processes. GAPDH functional diversity depends on various factors such as covalent modifications, subcellular localization, oligomeric state and intracellular concentration of substrates or ligands, as well as protein-protein interactions. In bacteria, alternative GAPDH functions have been associated with its extracellular location in pathogens or probiotics. In this study, new intracellular functions of E. coli GAPDH were investigated following a proteomic approach aimed at identifying interacting partners using in vivo formaldehyde cross-linking followed by mass spectrometry. The identified proteins were involved in metabolic processes, protein synthesis and folding or DNA repair. Some interacting proteins were also identified in immunopurification experiments in the absence of cross-linking. Pull-down experiments and overlay immunoblotting were performed to further characterize the interaction with phosphoglycolate phosphatase (Gph). This enzyme is involved in the metabolism of 2-phosphoglycolate formed in the DNA repair of 3"-phosphoglycolate ends generated by bleomycin damage. We show that interaction between Gph and GAPDH increases in cells challenged with bleomycin, suggesting involvement of GAPDH in cellular processes linked to DNA repair mechanisms.
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Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere "take over" their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children.