140 resultados para Closed Convex Process


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14C dating models are limited when considering recent groundwater for which the carbon isotopic signature of the total dissolved inorganic carbon (TDIC) is mainly acquired in the unsaturated zone. Reducing the uncertainties of dating thus implies a better identification of the processes controlling the carbon isotopic composition of the TDIC during groundwater recharge. Geochemical interactions between gas, water and carbonates in the unsaturated zone were investigated for two aquifers (the carbonate-free Fontainebleau sands and carbonate-bearing Astian sands, France) in order to identify the respective roles of CO2 and carbonates on the carbon isotopic signatures of the TDIC; this analysis is usually approached using open or closed system terms. Under fully open system conditions, the seasonality of the 13C values in the soil CO2 can lead to important uncertainties regarding the so-called "initial 14C activity" used in 14C correction models. In a carbonate-bearing unsaturated zone such as in the Astian aquifer, we show that an approach based on fully open or closed system conditions is not appropriate. Although the chemical saturation between water and calcite occurs rapidly within the first metre of the unsaturated zone, the carbon isotopic contents (δ13C) of the CO2 and the TDIC evolve downward, impacted by the dissolution-precipitation of the carbonates. In this study, we propose a numerical approach to describe this evolution. The δ13C and the A 14C (radiocarbon activity) of the TDIC at the base of the carbonate-hearing unsaturated zone depends on (i) the δ13C and the A 14C of the TDIC in the soil determined by the soil CO2, (ii) the water's residence time in the unsaturated zone and (iii) the carbonate precipitation-dissolution fluxes. In this type of situation, the carbonate δ13C-A 14C evolutions indicate the presence of secondary calcite and permit the calculation of its accretion flux, equal to ~ 4.5 ± 0.5 x 10-9 mol grock-1 yr-1. More generally, for other sites under temperate climate and with similar properties to the Astian sands site, this approach allows for a reliable determination of the carbon isotopic composition at the base of the unsaturated zone as the indispensable "input function" data of the carbon cycle into the aquifer.

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In the traditional actuarial risk model, if the surplus is negative, the company is ruined and has to go out of business. In this paper we distinguish between ruin (negative surplus) and bankruptcy (going out of business), where the probability of bankruptcy is a function of the level of negative surplus. The idea for this notion of bankruptcy comes from the observation that in some industries, companies can continue doing business even though they are technically ruined. Assuming that dividends can only be paid with a certain probability at each point of time, we derive closed-form formulas for the expected discounted dividends until bankruptcy under a barrier strategy. Subsequently, the optimal barrier is determined, and several explicit identities for the optimal value are found. The surplus process of the company is modeled by a Wiener process (Brownian motion).

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Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.

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In this study, a quantitative approach was used to investigate the role of D142, which belongs to the highly conserved E/DRY sequence, in the activation process of the alpha1B-adrenergic receptor (alpha1B-AR). Experimental and computer-simulated mutagenesis were performed by substituting all possible natural amino acids at the D142 site. The resulting congeneric set of proteins together with the finding that all the receptor mutants show various levels of constitutive (agonist-independent) activity enabled us to quantitatively analyze the relationships between structural/dynamic features and the extent of constitutive activity. Our results suggest that the hydrophobic/hydrophilic character of D142, which could be regulated by protonation/deprotonation of this residue, is an important modulator of the transition between the inactive (R) and active (R*) state of the alpha1B-AR. Our study represents an example of quantitative structure-activity relationship analysis of the activation process of a G protein-coupled receptor.

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Despite the fact that there are more than twenty thousand biomedical journals in the world, research into the work of editors and publication process in biomedical and health care journals is rare. In December 2012, the Esteve Foundation, a non-profit scientific institution that fosters progress in pharmacotherapy by means of scientific communication and discussion organized a discussion group of 7 editors and/or experts in peer review biomedical publishing. They presented findings of past editorial research, discussed the lack of competitive funding schemes and specialized journals for dissemination of editorial research, and reported on the great diversity of misconduct and conflict of interest policies, as well as adherence to reporting guidelines. Furthermore, they reported on the reluctance of editors to investigate allegations of misconduct or increase the level of data sharing in health research. In the end, they concluded that if editors are to remain gatekeepers of scientific knowledge they should reaffirm their focus on the integrity of the scientific record and completeness of the data they publish. Additionally, more research should be undertaken to understand why many journals are not adhering to editorial standards, and what obstacles editors face when engaging in editorial research.

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OBJECTIVE: To evaluate the results of closed and open grade I and II tibial shaft fractures treated by reamed nail and unreamed nailing. SUBJECTS AND METHODS: Between 1997 and 2000, 119 patients with tibial shaft fractures were treated with reamed tibial nails. Postoperatively 96 patients (70 closed and 26 grade I and II open fractures) were followed clinically and radiologically for up to 18 months. The nail was inserted either by patellar tendon splitting or by nonsplitting technique. The nail was inserted after overreaming by 1.5 mm. Postoperatively, patients with isolated tibial fracture were mobilized by permitting partial weight bearing on the injured leg for 6 weeks. Patients with associated ankle fractures were allowed to walk with a Sarmiento cast. RESULTS: Postoperatively, 6 (6.3%) patients developed a compartment syndrome after surgery. In 48 (50%) cases, dynamization of the nail was carried out after a mean period of 12 weeks for delayed union. Overall, a 90.6% union was obtained at a mean of 24 weeks without difference between closed or open fractures. Two (2.1%) patients with an open grade II fracture developed a deep infection requiring treatment. A 9.4% rate of malunion was observed. Eight (8.3%) patients developed screw failure without clinical consequences. At the last follow-up, 52% of patients with patellar tendon splitting had anterior knee pain, compared to those (14%) who did not have tendon splitting. CONCLUSION: Reamed intramedullary nail is a suitable implant in treating closed as well as grade I and II open tibial shaft fractures.

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Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

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Birds exhibit exceptional longevity and are thus regarded as a convenient model to study the intrinsic mechanisms of aging. The oxidative stress theory of aging suggests that individuals age because molecules, cells, tissues, organs, and, ultimately, animals accumulate oxidative damage over time. Accumulation of damage progressively reduces the level of antioxidant defences that are expected to decline with age. To test this theory, we measured the resistance of red blood cells to free radical attack in a captive population of greater flamingo (Phoenicopterus ruber roseus) of known age ranging from 0.3 to 45 years. We observed a convex relationship with young adults (12-20 years old) having greater resistance to oxidative stress than immature flamingos (5 months old) and old flamingos (30-45 years old). Our results suggest that the antioxidant detoxifying system must go through a maturation process before being completely functional. It then declines in older adults, supporting the oxidative theory of aging. Oxidative stress could hence play a significant role in shaping the pattern of senescence in a very long-lived bird species.

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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.