989 resultados para uncertainty estimation


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Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets.

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Electrical impedance tomography (EIT) allows the measurement of intra-thoracic impedance changes related to cardiovascular activity. As a safe and low-cost imaging modality, EIT is an appealing candidate for non-invasive and continuous haemodynamic monitoring. EIT has recently been shown to allow the assessment of aortic blood pressure via the estimation of the aortic pulse arrival time (PAT). However, finding the aortic signal within EIT image sequences is a challenging task: the signal has a small amplitude and is difficult to locate due to the small size of the aorta and the inherent low spatial resolution of EIT. In order to most reliably detect the aortic signal, our objective was to understand the effect of EIT measurement settings (electrode belt placement, reconstruction algorithm). This paper investigates the influence of three transversal belt placements and two commonly-used difference reconstruction algorithms (Gauss-Newton and GREIT) on the measurement of aortic signals in view of aortic blood pressure estimation via EIT. A magnetic resonance imaging based three-dimensional finite element model of the haemodynamic bio-impedance properties of the human thorax was created. Two simulation experiments were performed with the aim to (1) evaluate the timing error in aortic PAT estimation and (2) quantify the strength of the aortic signal in each pixel of the EIT image sequences. Both experiments reveal better performance for images reconstructed with Gauss-Newton (with a noise figure of 0.5 or above) and a belt placement at the height of the heart or higher. According to the noise-free scenarios simulated, the uncertainty in the analysis of the aortic EIT signal is expected to induce blood pressure errors of at least ± 1.4 mmHg.

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The growth of five variables of the tibia (diaphyseal length, diaphyseal length plus distal epiphysis, condylo-malleolar length, sagittal diameter of the proximal epiphysis, maximum breadth of the distal epiphysis) were analysed using polynomial regression in order to evaluate their significance and capacity for age and sex determination during and after growth. Data were collected from 181 (90♂ and 91♀) individuals ranging from birth to 25 years of age and belonging to three documented collections from Western Europe. Results indicate that all five variables exhibit linear behaviour during growth, which can be expressed by a first-degree polynomial function. Sexual significant differences were observed from age 15 onward in the two epiphysis measurements and condylo-malleolar length, suggesting that these three variables could be useful for sex determination in individuals older than 15 years. Strong correlation coefficients were identified between the five tibial variables and age. These results indicate that any of the studied tibial measurements is likely to serve as a useful source for estimating sub-adult age in both archaeological and forensic samples.

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We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

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Geophysical data may provide crucial information about hydrological properties, states, and processes that are difficult to obtain by other means. Large data sets can be acquired over widely different scales in a minimally invasive manner and at comparatively low costs, but their effective use in hydrology makes it necessary to understand the fidelity of geophysical models, the assumptions made in their construction, and the links between geophysical and hydrological properties. Geophysics has been applied for groundwater prospecting for almost a century, but it is only in the last 20 years that it is regularly used together with classical hydrological data to build predictive hydrological models. A largely unexplored venue for future work is to use geophysical data to falsify or rank competing conceptual hydrological models. A promising cornerstone for such a model selection strategy is the Bayes factor, but it can only be calculated reliably when considering the main sources of uncertainty throughout the hydrogeophysical parameter estimation process. Most classical geophysical imaging tools tend to favor models with smoothly varying property fields that are at odds with most conceptual hydrological models of interest. It is thus necessary to account for this bias or use alternative approaches in which proposed conceptual models are honored at all steps in the model building process.

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Managers can craft effective integrated strategy by properly assessing regulatory uncertainty. Leveraging the existing political markets literature, we predict regulatory uncertainty from the novel interaction of demand and supply side rivalries across a range of political markets. We argue for two primary drivers of regulatory uncertainty: ideology-motivated interests opposed to the firm and a lack of competition for power among political actors supplying public policy. We align three, previously disparate dimensions of nonmarket strategy - profile level, coalition breadth, and pivotal target - to levels of regulatory uncertainty. Through this framework, we demonstrate how and when firms employ different nonmarket strategies. To illustrate variation in nonmarket strategy across levels of regulatory uncertainty, we analyze several market entry decisions of foreign firms operating in the global telecommunications sector.

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Työn tavoitteena oli kehittää tutkittavan insinööriyksikön projektien kustannusestimointiprosessia, siten että yksikön johdolla olisi tulevaisuudessa käytettävänään tarkempaa kustannustietoa. Jotta tämä olisi mahdollista, ensin täytyi selvittää yksikön toimintatavat, projektien kustannusrakenteet sekä kustannusatribuutit. Tämän teki mahdolliseksi projektien kustannushistoriatiedon tutkiminen sekä asiantuntijoiden haastattelu. Työn tuloksena syntyi kohdeyksikön muiden prosessien kanssa yhteensopiva kustannusestimointiprosessi sekä –malli.Kustannusestimointimenetelmän ja –mallin perustana on kustannusatribuutit, jotka määritellään erikseen tutkittavassa ympäristössä. Kustannusatribuutit löydetään historiatietoa tutkimalla, eli analysoimalla jo päättyneitä projekteja, projektien kustannusrakenteita sekä tekijöitä, jotka ovat vaikuttaneet kustannusten syntyyn. Tämän jälkeen kustannusatribuuteille täytyy määritellä painoarvot sekä painoarvojen vaihteluvälit. Estimointimallin tarkuutta voidaan parantaa mallin kalibroinnilla. Olen käyttänyt Goal – Question – Metric (GQM) –menetelmää tutkimuksen kehyksenä.

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ABSTRACT The citriculture consists in several environmental risks, as weather changes and pests, and also consists in considerable financial risk, mainly due to the period ofreturn on the initial investment. This study was motivated by the need to assess the risks of a business activity such as citriculture. Our objective was to build a stochastic simulation model to achieve the economic and financial analysis of an orange producer in the Midwest region of the state of Sao Paulo, under conditions of uncertainty. The parameters used were the Net Present Value (NPV), the Modified Internal Rate of Return(MIRR), and the Discounted Payback. To evaluate the risk conditions we built a probabilistic model of pseudorandom numbers generated with Monte Carlo method. The results showed that the activity analyzed provides a risk of 42.8% to reach a NPV negative; however, the yield assessed by MIRR was 7.7%, higher than the yield from the reapplication of the positive cash flows. The financial investment pays itself after the fourteenth year of activity.

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Electroencephalographic (EEG) recordings are, most of the times, corrupted by spurious artifacts, which should be rejected or cleaned by the practitioner. As human scalp EEG screening is error-prone, automatic artifact detection is an issue of capital importance, to ensure objective and reliable results. In this paper we propose a new approach for discrimination of muscular activity in the human scalp quantitative EEG (QEEG), based on the time-frequency shape analysis. The impact of the muscular activity on the EEG can be evaluated from this methodology. We present an application of this scoring as a preprocessing step for EEG signal analysis, in order to evaluate the amount of muscular activity for two set of EEG recordings for dementia patients with early stage of Alzheimer’s disease and control age-matched subjects.

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BACKGROUND: The heart relies on continuous energy production and imbalances herein impair cardiac function directly. The tricarboxylic acid (TCA) cycle is the primary means of energy generation in the healthy myocardium, but direct noninvasive quantification of metabolic fluxes is challenging due to the low concentration of most metabolites. Hyperpolarized (13)C magnetic resonance spectroscopy (MRS) provides the opportunity to measure cellular metabolism in real time in vivo. The aim of this work was to noninvasively measure myocardial TCA cycle flux (VTCA) in vivo within a single minute. METHODS AND RESULTS: Hyperpolarized [1-(13)C]acetate was administered at different concentrations in healthy rats. (13)C incorporation into [1-(13)C]acetylcarnitine and the TCA cycle intermediate [5-(13)C]citrate was dynamically detected in vivo with a time resolution of 3s. Different kinetic models were established and evaluated to determine the metabolic fluxes by simultaneously fitting the evolution of the (13)C labeling in acetate, acetylcarnitine, and citrate. VTCA was estimated to be 6.7±1.7μmol·g(-1)·min(-1) (dry weight), and was best estimated with a model using only the labeling in citrate and acetylcarnitine, independent of the precursor. The TCA cycle rate was not linear with the citrate-to-acetate metabolite ratio, and could thus not be quantified using a ratiometric approach. The (13)C signal evolution of citrate, i.e. citrate formation was independent of the amount of injected acetate, while the (13)C signal evolution of acetylcarnitine revealed a dose dependency with the injected acetate. The (13)C labeling of citrate did not correlate to that of acetylcarnitine, leading to the hypothesis that acetylcarnitine formation is not an indication of mitochondrial TCA cycle activity in the heart. CONCLUSIONS: Hyperpolarized [1-(13)C]acetate is a metabolic probe independent of pyruvate dehydrogenase (PDH) activity. It allows the direct estimation of VTCA in vivo, which was shown to be neither dependent on the administered acetate dose nor on the (13)C labeling of acetylcarnitine. Dynamic (13)C MRS coupled to the injection of hyperpolarized [1-(13)C]acetate can enable the measurement of metabolic changes during impaired heart function.

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CONTEXT: Complex steroid disorders such as P450 oxidoreductase deficiency or apparent cortisone reductase deficiency may be recognized by steroid profiling using chromatographic mass spectrometric methods. These methods are highly specific and sensitive, and provide a complete spectrum of steroid metabolites in a single measurement of one sample which makes them superior to immunoassays. The steroid metabolome during the fetal-neonatal transition is characterized by (a) the metabolites of the fetal-placental unit at birth, (b) the fetal adrenal androgens until its involution 3-6 months postnatally, and (c) the steroid metabolites produced by the developing endocrine organs. All these developmental events change the steroid metabolome in an age- and sex-dependent manner during the first year of life. OBJECTIVE: The aim of this study was to provide normative values for the urinary steroid metabolome of healthy newborns at short time intervals in the first year of life. METHODS: We conducted a prospective, longitudinal study to measure 67 urinary steroid metabolites in 21 male and 22 female term healthy newborn infants at 13 time-points from week 1 to week 49 of life. Urine samples were collected from newborn infants before discharge from hospital and from healthy infants at home. Steroid metabolites were measured by gas chromatography-mass spectrometry (GC-MS) and steroid concentrations corrected for urinary creatinine excretion were calculated. RESULTS: 61 steroids showed age and 15 steroids sex specificity. Highest urinary steroid concentrations were found in both sexes for progesterone derivatives, in particular 20α-DH-5α-DH-progesterone, and for highly polar 6α-hydroxylated glucocorticoids. The steroids peaked at week 3 and decreased by ∼80% at week 25 in both sexes. The decline of progestins, androgens and estrogens was more pronounced than of glucocorticoids whereas the excretion of corticosterone and its metabolites and of mineralocorticoids remained constant during the first year of life. CONCLUSION: The urinary steroid profile changes dramatically during the first year of life and correlates with the physiologic developmental changes during the fetal-neonatal transition. Thus detailed normative data during this time period permit the use of steroid profiling as a powerful diagnostic tool.