974 resultados para Inverse analysis


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This dissertation studies the geometric static problem of under-constrained cable-driven parallel robots (CDPRs) supported by n cables, with n ≤ 6. The task consists of determining the overall robot configuration when a set of n variables is assigned. When variables relating to the platform posture are assigned, an inverse geometric static problem (IGP) must be solved; whereas, when cable lengths are given, a direct geometric static problem (DGP) must be considered. Both problems are challenging, as the robot continues to preserve some degrees of freedom even after n variables are assigned, with the final configuration determined by the applied forces. Hence, kinematics and statics are coupled and must be resolved simultaneously. In this dissertation, a general methodology is presented for modelling the aforementioned scenario with a set of algebraic equations. An elimination procedure is provided, aimed at solving the governing equations analytically and obtaining a least-degree univariate polynomial in the corresponding ideal for any value of n. Although an analytical procedure based on elimination is important from a mathematical point of view, providing an upper bound on the number of solutions in the complex field, it is not practical to compute these solutions as it would be very time-consuming. Thus, for the efficient computation of the solution set, a numerical procedure based on homotopy continuation is implemented. A continuation algorithm is also applied to find a set of robot parameters with the maximum number of real assembly modes for a given DGP. Finally, the end-effector pose depends on the applied load and may change due to external disturbances. An investigation into equilibrium stability is therefore performed.

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In this Thesis we consider a class of second order partial differential operators with non-negative characteristic form and with smooth coefficients. Main assumptions on the relevant operators are hypoellipticity and existence of a well-behaved global fundamental solution. We first make a deep analysis of the L-Green function for arbitrary open sets and of its applications to the Representation Theorems of Riesz-type for L-subharmonic and L-superharmonic functions. Then, we prove an Inverse Mean value Theorem characterizing the superlevel sets of the fundamental solution by means of L-harmonic functions. Furthermore, we establish a Lebesgue-type result showing the role of the mean-integal operator in solving the homogeneus Dirichlet problem related to L in the Perron-Wiener sense. Finally, we compare Perron-Wiener and weak variational solutions of the homogeneous Dirichlet problem, under specific hypothesis on the boundary datum.

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A climatological field is a mean gridded field that represents the monthly or seasonal trend of an ocean parameter. This instrument allows to understand the physical conditions and physical processes of the ocean water and their impact on the world climate. To construct a climatological field, it is necessary to perform a climatological analysis on an historical dataset. In this dissertation, we have constructed the temperature and salinity fields on the Mediterranean Sea using the SeaDataNet 2 dataset. The dataset contains about 140000 CTD, bottles, XBT and MBT profiles, covering the period from 1900 to 2013. The temperature and salinity climatological fields are produced by the DIVA software using a Variational Inverse Method and a Finite Element numerical technique to interpolate data on a regular grid. Our results are also compared with a previous version of climatological fields and the goodness of our climatologies is assessed, according to the goodness criteria suggested by Murphy (1993). Finally the temperature and salinity seasonal cycle for the Mediterranean Sea is described.

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Coarse graining is a popular technique used in physics to speed up the computer simulation of molecular fluids. An essential part of this technique is a method that solves the inverse problem of determining the interaction potential or its parameters from the given structural data. Due to discrepancies between model and reality, the potential is not unique, such that stability of such method and its convergence to a meaningful solution are issues.rnrnIn this work, we investigate empirically whether coarse graining can be improved by applying the theory of inverse problems from applied mathematics. In particular, we use the singular value analysis to reveal the weak interaction parameters, that have a negligible influence on the structure of the fluid and which cause non-uniqueness of the solution. Further, we apply a regularizing Levenberg-Marquardt method, which is stable against the mentioned discrepancies. Then, we compare it to the existing physical methods - the Iterative Boltzmann Inversion and the Inverse Monte Carlo method, which are fast and well adapted to the problem, but sometimes have convergence problems.rnrnFrom analysis of the Iterative Boltzmann Inversion, we elaborate a meaningful approximation of the structure and use it to derive a modification of the Levenberg-Marquardt method. We engage the latter for reconstruction of the interaction parameters from experimental data for liquid argon and nitrogen. We show that the modified method is stable, convergent and fast. Further, the singular value analysis of the structure and its approximation allows to determine the crucial interaction parameters, that is, to simplify the modeling of interactions. Therefore, our results build a rigorous bridge between the inverse problem from physics and the powerful solution tools from mathematics. rn

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The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.

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Assessment of regional blood flow changes is difficult in the clinical setting. We tested whether conventional pulmonary artery catheters (PACs) can be used to measure regional venous blood flows by inverse thermodilution (ITD). Inverse thermodilution was tested in vitro and in vivo using perivascular ultrasound Doppler (USD) flow probes as a reference. In anesthetized pigs, PACs were inserted in jugular, hepatic, renal, and femoral veins, and their measurements were compared with simultaneous USD flow measurements from carotid, hepatic, renal, and femoral arteries and from portal vein. Fluid boluses were injected through the PAC's distal port, and temperature changes were recorded from the proximally located thermistor. Injectates of 2 and 5 mL at 22 degrees C and 4 degrees C were used. Flows were altered by using a roller pump (in vitro), and infusion of dobutamine and induction of cardiac tamponade, respectively. In vitro: At blood flows between 400 mL . min-1 and 700 mL . min-1 (n = 50), ITD and USD correlated well (r = 0.86, P < 0.0001), with bias and limits of agreement of 3 +/- 101 mL . min-1. In vivo: 514 pairs of measurements had to be excluded from analysis for technical reasons, and 976 were analyzed. Best correlations were r = 0.87 (P < 0.0001) for renal flow and r = 0.46 (P < 0.0001) for hepatic flow. No significant correlation was found for cerebral and femoral flows. Inverse thermodilution using conventional PAC compared moderately well with USD for renal but not for other flows despite good in vitro correlation in various conditions. In addition, this method has significant technical limitations.

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High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

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We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

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BACKGROUND Preterm birth, low birth weight, and infant catch-up growth seem associated with an increased risk of respiratory diseases in later life, but individual studies showed conflicting results. OBJECTIVES We performed an individual participant data meta-analysis for 147,252 children of 31 birth cohort studies to determine the associations of birth and infant growth characteristics with the risks of preschool wheezing (1-4 years) and school-age asthma (5-10 years). METHODS First, we performed an adjusted 1-stage random-effect meta-analysis to assess the combined associations of gestational age, birth weight, and infant weight gain with childhood asthma. Second, we performed an adjusted 2-stage random-effect meta-analysis to assess the associations of preterm birth (gestational age <37 weeks) and low birth weight (<2500 g) with childhood asthma outcomes. RESULTS Younger gestational age at birth and higher infant weight gain were independently associated with higher risks of preschool wheezing and school-age asthma (P < .05). The inverse associations of birth weight with childhood asthma were explained by gestational age at birth. Compared with term-born children with normal infant weight gain, we observed the highest risks of school-age asthma in children born preterm with high infant weight gain (odds ratio [OR], 4.47; 95% CI, 2.58-7.76). Preterm birth was positively associated with an increased risk of preschool wheezing (pooled odds ratio [pOR], 1.34; 95% CI, 1.25-1.43) and school-age asthma (pOR, 1.40; 95% CI, 1.18-1.67) independent of birth weight. Weaker effect estimates were observed for the associations of low birth weight adjusted for gestational age at birth with preschool wheezing (pOR, 1.10; 95% CI, 1.00-1.21) and school-age asthma (pOR, 1.13; 95% CI, 1.01-1.27). CONCLUSION Younger gestational age at birth and higher infant weight gain were associated with childhood asthma outcomes. The associations of lower birth weight with childhood asthma were largely explained by gestational age at birth.

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BACKGROUND We aimed to describe the effects of ticagrelor versus clopidogrel on stent thrombosis in the Platelet Inhibition and Patient Outcomes (PLATO) trial. METHODS AND RESULTS Of 18 624 patients hospitalized for acute coronary syndromes, 11 289 (61%) had at least 1 intracoronary stent. Ticagrelor reduced stent thrombosis compared with clopidogrel across all definitions: definite, 1.37% (n=71) versus 1.93% (n=105; hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.50-0.90; P=0.0091); definite or probable, 2.21% (n=118) versus 2.87% (n=157; HR, 0.75; 95% CI, 0.59-0.95; P=0.017); and definite, probable, and possible, 2.94% (n=154) versus 3.77 (n=201; HR, 0.77; 95% CI, 0.62-0.95). The reduction in definite stent thrombosis was consistent regardless of acute coronary syndrome type, presence of diabetes mellitus, stent type (drug-eluting or bare metal stent), CYP2C19 genetic status, loading dose of aspirin, dose of clopidogrel before randomization, and use of glycoprotein IIb/IIIa inhibitors at randomization. The reduction in stent thrombosis with ticagrelor was numerically greater for late (>30 days; HR, 0.48; 95% CI, 0.24-0.96) and subacute (4 hours-30 days; HR, 0.60; 95% CI, 0.39-0.93) compared with acute (<24 hours; HR, 0.94; 95% CI, 0.43-2.05) stent thrombosis or for patients compliant to therapy (ie, taking blinded study treatment ≥80% of the time) compared with less compliant patients. Randomization to ticagrelor was a strong independent inverse predictor of definite stent thrombosis (HR, 0.65; 95% CI, 0.48-0.88). CONCLUSION Ticagrelor compared with clopidogrel reduces the incidence of stent thrombosis in patients with acute coronary syndromes, with consistent benefit across a broad range of patient, stent, and treatment characteristics.

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There have been numerous reports over the past several years on the ability of vitamin A analogs (retinoids) to modulate cell proliferation, malignant transformation, morphogenesis, and differentiation in a wide variety of cell types and organisms. Two families of nuclear retinoid-inducible, trans-acting, transcription-enhancing receptors that bear strong DNA sequence homology to thyroid and steroid hormone receptors have recently been discovered. The retinoic acid receptors (RARs) and retinoid X receptors (RXRs) each have at least three types designated $\alpha,$ $\beta,$ and $\gamma,$ which are encoded by separate genes and expressed in a tissue and cell type-specific manner. We have been interested in the mechanism by which retinoids inhibit tumor cell proliferation and induce differentiation. As a model system we have employed several murine melanoma cell lines (S91-C2, K1735P, and B16-F1), which are sensitive to the growth-inhibitory and differentiation-inducing effects of RA, as well as a RA-resistant subclone of one of the cell lines (S91-C154), in order to study the role of the nuclear RARs in these effects. The initial phase of this project consisted of the characterization of the expression pattern of the three known RAR and RXR types in the murine melanoma cell lines in order to determine whether any differences exist which may elucidate a role for any of the receptors in RA-induced growth inhibition and differentiation. The novel finding was made that the RAR-$\beta$ gene is rapidly induced from undetectable levels by RA treatment at the mRNA and protein level, and that the induction of RAR-$\beta$ by other biologically active retinoids correlated with their ability to inhibit the growth of the highly RA-sensitive S91-C2 cell line. This suggests a role for RAR-$\beta$ in the growth inhibiting effect of retinoids. The second phase of this project involves the stable expression of RAR-$\beta$ in the S91-C2 cells and the RAR-$\beta$ receptor-null cell line, K1735P. These studies have indicated an inverse correlation between RAR-$\beta$ expression and proliferation rate. ^

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BACKGROUND AND PURPOSE Inverse relationship between onset-to-door time (ODT) and door-to-needle time (DNT) in stroke thrombolysis was reported from various registries. We analyzed this relationship and other determinants of DNT in dedicated stroke centers. METHODS Prospectively collected data of consecutive ischemic stroke patients from 10 centers who received IV thrombolysis within 4.5 hours from symptom onset were merged (n=7106). DNT was analyzed as a function of demographic and prehospital variables using regression analyses, and change over time was considered. RESULTS In 6348 eligible patients with known treatment delays, median DNT was 42 minutes and kept decreasing steeply every year (P<0.001). Median DNT of 55 minutes was observed in patients with ODT ≤30 minutes, whereas it declined for patients presenting within the last 30 minutes of the 3-hour time window (median, 33 minutes) and of the 4.5-hour time window (20 minutes). For ODT within the first 30 minutes of the extended time window (181-210 minutes), DNT increased to 42 minutes. DNT was stable for ODT for 30 to 150 minutes (40-45 minutes). We found a weak inverse overall correlation between ODT and DNT (R(2)=-0.12; P<0.001), but it was strong in patients treated between 3 and 4.5 hours (R(2)=-0.75; P<0.001). ODT was independently inversely associated with DNT (P<0.001) in regression analysis. Octogenarians and women tended to have longer DNT. CONCLUSIONS DNT was decreasing steeply over the last years in dedicated stroke centers; however, significant oscillations of in-hospital treatment delays occurred at both ends of the time window. This suggests that further improvements can be achieved, particularly in the elderly.