965 resultados para Zeros of perturbed polynomials


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Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P(aw)) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H(2)O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P(aw) and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA(AL)). We aimed to develop and validate a mathematical algorithm to identify NAVA(AL). P(aw), Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P(aw) peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P(aw) peaks and Vt. The beginning of the P(aw) and Vt plateaus, and thus NAVA(AL), was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA(AL) visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H(2)O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H(2)O/μV. NAVA(AL) identified by our model was below the range of visually estimated NAVA(AL) in two instances and was above in one instance. We conclude that our model identifies NAVA(AL) in most instances with acceptable accuracy for application in clinical routine and research.

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A general approach is presented for implementing discrete transforms as a set of first-order or second-order recursive digital filters. Clenshaw's recurrence formulae are used to formulate the second-order filters. The resulting structure is suitable for efficient implementation of discrete transforms in VLSI or FPGA circuits. The general approach is applied to the discrete Legendre transform as an illustration.

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Custom modes at a wavelength of 1064 nm were generated with a deformable mirror. The required surface deformations of the adaptive mirror were calculated with the Collins integral written in a matrix formalism. The appropriate size and shape of the actuators as well as the needed stroke were determined to ensure that the surface of the controllable mirror matches the phase front of the custom modes. A semipassive bimorph adaptive mirror with five concentric ring-shaped actuators and one defocus actuator was manufactured and characterised. The surface deformation was modelled with the response functions of the adaptive mirror in terms of an expansion with Zernike polynomials. In the experiments the Nd:YAG laser crystal was quasi-CW pumped to avoid thermally induced distortions of the phase front. The adaptive mirror allows to switch between a super-Gaussian mode, a doughnut mode, a Hermite-Gaussian fundamental beam, multi-mode operation or no oscillation in real time during laser operation.

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This project addresses the potential impacts of changing climate on dry-season water storage and discharge from a small, mountain catchment in Tanzania. Villagers and water managers around the catchment have experienced worsening water scarcity and attribute it to increasing population and demand, but very little has been done to understand the physical characteristics and hydrological behavior of the spring catchment. The physical nature of the aquifer was characterized and water balance models were calibrated to discharge observations so as to be able to explore relative changes in aquifer storage resulting from climate changes. To characterize the shallow aquifer supplying water to the Jandu spring, water quality and geochemistry data were analyzed, discharge recession analysis was performed, and two water balance models were developed and tested. Jandu geochemistry suggests a shallow, meteorically-recharged aquifer system with short circulation times. Baseflow recession analysis showed that the catchment behavior could be represented by a linear storage model with an average recession constant of 0.151/month from 2004-2010. Two modified Thornthwaite-Mather Water Balance (TMWB) models were calibrated using historic rainfall and discharge data and shown to reproduce dry-season flows with Nash-Sutcliffe efficiencies between 0.86 and 0.91. The modified TMWB models were then used to examine the impacts of nineteen, perturbed climate scenarios to test the potential impacts of regional climate change on catchment storage during the dry season. Forcing the models with realistic scenarios for average monthly temperature, annual precipitation, and seasonal rainfall distribution demonstrated that even small climate changes might adversely impact aquifer storage conditions at the onset of the dry season. The scale of the change was dependent on the direction (increasing vs. decreasing) and magnitude of climate change (temperature and precipitation). This study demonstrates that small, mountain aquifer characterization is possible using simple water quality parameters, recession analysis can be integrated into modeling aquifer storage parameters, and water balance models can accurately reproduce dry-season discharges and might be useful tools to assess climate change impacts. However, uncertainty in current climate projections and lack of data for testing the predictive capabilities of the model beyond the present data set, make the forecasts of changes in discharge also uncertain. The hydrologic tools used herein offer promise for future research in understanding small, shallow, mountainous aquifers and could potentially be developed and used by water resource professionals to assess climatic influences on local hydrologic systems.

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This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

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This dissertation presents a detailed study in exploring quantum correlations of lights in macroscopic environments. We have explored quantum correlations of single photons, weak coherent states, and polarization-correlated/polarization-entangled photons in macroscopic environments. These included macroscopic mirrors, macroscopic photon number, spatially separated observers, noisy photons source and propagation medium with loss or disturbances. We proposed a measurement scheme for observing quantum correlations and entanglement in the spatial properties of two macroscopic mirrors using single photons spatial compass state. We explored the phase space distribution features of spatial compass states, such as chessboard pattern by using the Wigner function. The displacement and tilt correlations of the two mirrors were manifested through the propensities of the compass states. This technique can be used to extract Einstein-Podolsky-Rosen correlations (EPR) of the two mirrors. We then formulated the discrete-like property of the propensity Pb(m,n), which can be used to explore environmental perturbed quantum jumps of the EPR correlations in phase space. With single photons spatial compass state, the variances in position and momentum are much smaller than standard quantum limit when using a Gaussian TEM00 beam. We observed intrinsic quantum correlations of weak coherent states between two parties through balanced homodyne detection. Our scheme can be used as a supplement to decoy-state BB84 protocol and differential phase-shift QKD protocol. We prepared four types of bipartite correlations ±cos2(θ12) that shared between two parties. We also demonstrated bits correlations between two parties separated by 10 km optical fiber. The bits information will be protected by the large quantum phase fluctuation of weak coherent states, adding another physical layer of security to these protocols for quantum key distribution. Using 10 m of highly nonlinear fiber (HNLF) at 77 K, we observed coincidence to accidental-coincidence ratio of 130±5 for correlated photon-pair and Two-Photon Interference visibility >98% entangled photon-pair. We also verified the non-local behavior of polarization-entangled photon pair by violating Clauser-Horne-Shimony-Holt Bell’s inequality by more than 12 standard deviations. With the HNLF at 300 K (77 K), photon-pair production rate about factor 3(2) higher than a 300 m dispersion-shifted fiber is observed. Then, we studied quantum correlation and interference of photon-pairs; with one photon of the photon-air experiencing multiple scattering in a random medium. We observed that depolarization noise photon in multiple scattering degrading the purity of photon-pair, and the existence of Raman noise photon in a photon-pair source will contribute to the depolarization affect. We found that quantum correlation of polarization-entangled photon-pair is better preserved than polarization-correlated photon-pair as one photon of the photon-pair scattered through a random medium. Our findings showed that high purity polarization-entangled photon-pair is better candidate for long distance quantum key distribution.

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Despite enormous research in the field of hypertension, its pathophysiology still remains largely unresolved and appears to be multifactorial. In the present communication, we have analyzed the status of nitric oxide (NO) in the patients with essential hypertension and age matched controls. We have found that the levels of NO are lowered in essential hypertension. The normalization of blood pressure by administration of antihypertensive therapy causes rise in the NO level indicating that perturbed NO status in essential hypertension is reversible. Addition of antioxidant to the antihypertensive drugs causes a further, though non significant, rise in the levels of NO, suggesting that antioxidants may be combined with antihypertensive drugs as adjunct in the management of essential hypertension.

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Sr2+ co-doped LaBr3:5%Ce scintillators show a record low energy resolution of 2% at 662 keV and a considerably better proportional response compared to standard LaBr3:5%Ce. This paper reports on the optical properties and time response of Sr co-doped LaBr3:5%Ce. Multiple excitation and emission bands were observed in X-ray and optically excited luminescence measurements. Those bands are ascribed to three different Ce3+ sites. The first is the unperturbed site with the same luminescence properties as those of standard LaBr3:Ce. The other two are perturbed sites with red-shifted 4f-5d1 Ce3+ excitation and emission bands, longer Ce3+ decay times, and smaller Stokes shifts. The lowering of the lowest 5d level of Ce3+ was ascribed to larger crystal field interactions at the perturbed sites. Two types of point defects in the LaBr3 matrix were proposed to explain the observed results. No Ce4+ ions were detected in Sr co-doped LaBr3:5%Ce by diffuse reflectance measurements.

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Evidence of negative conspecific density dependence (NDD) operating on seedling survival and sapling recruitment has accumulated recently. In contrast, evidence of NDD operating on growth of trees has been circumstantial at best. Whether or not local NDD at the level of individual trees leads to NDD at the level of the community is still an open question. Moreover, whether and how perturbations interfere with these processes have rarely been investigated. We applied neighborhood models to permanent plot data from a Bornean dipterocarp forest censused over two 10-11 year periods. Although the first period was only lightly perturbed, a moderately strong El Nino event causing severe drought occurred in the first half of the second period. Such events are an important component of the environmental stochasticity affecting the region. We show that local NDD on growth of small-to-medium-sized trees may indeed translate to NDD at the level of the community. This interpretation is based on increasingly negative effects of bigger conspecific neighbors on absolute growth rates of individual trees with increasing basal area across the 18 most abundant overstory species in the first period. However, this relationship was much weaker in the second period. We interpreted this relaxation of local and community-level NDD as a consequence of increased light levels at the forest floor due to temporary leaf and twig loss of large trees in response to the drought event. Mitigation of NDD under climatic perturbation acts to decrease species richness, especially in forest overstory and therefore has an important role in determining species relative abundances at the site.

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In this article we propose an exact efficient simulation algorithm for the generalized von Mises circular distribution of order two. It is an acceptance-rejection algorithm with a piecewise linear envelope based on the local extrema and the inflexion points of the generalized von Mises density of order two. We show that these points can be obtained from the roots of polynomials and degrees four and eight, which can be easily obtained by the methods of Ferrari and Weierstrass. A comparative study with the von Neumann acceptance-rejection, with the ratio-of-uniforms and with a Markov chain Monte Carlo algorithms shows that this new method is generally the most efficient.

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Responses of many real-world problems can only be evaluated perturbed by noise. In order to make an efficient optimization of these problems possible, intelligent optimization strategies successfully coping with noisy evaluations are required. In this article, a comprehensive review of existing kriging-based methods for the optimization of noisy functions is provided. In summary, ten methods for choosing the sequential samples are described using a unified formalism. They are compared on analytical benchmark problems, whereby the usual assumption of homoscedastic Gaussian noise made in the underlying models is meet. Different problem configurations (noise level, maximum number of observations, initial number of observations) and setups (covariance functions, budget, initial sample size) are considered. It is found that the choices of the initial sample size and the covariance function are not critical. The choice of the method, however, can result in significant differences in the performance. In particular, the three most intuitive criteria are found as poor alternatives. Although no criterion is found consistently more efficient than the others, two specialized methods appear more robust on average.

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Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

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In Escherichia coli, the Min system, consisting of three proteins, MinC, MinD, and MinE, negatively regulates FtsZ assembly at the cell poles, helping to ensure that the Z ring will assemble only at midcell. Of the three Min proteins, MinC is sufficient to inhibit Z-ring assembly. By binding to MinD, which is mostly localized at the membrane near the cell poles, MinC is sequestered away from the cell midpoint, increasing the probability of Z-ring assembly there. Previously, it has been shown that the two halves of MinC have two distinct functions. The N-terminal half is sufficient for inhibition of FtsZ assembly, whereas the C-terminal half of the protein is required for binding to MinD as well as to a component of the division septum. In this study, we discovered that overproduction of the C-terminal half of MinC (MinC(122-231)) could also inhibit cell division and that this inhibition was at the level of Z-ring disassembly and dependent on MinD. We also found that fusing green fluorescent protein to either the N-terminal end of MinC(122-231), the C terminus of full-length MinC, or the C terminus of MinC(122-231) perturbed MinC function, which may explain why cell division inhibition by MinC(122-231) was not detected previously. These results suggest that the C-terminal half of MinC has an additional function in the regulation of Z-ring assembly.

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Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

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Mice that lack all beta1-class integrins in neurons and glia die prematurely after birth with severe brain malformations. Cortical hemispheres and cerebellar folia fuse, and cortical laminae are perturbed. These defects result from disorganization of the cortical marginal zone, where beta1-class integrins regulate glial endfeet anchorage, meningeal basement membrane remodeling, and formation of the Cajal-Retzius cell layer. Surprisingly, beta1-class integrins are not essential for neuron-glia interactions and neuronal migration during corticogenesis. The phenotype of the beta1-deficient mice resembles pathological changes observed in human cortical dysplasias, suggesting that defective integrin-mediated signal transduction contributes to the development of some of these diseases.