7,492 research outputs found

    A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons

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    In this paper, we present a comprehensive review of the data sources and estimation methods of 30 currently available global precipitation data sets, including gauge-based, satellite-related, and reanalysis data sets. We analyzed the discrepancies between the data sets from daily to annual timescales and found large differences in both the magnitude and the variability of precipitation estimates. The magnitude of annual precipitation estimates over global land deviated by as much as 300 mm/yr among the products. Reanalysis data sets had a larger degree of variability than the other types of data sets. The degree of variability in precipitation estimates also varied by region. Large differences in annual and seasonal estimates were found in tropical oceans, complex mountain areas, northern Africa, and some high-latitude regions. Overall, the variability associated with extreme precipitation estimates was slightly greater at lower latitudes than at higher latitudes. The reliability of precipitation data sets is mainly limited by the number and spatial coverage of surface stations, the satellite algorithms, and the data assimilation models. The inconsistencies described limit the capability of the products for climate monitoring, attribution, and model validation

    Quantisation of 2D-gravity with Weyl and area-preserving diffeomorphism invariances

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    The constraint structure of 2D-gravity with the Weyl and area-preserving diffeomorphism invariances is analysed in the ADM formulation. It is found that when the area-preserving diffeomorphism constraints are kept, the usual conformal gauge does not exist, whereas there is the possibility to choose the so-called ``quasi-light-cone'' gauge, in which besides the area-preserving diffeomorphism invariance, the reduced Lagrangian also possesses the SL(2,R) residual symmetry. The string-like approach is applied to quantise this model, but a fictitious non-zero central charge in the Virasoro algebra appears. When a set of gauge-independent SL(2,R) current-like fields is introduced instead of the string-like variables, a consistent quantum theory is obtained.Comment: 14 pages, Latex fil

    Iterative learning control method for improving the effectiveness of upper limb rehabilitation

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    In rehabilitation, passive control mode is common used at early stages of the post-stroke therapy, when the impaired limb is usually unresponsive. The simplest is the use of a proportional-integral-derivative (PID) feedback control which usually regulates the position or the interaction force along a known reference. Nonetheless PID method cannot achieve an ideal tracking performance due to dynamical uncertainties and unknown time-varying periodic disturbances from the environment. In order to minimize steady-state error with respect to uncertainties in exoskeleton passive control, Iterative Learning Control(ILC) and Neural PID control are proposed to improve the control effective of conventional linear PID. In this paper, two different control algorithms are introduced. Moreover, an experimental study on a 5-DOF upper limb exoskeleton with them is addressed for comparison

    Automatic Crack Detection Algorithm for Vibrothermography Sequence-of-Images Data

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    Vibrothermography (Sonic IR, thermosonics) is a technique for finding cracks through frictional heat given off in response to vibration. Vibrothermography provides a sequence of infrared images as output of the inspection process. A fast and accurate automatic crack‐detection algorithm for the sequence‐of‐images data will greatly increase the productivity of vibrothermography method. Matched filtering is a technique widely used in signal detection, and it is the optimal linear filter to maximize the signal‐to‐noise ratio in the presence of additive uncorrelated stochastic noise. Based on key features from images of known cracks, we can construct a three‐dimensional matched filter to detect cracks from the vibrothermography data. In this paper, we evaluate the matched filter developed from a vibrothermography inspection sequence‐of‐images. The probability of detection for the matched filter detection algorithm is then compared with the probability of detection for a simpler detection algorithm that is based on a scalar measure of the amount of heat generated in an inspection. Our results show the matched filter algorithm provides improved detection capability when a flaw signature is known approximately

    Design, synthesis and application of paramagnetic NMR ptobes for protein strucutre studies

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    The main subject of this thesis is the design and synthesis of paramagnetic molecules for protein studies with NMR and EPR spectroscopy. With the development of paraNMR and DEER experiments, synthetic paramagnetic centers are becoming popular. About half of the current paramagnetic probes were described in the past five years, reflecting this popularity. Several of them improved the stability and rigidity of the probes, mainly by introducing novel attachment groups forming thioether and triazole linkers.1–3 Such linkages help to extend the application of the probes to in-cell measurements.4,5 Some small probes were designed for 3d-block metal ions as well, but these probes show low metal ion binding affinity.6,7 The research described in this thesis contributed to the development of paramagnetic probes. Hereafter, the properties of these new probes are discussed, and some general conclusions and prospects are given.Macromolecular Biochemistr
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