3,980 research outputs found
The leptonic decay using the principle of maximum conformality
In the paper, we study the leptonic decay width
by using the principle of maximum
conformality (PMC) scale-setting approach. The PMC adopts the renormalization
group equation to set the correct momentum flow of the process, whose value is
independent to the choice of the renormalization scale and its prediction thus
avoids the conventional renormalization scale ambiguities. Using the known
next-to-next-to-next-to-leading order perturbative series together with the PMC
single scale-setting approach, we do obtain a renormalization scale independent
decay width, keV,
where the error is squared average of those from
, GeV and the choices of
factorization scales within of their central values. To compare with
the result under conventional scale-setting approach, this decay width agrees
with the experimental value within errors, indicating the importance of a
proper scale-setting approach.Comment: 6 pages, 4 figure
Clinical Research on Treatment of Vertebroarterial Type of Cervical Spondylosis with 5-step Manipulation and Traction
ObjectiveTo observe the therapeutic effect of 5-step manipulation and traction of cervical vertebrae on vertebroarterial type of cervical spondylosis and probe its mechanism.MethodsThe 120 patients were randomly divided into a treatment group (manipulation group) and a control group (traction group) with 60 cases in each. The curative effects in the two groups were evaluated after treatment.ResultsThe curative rate and the total effective rate is 26.7% and 93.4% respectively in the treatment group, and 13.3% and 86.7% respectively in the control group, with statistical significance in the total effective rate of the two groups (P<0.05).ConclusionManipulation and traction of cervical vertebrae can effectively improve the clinical symptoms of vetebroarterical type of cervical spondylosis with a good therapeutic effect
Multiple Model Rao-Blackwellized Particle Filter for Manoeuvring Target Tracking
Particle filters can become quite inefficient when applied to a high-dimensional state space since a prohibitively large number of samples may be required to approximate the underlying density functions with desired accuracy. In this paper, a novel multiple model Rao-Blackwellized particle filter (MMRBPF)-based algorithm has been proposed for manoeuvring target tracking in a cluttered environment. The advantage of the proposed approach is that the Rao-Blackwellization allows the algorithm to be partitioned into target tracking and model selection sub-problems, where the target tracking can be solved by the probabilistic data association filter, and the model selection by sequential importance sampling. The analytical relationship between target state and model is exploited to improve the efficiency and accuracy of the proposed algorithm. Moreover, to reduce the particle-degeneracy problem, the resampling approach is selectively carried out. Finally, experiment results, show that the proposed algorithm, has advantages over the conventional IMM-PDAF algorithm in terms of robust and efficiency.Defence Science Journal, 2009, 59(3), pp.197-204, DOI:http://dx.doi.org/10.14429/dsj.59.151
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