2,345 research outputs found
Time-varying parametric modelling and time-dependent spectral characterisation with applications to EEG signals using multi-wavelets
A new time-varying autoregressive (TVAR) modelling approach is proposed for nonstationary signal processing and analysis, with application to EEG data modelling and power spectral estimation. In the new parametric modelling framework, the time-dependent coefficients of the TVAR model are represented using a novel multi-wavelet decomposition scheme. The time-varying modelling problem is then reduced to regression selection and parameter estimation, which can be effectively resolved by using a forward orthogonal regression algorithm. Two examples, one for an artificial signal and another for an EEG signal, are given to show the effectiveness and applicability of the new TVAR modelling method
Probability distribution function for self-organization of shear flows
The first prediction of the probability distribution function (PDF) of self-organized shear flows is presented in a nonlinear diffusion model where shear flows are generated by a stochastic forcing while diffused by a nonlinear eddy diffusivity. A novel nonperturbative method based on a coherent structure is utilized for the prediction of the strongly intermittent exponential PDF tails of the gradient of shear flows. Numerical simulations using Gaussian forcing not only confirm these predictions but also reveal the significant contribution from the PDF tails with a large population of supercritical gradients. The validity of the nonlinear diffusion model is then examined using a threshold model where eddy diffusivity is given by discontinuous values, elucidating an important role of relative time scales of relaxation and disturbance in the determination of the PDFs
On property B(s), II
AbstractDenote by m(n,s) the size of a smallest family F; of n-element sets with the property that if |Sâ©F|â©Ÿ1 for all FâF, then |Sâ©F|â©Ÿs for some FâF;. We obtain some bounds for m(n,s)
Ramsey numbers for triples
AbstractSome recurrence inequalities for Ramsey numbers for triples are established by means of explicit constructions
Improving gas sensing properties of graphene by introducing dopants and defects: a first-principles study
The interactions between four different graphenes (including pristine, B- or N-doped and defective graphenes) and small gas molecules (CO, NO, NO2 and NH3) were investigated by using density functional computations to exploit their potential applications as gas sensors. The structural and electronic properties of the graphene-molecule adsorption adducts are strongly dependent on the graphene structure and the molecular adsorption configuration. All four gas molecules show much stronger adsorption on the doped or defective graphenes than that on the pristine graphene. The defective graphene shows the highest adsorption energy with CO, NO and NO2 molecules, while the B- doped graphene gives the tightest binding with NH3. Meanwhile, the strong interactions between the adsorbed molecules and the modified graphenes induce dramatic changes to graphene's electronic properties. The transport behavior of a gas sensor using B- doped graphene shows a sensitivity two orders of magnitude higher than that of pristine graphene. This work reveals that the sensitivity of graphene-based chemical gas sensors could be drastically improved by introducing the appropriate dopant or defect
Parameter estimation for VSI-Fed PMSM based on a dynamic PSO with learning strategies
© 1986-2012 IEEE.A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key parameter estimation for permanent magnet synchronous machines (PMSMs), where the voltage-source inverter (VSI) nonlinearities are taken into account in the parameter estimation model and can be estimated simultaneously with other machine parameters. In the DPSO-LS algorithm, a novel movement modification equation with variable exploration vector is designed to effectively update particles, enabling swarms to cover large areas of search space with large probability and thus the global search ability is enhanced. Moreover, a Gaussian-distribution-based dynamic opposition-based learning strategy is developed to help the pBest jump out local optima. The proposed DPSO-LS can significantly enhance the estimator model accuracy and dynamic performance. Finally, the proposed algorithm is applied to multiple parameter estimation including the VSI nonlinearities of a PMSM. The performance of DPSO-LS is compared with several existing PSO algorithms, and the comparison results show that the proposed parameters estimation method has better performance in tracking the variation of machine parameters effectively and estimating the VSI nonlinearities under different operation conditions
Effect of substituting guinea grass with sunflower hulls on production performance and digestion traits in fattening rabbits
[EN] The objective of this study was to evaluate the use of sunflower hulls (SH) to substitute guinea grass (GG), traditionally used as a fibre source in the diets of fattening rabbits, on production performance, coefficients of total tract apparent digestibility (CTTAD) of nutrients, gastrointestinal tract development and caecal fermentation. A total of 160 mixed sex Hyla commercial meat rabbits were allocated to 4 experimental groups (40 per treatment) differing in the SH level inclusion in the diet offered to rabbits from 40 to 90 d of age: 0, 30, 60 and 90 g/kg on as-fed basis: SH0, SH30, SH60 and SH90 groups, respectively. Growth performance was recorded from 47 to 90 d of age, CTTAD of nutrients from 86 to 90 d of age, and gastrointestinal tract development, caecal fermentation and carcass traits were determined at 90 d of age. Increasing substitutions of SH in the diet indicated effects on growth performance, as higher feed intake and lower feed efficiency were observed in SH90 compared with SH0 (P-linear<0.05). Moreover, the higher SH substitution diet (SH60 and SH90) increased the relative caecum weight (P-linear<0.05). A linear negative effect of SH inclusion was observed for the digestibility of neutral detergent fibre (CTTAD from 0.294 to 0.232) and acid detergent fibre (CTTAD from 0.182 to 0.136; P-linear<0.05). Dietary SH substitution level had a quadratic effect on the villus height of the duodenum, jejunum and ileum obtained (P-quadratic<0.05), and the highest were observed in the SH60 group. There was a quadratic effect on the pH of caecum content (P-quadratic<0.05), and the lowest was 6.08 in SH30 group. The total volatil fatty acids increased linearly with increasing SH in diets (from 71.11 to 76.98 mmol/L; P-linear<0.05), and when dietary SH increased, the proportion of acetate tended to increase (P-linear<0.05), and the proportions of propionic and butyric were decreased (P-linear<0.05, respectively). Substitution of GG with SH had no effect on carcass characteristics and meat quality. The current work shows that SH can replace up to 60 g/kg in diets for fattening rabbits, with no adverse impact on aspects of production performance or digestion traits.This study was supported by the earmarked fund for Modern Agro-industry Technology Research System (CARS-43-B-1) and Funds of Shandong âDouble Topsâ Programme.Liu, G.; Sun, C.; Zhao, X.; Liu, H.; Wu, Z.; Li, F. (2018). Effect of substituting guinea grass with sunflower hulls on production performance and digestion traits in fattening rabbits. World Rabbit Science. 26(3):217-225. https://doi.org/10.4995/wrs.2018.9375SWORD21722526
Short-segment posterior instrumentation combined with calcium sulfate cement vertebroplasty for thoracolumbar compression fractures: Radiographic outcomes including nonunion and other complications
AbstractObjectiveTo evaluate the radiographic outcomes of short-segment posterior instrumentation plus vertebroplasty using injectable calcium sulfate cement (CSC) for thoracolumbar compression fractures.Materials and methodsTwenty-eight patients with a single-level thoracolumbar compression fracture, who underwent short-segment pedicle screw fixation and CSC vertebroplasty, were included in the study. The anterior vertebral body height ratio, local kyphosis angle, and the height of the intervertebral disc adjacent to the fractured vertebra were used to evaluate the radiographic results. Complications including bone nonunion, instrument failure, cement leakage, and disc vacuum formation were also assessed.ResultsThe patients were followed up for an average of 24.20±5.40 months. The relative preoperative anterior body height was 55.71±15.29%, which improved to 94.93±5.39% immediately after surgery (P<0.001), and at final follow-up showed a 6.50±3.89% loss of height correction (P<0.001). The mean preoperative local kyphosis angle was 22.23±5.65°, which corrected to 2.67±4.43° immediately after surgery (P<0.001), but reverted to 6.71±4.95° at final follow-up, showing a 4.04±1.91° loss of correction (P<0.001). The mean height of the intervertebral disc proximal to the fractured vertebra was 9.87±0.91mm before surgery, 12.53±0.98mm after operation (P<0.001), and the loss of correction at final follow-up was 2.35±1.15mm with a significant difference compared to immediate postoperative values (P<0.001). Bone nonunion occurred in 7 patients, 2 patients had hardware failure, 9 patients had cement leakage, and 10 patients had disc vacuum phenomenon adjacent to the fractured vertebra.ConclusionsThe patients who underwent this procedure had a loss of correction of vertebral height and local kyphosis. Complications such as bone nonunion, instrument failure, cement leakage, and disc vacuum may occur. Rapid CSC resorption accounts for these radiographic outcomes and complications.Level of evidenceLevel IV, retrospective study
Spectral high resolution feature selection for retrieval of combustion temperature profiles
Proceeding of: 7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006 (Burgos, Spain, September 20-23, 2006)The use of high spectral resolution measurements to obtain a retrieval of certain physical properties related with the radiative transfer of energy leads a priori to a better accuracy. But this improvement in accuracy is not easy to achieve due to the great amount of data which makes difficult any treatment over it and it's redundancies. To solve this problem, a pick selection based on principal component analysis has been adopted in order to make the mandatory feature selection over the different channels. In this paper, the capability to retrieve the temperature profile in a combustion environment using neural networks jointly with this spectral high resolution feature selection method is studied.Publicad
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