Maximum Smoothed Likelihood Component Density Estimation in Mixture Models with Known Mixing Proportions

In this paper, we propose a maximum smoothed likelihood method to estimate the component density functions of mixture models, in which the mixing proportions are known and may differ among observations. The proposed estimates maximize a smoothed log likelihood function and inherit all the important properties of probability density functions. A majorization-minimization algorithm is suggested to compute the proposed estimates numerically. In theory, we show that starting from any initial value, this algorithm increases the smoothed likelihood function and further leads to estimates that maximize the smoothed likelihood function. This indicates the convergence of the algorithm. Furthermore, we theoretically establish the asymptotic convergence rate of our proposed estimators. An adaptive procedure is suggested to choose the bandwidths in our estimation procedure. Simulation studies show that the proposed method is more efficient than the existing method in terms of integrated squared errors. A real data example is further analyzed

Leflunomide inhibits inflammation and apoptosis of H9c2 cells induced by hydrogen peroxide

 Purpose: To investigate the effects of leflunomide (Lef) on inflammatory response and apoptosis after myocardial infarction, and to explore its molecular mechanisms of action.Methods: H2O2 and H9c2 cells were used to establish myocardial cell injury model in vitro. H9c2 cells were divided into 3 groups: control group, H2O2 group, H2O2 + Lef group. The CCK-8 assay was used to determine the optimal concentration of H2O2 and Lef, while the expressions of TNF-α, IL-6, IL-1β, Bcl-2, Bax, Bad, TLR4, IκB-α, P65 and p-P65 were evaluated by Western blot. PCI was utilized to detect the expression of TNF-α, IL-6, IL-1β, Bcl-2, Bax and Bad mRNA. The levels of TNF-α, IL-6 and IL-1β in supernatant were assessed by ELISA, while apoptosis of the three groups was evaluated by TUNEL staining and flow cytometry.Results: Compared with H2O2 group, TNF-α, IL-6, IL-1β, Bax and Bad expressions in H2O2+Lef group were significantly reduced (p < 0.05), but Bcl-2 expression significantly increased. The levels of TNF-α and IL-6 and IL-1β in supernatant of H2O2 + Lef group were also decreased compared to those in the H2O2 group (p < 0.05). In addition, TUNEL-positive cells and apoptotic rates were significantly reduced after treatment with Lef. Moreover, Lef inhibited expression of TLR4 and p-P65, but activated expression of IκB-α, indicating that Lef inhibited TLR4/NF-κB pathway (p < 0.05).Conclusion: The results show that Lef inhibits H2O2-induced H9c2 cell apoptosis and inflammatory responses by inhibiting TLR4/NF-κB pathway. These findings may provide new targets for the treatment of myocardial infarction

Quantitative spectroscopic analysis of heterogeneous mixtures: the correction of multiplicative effects caused by variations in physical properties of samples

Spectral measurements of complex heterogeneous types of mixture samples are often affected by significant multiplicative effects resulting from light scattering, due to physical variations (e.g. particle size and shape, sample packing and sample surface, etc.) inherent within the individual samples. Therefore, the separation of the spectral contributions due to variations in chemical compositions from those caused by physical variations is crucial to accurate quantitative spectroscopic analysis of heterogeneous samples. In this work, an improved strategy has been proposed to estimate the multiplicative parameters accounting for multiplicative effects in each measured spectrum, and hence mitigate the detrimental influence of multiplicative effects on the quantitative spectroscopic analysis of heterogeneous samples. The basic assumption of the proposed method is that light scattering due to physical variations has the same effects on the spectral contributions of each of the spectroscopically active chemical component in the same sample mixture. Based on this underlying assumption, the proposed method realizes the efficient estimation of the multiplicative parameters by solving a simple quadratic programming problem. The performance of the proposed method has been tested on two publicly available benchmark data sets (i.e. near-infrared total diffuse transmittance spectra of four-component suspension samples and near infrared spectral data of meat samples) and compared with some empirical approaches designed for the same purpose. It was found that the proposed method provided appreciable improvement in quantitative spectroscopic analysis of heterogeneous mixture samples. The study indicates that accurate quantitative spectroscopic analysis of heterogeneous mixture samples can be achieved through the combination of spectroscopic techniques with smart modeling methodology

A Vertical Resonance Heating Model for X- or Peanut-Shaped Galactic Bulges

We explore a second order Hamiltonian vertical resonance model for X-shaped or peanut-shaped galactic bulges. The X-shape is caused by the 2:1 vertical Lindblad resonance with the bar, with two vertical oscillation periods per orbital period in the bar frame. We examine N-body simulations and find that due to the bar slowing down and disk thickening during bar buckling, the resonance and associated peanut-shape moves outward. The peanut-shape is consistent with the location of the vertical resonance, independent of whether the bar buckled or not. We estimate the resonance width from the potential m=4 Fourier component and find that the resonance is narrow, affecting orbits over a narrow range in the angular momentum distribution, dL/L ~ 0.05. As the resonance moves outward, stars originally in the mid plane are forced out of the mid plane into orbits just within the resonance separatrix. The height of the separatrix orbits, estimated from the Hamiltonian model, is approximately consistent with the peanut-shape height. The X-shape is comprised of stars in the vicinity of the resonance separatrix. The velocity distributions from the simulations illustrate that low inclination orbits are depleted within resonance. Within resonance, the vertical velocity distribution is broad, consistent with resonant heating caused by the passage of the resonance through the disk. In the Milky Way bulge we relate the azimuthally averaged mid-plane mass density near the vertical resonance to the rotation curve and bar pattern speed. At an estimated vertical resonance galactocentric radius of ~1.3 kpc, we confirm a mid-plane density of ~5x10^8 Msol/kpc^3, consistent with recently estimated mass distributions. We find that the rotation curve, bar pattern speed, 2:1 vertical resonance location, X-shape tips, and mid-plane mass density, are all self-consistent in the Milky Way galaxy bulge.Comment: accepted for publication in MNRA

A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model. Journal web page & a lot of robotic related papers www.ars-journal.co