Robust stability of Metzler operators under parameter perturbations

In this paper we study how the spectral bound of Metzler operators changes under parameter perturbations. Characterizations of the stability radii of Metzler operator with respect to this type of disturbances are established. The results generalize those obtained in (Vietnam J. Math. 2006; 34 :357–368; Vietnam J. Math. 1998; 26 :147–163). Copyright © 2009 John Wiley & Sons, Ltd.     

Coupling strategy for matching different methods in solving singularity problems

For solving elliptic boundary value problems with singularities, we have proposed the combined methods consisting of the Ritz-Galerkin method using singular (or analytic) basic functions for one part,S ₂, of the solution domainS, where there exist singular points, and the finite element method for the remaining partS ₁ ofS, where the solution is smooth enough. In this paper, general approaches using additional integrals are presented to match different numerical methods along their common boundary Г₀. Errors and stability analyses are provided for such a general coupling strategy. These analyses are important because they form a theoretical basis for a number of combinations between the Ritz-Galerkin and finite element methods addressed in [7], and because they can lead to new combinations of other methods, such as the combined methods of the Ritz-Galerkin and finite difference methods. Moreover, the analyses in this paper can be applied or extended to solve general elliptic boundary value problems with angular singularities, interface singularity or unbounded domain.     

Sidegating in a GaAs MBE-grown HFET structure

The sidegating effect in a MBE-grown HFET GaAs structure is considerable and persists to large distances. On the other hand, the leakage current is very low. A model that takes into account the unusual features of sidegating in this structure and is consistent with other studies of similar structures is proposed. On the basis of the model, a change in the isolation process was implemented. This resulted in a large reduction of the sidegating effect and confirmed the main features of the model     

Calorimetric Cv-V-T measurements and the equation of state for n-Propyl alcohol

Calorimeteric C_v-V-T measurements have given a new equation of state for n-propyl alcohol, which incorporates qualitative features of the critical point and the stability limit for the homogeneous phase (spinodal).Deceased.Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 51, No. 2, pp. 275–281, August, 1986.     

Class-E amplifier with an inductive impedance inverter

A design procedure and experimental results are presented for a class-E amplifier with an inductive impedance inverter. Experimental waveforms and characteristics measured at 1 MHz with an IRF620 MOSFET are given for the amplifier, which can operate under zero-voltage switching conditions for load resistances ranging from a short circuit to an open circuit. As the load resistance is increased at a fixed frequency, (1) the output power decreases, (2) a maximum efficiency of 96% occurs for optimum operation, (3) the peak values of the transistor voltage and the transistor current decrease, (4) the normalized peak values of the transistor voltage decrease, and (5) the normalized peak values of the transistor current increase     

Improved fracture toughness and fatigue life of carbon fiber reinforced epoxy composite due to incorporation of rubber nanoparticles

In this study, core–shell rubber (CSR) nanoparticles with approximate particle size of 35 nm were used as a modifier for the epoxy polymer. The effects of various CSR contents in the epoxy matrix on mode I interlaminar fracture toughness, tensile strength, and fatigue life of the carbon fabric reinforced epoxy (CF/EP) composites were investigated. The experimental results showed that the mode I interlaminar fracture toughness at crack initiation and propagation significantly improved by 71.21 and 58.47 %, respectively, when 8.0 wt% CSR was dispersed in the epoxy matrix. The fatigue life of the modified CF/EP composites at all of CSR contents dramatically increased 75–100 times longer than that of the unmodified CF/EP composites at high cycle fatigue while tensile strength slightly increased by about 10 %. Field emission scanning electron microcopy (FESEM) observations of the fracture surfaces were conducted to explain failure mechanisms of CSR addition to the CF/EP composites. The evidences of the rubber nanoparticle debonding, plastic void growth, and microshear banding were credited for delaying the onset of matrix crack, and reducing the crack growth rate, as a result, attributed to increase in the mechanical properties of the CF/EP composites.     

Chitosan effects on glass matrices evaluated by biomaterial. MAS-NMR and biological investigations

Bioactive glass 46S6 and biodegradable therapeutic polymer (Chitosan: CH) have been elaborated to form 46S6-CH composite by freeze-drying process. The kinetics of chemical reactivity and bioactivity at the surface were investigated by using physicochemical techniques, particularly solid-state MAS-NMR. Immortalized cell line used to construct multicellular spheroids was employed as three-dimensional (3D) cell cultures for in vitro studies. Obtained results showed a novel structure of the composite; the chemical treatment (ultrasound, magnetic stirring, freeze drying process and lyophilization) led the bioactive glass particles to be loaded in the chitosan-based materials. ²⁹Si and ³¹P MAS-NMR results showed the emergence of two new species, Q _Si ³ (OH) and Q _Si ⁴ , which are characteristic of the vitreous network dissolution in simulated body fluid (SBF). MAS-NMR also confirmed the formation of amorphous calcium phosphate (ACP) at the surface of the initial 46S6-CH. Three-dimensional (3D) cell cultures highlighted the effect of chitosan, where the cell viability reached up to 78% in 46S6-CH composite and up to 67% in 46S6. The association of (CH) and bioactive glass (BG) matrix promotes a highly significant bioactivity, demonstrating surface bone formation and satisfactory behavior in biological environment.     

Efficient duration and hierarchical modeling for human activity recognition

A challenge in building pervasive and smart spaces is to learn and recognize human activities of daily living (ADLs). In this paper, we address this problem and argue that in dealing with ADLs, it is beneficial to exploit both their typical duration patterns and inherent hierarchical structures. We exploit efficient duration modeling using the novel Coxian distribution to form the Coxian hidden semi-Markov model (CxHSMM) and apply it to the problem of learning and recognizing ADLs with complex temporal dependencies. The Coxian duration model has several advantages over existing duration parameterization using multinomial or exponential family distributions, including its denseness in the space of nonnegative distributions, low number of parameters, computational efficiency and the existence of closed-form estimation solutions. Further we combine both hierarchical and duration extensions of the hidden Markov model (HMM) to form the novel switching hidden semi-Markov model (SHSMM), and empirically compare its performance with existing models. The model can learn what an occupant normally does during the day from unsegmented training data and then perform online activity classification, segmentation and abnormality detection. Experimental results show that Coxian modeling outperforms a range of baseline models for the task of activity segmentation. We also achieve a recognition accuracy competitive to the current state-of-the-art multinomial duration model, while gaining a significant reduction in computation. Furthermore, cross-validation model selection on the number of phases K in the Coxian indicates that only a small K is required to achieve the optimal performance. Finally, our models are further tested in a more challenging setting in which the tracking is often lost and the activities considerably overlap. With a small amount of labels supplied during training in a partially supervised learning mode, our models are again able to deliver reliable performance, again with a small number of phases, making our proposed framework an attractive choice for activity modeling.