Effect of the Geometric Parameters of a Layered Powder Composite on Its Magnetic Properties

The effect of thickness of magnetic conductor and number of electrically insulating layers on the magnetic properties in an alternating field of a layered powder-metallurgy soft-magnetic material based on iron was investigated. It was determined that increasing the thickness of the magnetic conductor and frequency of the alternating current deteriorated the magnetic properties of the material. Creation of a layered structure in which ferromagnetic layers alternate with electrically insulating layers decreased specific magnetic losses.     

SOME NEW ASPECT OF LYAPUNOV TYPE THEOREMS FOR STOCHASTIC DIFFERENCE EQUATIONS WITH CONTINUOUS TIME

Some new Lyapunov type theorems for stochastic difference equations with continuous time are proven. It is shown that these theorems simplify an application of Lyapunov functionals construction method.     

IR spectroscopic study of Pt/Kl zeolites using adsorption of CO as a molecular probe

FTIR spectra of CO adsorbed on Pt/KL catalysts show that the relative band intensities and the total dispersion markedly depend on the catalyst preparation method (ion exchange, incipient wetness impregnation or co-impregnation with KCl). The CO stretching frequency of the dominant band for linear CO is shifted to higher wavenumbers, parallel with the proton concentration in the reduced catalyst, which is derived independently from the intensity of the IR bands of the OH groups. The results are in accordance with the model that electron-deficient platinum particles are platinum-proton adducts.On leave from: N.D. Zelinsky Institute of Organic Chemistry, Academy of Sciences, Moscow, USSR.     

On stability of second-order quasi-polynomials with a single delay

In this note the stability of a second-order quasi-polynomial with a single delay is studied. Although there is a vast literature on this problem, most available solutions are limited to some particular cases. Moreover, some published results on this subject appear to contain imprecise, or even wrong, conditions. The purpose of this note is to show that by accurate application of known theories, a complete explicit characterization of stability regions can be derived in a most general case. As a byproduct of the proposed analysis, we show that in the high-order case the quasi-polynomial is delay-independent unstable whenever its delay-free version has an odd number of unstable roots (or, equivalently, a negative static gain).     

Human attributes from 3D pose tracking

It is well known that biological motion conveys a wealth of socially meaningful information. From even a brief exposure, biological motion cues enable the recognition of familiar people, and the inference of attributes such as gender, age, mental state, actions and intentions. In this paper we show that from the output of a video-based 3D human tracking algorithm we can infer physical attributes (e.g., gender and weight) and aspects of mental state (e.g., happiness or sadness). In particular, with 3D articulated tracking we avoid the need for view-based models, specific camera viewpoints, and constrained domains. The task is useful for man–machine communication, and it provides a natural benchmark for evaluating the performance of 3D pose tracking methods (vs. conventional Euclidean joint error metrics). We show results on a large corpus of motion capture data and on the output of a simple 3D pose tracker applied to videos of people walking.     

Cardioinotropic Effects in Subchronic Intoxication of Rats with Lead and/or Cadmium Oxide Nanoparticles

Subchronic intoxication was induced in outbred male rats by repeated intraperitoneal injections with lead oxide (PbO) and/or cadmium oxide (CdO) nanoparticles (NPs) 3 times a week during 6 weeks for the purpose of examining its effects on the contractile characteristics of isolated right ventricle trabeculae and papillary muscles in isometric and afterload contractions. Isolated and combined intoxication with these NPs was observed to reduce the mechanical work produced by both types of myocardial preparation. Using the in vitro motility assay, we showed that the sliding velocity of regulated thin filaments drops under both isolated and combined intoxication with CdO–NP and PbO–NP. These results correlate with a shift in the expression of myosin heavy chain (MHC) isoforms towards slowly cycling β–MHC. The type of CdO–NP + PbO–NP combined cardiotoxicity depends on the effect of the toxic impact, the extent of this effect, the ratio of toxicant doses, and the degree of stretching of cardiomyocytes and muscle type studied. Some indices of combined Pb–NP and CdO–NP cardiotoxicity and general toxicity (genotoxicity included) became fully or partly normalized if intoxication developed against background administration of a bioprotective complex.     

Combinatorial algorithms for distributed graph coloring

Numerous problems in Theoretical Computer Science can be solved very efficiently using powerful algebraic constructions. Computing shortest paths, constructing expanders, and proving the PCP Theorem, are just few examples of this phenomenon. The quest for combinatorial algorithms that do not use heavy algebraic machinery, but are roughly as efficient, has become a central field of study in this area. Combinatorial algorithms are often simpler than their algebraic counterparts. Moreover, in many cases, combinatorial algorithms and proofs provide additional understanding of studied problems. In this paper we initiate the study of combinatorial algorithms for Distributed Graph Coloring problems. In a distributed setting a communication network is modeled by a graph $G=(V,E)$ of maximum degree $\varDelta $ . The vertices of $G$ host the processors, and communication is performed over the edges of $G$ . The goal of distributed vertex coloring is to color $V$ with $(\varDelta + 1)$ colors such that any two neighbors are colored with distinct colors. Currently, efficient algorithms for vertex coloring that require $O(\varDelta + \log ^* n)$ time are based on the algebraic algorithm of Linial (SIAM J Comput 21(1):193–201, 1992) that employs set-systems. The best currently-known combinatorial set-system free algorithm, due to Goldberg et al. (SIAM J Discret Math 1(4):434–446, 1988), requires $O(\varDelta ^2+\log ^*n)$ time. We significantly improve over this by devising a combinatorial $(\varDelta + 1)$ -coloring algorithm that runs in $O(\varDelta + \log ^* n)$ time. This exactly matches the running time of the best-known algebraic algorithm. In addition, we devise a tradeoff for computing $O(\varDelta \cdot t)$ -coloring in $O(\varDelta /t + \log ^* n)$ time, for almost the entire range $1 < t < \varDelta $ . We also compute a Maximal Independent Set in $O(\varDelta + \log ^* n)$ time on general graphs, and in $O(\log n/ \log \log n)$ time on graphs of bounded arboricity. Prior to our work, these results could be only achieved using algebraic techniques. We believe that our algorithms are more suitable for real-life networks with limited resources, such as sensor networks.     

Domain Adaptation for Structured Regression

Discriminative regression models have proved effective for many vision applications (here we focus on 3D full-body and head pose estimation from image and depth data). However, dataset bias is common and is able to significantly degrade the performance of a trained model on target test sets. As we show, covariate shift, a form of unsupervised domain adaptation (USDA), can be used to address certain biases in this setting, but is unable to deal with more severe structural biases in the data. We propose an effective and efficient semi-supervised domain adaptation (SSDA) approach for addressing such more severe biases in the data. Proposed SSDA is a generalization of USDA, that is able to effectively leverage labeled data in the target domain when available. Our method amounts to projecting input features into a higher dimensional space (by construction well suited for domain adaptation) and estimating weights for the training samples based on the ratio of test and train marginals in that space. The resulting augmented weighted samples can then be used to learn a model of choice, alleviating the problems of bias in the data; as an example, we introduce SSDA twin Gaussian process regression (SSDA-TGP) model. With this model we also address the issue of data sharing, where we are able to leverage samples from certain activities (e.g., walking, jogging) to improve predictive performance on very different activities (e.g., boxing). In addition, we analyze the relationship between domain similarity and effectiveness of proposed USDA versus SSDA methods. Moreover, we propose a computationally efficient alternative to TGP (Bo and Sminchisescu 2010), and it’s variants, called the direct TGP. We show that our model outperforms a number of baselines, on two public datasets: HumanEva and ETH Face Pose Range Image Dataset. We can also achieve 8–15 times speedup in computation time, over the traditional formulation of TGP, using the proposed direct formulation, with little to no loss in performance.     

Polymerization characteristics of a dye of anthraquinone

A technical dye of the anthraquinone type was analyzed by GPC, mass spectroscopy, and elemental analysis. Along with the polymerizable component, N-[4-amino-3-methoxyanthraquinonyl-(1)] methacrylamide (I), it contained a saturated admixture, N-[4-amino-3-methoxyanthraquinonyl-(1)]-2-chloro-2-methylpropionamide (II). The homopolymerization of I was carried out, and admixture II was isolated and characterized. The copolymerization of the dye with styrene and methyl methacrylate was verified, and the retardation effect of II on the polymerization of these monomers was evaluated.     

Hydrothermal microwave-assisted synthesis of LaFeO3 catalyst for N2O decomposition

Lanthanum orthoferrite powders were synthesized via one-step hydrothermal reactions under mild conditions using microwave and conventional heating. The use of microwave irradiation during the synthesis allows one to obtain nanocrystalline LaFeO₃ with a higher yield and reduced crystallite and particle size within a 16 times shorter duration (3 hours) at a lower temperature of 220°C as compared to the conventional heating. The catalytic decomposition of nitrous oxide was performed over both samples, it was shown that the sample obtained under microwave conditions demonstrates enhanced activity as a catalyst: N₂O decomposes completely at 700°C over the catalyst formed at microwave conditions, while the comparative catalyst prepared by conventional heating reaches a lower conversion of only 60% at the same temperature and catalytic reaction conditions.