Chemical heat treatment of powder materials based on iron

Diffusion chromizing and boriding of iron-base powder materials SP30, SP90, and SP90D3 are studied. The growth kinetics for diffusion layers are determined depending on diffusion impregnation conditions, and material composition and porosity. Comparative bending and tensile strength tests as well as wear- and heat-resistance tests for materials after sintering by standard conditions or boriding and chromizing are performed. It is shown that the mechanical properties of materials after different types of processing are approximately the same whereas the wear and heat resistance after diffusion impregnation increase markedly. This makes it possible to conclude that a combination of sintering and boriding (or chromizing) is possible under the following conditions: boriding at 1000°C for 2–3 h; chromizing at 1100°C for 3–4 h.Kiev Polytechnic Institute. Translated from Poroshkovaya Metallurgiya, No. 8(368), pp. 37–43, August, 1993.     

Preparation of fibres based on copolymers of acrylonitrile,methyl acrylate,and acrylic or methacrylic acid

Conclusions -- The preparation of fibres from copolymers of acrylonitrile with methyl acrylate and acrylic or methacrylic acid by spinning using the thiocyanate method has been examined.-- The possibility has been demonstrated of preparing fibres from these copolymers which have high physico-mechanical properties and the expensive, relatively scarce itaconic acid has been replaced by the cheaper and more available acrylic or methacrylic acid.Translated from Khimicheskie Volokna, No. 4, pp. 22–23, July–August, 1990.     

Boosting MUC extraction in unsatisfiable constraint networks

One very fertile domain of applied Artificial Intelligence is constraint solving technologies. Especially, constraint networks that concern problems that can be represented using discrete variables, together with constraints on allowed instantiation values for these variables. Every solution to a constraint network must satisfy every constraint. When no solution exists, the user might want to know the actual reasons leading to the absence of global solution. In this respect, extracting mucs (Minimal Unsatisfiable Cores) from an unsatisfiable constraint network is a useful process when causes of unsatisfiability must be understood so that the network can be re-engineered and relaxed to become satisfiable. Despite bad worst-case computational complexity results, various muc-finding approaches that appear tractable for many real-life instances have been proposed. Many of them are based on the successive identification of so-called transition constraints. In this respect, we show how local search can be used to possibly extract additional transition constraints at each main iteration step. In the general constraint networks setting, the approach is shown to outperform a technique based on a form of model rotation imported from the sat-related technology and that also exhibits additional transition constraints. Our extensive computational experimentations show that this enhancement also boosts the performance of state-of-the-art DC(WCORE)-like MUC extractors.     

New refractory materials for the aluminum industry

A technology for production of andalusite-based refractory components for the lining of anode firing kilns is described. The formulation for a low-cement castable resistant to attack by molten aluminum is proposed. __________ Translated from Novye Ogneupory, No. 4, pp. 109–111, April, 2006. Based on materials reported to the conference “Aluminum of Siberia-2005.”     

Sex Pheromone of the Alfalfa Plant Bug,Adelphocoris lineolatus: Pheromone Composition and Antagonistic Effect of 1-Hexanol (Hemiptera: Miridae)

Journal of Chemical Ecology - The sex pheromone composition of alfalfa plant bugs, Adelphocoris lineolatus (Goeze), from Central Europe was investigated to test the hypothesis that insect species...     

Binary-image comparison with local-dissimilarity quantification

In this paper, we present a method for binary image comparison. For binary images, intensity information is poor and shape extraction is often difficult. Therefore binary images have to be compared without using feature extraction. Due to the fact that different scene patterns can be present in the images, we propose a modified Hausdorff distance (HD) locally measured in an adaptive way. The resulting set of measures is richer than a single global measure. The local HD measures result in a local-dissimilarity map (LDMap) including the dissimilarity spatial layout. A classification of the images in function of their similarity is carried out on the LDMaps using a support vector machine. The proposed method is tested on a medieval illustration database and compared with other methods to show its efficiency.