Studies on chemical resistance of polyesters

Chlorendic anhydride based polyester ( I ,) tetrachlorophthalic anhydride based polyester ( II ), dibromoneopentyl glycol based polyester ( III ,) general purpose polyester ( IV ,) blend of dibromoneopentyl glycol based polyester with general purpose polyester ( V ,) chlorendic anhydride and dibromoneopentyl glycol based polyester ( VI ), and a blend of chlorendic anhydride based polyester and dibromoneopentyl glycol based polyester ( VII ) were prepared and their chemical resistance and moisture absorption studied in various reagents, acid, alkali, and water, at 25 and 65°C. It is found that the polyester ( III ) is the least affected in the presence of the acids. In 20% NaOH, there was a decrease in weight for all polyesters at both the temperatures compared to the control except the polyester ( VII ). Increase in weight of all the polyesters was observed during the absorption of moisture both at 25 and 65°C. The increase was higher at higher temperature. Polyester ( III ) thus shows the least absorption of moisture.     

Effect of AlN addition on the electrical resistivity of pressureless sintered SiC ceramics with B4C and C

The effect of 0–12 wt% AlN addition on the electrical resistivity of SiC ceramics pressureless sintered with 0.7 wt% B₄C and 2.5 wt% C additives was investigated. The elemental analysis of SiC grains revealed a codoping of Al and N in the SiC lattice with a higher N concentration with 1 wt% AlN addition and a higher Al concentration with 12 wt% AlN addition. The electrical resistivity decreased by four orders of magnitude (1.7 × 10⁵ → 8.3 × 10¹ Ω cm) with 1 wt% AlN addition due to the increased carrier density (1.7 × 10¹⁰ → 2.3 × 10¹⁵ cm⁻³) caused by excess N-derived donors. However, subsequent AlN addition (4 → 12 wt%) led to an increase (2.9 × 10³ → 1.2 × 10⁴ Ω‧cm) in electrical resistivity due to (1) increased Al dopants which act as deep acceptors for trapping N-derived carriers causing a decrease in carrier density (2.3 × 10¹⁵ → 5.9 × 10¹³ cm⁻³), (2) the formation of electrically insulating SiC-AlN solid solution, and (3) the presence of electrically insulating AlN grains at the grain boundaries.     

Oxidation and sulfidation behavior of Fe-20Cr-16Ni-4Al-1Y2O3 oxide-dispersion-strengthened alloy

High-temperature oxidation and sulfidation studies were conducted on an oxide-dispersion-strengthened alloy of composition Fe-20Cr-16Ni-4Al-1Y₂O₃. The oxidation studies were conducted in air and low-PO₂ environments over a temperature range of 650–1200°C. Results are also reported on the sulfidation resistance of preformed oxide scales and the influence of reoxidation of preformed sulfide scales. Detailed microstructural results and x-ray diffraction analysis data are presented to substantiate the corrosion behavior of the alloy over the wide range of conditions anticipated in fossil-energy systems. Data are also presented on the corrosion behavior of the alloy in oxygen/sulfur mixed gas atmospheres, and the results are used to compare the corrosion behavior of the present alloy with other chromia- and alumina-forming alloys.     

Adaptive image denoising using cuckoo algorithm

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.     

Learning to Locate Informative Features for Visual Identification

Object identification is a specialized type of recognition in which the category (e.g. cars) is known and the goal is to recognize an object’s exact identity (e.g. Bob’s BMW). Two special challenges characterize object identification. First, inter-object variation is often small (many cars look alike) and may be dwarfed by illumination or pose changes. Second, there may be many different instances of the category but few or just one positive “training” examples per object instance. Because variation among object instances may be small, a solution must locate possibly subtle object-specific salient features, like a door handle, while avoiding distracting ones such as specular highlights. With just one training example per object instance, however, standard modeling and feature selection techniques cannot be used. We describe an on-line algorithm that takes one image from a known category and builds an efficient “same” versus “different” classification cascade by predicting the most discriminative features for that object instance. Our method not only estimates the saliency and scoring function for each candidate feature, but also models the dependency between features, building an ordered sequence of discriminative features specific to the given image. Learned stopping thresholds make the identifier very efficient. To make this possible, category-specific characteristics are learned automatically in an off-line training procedure from labeled image pairs of the category. Our method, using the same algorithm for both cars and faces, outperforms a wide variety of other methods.     

Developmental stages in experimental liver metastases: relation to invasiveness

We have previously reported that an invasive morphotype can be evoked in a rat colon carcinoma by transplanting it into pre-induced subcutaneous granulation tissue. We have now studied the interaction of the same tumor with liver tissue, which is extremely poor in connective tissue in comparison with the subcutaneous site. Tumor cells were injected into the portal system and the resulting experimental liver metastases were examined by electron microscopy and immunohistochemistry. Early metastases consisted of well-differentiated acini, fully surrounded by connective tissue that was derived from the periportal stroma. In a later stage, this connective tissue was overgrown by tumor cells and, almost immediately, acinar differentiation was lost. Most metastases eventually reached the liver capsule, which reacted by forming a layer of granulation tissue. Only in this layer, we observed invasion by thin tumor cell strands, which were often intimately associated with fibroblasts or with blood capillaries. The tumor cells remained smooth and rounded during this process. After fully penetrating the granulation tissue, the tumor cell strands reached the liver surface, where they formed poorly structured papillary masses that were nearly devoid of stroma. Our observations indicate that, even in a relatively homogeneous organ like the liver, the tumor-host interaction is highly complex and dynamic. They also confirm the notion that granulation tissue stimulates tumor invasiveness. Finally, they show that tumor cells can actively invade host tissues without exhibiting a "fibroblastic" morphology.     

A new method of reinforcing graphene nanoplatelets in glass/epoxy composites

This research aims to develop a method for the amalgamation of graphene nanoplatelets in glass/epoxy composites. The poor interface bonding between the fiber and matrix is critical and hinders the full performance of the composites. Glass fabric and epoxy were used as reinforcement and matrix in the composite, respectively. Graphene nanoplatelets were utilized as an additional nano-materials filler for the composites. Glass/graphene/epoxy and glass/epoxy composites were fabricated via vacuum infusion molding. The new method of applying graphene nanoplatelets as secondary reinforcement in the composite was developed based on proper functionalization in the sonication process. The physical, tensile, flexural, and short beam interlaminar properties of fabricated composites were examined to analyze the method's effectiveness. The results showed that density decreased by around 5 %; however, thickness increased by around 34 % after introducing graphene nanoplatelets into the composites. The tensile strength and modulus of the composites declined by approximately 19 %, on the other hand, flexural strength and modulus increased by around 63.3 % and 8.3 %, respectively, after the addition of graphene nanoplatelets into the composites. Moreover, interlaminar shear strength of the composite was enhanced by approximately 50 %.     

Primary structure of gene H of cattle plague virus strain K]

The paper analyzes the standard legal and methodological assurance of the quality and safety of animal food raw materials and foodstuffs (meat, meat products, fish, shellfish, crayfish and their processing products) by the parasitic purity rates according the requirements under the Russian Federation's laws "On Sanitary and Epidemiological Well-Being of the Population", "On Protection of Consumer's Rights", "On Certification of Products and Services", those of SanPiN, such as 2.3.2.560-96 "Sanitary Requirements for the Quality and Safety of Food Raw Materials and Foodstuffs" and 3.2.569-96 "Prevention of Parasitic Diseases in the Russian Federation".     

Ultra‐fast‐switching flexoelectric liquid‐crystal display with high contrast

Abstract— The flexoelectro‐optic effect provides a fast‐switching mechanism (0.01–0.1 msec), suitable for use in field‐sequential‐color full‐motion‐video displays. An in‐plane electric field is applied to a short‐pitch chiral nematic liquid crystal aligned in the uniform standing helix (or Grandjean) texture. The switching mechanism is experimentally demonstrated in a single‐pixel test cell, and the display performance is investigated as a function of device parameters. A contrast ratio of 2000:1 is predicted.     

Hardware/software co-design of a real-time kernel based tracking system

The probabilistic visual tracking methods using color histograms have been proven to be robust to target model variations and background illumination changes as shown by the recent research. However, the required computational cost is high due to intensive image data processing. The embedded solution of such algorithms become challenging due to high computational power demand and algorithm complexity. This paper presents a hardware/software co-design architecture for implementation of the well-known kernel based mean shift tracking algorithm. The design uses color histogram of the target as tracking feature. The target is searched in the consecutive images by maximizing the statistical match of the color distributions. The target localization is based on gradient based iterative search instead of exhaustive search which makes the system capable of achieving frame rate up to hundreds of frames per second while tracking multiple targets. The design, which is fully standalone, is implemented on a low-cost medium-size field programmable gate array (FPGA) device. The hardware cost of the design is compared with some other tracking systems. The performance of the system in terms of speed is evaluated and compared with the software based implementation. It is expected that the proposed solution will find its utility in applications like embedded automatic video surveillance systems.