Recombinant soluble murine IL-4 receptor can inhibit or enhance IgE responses in vivo

This study examines the effects of soluble IL-4R (sIL-4R) administration on IgE production in vivo by using an anti-IgD injection model. Anti-IgD-treated mice were given various doses of sIL-4R or anti-IL-4 mAb over a 3-day period and serum IgE levels were determined by ELISA on day 9. The sIL-4R inhibited IgE production by up to 85%. Anti-IL-4 mAb administration resulted in comparable levels of inhibition at considerably lower doses. The disparity in efficacy between sIL-4R and anti-IL-4 mAb was likely the result of differences in the biodistribution and in vivo half-life of the two IL-4-binding proteins. The specificity of the sIL-4R inhibitory effect was assessed by mixing sIL-4R with various concentrations of IL-4 before injection. Exogenous IL-4 partially overcame the inhibitory effect of high-dose sIL-4R or anti-IL-4 mAb. Unexpectedly, coadministration of suboptimal concentrations of anti-IL-4 mAb or sIL-4R with IL-4 resulted in superinduction of the IgE response. This stimulatory effect was dose dependent for both IL-4 and the IL-4 cognates and was not seen in the absence of exogenous IL-4 over the entire concentration range tested for either sIL-4R or anti-IL mAb. The results indicate that sIL-4R can block IgE secretion by neutralizing endogenous IL-4. Furthermore, sIL-4R can enhance, in a dose-dependent manner, the biologic effects of exogenously administered IL-4, presumably by altering the biodistribution of the cytokine. These findings suggest two alternative applications for cytokine-binding proteins, i.e., 1) as antagonists of biologic activities of endogenously produced cytokines and, 2) as vehicles for cytokine delivery.     

Image Processing Using RBF like Neural Networks: A ZISC-036 Based Fully Parallel Implementation Solving Real World and Real Complexity Industrial Problems

The present article concerns neural based image processing and solutions developed for industrial problems using the ZISC-036 neuro-processor, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm (RCE) and the K-Nearest Neighbor algorithm (KNN). The developed neural based techniques have been applied for image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). We also have developed and implemented on ZISC-036 neuro-processor, a neural network based solution for visual probe mark inspection in VLSI production for the IBM Essonnes plant. The main characteristics of such systems are real-time control and high reliability in detection and classification tasks. Experimental results, validating presented concepts, have been reported showing quantitative and qualitative improvement as well as the efficiency our solutions.     

On using nearly-independent feature families for high precision and confidence

Consider learning tasks where the precision requirement is very high, for example a 99 % precision requirement for a video classification application. We report that when very different sources of evidence such as text, audio, and video features are available, combining the outputs of base classifiers trained on each feature type separately, aka late fusion, can substantially increase the recall of the combination at high precisions, compared to the performance of a single classifier trained on all the feature types, i.e., early fusion, or compared to the individual base classifiers. We show how the probability of a joint false-positive mistake can be less—in some cases significantly less—than the product of individual probabilities of conditional false-positive mistakes (a NoisyOR combination). Our analysis highlights a simple key criterion for this boosted precision phenomenon and justifies referring to such feature families as (nearly) independent. We assess the relevant factors for achieving high precision empirically, and explore combination techniques informed by the analysis.     

Multitier heterogeneous network using stochastic geometry and factorial moment approaches

The rapid growth of small cells is driving cellular network toward randomness and heterogeneity. Usually, cellular networks are modeled by placing each tier (eg, macro, pico, and relay nodes) deterministically on a grid. In such a heterogeneous cellular network, the rational approach to characterize the base stations (BSs), user, and relay locations is by using random spatial models. When calculating the metric performances such as coverage probability, these networks are idealized without consideration of interference. Therefore, interference modeling remains the key issue for the deployment of small cells. This paper developed a single and multitier cellular network model that captures the downlink heterogeneous cellular network with variable parameters such as the target signal‐to‐interference ratio (SIR), transmitted power, and deployment density. In particular, we model ‐tier transmission and compare it with a single‐tier and traditional grid model to obtain tractable coverage probability using stochastic geometry and factorial moment. The obtained results demonstrate the effectiveness and analytical tractability to study the heterogeneous performance.     

Stress distribution in a 2024-T3 aluminum plate with a circular notch,repaired by a graphite/epoxy composite patch

The aim of this study is to analyze by finite element method the single- and double-sided composite patch repairs designed to reduce the concentration of the stresses at circular notches and cracks. The results show that there is a considerable reduction in the asymptotic value of the stress-intensity factors and the normal stresses at the crack tip. The use of a double-sided patch suppresses the bending effect due to the eccentricity of the patch on one side only and reduces the shear stresses in adhesive.     

Monitoring of the physical aging of radiation cross-linked conductive rubber blends containing clay nanofiller

Polymeric materials are widely used as insulation and jacketing materials in wire and cable. When such materials are used for long-term applications, they undergo thermal oxidation aging in the environment. It is necessary to develop an in situ and non-destructive condition monitoring (CM) method to follow the aging of cable materials. The main objective of this work was to investigate polymer composites as potential sensor materials for this purpose. Rubber/carbon black composites with a carbon black loading below the percolation threshold underwent accelerated thermal oxidation aging experiments. The results indicated that the substantial resistivity decreases of the composites could be directly related to the increases in volume fraction of the conductive carbon black, which was mainly caused by the mass loss of polymer matrix and sample shrinkage during the thermal oxidation aging process. Compared to existing CM method based on density change, the electrical resistivity is more explicit regarding its absolute changes throughout the thermal oxidation aging. The change in resistivity spanned over two orders of magnitude, whereas the composite density only increased 5%. The results offer strong evidence that resistivity measurements, which reflect property changes under thermal aging conditions, could represent a very useful and non-destructive CM approach as well as a more sensitive method than density CM approach.     

Synthesis and spectroscopic investigations of Mn3O4 nanoparticles

Trimanganese tetraoxide (Mn₃O₄) nanoparticles have been synthesized via hydrothermal process. Nevertheless, homogeneous nanoparticles of Mn₃O₄ with platelet lozange shape were obtained. The crystallite size ranged from 40 to 70 nm. The Mn₃O₄ product was investigated by X-ray diffraction, transmission electron microscopy (MET), and impedance spectroscopy. Electrical conductivity measurements showed that the as-synthesized Mn₃O₄ nanomaterial has a conductivity value which goes from 1.8 10⁻⁷ Ω⁻¹ cm⁻¹ at 298 K, to 23 10⁻⁵ Ω⁻¹ cm⁻¹ at 493 K. The temperature dependence of the conductivity between 298 and 493 K obeys to Arrhenius law with an activation energy of 0.48 eV.     

The effect of calcination on the corrosion performance of TiO2 sol–gel coatings doped with benzotriazole on steel CK45

Sol–gel method under dip coating process and tetra‐n‐butyle orthotitanate as precursor were used to produce titanium oxide coating on steel CK45. The effect of calcination at 400 °C, after drying at 120 °C, on the morphology and corrosion performance of the coatings was investigated. Benzotriazole (BTA) as an inhibitor was doped on titanium oxide coatings to improve corrosion performance of the coatings as well as its self‐healing properties. The morphology and structure of the coatings were studied by X‐ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive X‐ray spectroscopy (EDS) techniques. Potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques were used to study the corrosion behavior of the coatings. The results revealed that after calcination the dominant crystalline phase was anatase. The results obtained from potentiodynamic polarization curves and electrochemical impedance spectra showed that the calcinated and doped with BTA coatings possessed higher corrosion resistance than non‐calcinated although doped with BTA coatings.