Simulation of the percolation of water into rigid polyurethane foams at applied hydraulic pressures

The hydraulic resistance of polyurethane foams is studied by means of simulations of water penetration into model foams. The model foams of cubical shape are constructed by generating the centers of the cells randomly. The strength of the window separating two cells is assumed to be a function of the distance between the centers of the cells in one set of computations. In another set of computations the strengths of the windows are assigned randomly from a specified distribution. The foam is exposed to an elevated pressure at its boundaries and water penetrates into the foam by rupturing the windows with strengths lesser than the applied pressure. The variation of equilibrium volume fraction of the foam filled with water for increasing hydraulic pressures shows typical percolation behavior: there is a sharp increase in the volume filled beyond a threshold pressure. Simulations show that beyond a certain sample size there is no change in the percolation curve with sample size, and indicate that it is mainly the weaker windows that control the hydraulic resistance of the foam. The simulation results are compared with experimental data. POLYM. ENG. SCI. 46:970–983, 2006. © 2006 Society of Plastics Engineers     

Some aspects of deformation behavior

The deformation behavior of several single- and two-phase coarse microstructures has been examined using microhardness measurements. It has been found that the strength response of a coarse phase in isolation is distinctly different from its response when it exists in a two-phase system. The second phase alters the mechanical state of the first one andvice versa even in the plastically undeformed condition. This phenomenon is explained in terms of the existence of an appreciable amount of residual stresses in two-phase coarse microstructures. These stresses primarily arise due to the difference in thermal expansion coefficients of the phases. The in- fluence of elastic stress field on microhardness response is shown with a new type of experiment to support the proposed explanation. The present results question the existing expressions for deformation modeling of multiphase materials because of the uncertainties in the estimation of the average strength of the phases in a two-phase system.     

ANDES: efficient evaluation of NOT-twig queries in relational databases

Despite a large body of work on XPath query processing in relational environment, systematic study of queries containing not-predicates have received little attention in the literature. Particularly, several xml supports of industrial-strength commercial rdbms fail to efficiently evaluate such queries. In this paper, we present an efficient and novel strategy to evaluate not -twig queries in a tree-unaware relational environment. not -twig queries are XPath queries with ancestor–descendant and parent–child axis and contain one or more not-predicates. We propose a novel Dewey-based encoding scheme called Andes (ANcestor Dewey-based Encoding Scheme), which enables us to efficiently filter out elements satisfying a not-predicate by comparing their ancestor group identifiers. In this approach, a set of elements under the same common ancestor at a specific level in the xml tree is assigned same ancestor group identifier. Based on this scheme, we propose a novel sql translation algorithm for not-twig query evaluation. Experiments carried out confirm that our proposed approach built on top of an off-the-shelf commercial rdbms significantly outperforms state-of-the-art relational and native approaches. We also explore the query plans selected by a commercial relational optimizer to evaluate our translated queries in different input cardinality. Such exploration further validates the performance benefits of Andes.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

Developing a Dynamic Cluster Quantization based Lossless Audio Compression (DCQLAC)

In this paper, an approach has been made to produce a compressed audio without losing any information. The proposed scheme is fabricated with the help of dynamic cluster quantization followed by Burrows Wheeler Transform (BWT) and Huffman coding. The encoding algorithm has been designed in two phases, i.e., dynamic cluster selection (of sampled audio) followed by dynamic bit selection for determining quantization level of individual cluster. Quantization level of each cluster is selected dynamically based on mean square quantization error (MSQE). Bit stream is further compressed by applying Burrows Wheeler Transform (BWT) and Huffman code respectively. Experimental results are supported with current state-of-the-art in audio quality analysis (like statistical parameters (compression ratio, space savings, SNR, PSNR) along with other parameters (encoding time, decoding time, Mean Opinion Score (MOS) and entropy) and compared with other existing techniques.

     

Distributed probabilistic inferencing in sensor networks using variational approximation

This paper considers the problem of distributed inferencing in a sensor network. It particularly explores the probabilistic inferencing problem in the context of a distributed Boltzmann machine-based framework for monitoring the network. The paper offers a variational mean-field approach to develop communication-efficient local algorithm for variational inferencing in distributed environments (VIDE). It compares the performance of the proposed approximate variational technique with respect to the exact and centralized techniques. It shows that the VIDE offers a much more communication-efficient solution at very little cost in terms of the accuracy. It also offers experimental results in order to substantiate the scalability of the proposed algorithm.     

Biosynthesis of AgNPs using aqueous leaf extract of Ipomoea eriocarpa and their anti‐inflammatory effect on carrageenan‐induced paw edema in male Wistar rats

Silver nanoparticles (AgNPs) were synthesised from aqueous Ag nitrate through a simple, competent and eco‐friendly method using the leaf extract of Ipomoea eriocarpa as reducing as well as capping agent. Ultraviolet–visible absorption spectroscopy was used to confirm the formation of AgNPs which displayed the substantiation of surface plasmon bands at 425 nm. The NPs were also characterised using Fourier transformer infrared spectroscopy, X‐ray diffraction method, transmission electron microscope and zeta potential. The characterisation study confirmed the formation of AgNPs, their spherical shape and average diameter of 12.85 ± 8.65 nm. Zeta potential value of −20.5 mV suggested that the AgNPs are stable in the suspension. The aqueous extract and the AgNPs were further screened for in vivo anti‐inflammatory activity using carrageenan‐induced paw edema in male Wistar rats. The study demonstrated that the AgNPs (1 ml kg⁻¹) had a significant (p  < 0.05) anti‐edemic effect and inhibition was observed from the first hour (21.31 ± 1.34) until the sixth hour (52.67 ± 1.41), when the inhibitory effect was greatest and superior to the aqueous extract and the standard, diclofenac.Inspec keywords: silver, nanoparticles, nanofabrication, ultraviolet spectra, visible spectra, absorption coefficients, surface plasmons, Fourier transform infrared spectra, X‐ray diffraction, transmission electron microscopy, suspensions, drugs, nanomedicineOther keywords: biosynthesis, aqueous leaf extract, ipomoea eriocarpa, antiinflammatory effect, carrageenan‐induced paw edema, male Wistar rats, silver nanoparticles, aqueous nitrate, capping agent, ultraviolet‐visible absorption spectroscopy, surface plasmon band, Fourier transformer infrared spectroscopy, X‐ray diffraction, transmission electron microscopy, zeta potential, spherical shape, suspension, aqueous extract, in vivo antiinflammatory activity, antiedemic effect, inhibitory effect, diclofenac, wavelength 425 nm, size 12.85 nm to 8.65 nm, Ag     

33.7 MHz heavy-ion radio frequency quadrupole linac at VECC Kolkata

A 33.7 MHz heavy-ion radio frequency quadrupole (RFQ) linear accelerator has been designed, built, and tested. It is a four-rod-type RFQ designed for acceleration of 1.38 keVu, qA> or =116 ions to about 29 keVu. Transmission efficiencies of about 85% and 80% have been measured for the unanalyzed and analyzed beams, respectively, of oxygen ((16)O(2+), (16)O(3+), (16)O(4+)), nitrogen ((14)N(3+), (14)N(4+)), and argon ((40)Ar(4+)). The system design and measurements along with results of beam acceleration test will be presented.