Rheological characterization of hydroxypropylcellulose gels

The present paper describes the rheological properties of hydroxypropylcellulose (HPC) gels formulated in propylene glycol (PG), water, ethanol, and mixtures of these components. The effects of molecular weight, polymer concentration, and solvent composition on the apparent viscosity and flow characteristics have been studied by continuous shear rheometry. The HPC gels are shear thinning and do not exhibit significant yield or hysteresis in their rheograms. The apparent viscosity increases with increasing molecular weight and concentration of the polymer, as expected. Although not so pronounced at lower concentrations (≤ 1.5%), HPC gels tend to become increasingly non-Newtonian with increasing molecular weight at higher polymer concentrations (3%). A mathematical model has been proposed for the prediction of viscosities of HPC gels. There exists a high degree of dependence on molecular interactions between various solvent molecules in the prediction of mixture viscosities in ternary systems. The effects of solvent composition on the viscoelastic behavior of these gels have also been examined by dynamic mechanical analysis. The HPC gels are highly viscoelastic and exhibit greater degrees of elasticity with increased PG content in ternary solvent mixtures with water and ethanol. The study also suggests that dynamic mechanical analysis could prove to be a useful tool in the determination of zero-shear viscosities, viscosities that are representative of most realistic situations.     

A robust feature extraction with optimized DBN-SMO for facial expression recognition

Multimedia Tools and Applications - Facial expression is the most common technique is used to convey the expressions of human beings. Due to different ethnicity and age, faces differ from one...     

A technique for generating natural colour images from false colour composite images

Colour is widely used in remote sensing work. In many instances, the use of colour conveys additional information both visually and scientifically. Remote sensing satellites view the earth in different spectral bands, viz. near infrared (NIR), red, green, and blue bands, in a conventional multispectral imaging system. In the absence of a blue channel, colour images can be generated using near infrared, red, and green bands in what is known as a false colour composite (FCC) and does not look natural, like the image we see with the naked eye. For a trained interpreter, this does not pose any problems. However, when the intended use is a fly‐through of a draped terrain, visual interpretation, or a display, meant for the non‐remote sensing professional, this becomes a handicap. To overcome this, there is a requirement to generate natural colour composites (NCC) from the given false colour composite, which demands the simulation of a blue band to be combined with green and red bands. This paper describes a unique method of generating a blue band to form natural colour images from a given false colour image set. We use a spectral transformation method to establish a relationship between the false colour and true colour image pairs provided by a sensor with all the four bands, which has a broader spectral coverage. A transformation function is fitted by selecting radiometric control points along the line of geometric registration to find a set of coefficients to be used for simulating a blue band. This blue band, along with the green and red bands, provides a near true colour or ‘natural colour’ on the display. In this paper, we present a set of adjustable radiometric transformation coefficients to accommodate variation in spatial and dynamic range offered by sensors to generate natural colour. These coefficients seem to work on a large number of images of different seasons, provided similar spectral bands and terrain are used. The proposed ‘natural colour generator’ can be used in changing false colour images to natural colour images with the aim of ‘what you get is what you would have seen’.     

Structural health monitoring of railway tracks using IoT-based multi-robot system

Neural Computing and Applications - A multi-robot-based fault detection system for railway tracks is proposed to eliminate manual human visual inspection. A hardware prototype is designed to...     

Influence of sea water solution on mortar containing calcium carbonate

Normal Portland cement mortar discs containing precipitated or ground limestone at dosages of 0, 2.5, 5 and 15% were made at water/cement ratios of 0.42 or 0.60. They were hydrated in lime water or sea water solution for periods up to 1 year. The length and modulus of elasticity changes were monitored periodically. Some mortars containing CaCO₃ exhibited more than three times the expansion of the reference in sea water. The expansions were greater in samples containing fine CaCO₃. The modulus of elasticity was especially low for samples containing precipitated CaCO₃ and exposed to sea water.     

Influence of crack closure on the stress intensity factor for plates subjected to bending—A 3-D finite element analysis

Plates with central through cracks subjected to bending is analysed taking into account the closure of the crack faces on the compression side. A three-dimensional finite element method employing three-dimensional degenerate solid element is used for the analysis. The crack faces have been modelled such that they come in contact over an area on the compression side and interfere with each other. The influence of the crack closure on the variation of the stress intensity factor across the plate thickness is obtained for finite and infinite plate geometries.     

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing

Microtubules are involved in numerous cellular processes including chromosome segregation during mitosis and, as a result, their constituent protein, tubulin, has become a successful target of several chemotherapeutic drugs. In general, these drugs bind indiscriminately to tubulin within both cancerous and healthy cells, resulting in unwanted side effects. However, differences between beta-tubulin isotypes expressed in a wide range of cell types may aid in the development of anti-tubulin drugs having increased specificity for only certain types of cells. Here, we describe a digital signal processing (DSP) method that is capable of predicting hot spots for the tubulin family of proteins as well as determining relative differences in binding affinities to these hot spots based only on the primary sequence of 10 human tubulin isotypes. Due to the fact that several drug binding sites have already been characterized within beta-tubulin, we are able to correlate hot spots with the binding sites for known chemotherapy drugs. We have also verified the accuracy of this method using the correlation between the binding affinities of characterized drugs and the tubulin isotypes. Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined.     

A Randomized Linear-Work EREW PRAM Algorithm to Find a Minimum Spanning Forest

We present a randomized EREW PRAM algorithm to find a minimum spanning forest in a weighted undirected graph. On an n -vertex graph the algorithm runs in o(( log n) ^{1+ ɛ} ) expected time for any ɛ >0 and performs linear expected work. This is the first linear-work, polylog-time algorithm on the EREW PRAM for this problem. This also gives parallel algorithms that perform expected linear work on two general-purpose models of parallel computation—the QSM and the BSP.