Application of polymeric flocculant for enhancing settling of the pond ash particles and water drainage from hydraulically stowed pond ash

Delayed settling of the ash particles and poor drainage of water from the pond ash are the major problems faced during the hydraulic stowing of pond ash. In this study the effect of polymeric flocculant on settling of the ash particles and drainage of water during pond ash stowing are investigated. In addition, the parameters, viz. drainage and absorption of water during pond ash stowing are quantified by stowing a mine goaf model with pond ash slurries of five different concentrations added with and without flocculant. The study revealed that addition of only 5 × 10^?6 of Sodium Carboxymethyl Cellulose (Na-CMC) flocculant with the pond ash slurries during stowing offers best result in terms of quicker settling of the ash particles and enhanced water drainage from the hydraulically stowed pond ash. Besides, it resulted in drainage of more than 85% of the total water used in the initial 45 min of stowing. The improvement in drainage is caused due to coagulation and flocculation of the pond ash particles because of charge neutralization and particle–particle bridging. This study may provide a basis for estimating the drainage and absorption of water during the real pond ash stowing operation in underground mines.     

The complexity of approximately counting stable roommate assignments

We investigate the complexity of approximately counting stable roommate assignments in two models: (i) the k-attribute model, in which the preference lists are determined by dot products of “preference vectors” with “attribute vectors” and (ii) the k-Euclidean model, in which the preference lists are determined by the closeness of the “positions” of the people to their “preferred positions”. Exactly counting the number of assignments is #P-complete, since Irving and Leather demonstrated #P-completeness for the special case of the stable marriage problem (Irving and Leather, 1986 [11]). We show that counting the number of stable roommate assignments in the k-attribute model (#k-attribute SR, $k?4$) and the 3-Euclidean model (#k-Euclidean SR, $k?3$) is interreducible, in an approximation-preserving sense, with counting independent sets (of all sizes) ($\mathrm{\#}\mathit{IS}$) in a graph, or counting the number of satisfying assignments of a Boolean formula ($\mathrm{\#}\mathit{SAT}$). This means that there can be no FPRAS for any of these problems unless NP = RP. As a consequence, we infer that there is no FPRAS for counting stable roommate assignments ($\mathrm{\#}\mathit{SR}$) unless NP = RP. Utilizing previous results by Chebolu, Goldberg and Martin (2010) [3], we give an approximation-preserving reduction from counting the number of independent sets in a bipartite graph ($\mathrm{\#}\mathit{BIS}$) to counting the number of stable roommate assignments both in the 3-attribute model and in the 2-Euclidean model. $\mathrm{\#}\mathit{BIS}$ is complete with respect to approximation-preserving reductions in the logically-defined complexity class $\mathrm{\#}\mathrm{RH}{\mathrm{\Pi }}_1$. Hence, our result shows that an FPRAS for counting stable roommate assignments in the 3-attribute model would give an FPRAS for all $\mathrm{\#}\mathrm{RH}{\mathrm{\Pi }}_1$. We also show that the 1-attribute stable roommate problem always has either one or two stable roommate assignments, so the number of assignments can be determined exactly in polynomial time.     

Applications of 'TissueQuant'- a color intensity quantification tool for medical research

This paper demonstrates the use of TissueQuant - an image analysis tool for quantification of color intensities which was developed for use in medical research where the stained biological specimen such as tissue or antigen needs to be quantified. TissueQuant provides facilities for user interaction to choose and quantify the color of interest and its shades. Gaussian weighting functions are used to provide a color score which quantifies how close the shade is to the user specified reference color. We describe two studies in medical research which use TissueQuant for quantification. The first study evaluated the effect of petroleum-ether extract of Cissus quadrangularis (CQ) on osteoporotic rats. It was found that the analysis results correlated well with the manual evaluation, p < 0.001. The second study evaluated the nerve morphometry and it was found that the adipose and non adipose tissue content was maximum in radial nerve among the five nerves studied.     

Modeling of ammonothermal growth of gallium nitride single crystals

Ammonothermal growth of GaN crystals with a retrograde solubility has been modeled and simulated here using fluid dynamics, thermodynamics and heat transfer models. The nutrient is considered as a porous media bed and the flow in the porous charge is simulated using the Darcy-Brinkman-Forchheimer model. The resulting governing equations are solved using the finite volume method. For the case of retrograde solubility, the charge is put above the baffle. The temperature difference between the dissolving zone and growth zone is found smaller than that applied on the sidewall of autoclave. The baffle opening has a strong effect on the nutrient transport and supersaturation of GaN species in the growth zone.     

Artificial Neural Network Model for Predicting Stable and Unstable Regions in Cu-Zn Alloys

Processing maps are developed using the Dynamic Materials Model (DMM) and instability criterion, which help in choosing optimum process parameters for hot-working of materials. Certain high-level expertise is required to interpret and extract the information on instability regimes to be avoided during processing. In recent years, Artificial Neural Network (ANN) models have been developed to predict flow stress by using the input vector; namely, temperature, strain rate and strain. In this study, using the available Cu-Zn alloy data, ANN model has been developed to classify the hot-working process parameters, such as temperature, strain rate and flow stress for instability regime, directly from the corrected flow stress data without applying the DMM. This model uses 10 compositions of Cu-Zn system, ranging from 3% Zn to 51% Zn. The developed ANN model has been able to learn the nonlinear classifier, which separates unstable region from the stable region in the Cu-Zn alloy system with zinc content less than 40%.     

Dry sliding wear response of zinc-based alloy over a range of test speeds and loads: a comparative study with cast iron

This study pertains to the observations made during the sliding wear response of a zinc-based alloy in different test conditions. The effects of sliding speed and load on the wear behaviour of the alloy have been studied. The properties evaluated were wear rate, frictional heating and coefficient of friction. The wear performance of the zinc-based alloy has been compared with that of a conventional cast iron in identical test conditions. The wear rate of the samples increased with applied load and sliding speed while the seizure resistance (load) deteriorated with speed. The zinc-based alloy exhibited less wear rate and reduced frictional heating than that of the cast iron while friction coefficient followed a reverse trend. Observed wear response of the samples has been discussed in terms of specific features like lubricating, load carrying, microcracking and thermal stability of various microconstituents of the samples, and substantiated further through the features of wear surfaces, subsurface regions and debris.     

Growth and consumption rates of the phase layers during interdiffusion in a diffusion couple with finite end member

The relations for the growth and consumption rates of a layer with finite thickness as an end member and the product phases in the interdiffusion zone are developed. We have used two different methodologies, the diffusion based and the physico-chemical approach to develop the same relations. We have shown that the diffusion based approach is rather straightforward; however, the physico-chemical approach is much more versatile than the other method. It was found that the position of the marker plane becomes vague in the second stage of the interdiffusion process in pure A thin layer/B couple, where two phases grow simultaneously.     

Detecting localized homogeneous anomalies over spatio-temporal data

The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as—weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases—(i) discovering homogeneous regions, and (ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.