Revision of thermodynamic data on MnO Al2O3 melts

The high temperature region of the MnO-A1203 phase diagram has been redetermined to resolve some discrepancies reported in the literature regarding the melting behaviour of MnA1,04. This spinel was found to melt congruently at 2108 (+ 15) K. Theactivity of MnOin MnO-Al,03 meltsand in the two phase regions, melt + MnAI,04 and MnAI2O4 + A1203, has been determined by measuring the manganese concentration in platinum foils in equilibrium under controlled oxygen potentials. The activity of MnO obtained in this study for M ~ O - A I ,m~el~ts is in fair agreement with the results of Sharma and Richardson.However. the alumina-rich melt is found to be in equilibrium with MnAl,04 rather than AI2O3. as suggested by ~ha rmaan d Richardson. The value for the acthity of MnO in the M~AI ,O,+ A1,03 two phaseregion permits a rigorous application of the Gibbs-Duhem equation for calculating the activity of A1203 and the integral Gibbs' energy of mixing of MnO-A1203 melts, which are significantly different from those reported in the literature.

Gibbs energy formation of lead titanate

The Gibbs energy of formation of titania-saturated lead titanate has been determined by e.m.f. measurements on the solid state cell;Pt,Ir,Pb + Pb1−xTiO3−x + TiO2(rutile)/CaO-ZrO2/Ni + NiO,Pt in the temperature range 1075–1350 K. The results obtained are significantly different from those reported in the literature based upon vapour pressure measurements, employing Knudsen effusion and transportation techniques, and assuming that the vapor phase consisted entirely of monomeric PbO molecules. A reanalysis of the data obtained in the earlier vapor pressure studies using mass spectrometric measurements on polymeric PbO species in the gas phase, gives Gibbs energies of formation of lead titanate which are in better agreement with those obtained in this study. Earlier electrochemical measurements by Mehrotra et al. and more recent electrochemical measurements by Schmahl et al. both employing CaO-ZrO2 solid electrolytes are in good agreement with the present study. The electro-chemical measurements by Schmahl et al. using PbF 2 solid electrolyte give a slightly more positive Gibbs energy of formation. There was no evidence supporting the formation of compounds other than Pb1−xTiO3−x from yellow PbO and rutile form of TiO2 in the temperature range covered in this study.Résumé L'enthalpie libre de formation du titanate de plomb saturé en oxyde de titane a été déterminée par des mesures de FEM de la pile: Pt,Ir,Pb + Pb1−xTiO3−x + TiO2(rutile)/CaO-ZrO2/Ni + NiO,Pt dans le domaine de températures 1075–1350 K. Les résultats obtenus, different appréciablement de ceux publiés, déterminés par mesures de tensions de vapeur (techniques de transport et d'effusion de Knudsen) en supposant que la phase gazeuse etait uniquement constituée de molécules monomériques de PbO. Une réanalyse des résultats de la littérature, à partir de mesures par spectrométrie de masse sur les polymères de PbO gazeux, donne des enthalpies libres de formation du titanate de plomb se rapprochant de celles obtenues dans cette étude. Les mesures de Mehrotra et al. et plus récemment de Schmahl et al. utilisant toutes deux l'électrolyte CaO-ZrO2 concordent bien avec celles de la présente étude. Les mesures de Schmahl et al., à l'aide de l' électrolyte solide PbF2, donnent une enthalpie de formation légèrement plus positive. Pour la gammede températures étudiée, rien ne permet de supposer que des composés autres que Pb1−x TiO3−x puissent se former à partir du PbO Gaune) et du rutile (TiO2).

Interaction of guar gum with hydrophobic solids

The interaction of guar gum with the hydrophobic solids namely talc, mica and graphite has been investigated through adsorption, electrokinetic and flotation experiments. The adsorption densities of guar gum onto the above hydrophobic minerals show that they are more or less independent of pH. The adsorption isotherms of guar gum onto talc, mica and graphite indicate that the adsorption densities increase with increase in guar gum concentration and all the isotherms follow the as L1 type according to Giles classification. The magnitude of the adsorption density of guar gum onto the above minerals may be arranged in the following sequence: talc > graphite > mica The effect of particle size on the adsorption density of guar gum onto these minerals has indicated that higher adsorption takes place in the coarser size fraction, consequent to an increase in the surface face-to-edge ratio. In the case of the talc and mica samples pretreated with EDTA and the leached graphite sample, a decrease in the adsorption density of guar gum is observed, due to a reduction in the metallic adsorption sites. The adsorption densities of guar gum increase with decrease in sample weight for all the three minerals. Electrokinetic measurements have indicated that the isoelectric points (iep) of these minerals lie between pH 2-3, Addition of guar gum decreases the negative electrophoretic mobility values in proportion to the guar gum concentration without any observable shift in the iep values, resembling the influence of an indifferent electrolyte. The flotation recovery is diminished in the presence of guar gum for all the three minerals, The magnitude of depression follows the same sequence as observed in the adsorption studies. The floatability of EDTA treated talc and mica samples as well as the leached graphite sample is enhanced, complementing the adsorption data, Possible mechanisms of interaction between the hydrophobic minerals and guar gum are discussed.

Fast algorithms for frequent episode discovery in event sequences

In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

Recognition of Kannada characters extracted from scene images

In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

Charge Injection through Nanocomposite Electrode in Microfluidic Channel for Electrical Lysis of Biological Cells

Several concepts have been developed in the recent years for nanomaterial based integrated MEMS platform in order to accelerate the process of biological sample preparation followed by selective screening and identification of target molecules. In this context, there exist several challenges which need to be addressed in the process of electrical lysis of biological cells. These are due to (i) low resource settings while achieving maximal lysis (ii) high throughput of target molecules to be detected (iii) automated extraction and purification of relevant molecules such as DNA and protein from extremely small volume of sample (iv) requirement of fast, accurate and yet scalable methods (v) multifunctionality toward process monitoring and (vi) downward compatibility with already existing diagnostic protocols. This paper reports on the optimization of electrical lysis process based on various different nanocomposite coated electrodes placed in a microfluidic channel. The nanocomposites are synthesized using different nanomaterials like Zinc nanorod dispersion in polymer. The efficiency of electrical lysis with various different electrode coatings has been experimentally verified in terms of DNA concentration, amplification and protein yield. The influence of the coating thickness on the injection current densities has been analyzed. We further correlate experimentally the current density vs. voltage relationship with the extent of bacterial cell lysis. A coupled multiphysics based simulation model is used to predict the cell trajectories and lysis efficiencies under various electrode boundary conditions as estimated from experimental results. Detailed in-situ fluorescence imaging and spectroscopy studies are performed to validate various hypotheses.

Biological sulfate reduction of a sulfate-rich industrial waste liquor using sulfate reducing bacteria

An industrial waste liquor having high sulfate concentrations was subjected to biological treatment using the sulfate-reducing bacteria (SRB) Desulfovibrio desulfuricans. Toxicity levels of different sulfate, cobalt and nickel concentrations toward growth of the SRB with respect to biological sulfate reduction kinetics was initially established. Optimum sulfate concentration to promote SRB growth amounted to 0.8 - 1 g/L. The strain of D. desulfuricans used in this study initially tolerated up to 4 -5 g/L of sulfate or 50 mg/L of cobalt and nickel, while its tolerance could be further enhanced through adaptation by serial subculturing in the presence of increasing concentrations of sulfate, cobalt and nickel. From the waste liquor, more than 70% of sulfate and 95% of cobalt and nickel could be precipitated as sulfides, using a preadapted strain of D. desulfuricans. Probable mechanisms involving biological sulfide precipitation and metal adsorption onto precipitates and bacterial cells are discussed.

RAPID HUMAN ACTION RECOGNITION IN H.264/AVC COMPRESSED DOMAIN FOR VIDEO SURVEILLANCE

This paper discusses a novel high-speed approach for human action recognition in H. 264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of our work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can effect in reduced hardware utilization and fast recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust in outdoor as well as indoor testing scenarios. We have tested our method on two benchmark action datasets and achieved more than 85% accuracy. The proposed algorithm classifies actions with speed (>2000 fps) approximately 100 times more than existing state-of-the-art pixel-domain algorithms.

Holistic Measures for Evaluating Prediction Models in Smart Grids

The performance of prediction models is often based on ``abstract metrics'' that estimate the model's ability to limit residual errors between the observed and predicted values. However, meaningful evaluation and selection of prediction models for end-user domains requires holistic and application-sensitive performance measures. Inspired by energy consumption prediction models used in the emerging ``big data'' domain of Smart Power Grids, we propose a suite of performance measures to rationally compare models along the dimensions of scale independence, reliability, volatility and cost. We include both application independent and dependent measures, the latter parameterized to allow customization by domain experts to fit their scenario. While our measures are generalizable to other domains, we offer an empirical analysis using real energy use data for three Smart Grid applications: planning, customer education and demand response, which are relevant for energy sustainability. Our results underscore the value of the proposed measures to offer a deeper insight into models' behavior and their impact on real applications, which benefit both data mining researchers and practitioners.

Compressed domain human action recognition in H.264/AVC video streams

This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.