On the miscible Rayleigh-Taylor instability: two and three dimensions

We investigate the miscible Rayleigh-Taylor (RT) instability in both 2 and 3 dimensions using direct numerical simulations, where the working fluid is assumed incompressible under the Boussinesq approximation. We first consider the case of randomly perturbed interfaces. With a variety of diagnostics, we develop a physical picture for the detailed temporal development of the mixed layer: We identify three distinct evolutionary phases in the development of the mixed layer, which can be related to detailed variations in the growth of the mixing zone. Our analysis provides an explanation for the observed differences between two and three-dimensional RT instability; the analysis also leads us to concentrate on the RT models which (1) work equally well for both laminar and turbulent flows, and (2) do not depend on turbulent scaling within the mixing layer between fluids. These candidate RT models are based on point sources within bubbles (or plumes) and interaction with each other (or the background flow). With this motivation, we examine the evolution of single plumes, and relate our numerical results (of single plumes) to a simple analytical model for plume evolution.Comment: 31 pages, 27 figures, to appear in November issue of JFM, 2001. For better figures: http://astro.uchicago.edu/~young/ps/jfmtry08.ps.

A Speaker Diarization System for Studying Peer-Led Team Learning Groups

Peer-led team learning (PLTL) is a model for teaching STEM courses where small student groups meet periodically to collaboratively discuss coursework. Automatic analysis of PLTL sessions would help education researchers to get insight into how learning outcomes are impacted by individual participation, group behavior, team dynamics, etc.. Towards this, speech and language technology can help, and speaker diarization technology will lay the foundation for analysis. In this study, a new corpus is established called CRSS-PLTL, that contains speech data from 5 PLTL teams over a semester (10 sessions per team with 5-to-8 participants in each team). In CRSS-PLTL, every participant wears a LENA device (portable audio recorder) that provides multiple audio recordings of the event. Our proposed solution is unsupervised and contains a new online speaker change detection algorithm, termed G 3 algorithm in conjunction with Hausdorff-distance based clustering to provide improved detection accuracy. Additionally, we also exploit cross channel information to refine our diarization hypothesis. The proposed system provides good improvements in diarization error rate (DER) over the baseline LIUM system. We also present higher level analysis such as the number of conversational turns taken in a session, and speaking-time duration (participation) for each speaker.Comment: 5 Pages, 2 Figures, 2 Tables, Proceedings of INTERSPEECH 2016, San Francisco, US

Investigation of potential rhizospheric isolate for cypermethrin degradation

Rhizoremediation is the use of plant–microbe interaction for the enhanced degradation of contaminants. Rhizosphere bioremediation of pyrethroid pesticides will offer an attractive and potentially inexpensive approach for remediation of contaminated soil. The present study was done with the aim of establishment of highly effective remediation method using plant with degradative rhizosphere and isolation of naturally occurring rhizosphere associated potential degrader providing the possibility of both environmental and insitu detoxification of cypermethrin contamination. The remediation efficacy of Pennisetum pedicellatum was investigated using green house pot culture experiments in cypermethrin amended potting soil mix (10, 25, 50, 75 and 100 mg/kg) for periodic evaluation of changes in concentration. Total proportion of cypermethrin degraders was found to be higher in rhizosphere soil compared to bulk soil. The cypermethrin degrading strain associated with rhizosphere capable of surviving at higher concentrations of cypermethrin was designated as potential degrader. On the basis of morphological characteristics, biochemical tests and 16S rDNA analysis, isolate was identified as Stenotrophomonas maltophilia MHF ENV 22. Bioremediation data of cypermethrin by strain MHF ENV22 examined by HPLC and mass spectroscopy, indicated 100, 50 and 58 % degradation within the time period of 72, 24 and 192 h at concentrations 25, 50 and 100 mg/kg, respectively. This is the first report of effective degradation of cypermethrin by Stenotrophomonas spp. isolated from rhizosphere of Pennisetum pedicellatum. Rhizoremediation strategy will be of immense importance in remediation of cypermethrin residues to a level permissible for technogenic and natural environment

RCCNet: An Efficient Convolutional Neural Network for Histological Routine Colon Cancer Nuclei Classification

Efficient and precise classification of histological cell nuclei is of utmost importance due to its potential applications in the field of medical image analysis. It would facilitate the medical practitioners to better understand and explore various factors for cancer treatment. The classification of histological cell nuclei is a challenging task due to the cellular heterogeneity. This paper proposes an efficient Convolutional Neural Network (CNN) based architecture for classification of histological routine colon cancer nuclei named as RCCNet. The main objective of this network is to keep the CNN model as simple as possible. The proposed RCCNet model consists of only 1,512,868 learnable parameters which are significantly less compared to the popular CNN models such as AlexNet, CIFARVGG, GoogLeNet, and WRN. The experiments are conducted over publicly available routine colon cancer histological dataset "CRCHistoPhenotypes". The results of the proposed RCCNet model are compared with five state-of-the-art CNN models in terms of the accuracy, weighted average F1 score and training time. The proposed method has achieved a classification accuracy of 80.61% and 0.7887 weighted average F1 score. The proposed RCCNet is more efficient and generalized terms of the training time and data over-fitting, respectively.Comment: Published in ICARCV 201

Modeling Barkhausen Noise in Magnetic Glasses with Dipole-Dipole Interactions

Long-ranged dipole-dipole interactions in magnetic glasses give rise to magnetic domains having labyrinthine patterns. Barkhausen Noise is then expected to result from the movement of domain boundaries which is supposed to be modeled by the motion of elastic membranes with random pinning. We propose an atomistic model of such magnetic glasses in which we measure the Barkhausen Noise which indeed results from the movement of domain boundaries. Nevertheless the statistics of the Barkhausen Noise is found in striking disagreement with the expectations in the literature. In fact we find exponential statistics without any power law, stressing the fact that Barkhausen Noise can belong to very different universality classes. In this glassy system the essence of the phenomenon is the ability of spin-carrying particles to move and minimize the energy without any spin flip. A theory is offered in excellent agreement with the measured data without any free parameter.Comment: 5 Pages, 5 Figures, Submitted to EP

Experimental Investigation of the Effects of Hydrogen Addition with Diesel on Performance and Emission of a Single Cylinder Diesel Engine

Need of the hour in present day scenario is to cope with energy crisis and human life in India and around the globe which is associated with depletion in the percentage of petroleum products and increase in the share of pollution caused due to emissions from diesel operated engines. This work tries to address these two major concern with the use of alternative fuel for diesel engine .A lot of research is going on the use of alternative and innovative fuels in the word, among those one of the most promising alternative ought to be hydrogen for being a clean and non carbon in nature. However various ongoing researches shown hydrogen blending to be proved to show positive effect on performance and emission of a diesel engine, which has to be carried forwarded. In this work a flow rate of 4 lpm, 6 lpm and 8 lpm respectively blend of hydrogen proportion where used along which diesel at loading at a constant speed of 1500 rpm to determine various engine performance parameters such as brake thermal efficiency, brake specific fuel consumption ,brake power, indicated thermal efficiency, mechanical efficiency, volumetric efficiency, torque output and power output. along with these various emission parameters such as percentage of CO,HC ,NOx gas temperature with varying blend proportion are also observed and compared