Boundary-layer flow of the power-law fluid over a moving wedge: a linear stability analysis

We study the stability of the two-dimensional boundary-layer flow of a power-law (Ostwald de Waele) non-Newtonian fluid over a moving wedge. The mainstream velocity is assumed to have a power of distance from the leading boundary layer, such that the system admits to the self-similar solutions. We discuss the problem in question for both shear-thickening and shear-thinning fluids which lead to a non-uniqueness (double solutions) in the base flow solutions. We then address an issue of the stability of the non-unique solutions. A linear eigenvalue analysis of the double solution reveals that the basic flow represented by the first solution is always stable, and this flow is practically encountered. The system becomes unstable to the second solutions which have the mode-two perturbations with larger boundary-layer thickness. The first and second solutions form a tongue-like structure in the solution space. Furthermore, the modification of the viscosity for the power-law fluids reveals that the system predicts an infinite viscosity in the confinement of the boundary-layer region. Extensive comparisons of the solutions with the existing models with Newtonian fluid are made, and a physical explanation behind these solutions is proposed.

     

Improving the performance of speaker and language identification tasks using unique characteristics of a class

In classification tasks, the error rate is proportional to the commonality among classes. In conventional GMM-based modeling technique, since the model parameters of a class are estimated without considering other classes in the system, features that are common across various classes may also be captured, along with unique features. This paper proposes to use unique characteristics of a class at the feature-level and at the phoneme-level, separately, to improve the classification accuracy. At the feature-level, the performance of a classifier has been analyzed by capturing the unique features while modeling, and removing common feature vectors during classification. Experiments were conducted on speaker identification task, using speech data of 40 female speakers from NTIMIT corpus, and on a language identification task, using speech data of two languages (English and French) from OGI_MLTS corpus. At the phoneme-level, performance of a classifier has been analyzed by identifying a subset of phonemes, which are unique to a speaker with respect to his/her closely resembling speaker, in the acoustic sense, on a speaker identification task. In both the cases (feature-level and phoneme-level) considerable improvement in classification accuracy is observed over conventional GMM-based classifiers in the above mentioned tasks. Among the three experimental setup, speaker identification task using unique phonemes shows as high as 9.56 % performance improvement over conventional GMM-based classifier.     

Comparing composite scores based on maximal voluntary isometric contraction and on semiquantitative manual motor testing in measuring limb strength in patients with ALS

Maximal voluntary isometric contraction (MVIC) is a standardized tool for measuring disease progression in patients with ALS. After normalization, summation, and averaging, it generates composite scores (CS) ("megascores"). In a cross-sectional study, these scores were highly correlated with "average strength" composite scores based on semi-quantitative manual motor testing (SQMMT): r = 0.697 (p < 0.0001). Each 10% difference in the raw SQMMT-CS corresponds to a 0.56 difference in the MVIC-CS (95% confidence limits [CL], 0.38, 0.74). Controlling for height (a highly significant covariate, p < 0.0001), each 10% difference in SQMMT-CS corresponds to a 0.39 difference in MVIC-CS (95% CL, 0.24, 0.54).     

Modeling and Optimization of the Effect of Sintering Parameters on the Hardness of Copper/Graphene Nanosheet Composites by Response Surface Methodology

Metal Science and Heat Treatment - Composites obtained by powder metallurgy from a mixture of copper powders and graphene nanosheets are studied. The response surface methodology is used to design...     

rGO Sheets/ZnFe2O4 Nanocomposities as an Efficient Electro Catalyst Material for I3−/I− Reaction for High Performance DSSCs

In this paper, Reduced Graphene Oxide (rGO)/ZnFe₂O₄ (rZnF) nanocomposite is synthesized by a simple hydrothermal method and employed as a counter electrode (CE) material for tri-iodide redox reactions in Dye sensitized solar cells (DSSC) to replace the traditional high cost platinum (Pt) CE. X-ray diffraction analysis and High resolution Transmission electron microscopy, clearly indicated the formation of rZnF nanocomposite and also amorphous rGO sheets were smoothly distributed on the surface of ZnFe₂O₄ (ZnF) nanostructure. The rZnF-50 CE shows excellent electro catalytic activity toward I₃^? reduction, which has simultaneously been confirmed by cyclic voltammetry, electrochemical impedance spectroscopy and Tafel polarization measurements. A DSSC developed by rZnF-50 CE (η?=?8.71%) obtained quite higher than the Pt (η?=?8.53%) based CE under the same condition. The superior performances of rZnF-50 CE due to addition of graphene in to Spinel (ZnF) nanostructure results in creation of highly active electrochemical sites, fast electron transport linkage between CE and electrolyte. Thus it’s a promising low cost CE material for DSSCs.

     

The influence of mesoscale eddies on a commercial fishery in the coastal waters of the Andaman and Nicobar Islands,India

Mesoscale eddies enhance the productivity in a stratified coastal environment by upwelling. The seas around the Andaman and Nicobar Islands have been found to have frequent mesoscale eddy activity. Commercial fishing grounds coincide with upwelling areas associated with cyclonic and anticyclonic eddies and also with areas between two adjacent eddies. There are different eddy zones supporting different types of fishing gears and fish. The current study aims at identifying the different zones of mesoscale eddies in the Andaman Sea and compares the productivity and fishing activity in each of them. Data collected from 454 commercial fishing trips in the Andaman Sea along with maps of sea level anomaly and Moderate Resolution Imaging Spectroradiometer (MODIS) global level 3 mapped thermal infrared (IR) daytime sea surface temperature (SST) from the Aqua and Terra satellites were used for the study. Known upwelling areas such as the periphery of anticyclonic and the core of cyclonic eddies showed higher catches in longlines, ring seines among the fishing gears, and among all the fish species groups. Downwelling areas such as the periphery of cyclonic and the core of anticyclonic eddies showed lower catches with ring seines and the fish species groups. Areas in between adjacent eddies were explored in this study and the fish captures in such areas were found to be different with types of fishing and the target fish group. The study shows results that link eddy activity with the performance of a fishery.     

Ubiquitin-Specific Protease 29 Regulates Cdc25A-Mediated Tumorigenesis

Cell division cycle 25A (Cdc25A) is a dual-specificity phosphatase that is overexpressed in several cancer cells and promotes tumorigenesis. In normal cells, Cdc25A expression is regulated tightly, but the changes in expression patterns in cancer cells that lead to tumorigenesis are unknown. In this study, we showed that ubiquitin-specific protease 29 (USP29) stabilized Cdc25A protein expression in cancer cell lines by protecting it from ubiquitin-mediated proteasomal degradation. The presence of USP29 effectively blocked polyubiquitination of Cdc25A and extended its half-life. CRISPR-Cas9-mediated knockdown of USP29 in HeLa cells resulted in cell cycle arrest at the G0/G1 phase. We also showed that USP29 knockdown hampered Cdc25A-mediated cell proliferation, migration, and invasion of cancer cells in vitro. Moreover, NSG nude mice transplanted with USP29-depleted cells significantly reduced the size of the tumors, whereas the reconstitution of Cdc25A in USP29-depleted cells significantly increased the tumor size. Altogether, our results implied that USP29 promoted cell cycle progression and oncogenic transformation by regulating protein turnover of Cdc25A.     

Stance detection and mobile app recommendation discourse on tweets

Web‐based social networking such as microblogging administrations and long‐range informal communication locales are changing the way in which individuals collaborate on the web and search for data and opinions. An essential parameter of online networking discourse is searchability. A key semiotic asset supporting this capacity is the hashtag, a type of social label that enables microbloggers to insert metadata in online networking posts. In this paper, an attempt is made to analyze stance detection and app recommendation discourse on tweets in view of hashtag techniques, which is in the territory of etymology, and to spotlight the structure of dialect at the provision level. With a revival of enthusiasm for topics identified by modeling language at the discourse level, a graphical model of conversational structure (ie, the structural topic model) has been constructed by means of utilizing three methods: displaying words connected with topics or documents highly connected with topics, calculating topic correlations, and assessing associations between metadata and topical content, its capture of latent topics, and topical structures inside documents on a benchmark dataset (ie, SemEval 2016) has been scrutinized for stance detection, and data have been crawled from Twitter, using the hashtag #App for app recommendations.