Droplet size distribution in homogeneous isotropic turbulence

We study the physics of droplet breakup in a statistically stationary homogeneous and isotropic turbulent flow by means of high resolution numerical investigations based on the multicomponent lattice Boltzmann method. We verified the validity of the criterion proposed by Hinze (1955) for droplet breakup and we measured the full probability distribution function (pdf) of droplets radii at different Reynolds numbers and for different volume fraction. By means of a Lagrangian tracking we could follow individual droplets along their trajectories, define a local Weber number based on the velocity gradients and study its cross-correlation with droplet deformation.Comment: 10 pages, 6 figure

Mycodecolorization Activity of Pleurotus Citrinopileatus for Chemically Different Textile Dye Under Varied Aromatic Amino Acids and Trace Elements

In the present study, ligninolytic enzymes laccase (benzenediol: oxygen reductase EC; 1.10.3.2) and Manganese Peroxidase (Mn(II): hydrogen-peroxide oxidoreductase EC; 1.11.1.13) activity and of White Rot Fungi (WRF) Pleurotus citrinopileatus were enhanced with the application of trace metal i.e. Copper and Manganese at 25 ppm and 50 ppm followed by aromatic amino acids (Phenylalanine, Tryptophan and Tyrosine) at 0.02 μM and 0.4 μM. Laccase and MnP activity were 213.42U and 202.28U respectively, observed at 300ppm of Methyl Red supplemented with Tyrosine (0.2μM) followed by treatment of Tryptophan (198.45U and 195.16U) and Phenylalanine (195.85U and 188.15U). Maximum Laccase and MnP activity (Tyrosine treated) were revealed maximum decolorization of Phenol Red and Methyl Red (84.14% and 78.20%) followed by Phenylalanine (80.92% and 73.80%) and Trypatophan (71.22% and 70.12%).  The negative correlation of  Laccase and MnP activity was observed with a higher concentration (>50ppm) of trace metal in the medium, while at 25ppm of copper supplemented medium increase three-fold of Laccase activity (585.56U) as tyrosine medium and similarly, Manganese (25ppm) inosculated medium revealed three-fold more MnP activity (478.95U).  A lower amount of Cu hoists Laccase and MnP activity which decolorized 300ppm of Methyl Red and Phenol Red with maximum percent (92.3% and 88.15%) followed by Mn. Thus, Laccase and MnP enzymes both play an important role in decolorization of dyes, and its activity was enhanced with the application of lower concentration of trace metals followed by aromatic amino acids

Record statistics in random vectors and quantum chaos

The record statistics of complex random states are analytically calculated, and shown that the probability of a record intensity is a Bernoulli process. The correlation due to normalization leads to a probability distribution of the records that is non-universal but tends to the Gumbel distribution asymptotically. The quantum standard map is used to study these statistics for the effect of correlations apart from normalization. It is seen that in the mixed phase space regime the number of intensity records is a power law in the dimensionality of the state as opposed to the logarithmic growth for random states.Comment: figures redrawn, discussion adde

OVS+Tumor: a tool for enhanced lung tumor annotation in VR for machine learning training and analysis

OVS+Tumor creates a seamless VR environment designed for intuitive interaction aiding in the complex task of parsing through 3D CT-scans and annotating candidate tumors. Through interactive subsetting and on-the-fly iso-cloud generation, a wider range of users beyond just domain experts (radiologists/surgeons) can generate a viable machine-learning training dataset

OVS+Tumor: a tool for enhanced lung tumor annotation in VR for machine learning training and analysis

OVS+Tumor creates a seamless VR environment designed for intuitive interaction aiding in the complex task of parsing through 3D CT-scans and annotating candidate tumors. Through interactive subsetting and on-the-fly iso-cloud generation, a wider range of users beyond just domain experts (radiologists/surgeons) can generate a viable machine-learning training dataset

Exploring new potentials and generating hypothesis for management of locally advanced head neck cancer: Analysis of pooled data from two phase II trials

Background: To study the long term results of two phase II concurrent chemoradiotherapy protocols and conduct pooled data analysis with special emphasis on nodal density. Materials and Methods: In the period from April 2001 to May 2003, phase II Mitomycin C (MMC) and late chemo-intensification (LCI) protocols were started in the same institute, enrolling 69 and 74 patients respectively. Long term results for these individual trials are reported along with pooled data analysis. Results: Median follow-up time for whole group, MMC protocol and LCI protocol was 43.8 months (SD619.8), 55 months (SD 618.5) and 47.5 months (SD 620.9) respectively. LRFS, DFS and OS at five years for whole group was 59.4, 43.5 and 47.1% respectively, for MMC protocol was 59.9, 45.5 and 49.5% respectively and for LCI, protocol was 53.6%, 41.5% and 44.4% respectively. Subgroup analysis revealed that MMC protocol was more effective than LCI protocol in terms of DFS and OS in patients with hypo dense nodes while opposite was true for Isodense nodes. Multivariate analysis revealed nodal density as an independent variable that had an impact on treatment outcome. Risk of death in patients with hypo dense nodes was 2.91 times that of Isodense nodes. Conclusions: Innovative and pragmatic approach is required to address locally advanced head neck cancer. Long term results for MMC and LCI protocols are encouraging. Integrating the basic concepts of these protocols may help develop new protocols, which will facilitate the search for the optimal solution

Probabilistic Clustering of Time-Evolving Distance Data

We present a novel probabilistic clustering model for objects that are represented via pairwise distances and observed at different time points. The proposed method utilizes the information given by adjacent time points to find the underlying cluster structure and obtain a smooth cluster evolution. This approach allows the number of objects and clusters to differ at every time point, and no identification on the identities of the objects is needed. Further, the model does not require the number of clusters being specified in advance -- they are instead determined automatically using a Dirichlet process prior. We validate our model on synthetic data showing that the proposed method is more accurate than state-of-the-art clustering methods. Finally, we use our dynamic clustering model to analyze and illustrate the evolution of brain cancer patients over time

Long Non-Coding RNA ZFAS1 Is a Major Regulator of Epithelial-Mesenchymal Transition through miR-200/ZEB1/E-Cadherin, Vimentin Signaling in Colon Adenocarcinoma

Colon adenocarcinoma is a common cause of cancer-related deaths worldwide. Epithelial-mesenchymal transition is a major regulator of cancer metastasis, and increased understanding of this process is essential to improve patient outcomes. Long non-coding RNA (lncRNA) are important regulators of carcinogenesis. To identify lncRNAs associated with colon carcinogenesis, we performed an exploratory differential gene expression analysis comparing paired colon adenocarcinoma and normal colon epithelium using an RNA-sequencing data set. This analysis identified lncRNA ZFAS1 as significantly increased in colon cancer compared to normal colon epithelium. This finding was validated in an institutional cohort using laser capture microdissection. ZFAS1 was also found to be principally located in the cellular cytoplasm. ZFAS1 knockdown was associated with decreased cellular proliferation, migration, and invasion in two colon cancer cell lines (HT29 and SW480). MicroRNA-200b and microRNA-200c (miR-200b and miR-200c) are experimentally validated targets of ZFAS1, and this interaction was confirmed using reciprocal gene knockdown. ZFAS1 knockdown regulated ZEB1 gene expression and downstream targets E-cadherin and vimentin. Knockdown of miR-200b or miR-200c reversed the effect of ZFAS1 knockdown in the ZEB1/E-cadherin, vimentin signaling cascade, and the effects of cellular migration and invasion, but not cellular proliferation. ZFAS1 knockdown was also associated with decreased tumor growth in an in vivo mouse model. These results demonstrate the critical importance of ZFAS1 as a regulator of the miR-200/ZEB1/E-cadherin, vimentin signaling cascade

Working Group Report: Heavy-Ion Physics and Quark-Gluon Plasma

This is the report of Heavy Ion Physics and Quark-Gluon Plasma at WHEPP-09 which was part of Working Group-4. Discussion and work on some aspects of Quark-Gluon Plasma believed to have created in heavy-ion collisions and in early universe are reported.Comment: 20 pages, 6 eps figures, Heavy-ion physics and QGP activity report in "IX Workshop on High Energy Physics Phenomenology (WHEPP-09)" held in Institute of Physics, Bhubaneswar, India, during January 3-14, 2006. To be published in PRAMANA - Journal of Physics (Indian Academy of Science

Metabolomics-Driven Mining of Metabolite Resources:Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants