The Reynolds-averaged Navier-Stokes equations have been numerically solved to obtain a steady, threedimensional velocity field inside the six-strand billet caster tundish using the standard k-e model of turbulence. These steady flow fields so obtained are then used to predict the removal of inclusions from molten steel by solving the inclusion transport equation with the help of a commercial CFD software Fluent 6.1.22. The effects of height and position of dams in the tundish and size of the inclusion particles on percentage inclusion removal were studied. To simulate the chaotic effect of the turbulent eddies on the particle paths; a discrete random walk model was applied during inclusion trajectory calculations. The computational model was first validated with the results reported in the literature a good match was found between the two. It was found that with the increase in the height of the dams, the inclusion removal tendency increased whereas the shifting of the dams towards the outlets decreases the inclusion removal. An increase in the inclusion removal was found with an increase in the inclusion particle size.
Autoimmunity is thought to contribute to poor neurological outcomes after spinal cord injury (SCI). There are few mechanism-based therapies, however, designed to reduce tissue damage and neurotoxicity after SCI because the molecular and cellular bases for SCI-induced autoimmunity are not completely understood. Recent groundbreaking studies in rodents indicate that B cells are responsible for SCI-induced autoimmunity. This novel paradigm, if confirmed in humans, could aid in the design of neuroprotective immunotherapies. The aim of this study was to investigate the molecular signaling pathways and mechanisms by which autoimmunity is induced after SCI, with the goal of identifying potential targets in therapies designed to reduce tissue damage and inflammation in the chronic phase of SCI. To that end, we performed an exploratory microarray analysis of peripheral blood mononuclear cells to identify differentially expressed genes in chronic SCI. We identified a gene network associated with lymphoid tissue structure and development that was composed of 29 distinct molecules and five protein complexes, including two cytokines, a proliferation-inducing ligand (APRIL) and B-cell-activating factor (BAFF), and one receptor, B-cell maturation antigen (BMCA) involved in B cell development, proliferation, activation, and survival. Real-time polymerase chain reaction analysis from ribonucleic acid samples confirmed upregulation of these three genes in SCI. To our knowledge, this is the first report that peripheral blood mononuclear cells produce increased levels of BAFF and APRIL in chronic SCI. This finding provides evidence of systemic regulation of SCI-autoimmunity via APRIL and BAFF mediated activation of B cells through BMCA and points toward these molecules as potential targets of therapies designed to reduce neuroinflammation after SCI.
The Navier-Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a single strand bare tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlet of the tundish. The numerical prediction of the tracer concentration has been made with nine different turbulence models and has been compared with the experimental observation for the tundish. It has been found that the prediction from the standard k-1 model, the k-1 Chen-Kim (ck) and the standard k-1 with Yap correction (k-1 Yap), matches well with that of the experiment compared to the other turbulence models as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. It has been found that the initial transient development of the tracer concentration is best predicted by the low Reynolds number Lam-Bremhorst model (LB model) and then by the k-1 RNG model, while these two models under predict the mean residence time as well as the ratio of mixed to dead volume. The Chen-Kim low Reynolds number (CK low Re) model (with and without Yap correction) as well as the constant effective viscosity model over predict the mixing parameters, i.e. the mean residence time and the ratio of mixed to dead volume. Taking the solution of the k-1 model as a starting guess for the large eddy simulation (LES), a solution for the LES could be arrived after adopting a local refinement of the cells twice so that the near wall y + could be set lower than 1. Such a refined grid gave a time-independent solution for the LES which was used to solve the species continuity equation. The LES solution slightly over predicted the mean residence time but could predict fairly well the mixed volume. However, the LES could not predict both the peaks in the tracer concentration like the k-1, RNG and the Lam-Bremhorst model. An analysis of the tracer concentration on the bottom plane of the tundish could help to understand the presence of plug and mixed flow in it.
The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlet of a single strand bare tundish. The numerical prediction of the tracer concentration has been made with three different turbulence models; (a standard k‐ε, a k‐ε RNG and a Low Re number Lam‐Bremhorst model) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of k‐ε model with that of the experiment is better than the other two turbulence models as far as gross quantities like mean residence time and ratio of mixed to dead volume are concerned. However, it has been found that the initial transient development of the tracer concentration is best predicted by the Lam‐Bremhorst model and then by the RNG model. The k‐ε model predicts the tracer concentration much better than the other two models after the initial transience (t>40 per cent of mean residence time) and the RNG model lies in between the k‐ε and the Lam‐Bremhorst one. The numerical study has been extended to a multi strand tundish (having 6 outlets) where the effect of outlet positions on the ratio of mix to dead volume has been studied with the help of the above three turbulence models. It has been found that all the three turbulence models show a peak value for the ratio of mix to dead volume (a mixing parameter) when the outlets are placed 200 mm away from the wall (position‐2) thus signifying an optimum location for the outlets to get highest mixing in a given multi strand tundish.
Nanomaterials of noble metals with unique size, shape and composition receives much attention owing to their versatile functionality in personalized cancer nanomedicine. Chrysin (ChR), a natural anticancer bioflavonoid emerged as potential drug therapy for almost all types of cancer, however it has poor solubility and bioavailability. Herein, we report a new approach to formulate biofunctionlized metallic silver (ChR-AgNPs) and gold (ChR-AuNPs) nanoparticles using ChR as direct bioreductant and capping agent. Size and dispersity of nanoparticles (NPs) were controlled through fixing different reaction conditions such as temperature, pH, concentration of metal ion, stochiometric proportion of reaction mixture and incubation time based on their optical properties and SPR effect in UV-visible spectroscopy. Role of hydroxyl and carbonyl groups in functionalizing metal ions with ChR was confirmed with Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analysis. It also substantiate that oxygen group from ChR donates electron to metal ion and results in complexation, ionic Ag + and Au 3+ were reduced to Ag 0 and Au 0 nano-forms. Physiochemical state of obtained NPs were characterized through different exclusive instrumentation, which shows the presence of highly-stable, spherical, crystalline ChR-AgNPs with the average size of 14±6 nm and 6±2 nm ChR-AuNPs respectively. In vitro anticancer results revealed that the formulated metallic NPs exhibits enhanced cytotoxicity than ChR against treated two different breast carcinoma cell lines (MDA-MB-231 and MDA-MB-468). Furthermore, it was evident that NPs cause cell death via induction of apoptosis. Haemolysis assay with human erythrocytes demonstrates good blood biocompatibility of NPs. Thus, the ChR functionalized metal NPs can be potentially employed as combinational drug-nano platform for breast cancer therapy.
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