Development of a DEM–VOF Model for the Turbulent Free-Surface Flows with Particles and Its Application to Stirred Mixing System

The free-surface flows with particles are widely found in chemical engineering, and numerical modeling is a strong computing tool for in-depth understanding of the local and macrocharacteristics. In this study, a discrete element method–volume-of-fluid (DEM–VOF) model is extended to turbulent free-surface flows with particles, by means of Reynolds stress model. Also, we adopt a novel virtual dual-grid porosity model to calculate the fluid porosity. The simulated results of single particle sedimentation, the falling of sinking particles, and the floating of buoyant particles agree well to analytical and literatures, which validate the proposed DEM–VOF model. Furthermore, the DEM–VOF model developed in this paper is applied to the simulation of free surface flow with particles in solid–liquid mixing system for the first time. It is found that elliptical-head vessel is preferred to a flat-bottomed vessel for solid–liquid mixing by comparing the simulation results of four different stirred tanks, which agrees well to the related content of the book <i>Handbook of Industrial Mixing</i> (Paul, E. L.; Atiemo-Obeng, V. A.; Kresta, S. M. Eds.; John Wiley & Sons, 2004)

Immunohistochemistry of CHOP and Caspase-12 in hippocampus.

<p>(a) CHOP immunostain in control group ×400. (b) CHOP immunostain in sevoflurane group ×400. (c) Caspase-12 immunostain in control group ×400. (d) Caspase-12 immunostain in sevoflurane group ×400. (e) Numbers of CHOP and Caspase-12-positive cells. (f) Optical density of CHOP and Caspase-12-positive cells. Data are presented as mean ± SD. *<i>P</i><0.05, <i>vs</i> the control group.</p

Expression of CHOP and Caspase-12 mRNA in hippocampus were analyzed by real-time RT-PCR.

<p>The real time reactions were performed in duplicates for both the target gene and GAPDH used as a housekeeping control. The relative expression was calculated using 2^−ΔΔCt method. Data are presented as mean ± SD. **<i>P</i><0.01, <i>vs</i> control group.</p

Global Analysis of Transcriptome Responses and Gene Expression Profiles to Cold Stress of <i>Jatropha curcas</i> L.

<div><p>Background</p><p><i>Jatropha curcas</i> L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, <i>J. curcas</i> confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in <i>J. curcas</i>.</p> <p>Results</p><p>In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the <i>J. curcas</i> transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis.</p> <p>Conclusions</p><p>This study provides a global view of transcriptome response and gene expression profiling of <i>J. curcas</i> in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in <i>J. curcas</i>.</p> </div

Number and expression model of novel <i>Jatropha curcas</i> genes after cold exposure for schemed periods.

<p>A: Venn diagram indicating the total number of novel, expressed genes after 12, 24, and 48 h of 12°C. B: Expression model of common, novel genes at three time points. The vertical line indicates the raw expression of novel genes in each sample.</p

Simplified model of starch catabolism pathway.

<p>Simplified model of starch catabolism pathway.</p

The vital signs and arterial blood gas during anesthetics treatment.

*<p><i>P</i>>0.05 <i>vs</i> sham anesthesia rats.</p><p>HR:heart rate, MAP: mean artery pressure, PaCO₂: partial pressure of carbon dioxide in artery, SPO₂: saturation of arterial blood oxygen.</p

Venn diagrams showing differentially expressed <i>Jatropha curcas</i> genes after cold exposure for three time points.

<p>A: upregulated genes. B: downregulated genes.</p

Sevoflurane induced apoptosis of cells in the hippocampus of aged rats.

<p>Apoptosis was examined by the TUNEL method. Upper: Photomicrographs of TUNEL-positive cells. (a) Control group. (b) Sevoflurane group. (c) Number of TUNEL-positive cells in each group. Data are presented as mean ± SD. *<i>P</i><0.05, <i>vs</i> control group.</p

Ultrastructural changes of apoptotic neurons in sevoflurane group.

<p>These degenerating neurons showed an advanced stage of apoptosis, with chromatin clumping, condensation and margination (arrow), (a) a control rat. (b) a sevoflurane treated rat, Scale bar = 2 µm.</p