Fully Coupled Internal Radiative Heat Transfer for the 3D Material Response of Heat Shield

The radiative transfer equation (RTE) is strongly coupled to the material response code KATS. A P-1 approximation model of RTE is used to account for radiation heat transfer within the material. First, the verification of the RTE model is performed by comparing the numerical and analytical solutions. Next, the coupling scheme is validated by comparing the temperature profiles of pure conduction and conduction coupled with radiative emission. The validation study is conducted on Marschall et al. cases (radiant heating, arc-jet heating, and space shuttle entry), 3D Block, 2D IsoQ sample, and Stardust Return Capsule. The validation results agree well for all the cases within a margin of error of 10%. Thus, the validation results indicate that the coupling approach can simulate the thermal response of material accurately. The coupling scheme is then used to simulate a laser heating experiment that studied the impact of spectral radiate heat transfer on ablative material. The results from the laser ablation simulations indicate the expected behavior and match well with experimental ones implying the effect of spectral radiative flux on the material response

Numerical Investigation on the Effect of Spectral Radiative Heat Transfer within an Ablative Material

The spectral radiative heat flux could impact the material response. In order to evaluate it, a coupling scheme between KATS - MR and P1 approximation model of radiation transfer equation (RTE) is constructed and used. A Band model is developed that divides the spectral domain into small bands of unequal widths. Two verification studies are conducted: one by comparing the simulation computed by the Band model with pure conduction results and the other by comparing with similar models of RTE. The comparative results from the verification studies indicate that the Band model is computationally efficient and can be used to simulate the material\u27s response when exposed to spectral radiative heat flux. To further evaluate the effectiveness of the spectral form of heat transfer, material response simulations were run by taking into account spectral data as the boundary condition. The results indicate a significant difference in temperature and density distributions within the sample. The internal temperatures are predicted higher with early decomposition when the spectral radiative heat flux is considered

Numerical Reconstruction of Spalled Particle Trajectories in an Arc-Jet Environment

To evaluate the effects of spallation on ablative material, it is necessary to evaluate the mass loss. To do so, a Lagrangian particle trajectory code is used to reconstruct trajectories that match the experimental data for all kinematic parameters. The results from spallation experiments conducted at the NASA HYMETS facility over a wedge sample were used. A data-driven adaptive methodology was used to adapts the ejection parameters until the numerical trajectory matches the experimental data. The preliminary reconstruction results show that the size of the particles seemed to be correlated with the location of the ejection event. The size of the particles ejected from the bottom edge of the wedge varies over three orders of magnitude, whereas the size of the ones ejected from the top (inclined) surface were more uniform (around 10 microns). On the bottom edge, the particles ejected near the leading edge were bulkier (10-1000 microns), where those that ejected further along, had a smaller size (0.1-1 microns)

Annotation of gene promoters by integrative data-mining of ChIP-seq Pol-II enrichment data

BACKGROUND: Use of alternative gene promoters that drive widespread cell-type, tissue-type or developmental gene regulation in mammalian genomes is a common phenomenon. Chromatin immunoprecipitation methods coupled with DNA microarray (ChIP-chip) or massive parallel sequencing (ChIP-seq) are enabling genome-wide identification of active promoters in different cellular conditions using antibodies against Pol-II. However, these methods produce enrichment not only near the gene promoters but also inside the genes and other genomic regions due to the non-specificity of the antibodies used in ChIP. Further, the use of these methods is limited by their high cost and strong dependence on cellular type and context. METHODS: We trained and tested different state-of-art ensemble and meta classification methods for identification of Pol-II enriched promoter and Pol-II enriched non-promoter sequences, each of length 500 bp. The classification models were trained and tested on a bench-mark dataset, using a set of 39 different feature variables that are based on chromatin modification signatures and various DNA sequence features. The best performing model was applied on seven published ChIP-seq Pol-II datasets to provide genome wide annotation of mouse gene promoters. RESULTS: We present a novel algorithm based on supervised learning methods to discriminate promoter associated Pol-II enrichment from enrichment elsewhere in the genome in ChIP-chip/seq profiles. We accumulated a dataset of 11,773 promoter and 46,167 non-promoter sequences, each of length 500 bp, generated from RNA Pol-II ChIP-seq data of five tissues (Brain, Kidney, Liver, Lung and Spleen). We evaluated the classification models in building the best predictor and found that Bagging and Random Forest based approaches give the best accuracy. We implemented the algorithm on seven different published ChIP-seq datasets to provide a comprehensive set of promoter annotations for both protein-coding and non-coding genes in the mouse genome. The resulting annotations contain 13,413 (4,747) protein-coding (non-coding) genes with single promoters and 9,929 (1,858) protein-coding (non-coding) genes with two or more alternative promoters, and a significant number of unassigned novel promoters. CONCLUSION: Our new algorithm can successfully predict the promoters from the genome wide profile of Pol-II bound regions. In addition, our algorithm performs significantly better than existing promoter prediction methods and can be applied for genome-wide predictions of Pol-II promoters

Uncertainty in Damage Assessment and Remaining Life Prediction of Engineering Materials Used In Petrochemical Industry

In this paper creep damage assessment of about 11 years’ service exposed HP-40 grade of steel used in hydrogen reformer of a petrochemical industry has been carried out in terms of a discontinuous Markov process. Experimentally determined conventional creep data under identical testing condition were used in the present investigation. Scatter and damage accumulation due to creep deformation were evaluated through microstructural assessment using light optical microscope and scanning electron microscope. Quantification of creep damage was made from replicated creep data in terms of two damage parameters A and A*. Statistical analysis of void area fraction has been carried out extensively for the both top and bottom portions of the reformer tube at 870 o C in the stress range of 52-68 MPa. In addition, the proposed probabilistic model has been compared with the Kachanav’s Continuum Damage Mechanics (CDM) model. Both the approaches displayed quantitative experimental support. A residual life of > 10 years is estimated at 870 degree C / operating stress. For 55 years’ service exposed Catalytic Cold Cracking (CCU) reactor vessel and Feed Processing Unit (FPU) distillation column materials of a petrochemical industry remnant life assessment studies were estimated by incorporating the uncertainty involved in calculation of LMP (Larson Miller Parameter) values and from extrapolation of stress vs. LMP plot. Variability of normalized creep damage for reactor and column materials is well approximated with the aid of Weibull distribution. As expected, it is observed that the distributions shift towards the higher range of damage with increase in service exposure time

Nonlinear partial differential equations and applications: Gene expression profiling of isogenic cells with different TP53 gene dosage reveals numerous genes that are affected by TP53 dosage and identifies CSPG2 as a direct target of p53

TP53 does not fully comply with the Knudson model [Knudson, A. G., Jr. (1971) Proc. Natl. Acad. Sci. USA 68, 820–823] in that a reduction of constitutional expression of p53 may be sufficient for tumor predisposition . This finding suggests a gene-dosage effect for p53 function. To determine whether TP53 gene dosage affects the transcriptional regulation of target genes, we performed oligonucleotide-array gene expression analysis by using human cells with wild-type p53 (p53 +/+), or with one (p53 +/−), or both (p53 −/−) TP53 alleles disrupted by homologous recombination. We identified 35 genes whose expression is significantly correlated to the dosage of TP53. These genes are involved in a variety of cellular processes including signal transduction, cell adhesion, and transcription regulation. Several of them are involved in neurogenesis and neural crest migration, developmental processes in which p53 is known to play a role. Motif search analysis revealed that of the genes highly expressed in p53 +/+ and +/− cells, several contain a putative p53 consensus binding site (bs), suggesting that they could be directly regulated by p53. Among those genes, we chose CSPG2 (which encodes versican) for further study because it contains a bona fide p53 bs in its first intron and its expression highly correlates with TP53 dosage. By using in vitro and in vivo assays, we showed CSPG2 to be directly transactivated by p53. In conclusion, we developed a strategy to demonstrate that many genes are affected by TP53 gene dosage for their expression. We report several candidate genes as potential downstream targets of p53 in nonstressed cells. Among them, CSPG2 is validated as being directly transactivated by p53. Our method provides a useful tool to elucidate additional mechanisms by which p53 exerts its functions

PlantTFDB: a comprehensive plant transcription factor database

Transcription factors (TFs) play key roles in controlling gene expression. Systematic identification and annotation of TFs, followed by construction of TF databases may serve as useful resources for studying the function and evolution of transcription factors. We developed a comprehensive plant transcription factor database PlantTFDB (http://planttfdb.cbi.pku.edu.cn), which contains 26 402 TFs predicted from 22 species, including five model organisms with available whole genome sequence and 17 plants with available EST sequences. To provide comprehensive information for those putative TFs, we made extensive annotation at both family and gene levels. A brief introduction and key references were presented for each family. Functional domain information and cross-references to various well-known public databases were available for each identified TF. In addition, we predicted putative orthologs of those TFs among the 22 species. PlantTFDB has a simple interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis

Sequence determinants in human polyadenylation site selection

BACKGROUND: Differential polyadenylation is a widespread mechanism in higher eukaryotes producing mRNAs with different 3' ends in different contexts. This involves several alternative polyadenylation sites in the 3' UTR, each with its specific strength. Here, we analyze the vicinity of human polyadenylation signals in search of patterns that would help discriminate strong and weak polyadenylation sites, or true sites from randomly occurring signals. RESULTS: We used human genomic sequences to retrieve the region downstream of polyadenylation signals, usually absent from cDNA or mRNA databases. Analyzing 4956 EST-validated polyadenylation sites and their -300/+300 nt flanking regions, we clearly visualized the upstream (USE) and downstream (DSE) sequence elements, both characterized by U-rich (not GU-rich) segments. The presence of a USE and a DSE is the main feature distinguishing true polyadenylation sites from randomly occurring A(A/U)UAAA hexamers. While USEs are indifferently associated with strong and weak poly(A) sites, DSEs are more conspicuous near strong poly(A) sites. We then used the region encompassing the hexamer and DSE as a training set for poly(A) site identification by the ERPIN program and achieved a prediction specificity of 69 to 85% for a sensitivity of 56%. CONCLUSION: The availability of complete genomes and large EST sequence databases now permit large-scale observation of polyadenylation sites. Both U-rich sequences flanking both sides of poly(A) signals contribute to the definition of "true" sites. However, the downstream U-rich sequences may also play an enhancing role. Based on this information, poly(A) site prediction accuracy was moderately but consistently improved compared to the best previously available algorithm

Pro- and Antiinflammatory Cytokine Signaling: Reciprocal Antagonism Regulates Interferon-gamma Production by Human Natural Killer Cells

SummaryActivated monocytes produce proinflammatory cytokines (monokines) such as interleukin (IL)-12, IL-15, and IL-18 for induction of interferon-γ (IFN-γ) by natural killer (NK) cells. NK cells provide the antiinflammatory cytokine transforming growth factor (TGF)-β, an autocrine/negative regulator of IFN-γ. The ability of one signaling pathway to prevail over the other is likely important in controlling IFN-γ for the purposes of infection and autoimmunity, but the molecular mechanism(s) of how this counterregulation occurs is unknown. Here we show that in isolated human NK cells, proinflammatory monokines antagonize antiinflammatory TGF-β signaling by downregulating the expression of the TGF-β type II receptor, and its signaling intermediates SMAD2 and SMAD3. In contrast, TGF-β utilizes SMAD2, SMAD3, and SMAD4 to suppress IFN-γ and T-BET, a positive regulator of IFN-γ. Indeed, activated NK cells from Smad3−/− mice produce more IFN-γ in vivo than NK cells from wild-type mice. Collectively, our data suggest that pro- and antiinflammatory cytokine signaling reciprocally antagonize each other in an effort to prevail in the regulation of NK cell IFN-γ production

Preliminary Numerical and Experimental Analysis of the Spallation Phenomenon

The spallation phenomenon was studied through numerical analysis using a coupled Lagrangian particle tracking code and a hypersonic aerothermodynamics computational fluid dynamics solver. The results show that carbon emission from spalled particles results in a significant modification of the gas composition of the post shock layer. Preliminary results from a test-campaign at the NASA Langley HYMETS facility are presented. Using an automated image processing of high-speed images, two-dimensional velocity vectors of the spalled particles were calculated. In a 30 second test at 100 W/cm2 of cold-wall heat-flux, more than 1300 particles were detected, with an average velocity of 102 m/s, and most frequent observed velocity of 60 m/s