The Validation of a Two-Dimensional Transient Catalyst Model for Direct Injection Two-Stroke Applications

This paper describes the detailed validation of a computer model designed to simulate the transient light-off in a two-stroke oxidation catalyst. A plug flow reactor is employed to provide measurements of temperature and gas concentration at various radial and axial locations inside the catalyst. These measurements are recorded at discrete intervals during a transient light-off in which the inlet temperature is increased from ambient to 300oC at rates of up to 6oC/sec. The catalyst formulation used in the flow reactor, and its associated test procedures, are then simulated by the computer and a comparison made between experimental readings and model predictions. The design of the computer model to which this validation exercise relates is described in detail in a separate technical paper. The first section of the paper investigates the warm-up characteristics of the substrate and examines the validity of the heat transfer predictions between the wall and the gas in the absence of chemical reactions. The predictions from a typical single-component CO transient light-off test are discussed in the second section and are compared with experimental data. In particular the effect of the temperature ramp on the light-off curve and reaction zone development is examined. An analysis of the C3H6 conversion is given in the third section while the final section examines the accuracy of the light-off curves which are produced when both CO and C3H6 are present in the feed gas. The analysis shows that the heat and mass transfer calculations provided reliable predictions of the warm-up behaviour and post light-off gas concentration profiles. The self-inhibition and cross-inhibition terms in the global rate expressions were also found to be reasonably reliable although the surface reaction rates required calibration with experimental data.

Isotopic composition of tropospheric and soil N2O from successive depths of agricultural plots with contrasting crops and nitrogen amendments

Agricultural soils are the dominant contributor to increases in atmospheric nitrous oxide (N2O). Few studies have investigated the natural N and O isotopic composition of soil N2O. We collected soil gas samples using horizontal sampling tubes installed at successive depths under five contrasting agricultural crops (e.g., unamended alfalfa, fertilized cereal), and tropospheric air samples. Mean d 15N and d 18O values of soil N2O ranged from -28.0 to +8.9‰, and from +29.0 to +53.6‰. The mean d 15N and d 18O values of tropospheric N2O were +4.6 ± 0.7‰ and +48.3 ± 0.2‰, respectively. In general, d values were lowest at depth, they were negatively correlated to soil [N2O], and d 15N was positively correlated to d 18O for every treatment on all sampling dates. N2O from the different agricultural treatments had distinct d 15N and d 18O values that varied among sampling dates. Fertilized treatments had soil N2O with low d values, but the unamended alfalfa yielded N2O with the lowest d values. Diffusion was not the predominant process controlling N2O concentration profiles. Based on isotopic and concentration data, it appears that soil N2O was consumed, as it moved from deeper to shallower soil layers. To better assess the main process(es) controlling N2O within a soil profile, we propose a conceptual model that integrates data on net N2O production or consumption and isotopic data. The direct local impact of agricultural N2O on the isotopic composition of tropospheric N2O was recorded by a shift toward lower d values of locally measured tropospheric N2O on a day with very high soil N2O emissions.

Application of NMR based metabolomics for mapping metabolite variation in European wheat

In this study, we report on the use of NMR-based metabolomics to access variation in low molecular weight polar metabolites between the European wheat cultivars Apache, Charger, Claire and Orvantis. Previous unassigned resonances in the published NMR spectra of wheat extracts were identified using C NMR and two dimensional proton-carbon NMR. These included a peak for trans-aconitate (d3.43) and resonances corresponding to fructose in the crowded carbohydrate region of the spectra. Large metabolite differences were observed between two different growth stages, namely the coleoptile and two week old leaf tissue extracts which were consistent across cultivars. Two week old leaf tissue extracts had higher abundances of glutamine, glutamate, sucrose and trans-aconitate and less glucose and fructose than were observed in the coleoptile extracts. Across both growth stages the cultivars Apache and Charger showed the greatest differences in metabolite profiles. Charger had higher abundances of betaine, the single most influential metabolite in the principal component analysis, in addition to fructose and sucrose. However, Charger had lower levels of aspartate, choline and glucose than Apache. These findings demonstrate the potential for a biochemical mapping approach using NMR, across European wheat germplasm, for metabolites of known importance to functional characteristics. © Springer Science+Business Media, LLC 2009.

Application of connectivity mapping in predictive toxicology based on gene-expression similarity.

Connectivity mapping is the process of establishing connections between different biological states using gene-expression profiles or signatures. There are a number of applications but in toxicology the most pertinent is for understanding mechanisms of toxicity. In its essence the process involves comparing a query gene signature generated as a result of exposure of a biological system to a chemical to those in a database that have been previously derived. In the ideal situation the query gene-expression signature is characteristic of the event and will be matched to similar events in the database. Key criteria are therefore the means of choosing the signature to be matched and the means by which the match is made. In this article we explore these concepts with examples applicable to toxicology.

The Hekla 1947 tephra in the North of Ireland: regional distribution, concentration and geochemistry.

A cryptotephra layer from the eruption of Hekla in 1947 has recently been discovered in Irish peatlands. This tephra layer represents the most recent deposition of volcanic ash in the UK prior to the eruption of Eyjafjallajökull in 2010. Here we examine the concentration and geochemistry of the Hekla 1947 tephra in 14 peat profiles from across Northern Ireland. Electron probe microanalysis of individual tephra shards (n?=?91) reveals that the tephra is of dacitic–andesitic geochemistry and is highly similar to the Hekla 1510 tephra, although spheroidal carbonaceous particle profiles can be used for successful discrimination of the two layers. The highest concentrations of Hekla 1947 are found in western sites, probably reflecting the pathway of the ash fall event due to the prevailing wind direction. Comparable tephra concentrations from two cores (1?km apart) from a single bog and from nearby sites may suggest that tephra shard concentrations in peat profiles reflect ash fallout densities across a specific region, rather than site-specific factors associated with peatlands. This paper firmly establishes Hekla 1947 as a useful chronostratigraphic marker for the twentieth century, although within a restricted zone.

Mapping patterns of multiple deprivation using self-organising maps: An application to EU-SILC data for Ireland

The development of conceptual frameworks for the analysis of social exclusion has somewhat out-stripped related methodological developments. This paper seeks to contribute to filling this gap through the application of self-organising maps (SOMs) to the analysis of a detailed set of material deprivation indicators relating to the Irish case. The SOM approach allows us to offer a differentiated and interpretable picture of the structure of multiple deprivation in contemporary Ireland. Employing this approach, we identify 16 clusters characterised by distinct profiles across 42 deprivation indicators. Exploratory analyses demonstrate that, controlling for equivalised household income, SOM cluster membership adds substantially to our ability to predict subjective economic stress. Moreover, in comparison with an analogous latent class approach, the SOM analysis offers considerable additional discriminatory power in relation to individuals' experience of their economic circumstances. The results suggest that the SOM approach could prove a valuable addition to a 'methodological platform' for analysing the shape and form of social exclusion. (c) 2009 Elsevier Inc. All rights reserved.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.

Nanoscale mapping of oxygen vacancy kinetics in nanocrystalline Samarium doped ceria thin films

The position-dependent oxygen vacancy dynamics induced by a biased scanning probe microscopy tip in Samarium doped ceria thin films grown on MgO (100) substrates is investigated. The granularity of the samples gives rise to spatially dependent local electrochemical activity, as explored by electrochemical strain microscopy. The kinetics of the oxygen vacancy relaxation process is investigated separately for grain boundaries and grains. Higher oxygen vacancy concentration variation and slower diffusion are observed in the grain boundary regions as compared to the grains.

Genetic mapping of the rice ionome in leaves and grain:Identification of QTLs for 17 elements including arsenic, cadmium, iron and selenium

Research into the composition of cereal grains is motivated by increased interest in food quality. Here multi-element analysis is conducted on leaves and grain of the Bala x Azucena rice mapping population grown in the field. Quantitative trait loci (QTLs) for the concentration of 17 elements were detected, revealing 36 QTLs for leaves and 41 for grains. Epistasis was detected for most elements. There was very little correlation between leaf and grain element concentrations. For selenium, lead, phosphorus and magnesium QTLs were detected in the same location for both tissues. In general, there were no major QTL clusters, suggesting separate regulation of each element. QTLs for grain iron, zinc, molybdenum and selenium are potential targets for marker assisted selection to improve seed nutritional quality. An epistatic interaction for grain arsenic also looks promising to decrease the concentration of this carcinogenic element. © Springer Science+Business Media B.V. 2009.

A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping

Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.