Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Observational Constraints on the Catastrophic Disruption Rate of Small Main Belt Asteroids

We have calculated 90% confidence limits on the steady-state rate of catastrophic disruptions of main belt asteroids in terms of the absolute magnitude at which one catastrophic disruption occurs per year  as a function of the post-disruption increase in brightness (Δm) and subsequent brightness decay rate (τ  ). The confidence limits were calculated using the brightest unknown main belt asteroid (V=18.5) detected with the Pan-STARRS1 (Pan-STARRS1) telescope. We measured the Pan-STARRS1’s catastrophic disruption detection efficiency over a 453-day interval using the Pan-STARRS moving object processing system (MOPS) and a simple model for the catastrophic disruption event’s photometric behavior in a small aperture centered on the catastrophic disruption event. We then calculated the  contours in the ranges from  and  encompassing measured values from known cratering and disruption events and our model’s predictions. Our simplistic catastrophic disruption model suggests that  and  which would imply that H_0≳28—strongly inconsistent withH_{0,B2005=23.26±0.02} predicted by Bottke et al. (Bottke, W.F., Durda, D.D., Nesvorný, D., Jedicke, R., Morbidelli, A., Vokrouhlický, D., Levison, H.F. [2005]. Icarus, 179, 63–94.) using purely collisional models. However, if we assume that H_0=H0,B2005 our results constrain , inconsistent with our simplistic impact-generated catastrophic disruption model. We postulate that the solution to the discrepancy is that >99% of main belt catastrophic disruptions in the size range to which this study was sensitive (∼100 m) are not impact-generated, but are instead due to fainter rotational breakups, of which the recent discoveries of disrupted asteroids P/2013 P5 and P/2013 R3 are probable examples. We estimate that current and upcoming asteroid surveys may discover up to 10 catastrophic disruptions/year brighter than V=18.5.

Stress in parents of children born very preterm is predicted by child externalising behaviour and parent coping at age 7 years

Objective: To examine factors which predict parenting stress in a longitudinal cohort of children born very preterm seen at age seven years.
Methods: We recruited 100 very preterm (< 32 weeks GA) child-parent dyads and a control group of 50 term-born dyads born between 2001 and 2004 with follow-up at seven years. Parents completed the Parenting Stress Index, Ways of Coping Questionnaire, Child Behavior Check List, Beck Depression Inventory and the State Trait Anxiety Inventory questionnaires. Child IQ was assessed using the Wechsler Intelligence Scale-IV.
Results: After controlling for maternal education, parents of preterm children (95% CI, 111.1 to 121.4) scored higher (p = .027) on the Parenting Stress Index than term born controls (95% CI, 97.8 to 113.2). Regression analyses showed that child externalising behaviour, sex and parent escape/avoidance coping style, predicted higher parenting stress in the preterm group. Parents of preterm girls expressed higher levels of stress than those of boys. 
Conclusions: Maladaptive coping strategies contribute to greater stress in parents of very preterm children. Our findings suggest that these parents need support for many years after birth of a very preterm infant.

Mechanisms of reduced susceptibility and genotypic prediction of antibiotic resistance in Prevotella isolated from cystic fibrosis (CF) and non-CF patients

OBJECTIVES: To investigate mechanisms of reduced susceptibility to commonly used antibiotics in Prevotella cultured from patients with cystic fibrosis (CF), patients with invasive infection and healthy control subjects and to determine whether genotype can be used to predict phenotypic resistance.

METHODS: The susceptibility of 157 Prevotella isolates to seven antibiotics was compared, with detection of resistance genes (cfxA-type gene, ermF and tetQ), mutations within the CfxA-type β-lactamase and expression of efflux pumps.

RESULTS: Prevotella isolates positive for a cfxA-type gene had higher MICs of amoxicillin and ceftazidime compared with isolates negative for this gene (P < 0.001). A mutation within the CfxA-type β-lactamase (Y239D) was associated with ceftazidime resistance (P = 0.011). The UK CF isolates were 5.3-fold, 2.7-fold and 5.7-fold more likely to harbour ermF compared with the US CF, UK invasive and UK healthy control isolates, respectively. Higher concentrations of azithromycin (P < 0.001) and clindamycin (P < 0.001) were also required to inhibit the growth of the ermF-positive isolates compared with ermF-negative isolates. Furthermore, tetQ-positive Prevotella isolates had higher MICs of tetracycline (P = 0.001) and doxycycline (P < 0.001) compared with tetQ-negative isolates. Prevotella spp. were also shown, for the first time, to express resistance nodulation division (RND)-type efflux pumps.

CONCLUSIONS: This study has demonstrated that Prevotella isolated from various sources harbour a common pool of resistance genes and possess RND-type efflux pumps, which may contribute to tetracycline resistance. The findings indicate that antibiotic resistance is common in Prevotella spp., but the genotypic traits investigated do not reflect phenotypic antibiotic resistance in every instance.

Expertly validated models and phylogenetically-controlled analysis suggests responses to climate change are related to species traits in the Order Lagomorpha

Climate change during the last five decades has impacted significantly on natural ecosystems and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species’ bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical and habitat variables for all 87 lagomorph species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current models and only those deemed ‘modellable’ within our framework were projected under future climate scenarios (58 species). Phylogenetically-controlled regressions were used to test whether species traits correlated with predicted responses to climate change. Climate change is likely to impact more than two-thirds of lagomorph species, with leporids (rabbits, hares and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov’s Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management. We strongly advocate studies minimising data gaps in our knowledge of the Order, specifically collecting more specimens for biodiversity archives and targeting data deficient geographic regions.

PREDICTING THE SPATIAL-DISTRIBUTION OF CLIMATE - TEMPERATURE IN GREAT-BRITAIN

1. The prediction and mapping of climate in areas between climate stations is of increasing importance in ecology.

2. Four categories of model, simple interpolation, thin plate splines, multiple linear regression and mixed spline-regression, were tested for their ability to predict the spatial distribution of temperature on the British mainland. The models were tested by external cross-verification.

3. The British distribution of mean daily temperature was predicted with the greatest accuracy by using a mixed model: a thin plate spline fitted to the surface of the country, after correction of the data by a selection from 16 independent topographical variables (such as altitude, distance from the sea, slope and topographic roughness), chosen by multiple regression from a digital terrain model (DTM) of the country.

4. The next most accurate method was a pure multiple regression model using the DTM. Both regression and thin plate spline models based on a few variables (latitude, longitude and altitude) only were comparatively unsatisfactory, but some rather simple methods of surface interpolation (such as bilinear interpolation after correction to sea level) gave moderately satisfactory results. Differences between the methods seemed to be dependent largely on their ability to model the effect of the sea on land temperatures.

5. Prediction of temperature by the best methods was greater than 95% accurate in all months of the year, as shown by the correlation between the predicted and actual values. The predicted temperatures were calculated at real altitudes, not subject to sea-level correction.

6. A minimum of just over 30 temperature recording stations would generate a satisfactory surface, provided the stations were well spaced.

7. Maps of mean daily temperature, using the best overall methods are provided; further important variables, such as continentality and length of growing season, were also mapped. Many of these are believed to be the first detailed representations at real altitude.

8. The interpolated monthly temperature surfaces are available on disk.

The 'Ordinariness of the EU's Foreign Policy Power: The Use of WTO Litigation as a Means to Export EU Norms, Values and Interests

The EU has historically been portrayed as a distinctive international actor both in terms of the norms and values it exports in context of its international relations and the manner in which it seeks to influence others. However, such claims to the EU’s distinctiveness are increasingly being questioned. This article joins this chorus of voices arguing the non-distinctiveness of the EU’s foreign policy power by focusing on a specific feature of the EU’s external trade policy, the role of World Trade Organization (WTO) dispute settlement in the EU’s attempts to promote its interests, values and norms.

Bioinformatic evaluation of transcriptional regulation of WNT pathway genes with reference to diabetic nephropathy

Objective: Diabetic nephropathy (DN) is a microvascular complication of diabetes. Members of the WNT/ β-catenin pathways have been implicated in interstitial fibrosis and glomerular sclerosis, characteristic hallmarks of DN. These processes are controlled, in part, by transcription factors (TFs), proteins which bind to gene promoter regions attenuating their regulation. We sought to identify predicted cis-acting transcription factor binding sites (TFBS) over-represented within the promoter regions of WNT pathway members compared to genes across the genome.Methods: We assessed the frequency of 62 TFBS motifs from the JASPAR databases on 65 WNT pathway genes. P-values were estimated on the hypergeometric distribution for each TF. Gene expression profiles of enriched motifs were examined from DN-related datasets to assess clinical significance.Results: TFBS motifs transcription factor AP-2 alpha (TFAP2A), myeloid zinc finger 1 (MZF1), and specificity protein 1 (SP1) were significantly enriched within WNT pathway genes (P-values<6.83x10-29, 1.34x10-11 and 3.01x10-6 respectively). MZF1 gene expression was significantly increased in DN in a whole kidney dataset (fold change = 1.16; 16% increase; P = 0.03). TFAP2A gene expression was decreased in an independent dataset (fold change = -1.02; P = 0.03). SP1 was not differentially expressed in any datasets examined.Conclusions: Three TFBS profiles are significantly enriched within the WNT pathway genes examined highlighting the use of in silico analyses for identifying key regulators of this pathway. Modification of TF binding to gene promoter regions involved in DN pathology may limit progression, making refinement of targeted therapeutic strategies possible through clearer delineation of their role.

Characterization of nontypable Haemophilus influenzae isolates recovered from adult patients with underlying chronic lung disease reveals genotypic and phenotypic traits associated with persistent infection

Nontypable Haemophilus influenzae (NTHi) has emerged as an important opportunistic pathogen causing infection in adults suffering obstructive lung diseases. Existing evidence associates chronic infection by NTHi to the progression of the chronic respiratory disease, but specific features of NTHi associated with persistence have not been comprehensively addressed. To provide clues about adaptive strategies adopted by NTHi during persistent infection, we compared sequential persistent isolates with newly acquired isolates in sputa from six patients with chronic obstructive lung disease. Pulse field gel electrophoresis (PFGE) identified three patients with consecutive persistent strains and three with new strains. Phenotypic characterisation included infection of respiratory epithelial cells, bacterial self-aggregation, biofilm formation and resistance to antimicrobial peptides (AMP). Persistent isolates differed from new strains in showing low epithelial adhesion and inability to form biofilms when grown under continuous-flow culture conditions in microfermenters. Self-aggregation clustered the strains by patient, not by persistence. Increasing resistance to AMPs was observed for each series of persistent isolates; this was not associated with lipooligosaccharide decoration with phosphorylcholine or with lipid A acylation. Variation was further analyzed for the series of three persistent isolates recovered from patient 1. These isolates displayed comparable growth rate, natural transformation frequency and murine pulmonary infection. Genome sequencing of these three isolates revealed sequential acquisition of single-nucleotide variants in the AMP permease sapC, the heme acquisition systems hgpB, hgpC, hup and hxuC, the 3-deoxy-D-manno-octulosonic acid kinase kdkA, the long-chain fatty acid transporter ompP1, and the phosphoribosylamine glycine ligase purD. Collectively, we frame a range of pathogenic traits and a repertoire of genetic variants in the context of persistent infection by NTHi.