Constrained Multi-Objective Aerofoil Design Using a Multi-Level Optimisation Strategy

A novel approach for the multi-objective design optimisation of aerofoil profiles is presented. The proposed method aims to exploit the relative strengths of global and local optimisation algorithms, whilst using surrogate models to limit the number of computationally expensive CFD simulations required. The local search stage utilises a re-parameterisation scheme that increases the flexibility of the geometry description by iteratively increasing the number of design variables, enabling superior designs to be generated with minimal user intervention. Capability of the algorithm is demonstrated via the conceptual design of aerofoil sections for use on a lightweight laminar flow business jet. The design case is formulated to account for take-off performance while reducing sensitivity to leading edge contamination. The algorithm successfully manipulates boundary layer transition location to provide a potential set of aerofoils that represent the trade-offs between drag at cruise and climb conditions in the presence of a challenging constraint set. Variations in the underlying flow physics between Pareto-optimal aerofoils are examined to aid understanding of the mechanisms that drive the trade-offs in objective functions.

Late Holocene sea-level fall and turn-off of reef flat carbonate production: Rethinking bucket fill and coral reef growth models

Relative sea-level rise has been a major factor driving the evolution of reef systems during the Holocene. Most models of reef evolution suggest that reefs preferentially grow vertically during rising sea level then laterally from windward to leeward, once the reef flat reaches sea level. Continuous lagoonal sedimentation ("bucket fill") and sand apron progradation eventually lead to reef systems with totally filled lagoons. Lagoonal infilling of One Tree Reef (southern Great Barrier Reef) through sand apron accretion was examined in the context of late Holocene relative sea-level change. This analysis was conducted using sedimentological and digital terrain data supported by 50 radiocarbon ages from fossil microatolls, buried patch reefs, foraminifera and shells in sediment cores, and recalibrated previously published radiocarbon ages. This data set challenges the conceptual model of geologically continuous sediment infill during the Holocene through sand apron accretion. Rapid sand apron accretion occurred between 6000 and 3000 calibrated yr before present B.P. (cal. yr B.P.); followed by only small amounts of sedimentation between 3000 cal. yr B.P. and present, with no significant sand apron accretion in the past 2 k.y. This hiatus in sediment infill coincides with a sea-level fall of similar to 1-1.3 m during the late Holocene (ca. 2000 cal. yr B.P.), which would have caused the turn-off of highly productive live coral growth on the reef flats currently dominated by less productive rubble and algal flats, resulting in a reduced sediment input to back-reef environments and the cessation in sand apron accretion. Given that relative sea-level variations of similar to 1 m were common throughout the Holocene, we suggest that this mode of sand apron development and carbonate production is applicable to most reef systems.

The Prenatal Distress Questionnaire:An investigation of factor structure in a high risk population

Background: The Prenatal Distress Questionnaire (PDQ) is a short measure designed to assess specific worries and concerns related to pregnancy. The aim of this study was to confirm the factor structure of the PDQ in a group of pregnant women with a small for gestational age infant (< 10th centile). Methods: The first PDQ assessment for each of 337 pregnant women participating in the Prospective Observational Trial to Optimise paediatric health (PORTO) study was analysed. All women enrolled in the study were identified as having a small for gestational age foetus (< 10th centile), thus representing an 'elevated risk' group. Data were analysed using confirmatory factor analysis (CFA). Three models of the PDQ were evaluated and compared in the current study: a theoretical uni-dimensional measurement model, a bi-dimensional model, and a three-factor model solution. Results: The three-factor model offered the best fit to the data while maintaining sound theoretical grounds(χ² (51df) = 128.52; CFI = 0.97; TLI = 0.96; RMSEA = 0.07). Factor 1 contained items reflecting concerns about birth and the baby, factor 2 concerns about physical symptoms and body image and factor 3 concerns about emotions and relationships. Conclusions: CFA confirmed that the three-factor model provided the best fit, with the items in each factor reflecting the findings of an earlier exploratory data analysis. © 2013 Society for Reproductive and Infant Psychology.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

HPV16 Down-Regulates the Insulin-Like Growth Factor Binding Protein 2 to Promote Epithelial Invasion in Organotypic Cultures

Cervical cancer is a multi-stage disease caused by human papillomaviruses (HPV) infection of cervical epithelial cells, but the mechanisms regulating disease progression are not clearly defined. Using 3-dimensional organotypic cultures, we demonstrate that HPV16 E6 and E7 proteins alter the secretome of primary human keratinocytes resulting in local epithelial invasion. Mechanistically, absence of the IGF-binding protein 2 (IGFBP2) caused increases in IGFI/II signalling and through crosstalk with KGF/FGFR2b/AKT, cell invasion. Repression of IGFBP2 is mediated by histone deacetylation at the IGFBP2 promoter and was reversed by treatment with histone deacetylase (HDAC) inhibitors. Our in vitro findings were confirmed in 50 invasive cancers and 79 cervical intra-epithelial neoplastic lesions caused by HPV16 infection, where IGFBP2 levels were reduced with increasing disease severity. In summary, the loss of IGFBP2 is associated with progression of premalignant disease, and sensitises cells to pro-invasive IGF signalling, and together with stromal derived factors promotes epithelial invasion.

On the diversity of superluminous supernovae: ejected mass as the dominant factor

We assemble a sample of 24 hydrogen-poor superluminous supernovae(SLSNe). Parameterizing the light-curve shape through rise and declinetime-scales shows that the two are highly correlated. Magnetar-poweredmodels can reproduce the correlation, with the diversity in rise anddecline rates driven by the diffusion time-scale. Circumstellarinteraction models can exhibit a similar rise-decline relation, but onlyfor a narrow range of densities, which may be problematic for thesemodels. We find that SLSNe are approximately 3.5 mag brighter and havelight curves three times broader than SNe Ibc, but that the intrinsicshapes are similar. There are a number of SLSNe with particularly broadlight curves, possibly indicating two progenitor channels, butstatistical tests do not cleanly separate two populations. The generalspectral evolution is also presented. Velocities measured from Fe II aresimilar for SLSNe and SNe Ibc, suggesting that diffusion timedifferences are dominated by mass or opacity. Flat velocity evolution inmost SLSNe suggests a dense shell of ejecta. If opacities in SLSNe aresimilar to other SNe Ibc, the average ejected mass is higher by a factor2-3. Assuming κ = 0.1 cm2 g-1, we estimate amean (median) SLSN ejecta mass of 10 M⊙ (6M⊙), with a range of 3-30 M⊙. Doubling theassumed opacity brings the masses closer to normal SNe Ibc, but with ahigh-mass tail. The most probable mechanism for generating SLSNe seemsto be the core collapse of a very massive hydrogen-poor star, forming amillisecond magnetar.

Multi-agents modelling of EV purchase willingness based on questionnaires

Traditional experimental economics methods often consume enormous resources of qualified human participants, and the inconsistence of a participant’s decisions among repeated trials prevents investigation from sensitivity analyses. The problem can be solved if computer agents are capable of generating similar behaviors as the given participants in experiments. An experimental economics based analysis method is presented to extract deep information from questionnaire data and emulate any number of participants. Taking the customers’ willingness to purchase electric vehicles (EVs) as an example, multi-layer correlation information is extracted from a limited number of questionnaires. Multi-agents mimicking the inquired potential customers are modelled through matching the probabilistic distributions of their willingness embedded in the questionnaires. The authenticity of both the model and the algorithm is validated by comparing the agent-based Monte Carlo simulation results with the questionnaire-based deduction results. With the aid of agent models, the effects of minority agents with specific preferences on the results are also discussed.

Activated protein C inhibits tumor necrosis factor and macrophage migration inhibitory factor production in monocytes

The precise regulatory mechanisms of amplification and downregulation of the pro- and anti-inflammatory cytokines in the inflammatory response have not been fully delineated. Although activated protein C (APC) and its precursor protein C (PC) have recently been reported to be promising therapeutic agents in the management of meningococcal sepsis, direct evidence for the anti-inflammatory effect remains scarce. We report that APC inhibits in vitro the release of tumor necrosis factor (TNF) and macrophage migration inhibitory factor (MIF), two known cytokine mediators of bacterial septic shock, from lipopolysaccharide (LPS)-stimulated human monocytes. The THP-1 monocytic cell line, when stimulated with LPS and concomitant APC, exhibited a marked reduction in the release of TNF and MIF protein in a concentration-dependent manner compared to cells stimulated with LPS alone. This effect was observed only when incubations were performed in serum-free media, but not in the presence of 1-10% serum. Serum-mediated inhibition could only be overcome by increasing APC concentrations to far beyond physiological levels, suggesting the presence of endogenous serum-derived APC inhibitors. Inhibition of MIF release by APC was found to be independent of TNF, as stimulation of MIF release by LPS was unaltered in the presence of anti-TNF antibodies. Our data confirm that the suggested anti-inflammatory properties of APC are due to direct inhibition of the release of the pro-inflammatory monokine TNF, and imply that the anti-inflammatory action of APC is also mediated via inhibition of MIF release.

Activated protein C inhibits lipopolysaccharide-induced nuclear translocation of nuclear factor kappaB (NF-kappaB) and tumour necrosis factor alpha (TNF-alpha) production in the THP-1 monocytic cell line

Activated protein C (APC) protects against sepsis in animal models and inhibits the lipopolysacharide (LPS)-induced elaboration of proinflammatory cytokines from monocytes. The molecular mechanism responsible for this property is unknown. We assessed the effect of APC on LPS-induced tumour necrosis factor alpha (TNF-alpha) production and on the activation of the central proinflammatory transcription factor nuclear factor-kappaB (NF-kappaB) in a THP-1 cell line. Cells were preincubated with varying concentrations of APC (200 microg/ml, 100 microg/ml and 20 microg/ml) before addition of LPS (100 ng/ml and 10 microg/ml). APC inhibited LPS-induced production of TNF-alpha both in the presence and absence of fetal calf serum (FCS), although the effect was less marked with 10% FCS. APC also inhibited LPS-induced activation of NF-kappaB, with APC (200 microg/ml) abolishing the effect of LPS (100 ng/ml). The ability of APC to inhibit LPS-induced translocation of NF-kappaB is likely to be a significant event given the critical role of the latter in the host inflammatory response.

The dual EGFR/HER2 inhibitor lapatinib synergistically enhances the antitumor activity of the histone deacetylase inhibitor panobinostat in colorectal cancer models

As key molecules that drive progression and chemoresistance in gastrointestinal cancers, epidermal growth factor receptor (EGFR) and HER2 have become efficacious drug targets in this setting. Lapatinib is an EGFR/HER2 kinase inhibitor suppressing signaling through the RAS/RAF/MEK (MAP/ERK kinase)/MAPK (mitogen-activated protein kinase) and PI3K (phosphoinositide 3-kinase)/AKT pathways. Histone deacetylase inhibitors (HDACi) are a novel class of agents that induce cell cycle arrest and apoptosis following the acetylation of histone and nonhistone proteins modulating gene expression and disrupting HSP90 function inducing the degradation of EGFR-pathway client proteins. This study sought to evaluate the therapeutic potential of combining lapatinib with the HDACi panobinostat in colorectal cancer (CRC) cell lines with varying EGFR/HER2 expression and KRAS/BRAF/PIK3CA mutations. Lapatinib and panobinostat exerted concentration-dependent antiproliferative effects in vitro (panobinostat range 7.2-30 nmol/L; lapatinib range 7.6-25.8 μmol/L). Combined lapatinib and panobinostat treatment interacted synergistically to inhibit the proliferation and colony formation in all CRC cell lines tested. Combination treatment resulted in rapid induction of apoptosis that coincided with increased DNA double-strand breaks, caspase-8 activation, and PARP cleavage. This was paralleled by decreased signaling through both the PI3K and MAPK pathways and increased downregulation of transcriptional targets including NF-κB1, IRAK1, and CCND1. Panobinostat treatment induced downregulation of EGFR, HER2, and HER3 mRNA and protein through transcriptional and posttranslational mechanisms. In the LoVo KRAS mutant CRC xenograft model, the combination showed greater antitumor activity than either agent alone, with no apparent increase in toxicity. Our results offer preclinical rationale warranting further clinical investigation combining HDACi with EGFR and HER2-targeted therapies for CRC treatment.

5.9-keV Mn K-shell X-ray luminosity from the decay of 55Fe in Type Ia supernova models

We show that the X-ray line flux of the Mn Kα line at 5.9 keV from the decay of 55Fe is a promising diagnostic to distinguish between Type Ia supernova (SN Ia) explosion models. Using radiation transport calculations, we compute the line flux for two three-dimensional explosion models: a near-Chandrasekhar mass delayed detonation and a violent merger of two (1.1 and 0.9 M⊙) white dwarfs. Both models are based on solar metallicity zero-age main-sequence progenitors. Due to explosive nuclear burning at higher density, the delayed-detonation model synthesizes ˜3.5 times more radioactive 55Fe than the merger model. As a result, we find that the peak Mn Kα line flux of the delayed-detonation model exceeds that of the merger model by a factor of ˜4.5. Since in both models the 5.9-keV X-ray flux peaks five to six years after the explosion, a single measurement of the X-ray line emission at this time can place a constraint on the explosion physics that is complementary to those derived from earlier phase optical spectra or light curves. We perform detector simulations of current and future X-ray telescopes to investigate the possibilities of detecting the X-ray line at 5.9 keV. Of the currently existing telescopes, XMM-Newton/pn is the best instrument for close (≲1-2 Mpc), non-background limited SNe Ia because of its large effective area. Due to its low instrumental background, Chandra/ACIS is currently the best choice for SNe Ia at distances above ˜2 Mpc. For the delayed-detonation scenario, a line detection is feasible with Chandra up to ˜3 Mpc for an exposure time of 106 s. We find that it should be possible with currently existing X-ray instruments (with exposure times ≲5 × 105 s) to detect both of our models at sufficiently high S/N to distinguish between them for hypothetical events within the Local Group. The prospects for detection will be better with future missions. For example, the proposed Athena/X-IFU instrument could detect our delayed-detonation model out to a distance of ˜5 Mpc. This would make it possible to study future events occurring during its operational life at distances comparable to those of the recent supernovae SN 2011fe (˜6.4 Mpc) and SN 2014J (˜3.5 Mpc).

Using particle dispersal models to assist in the conservation and recovery of the overexploited native oyster (Ostrea edulis) in an enclosed sea lough

Oyster populations around the world have seen catastrophic decline which has been largely attributed to overexploitation, disease and pollution. While considerable effort and resources have been implemented into restoring these important environmental engineers, the success of oyster populations is often limited by poor understanding of site-specific dispersal patterns of propagules. Water-borne transport is a key factor controlling or regulating the dispersal of the larval stage of benthic marine invertebrates which have limited mobility. The distribution of the native oyster Ostrea edulis in Strangford Lough, Northern Ireland, together with their densities and population structure at subtidal and intertidal sites has been documented at irregular intervals between 1997 and 2013. This paper revisits this historical data and considers whether different prevailing environmental conditions can be used to explain the distribution, densities and population structure of O. edulis in Strangford Lough. The approach adopted involved comparing predictive 2D hydrodynamic models coupled with particle tracking to simulate the dispersal of oyster larvae with historical and recent field records of the distribution of both subtidal and intertidal, populations since 1995. Results from the models support the hypothesis that commercial stocks of O. edulis introduced into Strangford Lough in the 1990s resulted in the re-establishment of wild populations of oysters in the Northern Basin which in turn provided a potential source of propagules for subtidal populations. These results highlight that strategic site selection (while inadvertent in the case of the introduced population in 1995) for the re-introduction of important shellfish species can significantly accelerate their recovery and restoration.

Multi-wavelength observations of Proxima Centauri

Aims: We report simultaneous observations of the nearby flare star Proxima Centauri with VLT/UVES and XMM-Newton over three nights in March 2009. Our optical and X-ray observations cover the star's quiescent state, as well as its flaring activity and allow us to probe the stellar atmospheric conditions from the photosphere into the chromosphere, and then the corona during its different activity stages. Methods: Using the X-ray data, we investigate variations in coronal densities and abundances and infer loop properties for an intermediate-sized flare. The optical data are used to investigate the magnetic field and its possible variability, to construct an emission line list for the chromosphere, and use certain emission lines to construct physical models of Proxima Centauri's chromosphere. Results: We report the discovery of a weak optical forbidden Fe xiii line at 3388 Å during the more active states of Proxima Centauri. For the intermediate flare, we find two secondary flare events that may originate in neighbouring loops, and discuss the line asymmetries observed during this flare in H i, He i, and Ca ii lines. The high time-resolution in the Hα line highlights strong temporal variations in the observed line asymmetries, which re-appear during a secondary flare event. We also present theoretical modelling with the stellar atmosphere code PHOENIX to construct flaring chromospheric models. Based on observations collected at the European Southern Observatory, Paranal, Chile, 082.D-0953A and on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member states and NASA.Full Table 6 is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/534/A133

Computing probable maximum loss in catastrophe reinsurance portfolios on multi-core and many-core architectures

In the reinsurance market, the risks natural catastrophes pose to portfolios of properties must be quantified, so that they can be priced, and insurance offered. The analysis of such risks at a portfolio level requires a simulation of up to 800 000 trials with an average of 1000 catastrophic events per trial. This is sufficient to capture risk for a global multi-peril reinsurance portfolio covering a range of perils including earthquake, hurricane, tornado, hail, severe thunderstorm, wind storm, storm surge and riverine flooding, and wildfire. Such simulations are both computation and data intensive, making the application of high-performance computing techniques desirable.

In this paper, we explore the design and implementation of portfolio risk analysis on both multi-core and many-core computing platforms. Given a portfolio of property catastrophe insurance treaties, key risk measures, such as probable maximum loss, are computed by taking both primary and secondary uncertainties into account. Primary uncertainty is associated with whether or not an event occurs in a simulated year, while secondary uncertainty captures the uncertainty in the level of loss due to the use of simplified physical models and limitations in the available data. A combination of fast lookup structures, multi-threading and careful hand tuning of numerical operations is required to achieve good performance. Experimental results are reported for multi-core processors and systems using NVIDIA graphics processing unit and Intel Phi many-core accelerators.

Integration of design of experiment, surface response methodology and multi-layer validation to predict the effect of blanching on colour of tomato juice

Response surface methodology was used to develop models to predict the effect of tomato cultivar, juice pH, blanching temperature and time on colour change of tomato juice after blanching. The juice from three tomato cultivars with adjusted pH levels ranging from 3.9 to 4.6 were blanched at temperatures from 60-100 °C for 1-5 min using the central composite design (CCD). The colour change was assessed by calculating the redness (a/b) and total colour change (∆E) after measuring the Hunter L, a and b values. Developed models for both redness and ∆E were significant (p<0.0001) with satisfactory coefficient of determination (R2 = 0.99 and 0.97) and low coefficient of variation (CV% = 1.89 and 7.23), respectively. Multilevel validation that was implemented revealed that the variation between the predicted and experimental values obtained for redness and ∆E were within the acceptable error range of 7.3 and 22.4%, respectively