4,335 research outputs found
Actinometry of Hydrogen Plasmas
Optical emission spectroscopy (OES) can be used to map the electron energy distribution of hydrogen plasmas. Using actinometry, a type of OES where trace amounts of noble gases are introduced, the effect of discharge power on the electron temperature of hydrogen plasmas was explored. This was done using argon and krypton as actinometers for low pressure hydrogen plasmas. It was determined that the electron temperature decreased with respect to power supplied to the discharge
Approximation of Bayesian inverse problems for PDEs
Inverse problems are often ill posed, with solutions that depend sensitively on data. In any numerical approach to the solution of such problems, regularization of some form is needed to counteract the resulting instability. This paper is based on an approach to regularization, employing a Bayesian formulation of the problem, which leads to a notion of well posedness for inverse problems, at the level of probability measures. The stability which results from this well posedness may be used as the basis for quantifying the approximation, in finite dimensional spaces, of inverse problems for functions. This paper contains a theory which utilizes this stability property to estimate the distance between the true and approximate posterior distributions, in the Hellinger metric, in terms of error estimates for approximation of the underlying forward problem. This is potentially useful as it allows for the transfer of estimates from the numerical analysis of forward problems into estimates for the solution of the related inverse problem. It is noteworthy that, when the prior is a Gaussian random field model, controlling differences in the Hellinger metric leads to control on the differences between expected values of polynomially bounded functions and operators, including the mean and covariance operator. The ideas are applied to some non-Gaussian inverse problems where the goal is determination of the initial condition for the Stokes or Navier–Stokes equation from Lagrangian and Eulerian observations, respectively
Variational data assimilation using targetted random walks
The variational approach to data assimilation is a widely used methodology for both online prediction and for reanalysis (offline hindcasting). In either of these scenarios it can be important to assess uncertainties in the assimilated state. Ideally it would be desirable to have complete information concerning the Bayesian posterior distribution for unknown state, given data. The purpose of this paper is to show that complete computational probing of this posterior distribution is now within reach in the offline situation. In this paper we will introduce an MCMC method which enables us to directly sample from the Bayesian\ud
posterior distribution on the unknown functions of interest, given observations. Since we are aware that these\ud
methods are currently too computationally expensive to consider using in an online filtering scenario, we frame this in the context of offline reanalysis. Using a simple random walk-type MCMC method, we are able to characterize the posterior distribution using only evaluations of the forward model of the problem, and of the model and data mismatch. No adjoint model is required for the method we use; however more sophisticated MCMC methods are available\ud
which do exploit derivative information. For simplicity of exposition we consider the problem of assimilating data, either Eulerian or Lagrangian, into a low Reynolds number (Stokes flow) scenario in a two dimensional periodic geometry. We will show that in many cases it is possible to recover the initial condition and model error (which we describe as unknown forcing to the model) from data, and that with increasing amounts of informative data, the uncertainty in our estimations reduces
Improved surface quality of anisotropically etched silicon {111} planes for mm-scale integrated optics
We have studied the surface quality of millimeter-scale optical mirrors
produced by etching CZ and FZ silicon wafers in potassium hydroxide to expose
the planes. We find that the FZ surfaces have four times lower noise
power at spatial frequencies up to . We conclude that mirrors
made using FZ wafers have higher optical quality
MCMC methods for functions modifying old algorithms to make\ud them faster
Many problems arising in applications result in the need\ud
to probe a probability distribution for functions. Examples include Bayesian nonparametric statistics and conditioned diffusion processes. Standard MCMC algorithms typically become arbitrarily slow under the mesh refinement dictated by nonparametric description of the unknown function. We describe an approach to modifying a whole range of MCMC methods which ensures that their speed of convergence is robust under mesh refinement. In the applications of interest the data is often sparse and the prior specification is an essential part of the overall modeling strategy. The algorithmic approach that we describe is applicable whenever the desired probability measure has density with respect to a Gaussian process or Gaussian random field prior, and to some useful non-Gaussian priors constructed through random truncation. Applications are shown in density estimation, data assimilation in fluid mechanics, subsurface geophysics and image registration. The key design principle is to formulate the MCMC method for functions. This leads to algorithms which can be implemented via minor modification of existing algorithms, yet which show enormous speed-up on a wide range of applied problems
Impact of Environmental Factors on Bacteriocin Promoter Activity in Gut-Derived Lactobacillus salivarius
peer-reviewedBacteriocin production is regarded as a desirable probiotic trait that aids in colonization and persistence in the gastrointestinal tract (GIT). Strains of Lactobacillus salivarius, a species associated with the GIT, are regarded as promising probiotic candidates and have a number of associated bacteriocins documented to date. These include multiple class IIb bacteriocins (salivaricin T, salivaricin P, and ABP-118) and the class IId bacteriocin bactofencin A, which show activity against medically important pathogens. However, the production of a bacteriocin in laboratory media does not ensure production under stressful environmental conditions, such as those encountered within the GIT. To allow this issue to be addressed, the promoter regions located upstream of the structural genes encoding the L. salivarius bacteriocins mentioned above were fused to a number of reporter proteins (green fluorescent protein [GFP], red fluorescent protein [RFP], and luciferase [Lux]). Of these, only transcriptional fusions to GFP generated signals of sufficient strength to enable the study of promoter activity in L. salivarius. While analysis of the class IIb bacteriocin promoter regions indicated relatively weak GFP expression, assessment of the promoter of the antistaphylococcal bacteriocin bactofencin A revealed a strong promoter that is most active in the absence of the antimicrobial peptide and is positively induced in the presence of mild environmental stresses, including simulated gastric fluid. Taken together, these data provide information on factors that influence bacteriocin production, which will assist in the development of strategies to optimize in vivo and in vitro production of these antimicrobials.This work was funded by a SFI PI award “Obesibiotics” (11/PI/1137) to PD
Deep spectroscopy of z~1 6C radio galaxies - II. Breaking the redshift-radio power degeneracy
The results of a spectroscopic analysis of 3CR and 6C radio galaxies at
redshift z~1 are contrasted with the properties of lower redshift radio
galaxies, chosen to be matched in radio luminosity to the 6C sources studied at
z~1, thus enabling the P-z degeneracy to be broken. Partial rank correlations
and principal component analysis have been used to determine which of z and P
are the critical parameters underlying the observed variation of the ionization
state andd kinematics of the emission line gas. [OII]/H-beta is shown to be a
useful ionization mechanism diagnostic. Statistical analysis of the data shows
that the ionization state of the emission line gas is strongly correlated with
radio power, once the effects of other parameters are removed. No dependence of
ionization state on z is observed, implying that the ionization state of the
emission line gas is solely a function of the AGN properties rather than the
hostt galaxy and/or environment. Statistical analysis of the kinematic
properties of the emission line gas shows that these are strongly correlated
independently withh both P and z. The correlation with redshift is the stronger
of the two, suggesting that host galaxy composition or environment may play a
role in producing the less extreme gas kinematics observed in the emission line
regions of low redshift galaxies. For both the ionization and kinematic
properties of thee galaxies, the independent correlations observed with radio
size are strongest. Radio source age is a determining factor for the extended
emission line regions.Comment: 10 pages, 5 figures, accepted for publication in MNRA
Shotgun Metagenomic Sequencing Revealed the Prebiotic Potential of a Fruit Juice Drink with Fermentable Fibres in Healthy Humans
Fibre-based dietary interventions are at the forefront of gut microbiome modulation research, with a wealth of 16S rRNA information to demonstrate the prebiotic effects of isolated fibres. However, there is a distinct lack of data relating to the effect of a combination of soluble and insoluble fibres in a convenient-to-consume fruit juice food matrix on gut microbiota structure, diversity, and function. Here, we aimed to determine the impact of the MOJU Prebiotic Shot, an apple, lemon, ginger, and raspberry fruit juice drink blend containing chicory inulin, baobab, golden kiwi, and green banana powders, on gut microbiota structure and function. Healthy adults (n = 20) were included in a randomised, double-blind, placebo-controlled, cross-over study, receiving 60 mL MOJU Prebiotic Shot or placebo (without the fibre mix) for 3 weeks with a 3-week washout period between interventions. Shotgun metagenomics revealed significant between-group differences in alpha and beta diversity. In addition, the relative abundance of the phyla Actinobacteria and Desulfobacteria was significantly increased as a result of the prebiotic intervention. Nine species were observed to be differentially abundant (uncorrected p-value of <0.05) as a result of the prebiotic treatment. Of these, Bifidobacterium adolescentis and CAG-81 sp900066785 (Lachnospiraceae) were present at increased abundance relative to baseline. Additionally, KEGG analysis showed an increased abundance in pathways associated with arginine biosynthesis and phenylacetate degradation during the prebiotic treatment. Our results show the effects of the daily consumption of 60 mL MOJU Prebiotic Shot for 3 weeks and provide insight into the functional potential of B. adolescentis
ICP polishing of silicon for high quality optical resonators on a chip
Miniature concave hollows, made by wet etching silicon through a circular
mask, can be used as mirror substrates for building optical micro-cavities on a
chip. In this paper we investigate how ICP polishing improves both shape and
roughness of the mirror substrates. We characterise the evolution of the
surfaces during the ICP polishing using white-light optical profilometry and
atomic force microscopy. A surface roughness of 1 nm is reached, which reduces
to 0.5 nm after coating with a high reflectivity dielectric. With such smooth
mirrors, the optical cavity finesse is now limited by the shape of the
underlying mirror
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