8 resultados para Random surface
em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast
Resumo:
Acetylene coupling to benzene on the Pd(lll) surface is greatly enhanced by the presence of catalytically inert Au atoms. LEED and Auger spectroscopy show that progressive annealing of Au overlayers on Pd(lll) leads to the formation of a series of random surface alloys with continuously varying composition. Cyclization activity is a strong function of surface composition-the most efficient catalyst corresponds to a surface of composition similar to 85% Pd. CO TPD and HREELS data show that acetylene cyclization activity is not correlated with the availability of singleton Pd atoms, nor just with the presence of 3-fold pure Pd sites-the preferred chemisorption site for C2H2 on Pd{111}. The data can be quantitatively rationalized in terms of a simple model in which catalytic activity is dominated by Pd6Au and Pd-7 surface ensembles, allowance being made for the known degree to which pure Pd{111} decomposes the reactant and product molecules.
Resumo:
Aim Determination of the main directions of variance in an extensive data base of annual pollen deposition, and the relationship between pollen data from modified Tauber traps and palaeoecological data. Location Northern Finland and Norway. Methods Pollen analysis of annual samples from pollen traps and contiguous high-resolution samples from a peat sequence. Numerical analysis (principal components analysis) of the resulting data. Results The main direction of variation in the trap data is due to the vegetation region in which each trap is located. A secondary direction of variation is due to the annual variability of pollen production of some of the tree taxa, especially Betula and Pinus. This annual variability is more conspicuous in ‘absolute’ data than it is in percentage data which, at this annual resolution, becomes more random. There are systematic differences, with respect to peat-forming taxa, between pollen data from traps and pollen data from a peat profile collected over the same period of time. Main conclusions Annual variability in pollen production is rarely visible in fossil pollen samples because these cannot be sampled at precisely a 12-month resolution. At near-annual resolution sampling, it results in erratic percentage values which do not reflect changes in vegetation. Profiles sampled at near annual resolution are better analysed in terms of pollen accumulation rates with the realization that even these do not record changes in plant abundance but changes in pollen abundance. However, at the coarser temporal resolution common in most fossil samples it does not mask the origin of the pollen in terms of its vegetation region. Climate change may not be recognizable from pollen assemblages until the change has persisted in the same direction sufficiently long enough to alter the flowering (pollen production) pattern of the dominant trees.
Resumo:
This research investigated the unconfined flow through dams. The hydraulic conductivity was modeled as spatially random field following lognormal distribution. Results showed that the seepage flow produced from the stochastic solution was smaller than its deterministic value. In addition, the free surface was observed to exit at a point lower than that obtained from the deterministic solution. When the hydraulic conductivity was strongly correlated in the horizontal direction than the vertical direction, the flow through the dam has markedly increased. It is suggested that it may not be necessary to construct a core in dams made from soils that exhibit high degree of variability.
Resumo:
A wealth of palaeoecological studies (e.g. pollen, diatoms, chironomids and macrofossils from deposits such as lakes or bogs) have revealed major as well as more subtle ecosystem changes over decadal to multimillennial timescales. Such ecosystem changes are usually assumed to have been forced by specific environmental changes. Here, we test if the observed changes in palaeoecological records may be reproduced by random simulations, and we find that simple procedures generate abrupt events, long-term trends, quasi-cyclic behaviour, extinctions and immigrations. Our results highlight the importance of replicated and multiproxy data for reliable reconstructions of past climate and environmental changes.
Resumo:
We have developed a novel Multilocus Sequence Typing Scheme (MLST) and database (http://pubmlst.org/pacnes/) for Propionibacterium acnes based on the analysis of seven core housekeeping genes. The scheme, which was validated against previously described antibody, single locus and Random Amplification of Polymorphic DNA (RAPD) typing methods, displayed excellent resolution and differentiated 123 isolates into 37 sequence types (ST). An overall clonal population structure was detected with six eBURST groups representing the major clades I, II and III, along with two singletons. Two highly successful and global clonal lineages, ST6 (type IA) and ST10 (type IB1), representing 65% of this current MLST isolate collection were identified. The ST6 clone and closely related single locus variants (SLV), which comprise a large clonal complex CC6, dominated isolates from patients with acne, and were also significantly associated with ophthalmic infections. Our data therefore supports an association between acne and P. acnes strains from the type IA cluster and highlights the role of a widely disseminated clonal genotype in this condition. Characterisation of type I cell surface-associated antigens that are not detected in ST10 or strains of type II and III identified two dermatan-sulphate-binding proteins with putative phase/antigenic variation signatures. We propose that the expression of these proteins by type IA organisms contributes to their role in the pathophysiology of acne and helps explain the recurrent nature of the disease. The MLST scheme and database described in this study should provide a valuable platform for future epidemiological and evolutionary studies of P. acnes.
Resumo:
The electric field enhancement associated with detailed structure within novel optical antenna nanostructures is modeled using the surface integral equation technique in the context of surface-enhanced Raman scattering (SERS). The antennae comprise random arrays of vertically aligned, multi-walled carbon nanotubes dressed with highly granular Ag. Different types of "hot-spot" underpinning the SERS are identified, but contrasting characteristics are revealed. Those at the outer edges of the Ag grains are antenna driven with field enhancement amplified in antenna antinodes while intergrain hotspots are largely independent of antenna activity. Hot-spots between the tops of antennae leaning towards each other also appear to benefit from antenna amplification.
Resumo:
Fabrication of devices based on thin film structures deposited using the pulsed laser deposition technique relies on reproducibility and control of deposition rates over substrate areas as large as possible. Here we present an application of the random phase plate technique to smooth and homogenize the intensity distribution of a KrF laser footprint on the surface of a target which is to be ablated. It is demonstrated that intensity distributions over millimeter-sized spots on the target can be made insensitive to the typical changes that occur in the near-field intensity distribution of the ultraviolet output from a KrF laser. (C) 1999 American Institute of Physics. [S0034-6748(99)02504-6].
Resumo:
In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).