7,486 research outputs found
Effect of blade geometry on the aerodynamic loads produced by vertical-axis wind turbines
Accurate aerodynamic modelling of vertical-axis wind turbines poses a significant challenge. The rotation of the turbine induces large variations in the angle of attack of its blades that can manifest as dynamic stall. In addition, interactions between the blades of the turbine and the wake that they produce can result in impulsive changes to the aerodynamic loading. The Vorticity Transport Model has been used to simulate the aerodynamic performance and wake dynamics of three different vertical-axis wind turbine configurations. It is known that vertical-axis turbines with either straight or curved blades deliver torque to their shaft that fluctuates at the blade passage frequency of the rotor. In contrast, a turbine with helically twisted blades delivers a relatively steady torque to the shaft. In this article, the interactions between helically twisted blades and the vortices within their wake are shown to result in localized perturbations to the aerodynamic loading on the rotor that can disrupt the otherwise relatively smooth power output that is predicted by simplistic aerodynamic tools that do not model the wake to sufficient fidelity. Furthermore, vertical-axis wind turbines with curved blades are shown to be somewhat more susceptible to local dynamic stall than turbines with straight blades
Genetic Characterization of the Tick-Borne Orbiviruses
The International Committee for Taxonomy of Viruses (ICTV) recognizes four species of tick-borne orbiviruses (TBOs): Chenuda virus, Chobar Gorge virus, Wad Medani virus and Great Island virus (genus Orbivirus, family Reoviridae). Nucleotide (nt) and amino acid (aa) sequence comparisons provide a basis for orbivirus detection and classification, however full genome sequence data were only available for the Great Island virus species. We report representative genome-sequences for the three other TBO species (virus isolates: Chenuda virus (CNUV); Chobar Gorge virus (CGV) and Wad Medani virus (WMV)). Phylogenetic comparisons show that TBOs cluster separately from insect-borne orbiviruses (IBOs). CNUV, CGV, WMV and GIV share low level aa/nt identities with other orbiviruses, in 'conserved' Pol, T2 and T13 proteins/genes, identifying them as four distinct virus-species. The TBO genome segment encoding cell attachment, outer capsid protein 1 (OC1), is approximately half the size of the equivalent segment from insect-borne orbiviruses, helping to explain why tick-borne orbiviruses have a ~1 kb smaller genome
Low autocorrelated multi-phase sequences
The interplay between the ground state energy of the generalized Bernasconi
model to multi-phase, and the minimal value of the maximal autocorrelation
function, , , is examined analytically and
the main results are: (a) The minimal value of is
significantly smaller than the typical value for random
sequences . (b) over all sequences
of length N is obtained in an energy which is about 30% above the ground-state
energy of the generalized Bernasconi model, independent of the number of phases
m. (c) The maximal merit factor grows linearly with m. (d) For a
given N, indicating that for m=N,
, i.e. a Barker code exits. The analytical results are
confirmed by simulations.Comment: 4 pages, 4 figure
On the combination of omics data for prediction of binary outcomes
Enrichment of predictive models with new biomolecular markers is an important
task in high-dimensional omic applications. Increasingly, clinical studies
include several sets of such omics markers available for each patient,
measuring different levels of biological variation. As a result, one of the
main challenges in predictive research is the integration of different sources
of omic biomarkers for the prediction of health traits. We review several
approaches for the combination of omic markers in the context of binary outcome
prediction, all based on double cross-validation and regularized regression
models. We evaluate their performance in terms of calibration and
discrimination and we compare their performance with respect to single-omic
source predictions. We illustrate the methods through the analysis of two real
datasets. On the one hand, we consider the combination of two fractions of
proteomic mass spectrometry for the calibration of a diagnostic rule for the
detection of early-stage breast cancer. On the other hand, we consider
transcriptomics and metabolomics as predictors of obesity using data from the
Dietary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome
(DILGOM) study, a population-based cohort, from Finland
On the semiclassical treatment of anharmonic quantum oscillators via coherent states - The Toda chain revisited
We use coherent states as a time-dependent variational ansatz for a
semiclassical treatment of the dynamics of anharmonic quantum oscillators. In
this approach the square variance of the Hamiltonian within coherent states is
of particular interest. This quantity turns out to have natural interpretation
with respect to time-dependent solutions of the semiclassical equations of
motion. Moreover, our approach allows for an estimate of the decoherence time
of a classical object due to quantum fluctuations. We illustrate our findings
at the example of the Toda chain.Comment: 12 pages, some remarks added. Version to be published in J. Phys. A:
Math. Ge
Statistics of lattice animals (polyominoes) and polygons
We have developed an improved algorithm that allows us to enumerate the
number of site animals (polyominoes) on the square lattice up to size 46.
Analysis of the resulting series yields an improved estimate, , for the growth constant of lattice animals and confirms to a very
high degree of certainty that the generating function has a logarithmic
divergence. We prove the bound We also calculate the radius
of gyration of both lattice animals and polygons enumerated by area. The
analysis of the radius of gyration series yields the estimate , for both animals and polygons enumerated by area. The mean
perimeter of polygons of area is also calculated. A number of new amplitude
estimates are given.Comment: 10 pages, 2 eps figure
Number partitioning as random energy model
Number partitioning is a classical problem from combinatorial optimisation.
In physical terms it corresponds to a long range anti-ferromagnetic Ising spin
glass. It has been rigorously proven that the low lying energies of number
partitioning behave like uncorrelated random variables. We claim that
neighbouring energy levels are uncorrelated almost everywhere on the energy
axis, and that energetically adjacent configurations are uncorrelated, too.
Apparently there is no relation between geometry (configuration) and energy
that could be exploited by an optimization algorithm. This ``local random
energy'' picture of number partitioning is corroborated by numerical
simulations and heuristic arguments.Comment: 8+2 pages, 9 figures, PDF onl
Criticality of natural absorbing states
We study a recently introduced ladder model which undergoes a transition
between an active and an infinitely degenerate absorbing phase. In some cases
the critical behaviour of the model is the same as that of the branching
annihilating random walk with species both with and without hard-core
interaction. We show that certain static characteristics of the so-called
natural absorbing states develop power law singularities which signal the
approach of the critical point. These results are also explained using random
walk arguments. In addition to that we show that when dynamics of our model is
considered as a minimum finding procedure, it has the best efficiency very
close to the critical point.Comment: 6 page
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