9,289 research outputs found
In-situ EPR Studies of Reaction Pathways in Titania Photocatalyst-Promoted Alkylation of Alkenes
Acknowledgments This work was supported by Engineering and Physical Sciences Research Council (EPSRC) Grant EP/I00372X/1. The EPR spectrometer was purchased under EPSRC Grant EP/F032560/1. We thank Andrew Mills for use of the spectroradiometric measurement system.Peer reviewedPublisher PD
Trends in aircraft design
The improved performance of aircraft during the past decade has resulted
in the need for new design and production techniques. Particular examples are
integral construction and the use of sandwich panels. Although these processes
are costly, especially when applied to titanium and steel construction, their use
is likely to be necessary, at least to some extent. on many supersonic aircraft.
The supersonic airliner is no exception to this and the paper discusses the design
aspects of this type of aircraft which have a bearing on production problems. It
is concluded that more research aimed at reducing the cost of sophisticated forms
of construction is required
The teaching of aircraft design
Aircraft Design has been taught at the College of Aeronautics since
1946. The course is at postgraduate level and is of two years duration.
In the first year the students are given three exercises in component
design which aim to teach a logical approach and the fundamentals of the
subject. During the second year each student works as a member of a
team engaged in the design of a complete aircraft, which is chosen to be
of a type currently being investigated by industry. The project aircraft
invariably incorporates experimental features and the design work is
therefore of the nature of research
Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering
Purpose To investigate whether nonlinear dimensionality reduction improves unsupervised classification of 1H MRS brain tumor data compared with a linear method. Methods In vivo single-voxel 1H magnetic resonance spectroscopy (55 patients) and 1H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. Results An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With 1H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. Conclusion Purpose To investigate whether nonlinear dimensionality reduction improves unsupervised classification of 1H MRS brain tumor data compared with a linear method. Methods In vivo single-voxel 1H magnetic resonance spectroscopy (55 patients) and 1H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. Results An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With 1H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. Conclusion The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of 1H MRSI data after cluster analysis
Ozonation of cooling tower waters
Continuous ozone injection into water circulating between a cooling tower and heat exchanger with heavy scale deposits inhibits formation of further deposits, promotes flaking of existing deposits, inhibits chemical corrosion and controls algae and bacteria
Temporal fluctuations in the differential rotation of cool active stars
This paper reports positive detections of surface differential rotation on
two rapidly rotating cool stars at several epochs, by using stellar surface
features (both cool spots and magnetic regions) as tracers of the large scale
latitudinal shear that distorts the convective envelope in this type of stars.
We also report definite evidence that this differential rotation is different
when estimated from cool spots or magnetic regions, and that it undergoes
temporal fluctuations of potentially large amplitude on a time scale of a few
years. We consider these results as further evidence that the dynamo processes
operating in these stars are distributed throughout the convective zone rather
than being confined at its base as in the Sun. By comparing our observations
with two very simple models of the differential rotation within the convective
zone, we obtain evidence that the internal rotation velocity field of the stars
we investigated is not like that of the Sun, and may resemble that we expect
for rapid rotators. We speculate that the changes in differential rotation
result from the dynamo processes (and from the underlying magnetic cycle) that
periodically converts magnetic energy into kinetic energy and vice versa. We
emphasise that the technique outlined in this paper corresponds to the first
practical method for investigating the large scale rotation velocity field
within convective zones of cool active stars, and offers several advantages
over asteroseismology for this particular purpose and this specific stellar
class.Comment: 14 pages, 4 figure
Stable branching rules for classical symmetric pairs
We approach the problem of obtaining branching rules from the point of view
of dual reductive pairs. Specifically, we obtain a stable branching rule for
each of 10 classical families of symmetric pairs. In each case, the branching
multiplicities are expressed in terms of Littlewood-Richardson coefficients.
Some of the formulas are classical and include, for example, Littlewood's
restriction rule as a special case.Comment: 26 page
The supermembrane revisited
The M2-brane is studied from the perspective of superembeddings. We review
the derivation of the M2-brane dynamics and the supergravity constraints from
the standard superembedding constraint and we discuss explicitly the induced
d=3, N=8 superconformal geometry on the worldvolume. We show that the gauged
supermembrane, for a target space with a U(1) isometry, is the standard
D2-brane in a type IIA supergravity background. In particular, the D2-brane
action, complete with the Dirac-Born-Infeld term, arises from the gauged
Wess-Zumino worldvolume 4-form via the brane action principle. The discussion
is extended to the massive D2-brane considered as a gauged supermembrane in a
massive D=11 superspace background. Type IIA supergeometry is derived using
Kaluza-Klein techniques in superspace.Comment: Latex, 46 pages, clarifying remarks and references adde
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