9,882 research outputs found
Fractionation effects in phase equilibria of polydisperse hard sphere colloids
The equilibrium phase behaviour of hard spheres with size polydispersity is
studied theoretically. We solve numerically the exact phase equilibrium
equations that result from accurate free energy expressions for the fluid and
solid phases, while accounting fully for size fractionation between coexisting
phases. Fluids up to the largest polydispersities that we can study (around
14%) can phase separate by splitting off a solid with a much narrower size
distribution. This shows that experimentally observed terminal polydispersities
above which phase separation no longer occurs must be due to non-equilibrium
effects. We find no evidence of re-entrant melting; instead, sufficiently
compressed solids phase separate into two or more solid phases. Under
appropriate conditions, coexistence of multiple solids with a fluid phase is
also predicted. The solids have smaller polydispersities than the parent phase
as expected, while the reverse is true for the fluid phase, which contains
predominantly smaller particles but also residual amounts of the larger ones.
The properties of the coexisting phases are studied in detail; mean diameter,
polydispersity and volume fraction of the phases all reveal marked
fractionation. We also propose a method for constructing quantities that
optimally distinguish between the coexisting phases, using Principal Component
Analysis in the space of density distributions. We conclude by comparing our
predictions to perturbative theories for near-monodisperse systems and to Monte
Carlo simulations at imposed chemical potential distribution, and find
excellent agreement.Comment: 21 pages, 23 figures, 2 table
Convergence improvement for coupled cluster calculations
Convergence problems in coupled-cluster iterations are discussed, and a new
iteration scheme is proposed. Whereas the Jacobi method inverts only the
diagonal part of the large matrix of equation coefficients, we invert a matrix
which also includes a relatively small number of off-diagonal coefficients,
selected according to the excitation amplitudes undergoing the largest change
in the coupled cluster iteration. A test case shows that the new IPM (inversion
of partial matrix) method gives much better convergence than the
straightforward Jacobi-type scheme or such well-known convergence aids as the
reduced linear equations or direct inversion in iterative subspace methods.Comment: 7 pages, IOPP styl
The adult mouse hippocampal progenitor is neurogenic but not a stem cell
The aim of this investigation was to characterize the proliferative precursor cells in the adult mouse hippocampal region. Given that a very large number of new hippocampal cells are generated over the lifetime of an animal, it is predicted that a neural stem cell is ultimately responsible for maintaining this genesis. Although it is generally accepted that a proliferative precursor resides within the hippocampus, contradictory reports exist regarding the classification of this cell. Is it a true stem cell or a more limited progenitor? Using a strict functional definition of a neural stem cell and a number of in vitro assays, we report that the resident hippocampal precursor is a progenitor capable of proliferation and multipotential differentiation but is unable to self-renew and thus proliferate indefinitely. Furthermore, the mitogen FGF-2 stimulates proliferation of these cells to a greater extent than epidermal growth factor ( EGF). In addition, we found that BDNF was essential for the production of neurons from the hippocampal progenitor cells, being required during proliferation to trigger neuronal fate. In contrast, a bona fide neural stem cell was identified in the lateral wall of the lateral ventricle surrounding the hippocampus. Interestingly, EGF proved to be the stronger mitogenic factor for this cell, which was clearly a different precursor from the resident hippocampal progenitor. These results suggest that the stem cell ultimately responsible for adult hippocampal neurogenesis resides outside the hippocampus, producing progenitor cells that migrate into the neurogenic zones and proliferate to produce new neurons and glia
Electrochemical immobilisation of enzymes. Part 4.—Co-immobilisation of glucose oxidase and ferro/ferricyanide in poly(N-methylpyrrole) films
Glucose oxidase and ferro/ferricyanide can be co-immobilised in poly(N-methylpyrrole) films. The two species compete for incorporation into the films so that on increasing the concentration of enzyme in the growth solution less ferro/ferricyanide is incorporated into the film, and vice versa. The ferro/ferricyanide entrapped within the film acts as a redox mediator for the oxidation of the enzyme at 0.45 V vs. SCE. Studies of the effect of variation of film thickness, glucose concentration, enzyme loading and ferro/ferricyanide loading are consistent with a model in which diffusion and enzyme-catalysed reaction within the film are coupled. Analysis of data from these experiments allows the rate parameters for these processes to be determined. These data are compared with previous results for oxygen mediation in poly(N-methylpyrrole) films
Production of perovskite-like La(1-x)Ca(x)MnO(3+delta) ferromagnetic thin films by electrochemical reduction
Ferromagnetic and perovskite-like thin films (< 1 micron) of La(1-x)Ca(x)MnO(3+delta) have been routinely prepared by heat treatment of an amorphous La Ca Mn precursor. The precursor was electrodeposited cathodically in the absence of oxygen and water onto polished silver substrates from a non-aqueous solution of the components’ nitrates. Analysis by X-Ray diffraction and SQUID magnetometry shows these materials exhibit the appropriate structural and magnetic phases indicative of Colossal Magnetoresistance
MACiE: a database of enzyme reaction mechanisms.
SUMMARY: MACiE (mechanism, annotation and classification in enzymes) is a publicly available web-based database, held in CMLReact (an XML application), that aims to help our understanding of the evolution of enzyme catalytic mechanisms and also to create a classification system which reflects the actual chemical mechanism (catalytic steps) of an enzyme reaction, not only the overall reaction. AVAILABILITY: http://www-mitchell.ch.cam.ac.uk/macie/.EPSRC (G.L.H. and J.B.O.M.), the BBSRC (G.J.B. and J.M.T.—CASE studentship in association with Roche Products Ltd; N.M.O.B. and J.B.O.M.—grant BB/C51320X/1), the Chilean Government’s Ministerio de Planificacio´n y Cooperacio´n and
Cambridge Overseas Trust (D.E.A.) for funding and Unilever for supporting the Centre for Molecular Science Informatics.application note restricted to 2 printed pages web site: http://www-mitchell.ch.cam.ac.uk/macie
Efficient Classical Simulation of Optical Quantum Circuits
We identify a broad class of physical processes in an optical quantum circuit
that can be efficiently simulated on a classical computer: this class includes
unitary transformations, amplification, noise, and measurements. This
simulatability result places powerful constraints on the capability to realize
exponential quantum speedups as well as on inducing an optical nonlinear
transformation via linear optics, photodetection-based measurement and
classical feedforward of measurement results, optimal cloning, and a wide range
of other processes.Comment: 4 pages, published versio
The finite size effect of galaxies on the cosmic virial theorem and the pairwise peculiar velocity dispersions
We discuss the effect of the finite size of galaxies on estimating
small-scale relative pairwise peculiar velocity dispersions from the cosmic
virial theorem (CVT). Specifically we evaluate the effect by incorporating the
finite core radius in the two-point correlation function of mass, i.e.
and the effective gravitational force
softening on small scales. We analytically obtain the lowest-order
correction term for which is in quantitative agreement with the
full numerical evaluation. With a nonzero and/or the cosmic virial
theorem is no longer limited to the case of . We present accurate
fitting formulae for the CVT predicted pairwise velocity dispersion for the
case of . Compared with the idealistic point-mass approximation
(), the finite size effect can significantly reduce the small-scale
velocity dispersions of galaxies at scales much larger than and .
Even without considering the finite size of galaxies, nonzero values for
are generally expected, for instance, for cold dark matter (CDM) models with a
scale-invariant primordial spectrum. For these CDM models, a reasonable force
softening r_s\le 100 \hikpc would have rather tiny effect. We present the CVT
predictions for the small-scale pairwise velocity dispersion in the CDM models
normalized by the COBE observation. The implication of our results for
confrontation of observations of galaxy pair-wise velocity dispersions and
theoretical predictions of the CVT is also discussed.Comment: 18 pages. LaTeX text and 8 postcript figures. submitted to Ap
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining
We present MCRapper, an algorithm for efficient computation of Monte-Carlo
Empirical Rademacher Averages (MCERA) for families of functions exhibiting
poset (e.g., lattice) structure, such as those that arise in many pattern
mining tasks. The MCERA allows us to compute upper bounds to the maximum
deviation of sample means from their expectations, thus it can be used to find
both statistically-significant functions (i.e., patterns) when the available
data is seen as a sample from an unknown distribution, and approximations of
collections of high-expectation functions (e.g., frequent patterns) when the
available data is a small sample from a large dataset. This feature is a strong
improvement over previously proposed solutions that could only achieve one of
the two. MCRapper uses upper bounds to the discrepancy of the functions to
efficiently explore and prune the search space, a technique borrowed from
pattern mining itself. To show the practical use of MCRapper, we employ it to
develop an algorithm TFP-R for the task of True Frequent Pattern (TFP) mining.
TFP-R gives guarantees on the probability of including any false positives
(precision) and exhibits higher statistical power (recall) than existing
methods offering the same guarantees. We evaluate MCRapper and TFP-R and show
that they outperform the state-of-the-art for their respective tasks
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