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The effect of flavanol rich cocoa on cerebral perfusion in older adults during conscious resting state : a placebo controlled, crossover, acute trial
Rationale: There has recently been increasing interest in the potential of flavanols, plant derived compounds found in foods such as fruit and vegetables, to ameliorate age-related cognitive decline. Research suggests that cocoa flavanols improve memory and learning, possibly as a result of their anti-inflammatory and neuroprotective effects. These effects may be mediated by increased cerebral blood flow (CBF), thus stimulating neuronal function.
Objectives: The present study employed arterial spin labelling (ASL) functional magnetic resonance imaging (FMRI) to explore the effect of a single acute dose of cocoa flavanols on regional CBF.
Methods: CBF was measured pre and post consumption of low (23mg) or high (494mg) 330ml equicaloric flavanol drinks matched for caffeine, theobromine, taste and appearance according to a randomised counterbalanced crossover double-blind design in eight males and ten females, aged 50-65 years. Changes in perfusion from pre to post consumption were calculated as a function of each drink.
Results: Significant increases in regional perfusion across the brain were observed following consumption of the high flavanol drink relative to the low flavanol drink, particularly in the anterior cingulate cortex (ACC) and the central opercular cortex of the parietal lobe.
Conclusions: Consumption of cocoa flavanol improves regional cerebral perfusion in older adults. This provides evidence for a possible acute mechanism by which cocoa flavanols are associated with benefits for cognitive performance
Corrections to the Central Limit Theorem for Heavy-Tailed Probability Densities
Classical Edgeworth expansions provide asymptotic correction terms to the
Central Limit Theorem (CLT) up to an order that depends on the number of
moments available. In this paper, we provide subsequent correction terms beyond
those given by a standard Edgeworth expansion in the general case of regularly
varying distributions with diverging moments (beyond the second). The
subsequent terms can be expressed in a simple closed form in terms of certain
special functions (Dawson's integral and parabolic cylinder functions), and
there are qualitative differences depending on whether the number of moments
available is even, odd or not an integer, and whether the distributions are
symmetric or not. If the increments have an even number of moments, then
additional logarithmic corrections must also be incorporated in the expansion
parameter. An interesting feature of our correction terms for the CLT is that
they become dominant outside the central region and blend naturally with known
large-deviation asymptotics when these are applied formally to the spatial
scales of the CLT
Time-delayed feedback control of unstable periodic orbits near a subcritical Hopf bifurcation
We show that Pyragas delayed feedback control can stabilize an unstable
periodic orbit (UPO) that arises from a generic subcritical Hopf bifurcation of
a stable equilibrium in an n-dimensional dynamical system. This extends results
of Fiedler et al. [PRL 98, 114101 (2007)], who demonstrated that such feedback
control can stabilize the UPO associated with a two-dimensional subcritical
Hopf normal form. Pyragas feedback requires an appropriate choice of a feedback
gain matrix for stabilization, as well as knowledge of the period of the
targeted UPO. We apply feedback in the directions tangent to the
two-dimensional center manifold. We parameterize the feedback gain by a modulus
and a phase angle, and give explicit formulae for choosing these two parameters
given the period of the UPO in a neighborhood of the bifurcation point. We
show, first heuristically, and then rigorously by a center manifold reduction
for delay differential equations, that the stabilization mechanism involves a
highly degenerate Hopf bifurcation problem that is induced by the time-delayed
feedback. When the feedback gain modulus reaches a threshold for stabilization,
both of the genericity assumptions associated with a two-dimensional Hopf
bifurcation are violated: the eigenvalues of the linearized problem do not
cross the imaginary axis as the bifurcation parameter is varied, and the real
part of the cubic coefficient of the normal form vanishes. Our analysis of this
degenerate bifurcation problem reveals two qualitatively distinct cases when
unfolded in a two-parameter plane. In each case, Pyragas-type feedback
successfully stabilizes the branch of small-amplitude UPOs in a neighborhood of
the original bifurcation point, provided that the phase angle satisfies a
certain restriction.Comment: 35 pages, 19 figure
Avalanche dynamics, surface roughening and self-organized criticality - experiments on a 3 dimensional pile of rice
We present a two-dimensional system which exhibits features of self-organized
criticality. The avalanches which occur on the surface of a pile of rice are
found to exhibit finite size scaling in their probability distribution. The
critical exponents are = 1.21(2) for the avalanche size distribution and
= 1.99(2) for the cut-off size. Furthermore the geometry of the avalanches
is studied leading to a fractal dimension of the active sites of =
1.58(2). Using a set of scaling relations, we can calculate the roughness
exponent = 0.41(3) and the dynamic exponent = 1.56(8). This result is compared with that obtained from a power
spectrum analysis of the surface roughness, which yields = 0.42(3) and
= 1.5(1) in excellent agreement with those obtained from the scaling
relations.Comment: 7 pages, 8 figures, accepted for publication in PR
Dilepton production in proton-nucleus and nucleus-nucleus collisions at SPS energies
Dilepton production in proton- and nucleus-induced reactions is studied in
relativistic transport model using initial conditions determined by the string
dynamics from RQMD. It is found that both the CERES and HELIOS-3 data for
dilepton spectra in proton-nucleus reactions can be well described by the
`conventional' mechanism of Dalitz decay and direct vector meson decay.
However, to provide a quantitative explanation of the observed dilepton spectra
in central S+Au and S+W collisions requires contributions other than these
direct decays. Introducing a decrease of vector meson masses in hot and dense
medium, we find that these heavy-ion data can also be satisfactorily explained.
This agrees with our earlier conclusions based on a fire cylinder model. We
also give predictions for Pb+Au collisions at 160 GeV/nucleon using current
CERES mass resolution and acceptance.Comment: RevTeX, 45 pages, including 21 postscript figures, to be published in
Nuclear Physics
Meson Cloud of the Nucleon in Polarized Semi-Inclusive Deep-Inelastic Scattering
We investigate the possibility of identifying an explicit pionic component of
the nucleon through measurements of polarized baryon fragments
produced in deep-inelastic leptoproduction off polarized protons, which may
help to identify the physical mechanism responsible for the breaking of the
Gottfried sum rule. The pion-exchange model predicts highly correlated
polarizations of the and target proton, in marked contrast with
the competing diquark fragmentation process. Measurement of asymmetries in
polarized production may also reveal the presence of a kaon cloud in
the nucleon.Comment: 23 pages REVTeX, 7 uuencoded figures, accepted for publication in
Zeit. Phys.
Interstellar MHD Turbulence and Star Formation
This chapter reviews the nature of turbulence in the Galactic interstellar
medium (ISM) and its connections to the star formation (SF) process. The ISM is
turbulent, magnetized, self-gravitating, and is subject to heating and cooling
processes that control its thermodynamic behavior. The turbulence in the warm
and hot ionized components of the ISM appears to be trans- or subsonic, and
thus to behave nearly incompressibly. However, the neutral warm and cold
components are highly compressible, as a consequence of both thermal
instability in the atomic gas and of moderately-to-strongly supersonic motions
in the roughly isothermal cold atomic and molecular components. Within this
context, we discuss: i) the production and statistical distribution of
turbulent density fluctuations in both isothermal and polytropic media; ii) the
nature of the clumps produced by thermal instability, noting that, contrary to
classical ideas, they in general accrete mass from their environment; iii) the
density-magnetic field correlation (or lack thereof) in turbulent density
fluctuations, as a consequence of the superposition of the different wave modes
in the turbulent flow; iv) the evolution of the mass-to-magnetic flux ratio
(MFR) in density fluctuations as they are built up by dynamic compressions; v)
the formation of cold, dense clouds aided by thermal instability; vi) the
expectation that star-forming molecular clouds are likely to be undergoing
global gravitational contraction, rather than being near equilibrium, and vii)
the regulation of the star formation rate (SFR) in such gravitationally
contracting clouds by stellar feedback which, rather than keeping the clouds
from collapsing, evaporates and diperses them while they collapse.Comment: 43 pages. Invited chapter for the book "Magnetic Fields in Diffuse
Media", edited by Elisabete de Gouveia dal Pino and Alex Lazarian. Revised as
per referee's recommendation
Grain Surface Models and Data for Astrochemistry
AbstractThe cross-disciplinary field of astrochemistry exists to understand the formation, destruction, and survival of molecules in astrophysical environments. Molecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. A broad consensus has been reached in the astrochemistry community on how to suitably treat gas-phase processes in models, and also on how to present the necessary reaction data in databases; however, no such consensus has yet been reached for grain-surface processes. A team of ∼25 experts covering observational, laboratory and theoretical (astro)chemistry met in summer of 2014 at the Lorentz Center in Leiden with the aim to provide solutions for this problem and to review the current state-of-the-art of grain surface models, both in terms of technical implementation into models as well as the most up-to-date information available from experiments and chemical computations. This review builds on the results of this workshop and gives an outlook for future directions
Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events
The - oscillation frequency has been measured with a sample of
23 million \B\bar B pairs collected with the BABAR detector at the PEP-II
asymmetric B Factory at SLAC. In this sample, we select events in which both B
mesons decay semileptonically and use the charge of the leptons to identify the
flavor of each B meson. A simultaneous fit to the decay time difference
distributions for opposite- and same-sign dilepton events gives ps.Comment: 7 pages, 1 figure, submitted to Physical Review Letter
Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya
Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization
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