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ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program
ToScA North America will address key areas of science,
including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast,
Educational Outreach, Data, Materials Science and Medical and Biological
Science.University of Texas High-Resolution X-ray CT Facility (UTCT);
Jackson School of Geosciences, The University of Texas at Austin;
Natural History Museum (London);
Royal Microscopical Society (Oxford, UK)Geological Science
Enhanced structural correlations accelerate diffusion in charge-stabilized colloidal suspensions
Theoretical calculations for colloidal charge-stabilized and hard sphere
suspensions show that hydrodynamic interactions yield a qualitatively different
particle concentration dependence of the short-time self-diffusion coefficient.
The effect, however, is numerically small and hardly accessible by conventional
light scattering experiments. Applying multiple-scattering decorrelation
equipment and a careful data analysis we show that the theoretical prediction
for charged particles is in agreement with our experimental results from
aqueous polystyrene latex suspensions.Comment: 1 ps-file (MS-Word), 14 page
Contrast-enhanced ultrasound examination for the assessment of renal perfusion in cats with chronic kidney disease
Background: Contrast-enhanced ultrasound examination (CEUS) is a functional imaging technique allowing noninvasive assessment of tissue perfusion. Studies in humans show that the technique holds great potential to be used in the diagnosis of chronic kidney disease (CKD). However, data in veterinary medicine are currently lacking.
Objectives: To evaluate renal perfusion using CEUS in cats with CKD.
Animals: Fourteen client-owned cats with CKD and 43 healthy control cats.
Methods: Prospective case-controlled clinical trial using CEUS to evaluate renal perfusion in cats with CKD compared to healthy control cats. Time-intensity curves were created, and perfusion parameters were calculated using off-line software. A linear mixed model was used to examine differences between perfusion parameters of cats with CKD and healthy cats.
Results: In cats with CKD, longer time to peak and shorter mean transit times were observed for the renal cortex. In contrast, a shorter time to peak and rise time were seen for the renal medulla. The findings for the renal cortex indicate decreased blood velocity and shorter total duration of enhancement, likely caused by increased vascular resistance in CKD. Increased blood velocity in the renal medulla has not been described before and may be because of a different response to regulatory factors in cortex and medulla.
Conclusions and Clinical Importance: Contrast-enhanced ultrasound examination was capable of detecting perfusion changes in cats with CKD. Further research is warranted to assess the diagnostic capabilities of CEUS in early stage of the disease process
Universality class of non-Fermi liquid behavior in mixed valence systems
A generalized Anderson single-impurity model with off-site Coulomb
interactions is derived from the extended three-band Hubbard model, originally
proposed to describe the physics of the copper-oxides. Using the abelian
bosonization technique and canonical transformations, an effective Hamiltonian
is derived in the strong coupling limit, which is essentially analogous to the
Toulouse limit of the ordinary Kondo problem. In this limit, the effective
Hamiltonian can be exactly solved, with a mixed valence quantum critical point
separating two different Fermi liquid phases, {\it i.e.} the Kondo phase and
the empty orbital phase. In the mixed valence quantum critical regime, the
local moment is only partially quenched and X-ray edge singularities are
generated. Around the quantum critical point, a new type of non-Fermi liquid
behavior is predicted with an extra specific heat and a
singular spin-susceptibility . At the same time, the
effective Hamiltonian under single occupancy is transformed into a
resonant-level model, from which the correct Kondo physical properties
(specific heat, spin susceptibility, and an enhanced Wilson ratio) are easily
rederived. Finally, a brief discussion is given to relate these theoretical
results to observations in () alloys, which show
single-impurity critical behavior consistent with our predictions.Comment: 26 pages, revtex, no figure. Some corrections have been made, but the
basic results are kept. To be published in Physical Review
False discovery rate regression: an application to neural synchrony detection in primary visual cortex
Many approaches for multiple testing begin with the assumption that all tests
in a given study should be combined into a global false-discovery-rate
analysis. But this may be inappropriate for many of today's large-scale
screening problems, where auxiliary information about each test is often
available, and where a combined analysis can lead to poorly calibrated error
rates within different subsets of the experiment. To address this issue, we
introduce an approach called false-discovery-rate regression that directly uses
this auxiliary information to inform the outcome of each test. The method can
be motivated by a two-groups model in which covariates are allowed to influence
the local false discovery rate, or equivalently, the posterior probability that
a given observation is a signal. This poses many subtle issues at the interface
between inference and computation, and we investigate several variations of the
overall approach. Simulation evidence suggests that: (1) when covariate effects
are present, FDR regression improves power for a fixed false-discovery rate;
and (2) when covariate effects are absent, the method is robust, in the sense
that it does not lead to inflated error rates. We apply the method to neural
recordings from primary visual cortex. The goal is to detect pairs of neurons
that exhibit fine-time-scale interactions, in the sense that they fire together
more often than expected due to chance. Our method detects roughly 50% more
synchronous pairs versus a standard FDR-controlling analysis. The companion R
package FDRreg implements all methods described in the paper
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