677 research outputs found
Degenerate distributions in complex Langevin dynamics: one-dimensional QCD at finite chemical potential
We demonstrate analytically that complex Langevin dynamics can solve the sign
problem in one-dimensional QCD in the thermodynamic limit. In particular, it is
shown that the contributions from the complex and highly oscillating spectral
density of the Dirac operator to the chiral condensate are taken into account
correctly. We find an infinite number of classical fixed points of the Langevin
flow in the thermodynamic limit. The correct solution originates from a
continuum of degenerate distributions in the complexified space.Comment: 20 pages, several eps figures, minor comments added, to appear in
JHE
Developments in lattice quantum chromodynamics for matter at high temperature and density
A brief overview of the QCD phase diagram at nonzero temperature and density is provided. It is explained why standard lattice QCD techniques are not immediately applicable for its determination, due to the sign problem. We then discuss a selection of recent lattice approaches that attempt to evade the sign problem and classify them according to the underlying principle: constrained simulations (density of states, histograms), holomorphicity (complex Langevin, Lefschetz thimbles), partial summations (clusters, subsets, bags) and change in integration order (strong coupling, dual formulations)
The sign problem across the QCD phase transition
The average phase factor of the QCD fermion determinant signals the strength
of the QCD sign problem. We compute the average phase factor as a function of
temperature and baryon chemical potential using a two-flavor NJL model. This
allows us to study the strength of the sign problem at and above the chiral
transition. It is discussed how the anomaly affects the sign problem.
Finally, we study the interplay between the sign problem and the endpoint of
the chiral transition.Comment: 9 pages and 9 fig
Learning Moore Machines from Input-Output Traces
The problem of learning automata from example traces (but no equivalence or
membership queries) is fundamental in automata learning theory and practice. In
this paper we study this problem for finite state machines with inputs and
outputs, and in particular for Moore machines. We develop three algorithms for
solving this problem: (1) the PTAP algorithm, which transforms a set of
input-output traces into an incomplete Moore machine and then completes the
machine with self-loops; (2) the PRPNI algorithm, which uses the well-known
RPNI algorithm for automata learning to learn a product of automata encoding a
Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore
machine using PTAP extended with state merging. We prove that MooreMI has the
fundamental identification in the limit property. We also compare the
algorithms experimentally in terms of the size of the learned machine and
several notions of accuracy, introduced in this paper. Finally, we compare with
OSTIA, an algorithm that learns a more general class of transducers, and find
that OSTIA generally does not learn a Moore machine, even when fed with a
characteristic sample
Conductivity and quasinormal modes in holographic theories
We show that in field theories with a holographic dual the retarded Green's
function of a conserved current can be represented as a convergent sum over the
quasinormal modes. We find that the zero-frequency conductivity is related to
the sum over quasinormal modes and their high-frequency asymptotics via a sum
rule. We derive the asymptotics of the quasinormal mode frequencies and their
residues using the phase-integral (WKB) approach and provide analytic insight
into the existing numerical observations concerning the asymptotic behavior of
the spectral densities.Comment: 24 pages, 3 figure
In vivo validation of the electronic depth control probes.
In this article, we evaluated the electrophysiological performance of a novel, high-complexity silicon probe array. This brain-implantable probe implements a dynamically reconfigurable voltage-recording device, coordinating large numbers of electronically switchable recording sites, referred to as electronic depth control (EDC). Our results show the potential of the EDC devices to record good-quality local field potentials, and single- and multiple-unit activities in cortical regions during pharmacologically induced cortical slow wave activity in an animal model
Bayesian modeling of recombination events in bacterial populations
Background: We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. The currently available methods for recombination detection capable of probabilistic characterization of uncertainty have a limited applicability in practice as the number of
strains in a data set increases.
Results: We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the
corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites.
Conclusion: A multitude of challenging simulation scenarios and an analysis of real data from seven
housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities
offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/
mnf//mate/jc/software/brat.html
Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke.
Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation
Disposition of Federally Owned Surpluses
PDZ domains are scaffolding modules in protein-protein interactions that mediate numerous physiological functions by interacting canonically with the C-terminus or non-canonically with an internal motif of protein ligands. A conserved carboxylate-binding site in the PDZ domain facilitates binding via backbone hydrogen bonds; however, little is known about the role of these hydrogen bonds due to experimental challenges with backbone mutations. Here we address this interaction by generating semisynthetic PDZ domains containing backbone amide-to-ester mutations and evaluating the importance of individual hydrogen bonds for ligand binding. We observe substantial and differential effects upon amide-to-ester mutation in PDZ2 of postsynaptic density protein 95 and other PDZ domains, suggesting that hydrogen bonding at the carboxylate-binding site contributes to both affinity and selectivity. In particular, the hydrogen-bonding pattern is surprisingly different between the non-canonical and canonical interaction. Our data provide a detailed understanding of the role of hydrogen bonds in protein-protein interactions
Wake up, wake up! It's me! It's my life! patient narratives on person-centeredness in the integrated care context: a qualitative study
Person-centered care emphasizes a holistic, humanistic approach that puts patients first, at the center of medical care. Person-centeredness is also considered a core element of integrated care. Yet typologies of integrated care mainly describe how patients fit within integrated services, rather than how services fit into the patient's world. Patient-centeredness has been commonly defined through physician's behaviors aimed at delivering patient-centered care. Yet, it is unclear how 'person-centeredness' is realized in integrated care through the patient voice. We aimed to explore patient narratives of person-centeredness in the integrated care context
- …