621 research outputs found
Critical Opalescence in Baryonic QCD Matter
We show that critical opalescence, a clear signature of second-order phase
transition in conventional matter, manifests itself as critical intermittency
in QCD matter produced in experiments with nuclei. This behaviour is revealed
in transverse momentum spectra as a pattern of power laws in factorial moments,
to all orders, associated with baryon production. This phenomenon together with
a similar effect in the isoscalar sector of pions (sigma mode) provide us with
a set of observables associated with the search for the QCD critical point in
experiments with nuclei at high energies.Comment: 7 pages, 1 figur
Competition between electron pairing and phase coherence in superconducting interfaces
In LaAlO3/SrTiO3 heterostructures, a gate tunable superconducting electron gas is confined in a quantum well at the interface between two insulating oxides. Remarkably, the gas coexists with both magnetism and strong Rashba spin–orbit coupling. However, both the origin of superconductivity and the nature of the transition to the normal state over the whole doping range remain elusive. Here we use resonant microwave transport to extract the superfluid stiffness and the superconducting gap energy of the LaAlO3/SrTiO3 interface as a function of carrier density. We show that the superconducting phase diagram of this system is controlled by the competition between electron pairing and phase coherence. The analysis of the superfluid density reveals that only a very small fraction of the electrons condenses into the superconducting state. We propose that this corresponds to the weak filling of high- energy dxz/dyz bands in the quantum well, more apt to host superconductivity
beta-amyloid modulation of synaptic transmission and plasticity
The sequencing of β amyloid protein (Aβ) in 1984 led to the formulation of the “amyloid hypothesis” of Alzheimer's disease (AD) (Glenner and Wong, 1984). The hypothesis proposed that accumulation of Aβ is responsible for AD-related pathology, including Aβ deposits, neurofibrillary tangles, and eventual neuronal cell death (Tanzi and Bertram, 2005). Within a few years, four groups cloned the amyloid precursor protein (APP) gene from which Aβ is processed (Goldgaber et al., 1987; Kang et al., 1987; Robakis et al., 1987; Tanzi et al., 1987). Linkage analysis mapped the gene to chromosome 21, and mutations in APP were found that led to the inappropriate processing of APP into the Aβ1–42 peptide (Goate et al., 1991; Mullan et al., 1992) (for review, see Tanzi and Bertram, 2005). However, these mutations are responsible for only a small fraction of the early-onset familial AD, and the search began for other genes that might also influence the processing of Aβ. Several novel mutations were identified in the presenilins (Levy-Lahad et al., 1995; Rogaev et al., 1995; Sherrington et al., 1995), and apolipoprotein E4 was identified as a major risk factor for the most frequent form of AD (Strittmatter et al., 1993; Mahley et al., 2006)
Renormalization Group Approach to Causal Viscous Cosmological Models
The renormalization group method is applied to the study of homogeneous and
flat Friedmann-Robertson-Walker type Universes, filled with a causal bulk
viscous cosmological fluid. The starting point of the study is the
consideration of the scaling properties of the gravitational field equations,
of the causal evolution equation of the bulk viscous pressure and of the
equations of state. The requirement of scale invariance imposes strong
constraints on the temporal evolution of the bulk viscosity coefficient,
temperature and relaxation time, thus leading to the possibility of obtaining
the bulk viscosity coefficient-energy density dependence. For a cosmological
model with bulk viscosity coefficient proportional to the Hubble parameter, we
perform the analysis of the renormalization group flow around the scale
invariant fixed point, therefore obtaining the long time behavior of the scale
factor.Comment: 19 pages. RevTeX4. Revised version. Accepted in Classical and Quantum
Gravit
On the Second Law of thermodynamics and the piston problem
The piston problem is investigated in the case where the length of the
cylinder is infinite (on both sides) and the ratio is a very small
parameter, where is the mass of one particle of the gaz and is the mass
of the piston. Introducing initial conditions such that the stochastic motion
of the piston remains in the average at the origin (no drift), it is shown that
the time evolution of the fluids, analytically derived from Liouville equation,
agrees with the Second Law of thermodynamics.
We thus have a non equilibrium microscopical model whose evolution can be
explicitly shown to obey the two laws of thermodynamics.Comment: 29 pages, 9 figures submitted to Journal of Statistical Physics
(2003
Epitaxial growth, structural characterization and exchange bias of non-collinear antiferromagnetic MnIr thin films
Antiferromagnetic materials are of great interest for spintronics. Here we
present a comprehensive study of the growth, structural characterization, and
resulting magnetic properties of thin films of the non-collinear
antiferromagnet MnIr. Using epitaxial engineering on MgO (001) and
AlO (0001) single crystal substrates, we control the growth of
cubic -MnIr in both (001) and (111) crystal orientations, and
discuss the optimization of growth conditions to achieve high-quality crystal
structures with low surface roughness. Exchange bias is studied in bilayers,
with exchange bias fields as large as -29 mT (equivalent to a unidirectional
anisotropy constant of 11.5 nJ cm) measured in MnIr (111) /
permalloy heterostructures at room temperature. In addition, a distinct
dependence of blocking temperature on in-plane crystallographic direction in
MnIr (001) / Py bilayers is observed. These findings are discussed in the
context of chiral antiferromagnetic domain structures, and will inform progress
towards topological antiferromagnetic spintronic devices.Comment: 15 pages, 10 figure
Randomness Increases Order in Biological Evolution
n this text, we revisit part of the analysis of anti-entropy in Bailly and Longo (2009} and develop further theoretical reflections. In particular, we analyze how randomness, an essential component of biological variability, is associated to the growth of biological organization, both in ontogenesis and in evolution. This approach, in particular, focuses on the role of global entropy production and provides a tool for a mathematical understanding of some fundamental observations by Gould on the increasing phenotypic complexity along evolution. Lastly, we analyze the situation in terms of theoretical symmetries, in order to further specify the biological meaning of anti-entropy as well as its strong link with randomness
Probability landscapes for integrative genomics
<p>Abstract</p> <p>Background</p> <p>The comprehension of the gene regulatory code in eukaryotes is one of the major challenges of systems biology, and is a requirement for the development of novel therapeutic strategies for multifactorial diseases. Its bi-fold degeneration precludes brute force and statistical approaches based on the genomic sequence alone. Rather, recursive integration of systematic, whole-genome experimental data with advanced statistical regulatory sequence predictions needs to be developed. Such experimental approaches as well as the prediction tools are only starting to become available and increasing numbers of genome sequences and empirical sequence annotations are under continual discovery-driven change. Furthermore, given the complexity of the question, a decade(s) long multi-laboratory effort needs to be envisioned. These constraints need to be considered in the creation of a framework that can pave a road to successful comprehension of the gene regulatory code.</p> <p>Results</p> <p>We introduce here a concept for such a framework, based entirely on systematic annotation in terms of probability profiles of genomic sequence using any type of relevant experimental and theoretical information and subsequent cross-correlation analysis in hypothesis-driven model building and testing.</p> <p>Conclusion</p> <p>Probability landscapes, which include as reference set the probabilistic representation of the genomic sequence, can be used efficiently to discover and analyze correlations amongst initially heterogeneous and un-relatable descriptions and genome-wide measurements. Furthermore, this structure is usable as a support for automatically generating and testing hypotheses for alternative gene regulatory grammars and the evaluation of those through statistical analysis of the high-dimensional correlations between genomic sequence, sequence annotations, and experimental data. Finally, this structure provides a concrete and tangible basis for attempting to formulate a mathematical description of gene regulation in eukaryotes on a genome-wide scale.</p
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