642 research outputs found
Aubry transition studied by direct evaluation of the modulation functions of infinite incommensurate systems
Incommensurate structures can be described by the Frenkel Kontorova model.
Aubry has shown that, at a critical value K_c of the coupling of the harmonic
chain to an incommensurate periodic potential, the system displays the
analyticity breaking transition between a sliding and pinned state. The ground
state equations coincide with the standard map in non-linear dynamics, with
smooth or chaotic orbits below and above K_c respectively. For the standard
map, Greene and MacKay have calculated the value K_c=.971635. Conversely,
evaluations based on the analyticity breaking of the modulation function have
been performed for high commensurate approximants. Here we show how the
modulation function of the infinite system can be calculated without using
approximants but by Taylor expansions of increasing order. This approach leads
to a value K_c'=.97978, implying the existence of a golden invariant circle up
to K_c' > K_c.Comment: 7 pages, 5 figures, file 'epl.cls' necessary for compilation
provided; Revised version, accepted for publication in Europhysics Letter
Towards structured sharing of raw and derived neuroimaging data across existing resources
Data sharing efforts increasingly contribute to the acceleration of
scientific discovery. Neuroimaging data is accumulating in distributed
domain-specific databases and there is currently no integrated access mechanism
nor an accepted format for the critically important meta-data that is necessary
for making use of the combined, available neuroimaging data. In this
manuscript, we present work from the Derived Data Working Group, an open-access
group sponsored by the Biomedical Informatics Research Network (BIRN) and the
International Neuroimaging Coordinating Facility (INCF) focused on practical
tools for distributed access to neuroimaging data. The working group develops
models and tools facilitating the structured interchange of neuroimaging
meta-data and is making progress towards a unified set of tools for such data
and meta-data exchange. We report on the key components required for integrated
access to raw and derived neuroimaging data as well as associated meta-data and
provenance across neuroimaging resources. The components include (1) a
structured terminology that provides semantic context to data, (2) a formal
data model for neuroimaging with robust tracking of data provenance, (3) a web
service-based application programming interface (API) that provides a
consistent mechanism to access and query the data model, and (4) a provenance
library that can be used for the extraction of provenance data by image
analysts and imaging software developers. We believe that the framework and set
of tools outlined in this manuscript have great potential for solving many of
the issues the neuroimaging community faces when sharing raw and derived
neuroimaging data across the various existing database systems for the purpose
of accelerating scientific discovery
Breakdown of Lindstedt Expansion for Chaotic Maps
In a previous paper of one of us [Europhys. Lett. 59 (2002), 330--336] the
validity of Greene's method for determining the critical constant of the
standard map (SM) was questioned on the basis of some numerical findings. Here
we come back to that analysis and we provide an interpretation of the numerical
results by showing that no contradiction is found with respect to Greene's
method. We show that the previous results based on the expansion in Lindstedt
series do correspond to the transition value but for a different map: the
semi-standard map (SSM). Moreover, we study the expansion obtained from the SM
and SSM by suppressing the small divisors. The first case turns out to be
related to Kepler's equation after a proper transformation of variables. In
both cases we give an analytical solution for the radius of convergence, that
represents the singularity in the complex plane closest to the origin. Also
here, the radius of convergence of the SM's analogue turns out to be lower than
the one of the SSM. However, despite the absence of small denominators these
two radii are lower than the ones of the true maps for golden mean winding
numbers. Finally, the analyticity domain and, in particular, the critical
constant for the two maps without small divisors are studied analytically and
numerically. The analyticity domain appears to be an perfect circle for the SSM
analogue, while it is stretched along the real axis for the SM analogue
yielding a critical constant that is larger than its radius of convergence.Comment: 12 pages, 3 figure
Bubbles and denaturation in DNA
The local opening of DNA is an intriguing phenomenon from a statistical
physics point of view, but is also essential for its biological function. For
instance, the transcription and replication of our genetic code can not take
place without the unwinding of the DNA double helix. Although these biological
processes are driven by proteins, there might well be a relation between these
biological openings and the spontaneous bubble formation due to thermal
fluctuations. Mesoscopic models, like the Peyrard-Bishop-Dauxois model, have
fairly accurately reproduced some experimental denaturation curves and the
sharp phase transition in the thermodynamic limit. It is, hence, tempting to
see whether these models could be used to predict the biological activity of
DNA. In a previous study, we introduced a method that allows to obtain very
accurate results on this subject, which showed that some previous claims in
this direction, based on molecular dynamics studies, were premature. This could
either imply that the present PBD should be improved or that biological
activity can only be predicted in a more complex frame work that involves
interactions with proteins and super helical stresses. In this article, we give
detailed description of the statistical method introduced before. Moreover, for
several DNA sequences, we give a thorough analysis of the bubble-statistics as
function of position and bubble size and the so-called -denaturation curves
that can be measured experimentally. These show that some important
experimental observations are missing in the present model. We discuss how the
present model could be improved.Comment: 15 pages, 5 figures, published as Eur. Phys. J. E 20 : 421-434 AUG
200
Bubbles, clusters and denaturation in genomic DNA: modeling, parametrization, efficient computation
The paper uses mesoscopic, non-linear lattice dynamics based
(Peyrard-Bishop-Dauxois, PBD) modeling to describe thermal properties of DNA
below and near the denaturation temperature. Computationally efficient notation
is introduced for the relevant statistical mechanics. Computed melting profiles
of long and short heterogeneous sequences are presented, using a recently
introduced reparametrization of the PBD model, and critically discussed. The
statistics of extended open bubbles and bound clusters is formulated and
results are presented for selected examples.Comment: to appear in a special issue of the Journal of Nonlinear Mathematical
Physics (ed. G. Gaeta
Highly parallelizable path sampling with minimal rejections using asynchronous replica exchange and infinite swaps
Capturing rare yet pivotal events poses a significant challenge for molecular simulations. Path sampling provides a unique approach to tackle this issue without altering the potential energy landscape or dynamics, enabling recovery of both thermodynamic and kinetic information. However, despite its exponential acceleration compared to standard molecular dynamics, generating numerous trajectories can still require a long time. By harnessing our recent algorithmic innovations—particularly subtrajectory moves with high acceptance, coupled with asynchronous replica exchange featuring infinite swaps—we establish a highly parallelizable and rapidly converging path sampling protocol, compatible with diverse high-performance computing architectures. We demonstrate our approach on the liquid–vapor phase transition in superheated water, the unfolding of the chignolin protein, and water dissociation. The latter, performed at the ab initio level, achieves comparable statistical accuracy within days, in contrast to a previous study requiring over a year
PyRETISÂ 3: Conquering rare and slow events without boundaries
We present and discuss the advancements made in PyRETIS 3, the third instalment of our Python library for an efficient and user-friendly rare event simulation, focused to execute molecular simulations with replica exchange transition interface sampling (RETIS) and its variations. Apart from a general rewiring of the internal code towards a more modular structure, several recently developed sampling strategies have been implemented. These include recently developed Monte Carlo moves to increase path decorrelation and convergence rate, and new ensemble definitions to handle the challenges of long-lived metastable states and transitions with unbounded reactant and product states. Additionally, the post-analysis software PyVisa is now embedded in the main code, allowing fast use of machine-learning algorithms for clustering and visualising collective variables in the simulation data
Heritability and reliability of automatically segmented human hippocampal formation subregions
The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test-retest reliability and transplatform reliability (1.5 T versus 3 T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N=39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N=163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N=598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h(2)) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test-retest reliability was high for all twelve subregions in the 3 T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70-0.97) and moderate-to-high in the 4 TQTIM sample (ICC=0.5-0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC=0.66-0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5 T and 3 T field strengths (ICC=0.47-0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC=0.78-0.84; Dice Similarity Coefficient (DSC)=0.55-0.70), and poor for all other subregions (ICC=0.34-0.81; DSC=0.28-0.51). All hippocampal subregion volumes were highly heritable (h(2)=0.67-0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium. (C) 2016 The Authors. Published by Elsevier Inc
The NeuroDante Project: Neurometric measurements of participant’s reaction to literary auditory stimuli from dante’s “divina commedia”
Neurodante. Progetto di analisi neurometrica di alcuni brani della Commedi
ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors
- …