3,897 research outputs found
Magnetic and structural-properties of electrodeposited Co1-xPx amorphous ribbons
The specific magnetic moment, coercive force, anisotropy field, and saturation magnetostriction constant have been measured in Co(1-x)P(x) amorphous ribbons with 0.04 less-than-or-equal-to x less-than-or-equal-to 0.27. Differential scanning calorimetry, x-ray diffraction, and transmission electron microscopy analysis have been made in order to study the transition from the amorphous state to the crystalline one. Results suggest that transition takes place when x decreases from 0.19
Graph Metrics for Temporal Networks
Temporal networks, i.e., networks in which the interactions among a set of
elementary units change over time, can be modelled in terms of time-varying
graphs, which are time-ordered sequences of graphs over a set of nodes. In such
graphs, the concepts of node adjacency and reachability crucially depend on the
exact temporal ordering of the links. Consequently, all the concepts and
metrics proposed and used for the characterisation of static complex networks
have to be redefined or appropriately extended to time-varying graphs, in order
to take into account the effects of time ordering on causality. In this chapter
we discuss how to represent temporal networks and we review the definitions of
walks, paths, connectedness and connected components valid for graphs in which
the links fluctuate over time. We then focus on temporal node-node distance,
and we discuss how to characterise link persistence and the temporal
small-world behaviour in this class of networks. Finally, we discuss the
extension of classic centrality measures, including closeness, betweenness and
spectral centrality, to the case of time-varying graphs, and we review the work
on temporal motifs analysis and the definition of modularity for temporal
graphs.Comment: 26 pages, 5 figures, Chapter in Temporal Networks (Petter Holme and
Jari Saram\"aki editors). Springer. Berlin, Heidelberg 201
Reconstruction of the Dark Energy equation of state
One of the main challenges of modern cosmology is to investigate the nature
of dark energy in our Universe. The properties of such a component are normally
summarised as a perfect fluid with a (potentially) time-dependent
equation-of-state parameter . We investigate the evolution of this
parameter with redshift by performing a Bayesian analysis of current
cosmological observations. We model the temporal evolution as piecewise linear
in redshift between `nodes', whose -values and redshifts are allowed to
vary. The optimal number of nodes is chosen by the Bayesian evidence. In this
way, we can both determine the complexity supported by current data and locate
any features present in . We compare this node-based reconstruction with
some previously well-studied parameterisations: the Chevallier-Polarski-Linder
(CPL), the Jassal-Bagla-Padmanabhan (JBP) and the Felice-Nesseris-Tsujikawa
(FNT). By comparing the Bayesian evidence for all of these models we find an
indication towards possible time-dependence in the dark energy
equation-of-state. It is also worth noting that the CPL and JBP models are
strongly disfavoured, whilst the FNT is just significantly disfavoured, when
compared to a simple cosmological constant . We find that our node-based
reconstruction model is slightly disfavoured with respect to the CDM
model.Comment: 17 pages, 5 figures, minor correction
Mesoscopic organization reveals the constraints governing C. elegans nervous system
One of the biggest challenges in biology is to understand how activity at the
cellular level of neurons, as a result of their mutual interactions, leads to
the observed behavior of an organism responding to a variety of environmental
stimuli. Investigating the intermediate or mesoscopic level of organization in
the nervous system is a vital step towards understanding how the integration of
micro-level dynamics results in macro-level functioning. In this paper, we have
considered the somatic nervous system of the nematode Caenorhabditis elegans,
for which the entire neuronal connectivity diagram is known. We focus on the
organization of the system into modules, i.e., neuronal groups having
relatively higher connection density compared to that of the overall network.
We show that this mesoscopic feature cannot be explained exclusively in terms
of considerations, such as optimizing for resource constraints (viz., total
wiring cost) and communication efficiency (i.e., network path length).
Comparison with other complex networks designed for efficient transport (of
signals or resources) implies that neuronal networks form a distinct class.
This suggests that the principal function of the network, viz., processing of
sensory information resulting in appropriate motor response, may be playing a
vital role in determining the connection topology. Using modular spectral
analysis, we make explicit the intimate relation between function and structure
in the nervous system. This is further brought out by identifying functionally
critical neurons purely on the basis of patterns of intra- and inter-modular
connections. Our study reveals how the design of the nervous system reflects
several constraints, including its key functional role as a processor of
information.Comment: Published version, Minor modifications, 16 pages, 9 figure
Random Walks on Stochastic Temporal Networks
In the study of dynamical processes on networks, there has been intense focus
on network structure -- i.e., the arrangement of edges and their associated
weights -- but the effects of the temporal patterns of edges remains poorly
understood. In this chapter, we develop a mathematical framework for random
walks on temporal networks using an approach that provides a compromise between
abstract but unrealistic models and data-driven but non-mathematical
approaches. To do this, we introduce a stochastic model for temporal networks
in which we summarize the temporal and structural organization of a system
using a matrix of waiting-time distributions. We show that random walks on
stochastic temporal networks can be described exactly by an
integro-differential master equation and derive an analytical expression for
its asymptotic steady state. We also discuss how our work might be useful to
help build centrality measures for temporal networks.Comment: Chapter in Temporal Networks (Petter Holme and Jari Saramaki
editors). Springer. Berlin, Heidelberg 2013. The book chapter contains minor
corrections and modifications. This chapter is based on arXiv:1112.3324,
which contains additional calculations and numerical simulation
The SERRATE protein is involved in alternative splicing in <em>Arabidopsis thaliana</em>
Howalternative splicing (AS) is regulated in plants has not yet been elucidated. Previously, we have shown that the nuclear cap-binding protein complex (AtCBC) is involved in AS in Arabidopsis thaliana. Here we show that both subunits of AtCBC (AtCBP20 and AtCBP80) interact with SERRATE (AtSE), a protein involved in the microRNA biogenesis pathway. Moreover, using a high-resolution reverse transcript-ase-polymerase chain reaction AS system we have found that AtSE influences AS in a similar way to the cap-binding complex (CBC), preferentially affecting selection of 50 splice site of first introns. The AtSE protein acts in cooperation with AtCBC: many changes observed in the mutant lacking the correct SERRATE activity were common to those observed in the cbp mutants. Interestingly, significant changes in AS of some genes were also observed in other mutants of plant microRNA biogenesis pathway, hyl1-2 and dcl1-7, but a majority of them did not cor-respond to the changes observed in the se-1mutant. Thus, the role of SERRATE in AS regulation is distinct from that of HYL1andDCL1, and is similar to the regu-lation of AS in which CBC is involved
Measurement of ISR-FSR interference in the processes e+ e- --> mu+ mu- gamma and e+ e- --> pi+ pi- gamma
Charge asymmetry in processes e+ e- --> mu+ mu- gamma and e+ e- --> pi+ pi-
gamma is measured using 232 fb-1 of data collected with the BABAR detector at
center-of-mass energies near 10.58 GeV. An observable is introduced and shown
to be very robust against detector asymmetries while keeping a large
sensitivity to the physical charge asymmetry that results from the interference
between initial and final state radiation. The asymmetry is determined as
afunction of the invariant mass of the final-state tracks from production
threshold to a few GeV/c2. It is compared to the expectation from QED for e+ e-
--> mu+ mu- gamma and from theoretical models for e+ e- --> pi+ pi- gamma. A
clear interference pattern is observed in e+ e- --> pi+ pi- gamma, particularly
in the vicinity of the f_2(1270) resonance. The inferred rate of lowest order
FSR production is consistent with the QED expectation for e+ e- --> mu+ mu-
gamma, and is negligibly small for e+ e- --> pi+ pi- gamma.Comment: 32 pages,29 figures, to be submitted to Phys. Rev.
Measurement of the quasi-elastic axial vector mass in neutrino-oxygen interactions
The weak nucleon axial-vector form factor for quasi-elastic interactions is
determined using neutrino interaction data from the K2K Scintillating Fiber
detector in the neutrino beam at KEK. More than 12,000 events are analyzed, of
which half are charged-current quasi-elastic interactions nu-mu n to mu- p
occurring primarily in oxygen nuclei. We use a relativistic Fermi gas model for
oxygen and assume the form factor is approximately a dipole with one parameter,
the axial vector mass M_A, and fit to the shape of the distribution of the
square of the momentum transfer from the nucleon to the nucleus. Our best fit
result for M_A = 1.20 \pm 0.12 GeV. Furthermore, this analysis includes updated
vector form factors from recent electron scattering experiments and a
discussion of the effects of the nucleon momentum on the shape of the fitted
distributions.Comment: 14 pages, 10 figures, 6 table
Single-molecule experiments in biological physics: methods and applications
I review single-molecule experiments (SME) in biological physics. Recent
technological developments have provided the tools to design and build
scientific instruments of high enough sensitivity and precision to manipulate
and visualize individual molecules and measure microscopic forces. Using SME it
is possible to: manipulate molecules one at a time and measure distributions
describing molecular properties; characterize the kinetics of biomolecular
reactions and; detect molecular intermediates. SME provide the additional
information about thermodynamics and kinetics of biomolecular processes. This
complements information obtained in traditional bulk assays. In SME it is also
possible to measure small energies and detect large Brownian deviations in
biomolecular reactions, thereby offering new methods and systems to scrutinize
the basic foundations of statistical mechanics. This review is written at a
very introductory level emphasizing the importance of SME to scientists
interested in knowing the common playground of ideas and the interdisciplinary
topics accessible by these techniques. The review discusses SME from an
experimental perspective, first exposing the most common experimental
methodologies and later presenting various molecular systems where such
techniques have been applied. I briefly discuss experimental techniques such as
atomic-force microscopy (AFM), laser optical tweezers (LOT), magnetic tweezers
(MT), biomembrane force probe (BFP) and single-molecule fluorescence (SMF). I
then present several applications of SME to the study of nucleic acids (DNA,
RNA and DNA condensation), proteins (protein-protein interactions, protein
folding and molecular motors). Finally, I discuss applications of SME to the
study of the nonequilibrium thermodynamics of small systems and the
experimental verification of fluctuation theorems. I conclude with a discussion
of open questions and future perspectives.Comment: Latex, 60 pages, 12 figures, Topical Review for J. Phys. C (Cond.
Matt
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