2,961 research outputs found
Effect of Collector Configuration on Test Section Turbulence Levels in an Open-Jet Wind Tunnel
Flow quality studies in the Langley 14- by 22-Foot Subsonic Tunnel indicated periodic flow pulsation at discrete frequencies in the test section when the tunnel operated in an open-jet configuration. To alleviate this problem, experiments were conducted in a 1/24-scale model of the full-scale tunnel to evaluate the turbulence reduction potential of six collector configurations. As a result of these studies, the original bell-mouth collector of the 14- by 22-Foot Subsonic Tunnel was replaced by a collector with straight walls, and a slot was incorporated between the trailing edge of the collector and the entrance of the diffuser
Percolation transition and distribution of connected components in generalized random network ensembles
In this work, we study the percolation transition and large deviation
properties of generalized canonical network ensembles. This new type of random
networks might have a very rich complex structure, including high heterogeneous
degree sequences, non-trivial community structure or specific spatial
dependence of the link probability for networks embedded in a metric space. We
find the cluster distribution of the networks in these ensembles by mapping the
problem to a fully connected Potts model with heterogeneous couplings. We show
that the nature of the Potts model phase transition, linked to the birth of a
giant component, has a crossover from second to first order when the number of
critical colors in all the networks under study. These results shed
light on the properties of dynamical processes defined on these network
ensembles.Comment: 27 pages, 15 figure
Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities
Many complex networks display a mesoscopic structure with groups of nodes
sharing many links with the other nodes in their group and comparatively few
with nodes of different groups. This feature is known as community structure
and encodes precious information about the organization and the function of the
nodes. Many algorithms have been proposed but it is not yet clear how they
should be tested. Recently we have proposed a general class of undirected and
unweighted benchmark graphs, with heterogenous distributions of node degree and
community size. An increasing attention has been recently devoted to develop
algorithms able to consider the direction and the weight of the links, which
require suitable benchmark graphs for testing. In this paper we extend the
basic ideas behind our previous benchmark to generate directed and weighted
networks with built-in community structure. We also consider the possibility
that nodes belong to more communities, a feature occurring in real systems,
like, e. g., social networks. As a practical application, we show how
modularity optimization performs on our new benchmark.Comment: 9 pages, 13 figures. Final version published in Physical Review E.
The code to create the benchmark graphs can be freely downloaded from
http://santo.fortunato.googlepages.com/inthepress
Evolution equation for a model of surface relaxation in complex networks
In this paper we derive analytically the evolution equation of the interface
for a model of surface growth with relaxation to the minimum (SRM) in complex
networks. We were inspired by the disagreement between the scaling results of
the steady state of the fluctuations between the discrete SRM model and the
Edward-Wilkinson process found in scale-free networks with degree distribution
for [Pastore y Piontti {\it et al.},
Phys. Rev. E {\bf 76}, 046117 (2007)]. Even though for Euclidean lattices the
evolution equation is linear, we find that in complex heterogeneous networks
non-linear terms appear due to the heterogeneity and the lack of symmetry of
the network; they produce a logarithmic divergency of the saturation roughness
with the system size as found by Pastore y Piontti {\it et al.} for .Comment: 9 pages, 2 figure
Exercise and the microbiota
The authors are supported in part by research grants from Science Foundation Ireland including a centre grant (Alimentary Pharmabiotic Centre; Grant Numbers SFI/12/RC/2273 and 12/RC/2273). Dr. Orla OâSullivan is funded by a Starting Investigator Research Grant from Science Foundation Ireland (Grant number 13/SIRG/2160). Dr. Paul Cotter is funded by a Principal Investigator Award from Science Foundation Ireland P.D.C are supported by a SFI PI award (Grant number 11/PI/1137).peer-reviewedSedentary lifestyle is linked with poor health, most commonly obesity and associated disorders, the corollary being that exercise offers a preventive strategy. However, the scope of exercise biology extends well beyond energy expenditure and has emerged as a great âpolypillâ, which is safe, reliable and cost-effective not only in disease prevention but also treatment. Biological mechanisms by which exercise influences homeostasis are becoming clearer and involve multi-organ systemic adaptations. Most of the elements of a modern lifestyle influence the indigenous microbiota but few studies have explored the effect of increased physical activity. While dietary responses to exercise obscure the influence of exercise alone on gut microbiota, professional athletes operating at the extremes of performance provide informative data. We assessed the relationship between extreme levels of exercise, associated dietary habits and gut microbiota composition, and discuss potential mechanisms by which exercise may exert a direct or indirect influence on gut microbiota.The authors are supported in part by research grants from Science Foundation Ireland including a centre grant (Alimentary Pharmabiotic Centre; Grant Numbers SFI/12/RC/2273 and 12/RC/2273). Dr. Orla OâSullivan is funded by a Starting Investigator Research Grant from Science Foundation Ireland (Grant number 13/SIRG/2160). Dr. Paul Cotter is funded by a Principal Investigator Award from Science Foundation Ireland P.D.C are supported by a SFI PI award (Grant number 11/PI/1137)
Non-equilibrium mean-field theories on scale-free networks
Many non-equilibrium processes on scale-free networks present anomalous
critical behavior that is not explained by standard mean-field theories. We
propose a systematic method to derive stochastic equations for mean-field order
parameters that implicitly account for the degree heterogeneity. The method is
used to correctly predict the dynamical critical behavior of some binary spin
models and reaction-diffusion processes. The validity of our non-equilibrium
theory is furtherly supported by showing its relation with the generalized
Landau theory of equilibrium critical phenomena on networks.Comment: 4 pages, no figures, major changes in the structure of the pape
Vertex similarity in networks
We consider methods for quantifying the similarity of vertices in networks.
We propose a measure of similarity based on the concept that two vertices are
similar if their immediate neighbors in the network are themselves similar.
This leads to a self-consistent matrix formulation of similarity that can be
evaluated iteratively using only a knowledge of the adjacency matrix of the
network. We test our similarity measure on computer-generated networks for
which the expected results are known, and on a number of real-world networks
Effectiveness of a social support intervention on infant feeding practices : randomised controlled trial
Background: To assess whether monthly home visits from trained volunteers could improve infant feeding practices at age 12 months, a randomised controlled trial was carried out in two disadvantaged inner city London boroughs.
Methods: Women attending baby clinics with their infants (312) were randomised to receive monthly home visits from trained volunteers over a 9-month period (intervention group) or standard professional care only (control group). The primary outcome was vitamin C intakes from fruit. Secondary outcomes included selected macro and micro-nutrients, infant feeding habits, supine length and weight. Data were collected at baseline when infants were aged approximately 10 weeks, and subsequently when the child was 12 and 18 months old.
Results: Two-hundred and twelve women (68%) completed the trial. At both follow-up points no significant differences were found between the groups for vitamin C intakes from fruit or other nutrients. At first follow-up, however, infants in the intervention group were significantly less likely to be given goatsâ or soya milks, and were more likely to have three solid meals per day. At the second follow-up, intervention group children were significantly less likely to be still using a bottle. At both follow-up points, intervention group children also consumed significantly more specific fruit and vegetables.
Conclusions: Home visits from trained volunteers had no significant effect on nutrient intakes but did promote some other recommended infant feeding practices
Spin Glass Phase Transition on Scale-Free Networks
We study the Ising spin glass model on scale-free networks generated by the
static model using the replica method. Based on the replica-symmetric solution,
we derive the phase diagram consisting of the paramagnetic (P), ferromagnetic
(F), and spin glass (SG) phases as well as the Almeida-Thouless line as
functions of the degree exponent , the mean degree , and the
fraction of ferromagnetic interactions . To reflect the inhomogeneity of
vertices, we modify the magnetization and the spin glass order parameter
with vertex-weights. The transition temperature () between the
P-F (P-SG) phases and the critical behaviors of the order parameters are found
analytically. When , and are infinite, and the
system is in the F phase or the mixed phase for , while it is in the
SG phase at . and decay as power-laws with increasing
temperature with different -dependent exponents. When ,
the and are finite and related to the percolation threshold. The
critical exponents associated with and depend on for () at the P-F (P-SG) boundary.Comment: Phys. Rev. E in pres
Predicting the size and probability of epidemics in a population with heterogeneous infectiousness and susceptibility
We analytically address disease outbreaks in large, random networks with
heterogeneous infectivity and susceptibility. The transmissibility
(the probability that infection of causes infection of ) depends on the
infectivity of and the susceptibility of . Initially a single node is
infected, following which a large-scale epidemic may or may not occur. We use a
generating function approach to study how heterogeneity affects the probability
that an epidemic occurs and, if one occurs, its attack rate (the fraction
infected). For fixed average transmissibility, we find upper and lower bounds
on these. An epidemic is most likely if infectivity is homogeneous and least
likely if the variance of infectivity is maximized. Similarly, the attack rate
is largest if susceptibility is homogeneous and smallest if the variance is
maximized. We further show that heterogeneity in infectious period is
important, contrary to assumptions of previous studies. We confirm our
theoretical predictions by simulation. Our results have implications for
control strategy design and identification of populations at higher risk from
an epidemic.Comment: 5 pages, 3 figures. Submitted to Physical Review Letter
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