697 research outputs found
The Origin of Power-Law Emergent Scaling in Large Binary Networks
In this paper we study the macroscopic conduction properties of large but
finite binary networks with conducting bonds. By taking a combination of a
spectral and an averaging based approach we derive asymptotic formulae for the
conduction in terms of the component proportions p and the total number of
components N. These formulae correctly identify both the percolation limits and
also the emergent power law behaviour between the percolation limits and show
the interplay between the size of the network and the deviation of the
proportion from the critical value of p = 1/2. The results compare excellently
with a large number of numerical simulations
Multi-parameter models of innovation diffusion on complex networks
A model, applicable to a range of innovation diffusion applications with a
strong peer to peer component, is developed and studied, along with methods for
its investigation and analysis. A particular application is to individual
households deciding whether to install an energy efficiency measure in their
home. The model represents these individuals as nodes on a network, each with a
variable representing their current state of adoption of the innovation. The
motivation to adopt is composed of three terms, representing personal
preference, an average of each individual's network neighbours' states and a
system average, which is a measure of the current social trend. The adoption
state of a node changes if a weighted linear combination of these factors
exceeds some threshold. Numerical simulations have been carried out, computing
the average uptake after a sufficient number of time-steps over many
realisations at a range of model parameter values, on various network
topologies, including random (Erdos-Renyi), small world (Watts-Strogatz) and
(Newman's) highly clustered, community-based networks. An analytical and
probabilistic approach has been developed to account for the observed
behaviour, which explains the results of the numerical calculations
Modelling the uptake of domestic energy technologies via local networks and integrating real-world data
Modelling the uptake of domestic energy technologies via local networks and integrating real-world data
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Wavelet based detection of changes in the composition of RLC networks
The current work discusses the compositional analysis of spectra that may be related to amorphous materials that lack discernible Lorentzian, Debye or Drude responses. We propose to model such response using a 3-dimensional random RLC network using a descriptor formulation which is converted into an input-output transfer function representation. A wavelet identification study of these networks is performed to infer the composition of the networks. It was concluded that wavelet filter banks enable a parsimonious representation of the dynamics in excited randomly connected RLC networks. Furthermore, chemometric classification using the proposed technique enables the discrimination of dielectric samples with different composition. The methodology is promising for the classification of amorphous dielectrics
Experimental evidence for 56Ni-core breaking from the low-spin structure of the N=Z nucleus 58Cu
Low-spin states in the odd-odd N=Z nucleus 58Cu were investigated with the
58Ni(p,n gamma)58Cu fusion evaporation reaction at the FN-tandem accelerator in
Cologne. Seventeen low spin states below 3.6 MeV and 17 new transitions were
observed. Ten multipole mixing ratios and 17 gamma-branching ratios were
determined for the first time. New detailed spectroscopic information on the
2+,2 state, the Isobaric Analogue State (IAS) of the 2+,1,T=1 state of 58Ni,
makes 58Cu the heaviest odd-odd N=Z nucleus with known B(E2;2+,T=1 --> 0+,T=1)
value. The 4^+ state at 2.751 MeV, observed here for the first time, is
identified as the IAS of the 4+,1,T=1 state in 58Ni. The new data are compared
to full pf-shell model calculations with the novel GXPF1 residual interaction
and to calculations within a pf5/2 configurational space with a residual
surface delta interaction. The role of the 56Ni core excitations for the
low-spin structure in 58Cu is discussed.Comment: 15 pages, 7 figures, submitted to Phys. Rev.
Ranking species in mutualistic networks
Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic ânestedâ structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm âsimilar in spirit to Google's PageRank but with a built-in non-linearityâ here we propose a method which âby exploiting their nested architectureâ allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made
Microfabrication of a biomimetic arcade-like electrospun scaffold for cartilage tissue engineering applications
Designing and fabricating hierarchical geometries for tissue engineering (TE) applications is the major challenge and also the biggest opportunity of regenerative medicine in recent years, being the in vitro recreation of the arcade-like cartilaginous tissue one of the most critical examples due to the current inefficient standard medical procedures and the lack of fabrication techniques capable of building scaffolds with the required architecture in a cost and time effective way. Taking this into account, we suggest a feasible and accurate methodology that uses a sequential adaptation of an electrospinning-electrospraying set up to construct a system comprising both fibres and sacrificial microparticles. Polycaprolactone (PCL) and polyethylene glycol were respectively used as bulk and sacrificial biomaterials, leading to a bi-layered PCL scaffold which presented not only a depth-dependent fibre orientation similar to natural cartilage, but also mechanical features and porosity compatible with cartilage TE approaches. In fact, cell viability studies confirmed the biocompatibility of the scaffold and its ability to guarantee suitable cell adhesion, proliferation and migration throughout the 3D anisotropic fibrous network. Additionally, likewise the natural anisotropic cartilage, the PCL scaffold was capable of inducing oriented cell-material interactions since the morphology, alignment and density of the chondrocytes changed relatively to the specific topographic cues of each electrospun layer.publishe
Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET
Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate
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