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

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.

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

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 “nested” 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 –similar in spirit to Google's PageRank but with a built-in non-linearity– here we propose a method which –by exploiting their nested architecture– 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

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

Tritium distributions on W-coated divertor tiles used in the third JET ITER-like wall campaign

Tritium (T) distributions on tungsten (W)-coated plasma-facing tiles used in the third ITER-like wall campaign (2015–2016) of the Joint European Torus (JET) were examined by means of an imaging plate technique and β-ray induced x-ray spectrometry, and they were compared with the distributions after the second (2013–2014) campaign. Strong enrichment of T in beryllium (Be) deposition layers was observed after the second campaign. In contrast, T distributions after the third campaign was more uniform though Be deposition layers were visually recognized. The one of the possible explanations is enhanced desorption of T from Be deposition layers due to higher tile temperatures caused by higher energy input in the third campaign