Properties of tetrahedral amorphous carbon prepared by vacuum arc deposition

The structural, optical, electrical and physical properties of amorphous carbon deposited from the filtered plasma stream of a vacuum arc were investigated. The structure was determined by electron diffraction, neutron diffraction and energy loss spectroscopy and the tetrahedral coordination of the material was confirmed. The measurements gave a nearest neighbour distance of 1.53 Å, a bond angle of 110 and a coordination number of four. A model is proposed in which the compressive stress generated in the film by energetic ion impact produces pressure and temperature conditions lying well inside the region of the carbon phase diagram within which diamond is stable. The model is confirmed by measurements of stress and plasmon energy as a function of ion energy. The model also predicts the formation of sp2-rich materials on the surface owing to stress relaxation and this is confirmed by a study of the surface plasmon energy. Some nuclear magnetic resonance, infrared and optical properties are reported and the behaviour of diodes using tetrahedral amorphous carbon is discussed. © 1991.

Decentralised minimal-time consensus

This study considers the discrete-time dynamics of a network of agents that exchange information according to the nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the consensus value of the whole network in finite time using only the minimal number of successive values of its own history. We show that this minimal number of steps is related to a Jordan block decomposition of the network dynamics and present an algorithm to obtain the minimal number of steps in question by checking a rank condition on a Hankel matrix of the local observations. Furthermore, we prove that the minimal number of steps is related to other algebraic and graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the underlying graph topology. © 2011 IEEE.

In-situ deposition of sparse vertically aligned carbon nanofibres on catalytically activated stainless steel mesh for field emission applications

We report on an inexpensive, facile and industry viable carbon nanofibre catalyst activation process achieved by exposing stainless steel mesh to an electrolyzed metal etchant. The surface evolution of the catalyst islands combines low-rate electroplating and substrate dissolution. The plasma enhanced chemical vapour deposited carbon nanofibres had aspect-ratios > 150 and demonstrated excellent height and crystallographic uniformity with localised coverage. The nanofibres were well-aligned with spacing consistent with the field emission nearest neighbour electrostatic shielding criteria, without the need of any post-growth processing. Nanofibre inclusion significantly reduced the emission threshold field from 4.5 V/μm (native mesh) to 2.5 V/μm and increased the field enhancement factor to approximately 7000. © 2011 Elsevier B.V. All rights reserved.

Decentralised minimum-time consensus

We consider the discrete-time dynamics of a network of agents that exchange information according to a nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the final consensus value of the whole network in finite time using the minimum number of successive values of its own state history. We show that the minimum number of steps is related to a Jordan block decomposition of the network dynamics, and present an algorithm to compute the final consensus value in the minimum number of steps by checking a rank condition of a Hankel matrix of local observations. Furthermore, we prove that the minimum number of steps is related to graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the minimum external equitable partition. © 2013 Elsevier Ltd. All rights reserved.

The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, and objects in different concepts have dissimilar latent values. We formulate the supervised infinite latent variable problem based on an intuitive principle of pulling objects together if they are of the same type, and pushing them apart if they are not. We then combine this principle with a flexible Indian Buffet Process prior on the latent variables. We show that the inferred supervised latent variables can be directly used to perform a nearest neighbour search for the purpose of retrieval. We introduce a new application of dynamically extending hash codes, and show how to effectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving infinite latent feature space.

Oxygen carrier dispersion in inert packed beds to improve performance in chemical looping combustion

Various packed beds of copper-based oxygen carriers (CuO on Al2O3) were tested over 100 cycles of low temperature (673K) Chemical Looping Combustion (CLC) with H2 as the fuel gas. The oxygen carriers were uniformly mixed with alumina (Al2O3) in order to investigate the level of separation necessary to prevent agglomeration. It was found that a mass ratio of 1:6 oxygen carrier to alumina gave the best performance in terms of stable, repeating hydrogen breakthrough curves over 100 cycles. In order to quantify the average separation achieved in the mixed packed beds, two sphere-packing models were developed. The hexagonal close-packing model assumed a uniform spherical packing structure, and based the separation calculations on a hypergeometric probability distribution. The more computationally intensive full-scale model used discrete element modelling to simulate random packing arrangements governed by gravity and contact dynamics. Both models predicted that average 'nearest neighbour' particle separation drops to near zero for oxygen carrier mass fractions of x≥0.25. For the packed bed systems studied, agglomeration was observed when the mass fraction of oxygen carrier was above this threshold. © 2013 Elsevier B.V.

Development and transition of spiral wave in the coupled Hindmarsh-Rose neurons in two-dimensional space

The dynamics and the transition of spiral waves in the coupled Hindmarsh-Rose (H-R) neurons in two-dimensional space are investigated in the paper. It is found that the spiral wave can be induced and developed in the coupled HR neurons in two-dimensional space, with appropriate initial values and a parameter region given. However, the spiral wave could encounter instability when the intensity of the external current reaches a threshold value of 1.945. The transition of spiral wave is found to be affected by coupling intensity D and bifurcation parameter r. The spiral wave becomes sparse as the coupling intensity increases, while the spiral wave is eliminated and the whole neuronal system becomes homogeneous as the bifurcation parameter increases to a certain threshold value. Then the coupling action of the four sub-adjacent neurons, which is described by coupling coefficient D', is also considered, and it is found that the spiral wave begins to breakup due to the introduced coupling action from the sub-adjacent neurons (or sites) and together with the coupling action of the nearest-neighbour neurons, which is described by the coupling intensity D.

STRUCTURE-ANALYSIS OF MOLTEN CACL2-KCL SYSTEM BY X-RAY-DIFFRACTION

Radial distribution function of CaCl2-KCl (1:2 mol) melt was measured by X-ray scattering of high temperature liquid. The nearest neighbour distances of Ca2+-Cl-, K+-Cl- and Cl--Cl- ionic pairs are 0.278, 0.306 and 0.380 nm, respectively, Discussion on the relation between structure and physicochemical properties in the melt was simply done in this paper.

MULTIVARIATE CLASSIFICATION BASED ON METAL CONTENTS IN HUMAN SENILE CATARACT LENSES

Multivariate classification methods were used to evaluate data on the concentrations of eight metals in human senile lenses measured by atomic absorption spectrometry. Principal components analysis and hierarchical clustering separated senile cataract lenses, nuclei from cataract lenses, and normal lenses into three classes on the basis of the eight elements. Stepwise discriminant analysis was applied to give discriminant functions with five selected variables. Results provided by the linear learning machine method were also satisfactory; the k-nearest neighbour method was less useful.

Myroides profundi sp nov., isolated from deep-sea sediment of the southern Okinawa Trough

A Gram-negative, nonmotile, aerobic and oxidase- and catalase-positive bacterium,, designated D25(T), was isolated from the deep-sea sediments of the southern Okinawa Trough area. Phylogenetic analyses of 16S rRNA gene sequences showed that strain D25(T), fell within the genus Myroides, with 99.2%, 96.0% and 93.4% sequence similarities to the only three recognized species of Myroides. However, the DNA-DNA similarity Value between strain D25(T) and its nearest neighbour Myroides odoratimimus JCM 7460(T) was only 49.9% ( < 70%). Several phenotypic properties could be used to distinguish strain D25(T) from other Myroides species. The main cellular fatty acids of strain D25(T) were iso-C-15:0, iso-C-17:1 omega 9C, iso-C(17:0)3-OH and Summed Feature 3 (comprising C-16:1 omega 7c and/or iso-C(15:0)2-OH). The major respiratory quinone was MK-6. The DNA G+C content was 33.0 mol%. The results of the polyphasic taxonomy analysis suggested that strain D251(T) represents a novel species of the genus Myroides, for which the name Myroides profundi sp. nov. is proposed. The type strain is D25(T) (=CCTCC M 208030(T) = DSM 19823(T)).

Polyamorphism in aluminate liquids

McMillan, P. F., Wilson, M., Wilding, M. C. (2003). Polyamorphism in aluminate liquids. Journal of Physics: Condensed Matter, 15 (36), 6105-6121 RAE2008

Studies on Formica lugubris Zetterstedt in Ireland (Hymenoptera, Formicidae)

This thesis is based on studies of Formica lugubris from 1972-1975. While this species' range is diminishing in Ireland, the nests are quite common in the State plantations of South Tipperary. It is not certain that the species is indigenous. Above-ground activity occurs from late-February to the end of October; foraging begins in April. Two territorial "spring-battles" between neighbouring nests are described. Most active nests produced alatae of both sexes and flights were observed on successive June mornings above l7.5°C air temperature. Both polygyny and polycaly seem to be rare. Where the nests occur commonly, the recorded densities are similar to those reported from the continent. Most nests persisted at the same site since 1973. The nest-sites are described by recording an array of nest, soil, tree, vegetation and location variables at each site. Pinus sylvestris is the most important overhead tree. Nests seem to be the same age as their surrounding plantation and reach a maximum of c. 30 years. Nearest-neighbour analysis suggests the sites are overdispersed. Forager route-fidelity was studied and long-term absence from the route, anaesthetization and "removal" of an aphid tree had little effect on this fidelity. There were no identifiable groups of workers specifically honeydew or prey-carriers. Size-duty relationships of workers participating in adult transport are described. Foraging rhythms were studied on representative days: the numbers foraging were linearly related to temperature. Route-traffic passed randomly and an average foraging trip lasted c. four hours. Annual food intake to a nest with 25 000 foragers was estimated at approximately 75 kg honeydew and 2 million prey-items. Forager-numbers and colony-size were estimated using the capture-mark - recapture method: paint marking was used for the forager estimate and an interval radiophosphorus mark, detected by autoradiography, was used for the colony-size estimate. The aphids attended by lugubris and the nest myrmecophiles are recorded.

Case base adaptation using solution-space metrics

In this paper we propose a generalisation of the k-nearest neighbour (k-NN) retrieval method based on an error function using distance metrics in the solution and problem space. It is an interpolative method which is proposed to be effective for sparse case bases. The method applies equally to nominal, continuous and mixed domains, and does not depend upon an embedding n-dimensional space. In continuous Euclidean problem domains, the method is shown to be a generalisation of the Shepard's Interpolation method. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The performance of the retrieval method is examined with reference to the Iris classification problem,and to a simulated sparse nominal value test problem. The introducion of a solution-space metric is shown to out-perform conventional nearest neighbours methods on sparse case bases.

Case base reduction using solution-space metrics

In this paper we propose a case base reduction technique which uses a metric defined on the solution space. The technique utilises the Generalised Shepard Nearest Neighbour (GSNN) algorithm to estimate nominal or real valued solutions in case bases with solution space metrics. An overview of GSNN and a generalised reduction technique, which subsumes some existing decremental methods, such as the Shrink algorithm, are presented. The reduction technique is given for case bases in terms of a measure of the importance of each case to the predictive power of the case base. A trial test is performed on two case bases of different kinds, with several metrics proposed in the solution space. The tests show that GSNN can out-perform standard nearest neighbour methods on this set. Further test results show that a caseremoval order proposed based on a GSNN error function can produce a sparse case base with good predictive power.

Case based adaptation using interpolation over nominal values

In this paper we propose a method for interpolation over a set of retrieved cases in the adaptation phase of the case-based reasoning cycle. The method has two advantages over traditional systems: the first is that it can predict “new” instances, not yet present in the case base; the second is that it can predict solutions not present in the retrieval set. The method is a generalisation of Shepard’s Interpolation method, formulated as the minimisation of an error function defined in terms of distance metrics in the solution and problem spaces. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The method is illustrated in the paper with reference to the Irises classification problem. It is evaluated with reference to a simulated nominal value test problem, and to a benchmark case base from the travel domain. The algorithm is shown to out-perform conventional nearest neighbour methods on these problems. Finally, GSNN is shown to improve in efficiency when used in conjunction with a diverse retrieval algorithm.