Reactive plasmas as a versatile nanofabrication tool

The underlying physics of the application of low-temperature, low-pressure reactive plasmas in various nanoassembly processes is described. From the viewpoint of the "cause and effect" approach, this Colloquium focuses on the benefits and challenges of using plasma-based systems in nanofabrication of nanostructured silicon films, low-dimensional semiconducting quantum structures, ordered carbon nanotip arrays, highly crystalline TiO2 coatings, and nanostructured hydroxyapatite bioceramics. Other examples and future prospects of plasma-aided nanofabrication are also discussed. © 2005 The American Physical Society.

Defect healing and enhanced nucleation of carbon nanotubes by low-energy ion bombardment

Structural defects inevitably appear during the nucleation event that determines the structure and properties of single-walled carbon nanotubes. By combining ion bombardment experiments with atomistic simulations we reveal that ion bombardment in a suitable energy range allows these defects to be healed resulting in an enhanced nucleation of the carbon nanotube cap. The enhanced growth of the nanotube cap is explained by a nonthermal ion-induced graphene network restructuring mechanism.

Interacting motile agents : taking a mean-field approach beyond monomers and nearest-neighbor steps

We consider a discrete agent-based model on a one-dimensional lattice, where each agent occupies L sites and attempts movements over a distance of d lattice sites. Agents obey a strict simple exclusion rule. A discrete-time master equation is derived using a mean-field approximation and careful probability arguments. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy are obtained. Averaged discrete simulation data are generated and shown to compare very well with the solution to the derived nonlinear diffusion equations. This framework allows us to approach a lattice-free result using all the advantages of lattice methods. Since different cell types have different shapes and speeds of movement, this work offers insight into population-level behavior of collective cellular motion.

Collective motion of dimers

We consider a discrete agent-based model on a one-dimensional lattice and a two-dimensional square lattice, where each agent is a dimer occupying two sites. Agents move by vacating one occupied site in favor of a nearest-neighbor site and obey either a strict simple exclusion rule or a weaker constraint that permits partial overlaps between dimers. Using indicator variables and careful probability arguments, a discrete-time master equation for these processes is derived systematically within a mean-field approximation. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy of the dimer population are obtained. In addition, we show that multiple species of interacting subpopulations give rise to advection-diffusion equations. Averaged discrete simulation data compares very well with the solution to the continuum partial differential equation models. Since many cell types are elongated rather than circular, this work offers insight into population-level behavior of collective cellular motion.

Building macroscale models from microscale probabilistic models : a general probabilistic approach for nonlinear diffusion and multispecies phenomena

A discrete agent-based model on a periodic lattice of arbitrary dimension is considered. Agents move to nearest-neighbor sites by a motility mechanism accounting for general interactions, which may include volume exclusion. The partial differential equation describing the average occupancy of the agent population is derived systematically. A diffusion equation arises for all types of interactions and is nonlinear except for the simplest interactions. In addition, multiple species of interacting subpopulations give rise to an advection-diffusion equation for each subpopulation. This work extends and generalizes previous specific results, providing a construction method for determining the transport coefficients in terms of a single conditional transition probability, which depends on the occupancy of sites in an influence region. These coefficients characterize the diffusion of agents in a crowded environment in biological and physical processes.

Affinity purification of plasmid DNA directly from crude bacterial cell lysates

We have shown previously that a sequence-specific DNA-binding protein based on the Lac repressor protein can isolate pre-purified DNA efficiently from simple buffer solution but our attempts to purify plasmids directly from crude starting materials were disappointing with unpractically low DNA yields. We have optimized tbe procedure and present a simple affinity methodology whereby plasmid DNA is purified directly by mixing two crude cell lysates, one cell lysate containing the plasmid and the other the protein affinity ligand, without the need for treatment by RNaseA. After IMAC chromatography, high purity supercoiled DNA is recovered in good yields of 100-150 μg plasmid per 200 mL shake flask culture. Moreover, the resulting DNA is free from linear or open-circular plasmid DNA, genomic DNA, RNA, and protein, to the limits of our detection. Furthermore, we show that lyophilized affinity ligand can be stored at room temperature and re-hydrated for use when required.

Saffman-Taylor fingers with kinetic undercooling

The mathematical model of a steadily propagating Saffman-Taylor finger in a Hele-Shaw channel has applications to two-dimensional interacting streamer discharges which are aligned in a periodic array. In the streamer context, the relevant regularisation on the interface is not provided by surface tension, but instead has been postulated to involve a mechanism equivalent to kinetic undercooling, which acts to penalise high velocities and prevent blow-up of the unregularised solution. Previous asymptotic results for the Hele-Shaw finger problem with kinetic undercooling suggest that for a given value of the kinetic undercooling parameter, there is a discrete set of possible finger shapes, each analytic at the nose and occupying a different fraction of the channel width. In the limit in which the kinetic undercooling parameter vanishes, the fraction for each family approaches 1/2, suggesting that this selection of 1/2 by kinetic undercooling is qualitatively similar to the well-known analogue with surface tension. We treat the numerical problem of computing these Saffman-Taylor fingers with kinetic undercooling, which turns out to be more subtle than the analogue with surface tension, since kinetic undercooling permits finger shapes which are corner-free but not analytic. We provide numerical evidence for the selection mechanism by setting up a problem with both kinetic undercooling and surface tension, and numerically taking the limit that the surface tension vanishes.

A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

Older entrepreneurs: Do they work smarter or harder?

Entrepreneurs starting their first businesses between the ages of 55 and 64 years represent the fastest growing entrepreneurship segment in America and Australia. There is sparse research on older entrepreneurs with conflicting results, particularly with respect to generational differences. Previous literature on generational differences focuses on family businesses, but characteristics of founders of family businesses are quite different than those of founders of non-family businesses. Consequently, we compare characteristics of older entrepreneurs to younger entrepreneurs as they start new ventures. Are there differences in their work styles and venture performance? This study makes a contribution to entrepreneurship literature by studying the growing phenomenon of older entrepreneurs. We make a contribution to practice by helping older entrepreneurs identify their strengths, which could lead to more successful older entrepreneurs and provide satisfying and rewarding careers to those leaving wage and salary employment to pursue self employment.

Topological properties and fractal analysis of a recurrence network constructed from fractional Brownian motions

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent 〈λ〉 increases first and then decreases with the increase of Hurst index H of the associated FBMs; the relationship between H and 〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the associated FBMs, and their dependence approximately satisfies the linear formula 〈dB〉≈2-H, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index H=0.5 possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension 〈D(1)〉 and the average correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.

Single 2×1 domain orientation on Si(001) surfaces using aperiodic Bi line arrays

Studies of Bi heteroepitaxy on Si(001) have shown that lines grow to lengths of up to 500nm if the substrate is heated to above the Bi desorption temperature (500°C) during or after Bi deposition. Unlike many other nanoline systems, the lines formed by this nonequilibrium growth process have no detectable width dispersion. Although much attention has been given to the atomic geometery of the line, in this paper, we focus on how the lines can be used to create a majority 2×1 domain orientation. It is demonstrated that the Bi lines can be used to produce a single-domain orientation on Si(001) if the lines are grown on Si(001) surfaces with a regular distribution of single height steps. This is a compelling example of how a nanoscale motif can be used to modify mesoscopic surface structure on Si(001).