Capture numbers and islands size distributions in models of submonolayer surface growth

The capture numbers entering the rate equations (RE) for submonolayer film growth are determined from extensive kinetic Monte Carlo (KMC) simulations for simple representative growth models yielding point, compact, and fractal island morphologies. The full dependence of the capture numbers on island size, and on both the coverage and the D/F ratio between the adatom diffusion coefficient D and deposition rate F is determined. Based on this information, the RE are solved to give the RE island size distribution (RE-ISD). The RE-ISDs are shown to agree well with the corresponding KMC-ISDs for all island morphologies. For compact morphologies, however, this agreement is only present for coverages smaller than about 5% due to a significantly increased coalescence rate compared to fractal morphologies. As found earlier, the scaled KMC-ISDs as a function of scaled island size approach, for fixed coverage, a limiting curve for D/F going to infinity. Our findings provide evidence that the limiting curve is independent of the coverage for point islands, while the results for compact and fractal island morphologies indicate a dependence on the coverage.Comment: 13 pages, 12 figure

Island size distributions in submonolayer growth: successful prediction by mean field theory with coverage dependent capture numbers

We show that mean-field rate equations for submonolayer growth can successfully predict island size distributions in the pre-coalescence regime if the full dependence of capture numbers on both the island size and the coverage is taken into account. This is demonstrated by extensive Kinetic Monte Carlo simulations for a growth kinetics with hit and stick aggregation. A detailed analysis of the capture numbers reveals a nonlinear dependence on the island size for small islands. This nonlinearity turns out to be crucial for the successful prediction of the island size distribution and renders an analytical treatment based on a continuum limit of the mean-field rate equations difficult.Comment: 4 pages, 4 figue

Gun Homicide Rate Down 49% Since 1993 Peak - Public Unaware

National rates of gun homicide and other violent gun crimes are strikingly lower now than during their peak in the mid-1990s, paralleling a general decline in violent crime, according to a Pew Research Center analysis of government data. Beneath the long-term trend, though, are big differences by decade: Violence plunged through the 1990s, but has declined less dramatically since 2000.Despite national attention to the issue of firearm violence, most Americans are unaware that gun crime is lower today than it was two decades ago. According to a new Pew Research Center survey, today 56% of Americans believe gun crime is higher than 20 years ago and only 12% think it is lower.This report examines trends in firearm homicide, non-fatal violent gun crime victimization and non-fatal violent crime victimization overall since 1993. Its findings on firearm crime are based mainly on analysis of data from two federal agencies. Data from the Centers for Disease Control and Prevention, using information from death certificates, are the source of rates, counts and trends for all firearm deaths, homicide and suicide, unless otherwise specified. The Department of Justice's National Crime Victimization Survey, a household survey conducted by the Census Bureau, supplies annual estimates of non-fatal crime victimization, including those where firearms are used, regardless of whether the crimes were reported to police. Where relevant, this report also quotes from the FBI's Uniform Crime Reports

Influence of external magnetic fields on growth of alloy nanoclusters

Kinetic Monte Carlo simulations are performed to study the influence of external magnetic fields on the growth of magnetic fcc binary alloy nanoclusters with perpendicular magnetic anisotropy. The underlying kinetic model is designed to describe essential structural and magnetic properties of CoPt_3-type clusters grown on a weakly interacting substrate through molecular beam epitaxy. The results suggest that perpendicular magnetic anisotropy can be enhanced when the field is applied during growth. For equilibrium bulk systems a significant shift of the onset temperature for L1_2 ordering is found, in agreement with predictions from Landau theory. Stronger field induced effects can be expected for magnetic fcc-alloys undergoing L1_0 ordering.Comment: 10 pages, 3 figure

Improved feeding and forages at a crossroads: Farming systems approaches for sustainable livestock development in East Africa

Dairy development provides substantial potential economic opportunities for smallholder farmers in East Africa, but productivity is constrained by the scarcity of quantity and quality feed. Ruminant livestock production is also associated with negative environmental impacts, including greenhouse gas (GHG) emissions, air pollution, high water consumption, land-use change, and loss of biodiversity. Improved livestock feeding and forages have been highlighted as key entry point to sustainable intensification, increasing food security, and decreasing environmental trade-offs including GHG emission intensities. In this perspective article, we argue that farming systems approaches are essential to understand the multiple roles and impacts of forages in smallholder livelihoods. First, we outline the unique position of forages in crop-livestock systems and systemic obstacles to adoption that call for multidisciplinary thinking. Second, we discuss the importance of matching forage technologies with agroecological and socioeconomic contexts and niches, and systems agronomy that is required. Third, we demonstrate the usefulness of farming systems modeling to estimate multidimensional impacts of forages and for reducing agro-environmental trade-offs. We conclude that improved forages in East Africa are at a crossroads: if adopted by farmers at scale, they can be a cornerstone of pathways toward sustainable livestock systems in East Africa.</p

Hopping Transport in the Presence of Site Energy Disorder: Temperature and Concentration Scaling of Conductivity Spectra

Recent measurements on ion conducting glasses have revealed that conductivity spectra for various temperatures and ionic concentrations can be superimposed onto a common master curve by an appropriate rescaling of the conductivity and frequency. In order to understand the origin of the observed scaling behavior, we investigate by Monte Carlo simulations the diffusion of particles in a lattice with site energy disorder for a wide range of both temperatures and concentrations. While the model can account for the changes in ionic activation energies upon changing the concentration, it in general yields conductivity spectra that exhibit no scaling behavior. However, for typical concentrations and sufficiently low temperatures, a fairly good data collapse is obtained analogous to that found in experiment.Comment: 6 pages, 4 figure

Towards a neural hierarchy of time scales for motor control

Animals show remarkable rich motion skills which are still far from realizable with robots. Inspired by the neural circuits which generate rhythmic motion patterns in the spinal cord of all vertebrates, one main research direction points towards the use of central pattern generators in robots. On of the key advantages of this, is that the dimensionality of the control problem is reduced. In this work we investigate this further by introducing a multi-timescale control hierarchy with at its core a hierarchy of recurrent neural networks. By means of some robot experiments, we demonstrate that this hierarchy can embed any rhythmic motor signal by imitation learning. Furthermore, the proposed hierarchy allows the tracking of several high level motion properties (e.g.: amplitude and offset), which are usually observed at a slower rate than the generated motion. Although these experiments are preliminary, the results are promising and have the potential to open the door for rich motor skills and advanced control

A Survey on Continuous Time Computations

We provide an overview of theories of continuous time computation. These theories allow us to understand both the hardness of questions related to continuous time dynamical systems and the computational power of continuous time analog models. We survey the existing models, summarizing results, and point to relevant references in the literature

Turing degrees of limit sets of cellular automata

Cellular automata are discrete dynamical systems and a model of computation. The limit set of a cellular automaton consists of the configurations having an infinite sequence of preimages. It is well known that these always contain a computable point and that any non-trivial property on them is undecidable. We go one step further in this article by giving a full characterization of the sets of Turing degrees of cellular automata: they are the same as the sets of Turing degrees of effectively closed sets containing a computable point