Asymptotic Capture-Number and Island-Size Distributions for One-Dimensional Irreversible Submonolayer Growth

Using a set of evolution equations [J.G. Amar {\it et al}, Phys. Rev. Lett. {\bf 86}, 3092 (2001)] for the average gap-size between islands, we calculate analytically the asymptotic scaled capture-number distribution (CND) for one-dimensional irreversible submonolayer growth of point islands. The predicted asymptotic CND is in reasonably good agreement with kinetic Monte-Carlo (KMC) results and leads to a \textit{non-divergent asymptotic} scaled island-size distribution (ISD). We then show that a slight modification of our analytical form leads to an analytic expression for the asymptotic CND and a resulting asymptotic ISD which are in excellent agreement with KMC simulations. We also show that in the asymptotic limit the self-averaging property of the capture zones holds exactly while the asymptotic scaled gap distribution is equal to the scaled CND.Comment: 4 pages, 1 figure, submitted to Phys. Rev.

Good methods for coping with missing data in decision trees

We propose a simple and effective method for dealing with missing data in decision trees used for classification. We call this approach 'missingness incorporated in attributes' (MIA). It is very closely related to the technique of treating 'missing' as a category in its own right, generalizing it for use with continuous as well as categorical variables. We show through a substantial data-based study of classification accuracy that MIA exhibits consistently good performance across a broad range of data types and of sources and amounts of missingness. It is competitive with the best of the rest (particularly, a multiple imputation EM algorithm method; EMMI) while being conceptually and computationally simpler. A simple combination of MIA and EMMI is slower but even more accurate

Diffusion of Pt dimers on Pt(111)

We report the results of a density-functional study of the diffusion of Pt dimers on the (111) surface of Pt. The calculated activation energy of 0.37 eV is in {\em exact} agreement with the recent experiment of Kyuno {\em et al.} \protect{[}Surf. Sci. {\bf 397}, 191 (1998)\protect{]}. Our calculations establish that the dimers are mobile at temperatures of interest for adatom diffusion, and thus contribute to mass transport. They also indicate that the diffusion path for dimers consists of a sequence of one-atom and (concerted) two-atom jumps.Comment: Pour pages postscript formatted, including one figure; submitted to Physical Review B; other papers of interest can be found at url http://www.centrcn.umontreal.ca/~lewi

Magic Islands and Barriers to Attachment: A Si/Si(111)7x7 Growth Model

Surface reconstructions can drastically modify growth kinetics during initial stages of epitaxial growth as well as during the process of surface equilibration after termination of growth. We investigate the effect of activation barriers hindering attachment of material to existing islands on the density and size distribution of islands in a model of homoepitaxial growth on Si(111)7x7 reconstructed surface. An unusual distribution of island sizes peaked around "magic" sizes and a steep dependence of the island density on the growth rate are observed. "Magic" islands (of a different shape as compared to those obtained during growth) are observed also during surface equilibration.Comment: 4 pages including 5 figures, REVTeX, submitted to Physical Review

Mass-Transport Models with Multiple-Chipping Processes

We study mass-transport models with multiple-chipping processes. The rates of these processes are dependent on the chip size and mass of the fragmenting site. In this context, we consider k-chip moves (where k = 1, 2, 3, ....); and combinations of 1-chip, 2-chip and 3-chip moves. The corresponding mean-field (MF) equations are solved to obtain the steady-state probability distributions, P (m) vs. m. We also undertake Monte Carlo (MC) simulations of these models. The MC results are in excellent agreement with the corresponding MF results, demonstrating that MF theory is exact for these models.Comment: 18 pages, 4 figures, To appear in European Physical Journal

Technical summary

The Working Group III (WGIII) contribution to the IPCC's Fifth Assessment Report (AR5) assesses literature on the scientific, technological, environmental, economic and social aspects of mitigation of climate change. It builds upon the WGIII contribution to the IPCC's Fourth Assessment Report (AR4), the Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) and previous reports and incorporates subsequent new findings and research. Throughout, the focus is on the implications of its findings for policy, without being prescriptive about the particular policies that governments and other important participants in the policy process should adopt. In light of the IPCC's mandate, authors in WGIII were guided by several principles when assembling this assessment: (1) to be explicit about mitigation options, (2) to be explicit about their costs and about their risks and opportunities vis-a-vis other development priorities, (3) and to be explicit about the underlying criteria, concepts, and methods for evaluating alternative policies. This summary offers the main findings of the report

Physical and biogeochemical controls on the variability in surface pH and calcium carbonate saturation states in the Atlantic sectors of the Arctic and Southern Oceans

Polar oceans are particularly vulnerable to ocean acidification due to their low temperatures and reduced buffering capacity, and are expected to experience extensive low pH conditions and reduced carbonate mineral saturations states (Ω) in the near future. However, the impact of anthropogenic CO2 on pH and Ω will vary regionally between and across the Arctic and Southern Oceans. Here we investigate the carbonate chemistry in the Atlantic sector of two polar oceans, the Nordic Seas and Barents Sea in the Arctic Ocean, and the Scotia and Weddell Seas in the Southern Ocean, to determine the physical and biogeochemical processes that control surface pH and Ω. High-resolution observations showed large gradients in surface pH (0.10–0.30) and aragonite saturation state (Ωar) (0.2–1.0) over small spatial scales, and these were particularly strong in sea-ice covered areas (up to 0.45 in pH and 2.0 in Ωar). In the Arctic, sea-ice melt facilitated bloom initiation in light-limited and iron replete (dFe>0.2 nM) regions, such as the Fram Strait, resulting in high pH (8.45) and Ωar (3.0) along the sea-ice edge. In contrast, accumulation of dissolved inorganic carbon derived from organic carbon mineralisation under the ice resulted in low pH (8.05) and Ωar (1.1) in areas where thick ice persisted. In the Southern Ocean, sea-ice retreat resulted in bloom formation only where terrestrial inputs supplied sufficient iron (dFe>0.2 nM), such as in the vicinity of the South Sandwich Islands where enhanced pH (8.3) and Ωar (2.3) were primarily due to biological production. In contrast, in the adjacent Weddell Sea, weak biological uptake of CO2 due to low iron concentrations (dFe<0.2 nM) resulted in low pH (8.1) and Ωar (1.6). The large spatial variability in both polar oceans highlights the need for spatially resolved surface data of carbonate chemistry variables but also nutrients (including iron) in order to accurately elucidate the large gradients experienced by marine organisms and to understand their response to increased CO2 in the future

Towards a simple global-standard bioassay for a key ecosystem process: organic-matter decomposition using cotton strips

Cotton-strip bioassays are increasingly used to assess ecosystem integrity because they provide a standardized measure of organic-matter decomposition – a fundamental ecosystem process. However, several different cotton- strip assays are routinely used, complicating the interpretation of results across studies, and hindering broader synthesis. Here, we compare the decay rates and assemblages of bacteria and fungi colonizing the three most commonly used cotton materials: Artist’s canvas, Calico cloth, and Empa fabric. Cotton strips from each material type were incubated in 10 streams that span a wide range of physicochemical properties across five ecoregions. Additionally, to evaluate responses to environmental stress without potentially confounding biogeographical effects, we deployed identical bioassays in five streams across an acidification gradient within a single ecoregion. Across all streams decomposition rates (as tensile strength loss [TSL]) differed among the three cotton ma- terials; Calico cloth decomposed fastest (time to 50% TSL [T50]=16.7d), followed by the Empa fabric (T50 = 18.3 d) and then Artist’s canvas (T50 = 21.4 d). Despite these differences, rates of TSL of the three cotton materials responded consistently to variation in environmental conditions; TSL of each fabric increased with stream temperature, dissolved-nutrient concentrations and acid-neutralizing capacity, although Artist’s canvas and Calico cloth were more sensitive than Empa fabric. Microbial communities were similar among the mate- rials, and values of community structure (e.g., phylotype richness and diversity) were comparable to those reported for decaying leaves in streams from the same region, the major natural basal carbon resource in forested-stream ecosystems. We present linear calibrations among pairs of assays so that past and future studies can be expressed in a “common currency” (e.g., Artist’s-fabric equivalents) ‘past and future studies’ repeated two times in the sentence. Lastly, given its relatively low within-site variability, and the large number of streams where it has been used (> 700 across the globe), we recommend Artist’s fabric for future work. These results show that cotton provides an effective and realistic standardized substrate for studying heterotrophic microbial assemblages, and acts as a reasonable proxy for more chemically complex forms of detritus. These findings add to growing evidence that cotton-strip bioassays are simple, effective and easily standardized indicators of het- erotrophic microbial activity and the ecosystem processes that result