Dynamic and static properties of the invaded cluster algorithm

Simulations of the two-dimensional Ising and 3-state Potts models at their critical points are performed using the invaded cluster (IC) algorithm. It is argued that observables measured on a sub-lattice of size l should exhibit a crossover to Swendsen-Wang (SW) behavior for l sufficiently less than the lattice size L, and a scaling form is proposed to describe the crossover phenomenon. It is found that the energy autocorrelation time tau(l,L) for an l*l sub-lattice attains a maximum in the crossover region, and a dynamic exponent z for the IC algorithm is defined according to tau_max ~ L^z. Simulation results for the 3-state model yield z=.346(.002) which is smaller than values of the dynamic exponent found for the SW and Wolff algorithms and also less than the Li-Sokal bound. The results are less conclusive for the Ising model, but it appears that z<.21 and possibly that tau_max ~ log L so that z=0 -- similar to previous results for the SW and Wolff algorithms.Comment: 21 pages with 12 figure

Dynamic Critical Behavior of the Swendsen-Wang Algorithm: The Two-Dimensional 3-State Potts Model Revisited

We have performed a high-precision Monte Carlo study of the dynamic critical behavior of the Swendsen-Wang algorithm for the two-dimensional 3-state Potts model. We find that the Li-Sokal bound ($\tau_{int,E} \geq const \times C_H$) is almost but not quite sharp. The ratio $\tau_{int,E} / C_H$ seems to diverge either as a small power ($\approx 0.08$) or as a logarithm.Comment: 35 pages including 3 figures. Self-unpacking file containing the LaTeX file, the needed macros (epsf.sty, indent.sty, subeqnarray.sty, and eqsection.sty) and the 3 Postscript figures. Revised version fixes a normalization error in \xi (with many thanks to Wolfhard Janke for finding the error!). To be published in J. Stat. Phys. 87, no. 1/2 (April 1997

The ability of hop extracts to reduce the methane production of methanobrevibacter ruminantium

Background. Methane emissions from agriculture are responsible for over 40% of the world’s greenhouse gas emissions. In the past, antibiotics were used to control methane production by animals, but concerns over the emergence and spread of antibiotic-resistant bacteria to humans have prompted a search for alternative approaches. Hops are the flowers of the hop plant Humulus lupulus. They have been used to feed cattle for many years and are known to contain antibacterial compounds, and their extracts have been shown to kill members of the Mycobacterium spp including Mycobacterium bovis, the causative agent of bovine tuberculosis as well as a number of human pathogens. In this study, hop extracts were studied for their ability to inhibit methane production from Methanobrevibacter ruminantium, a major methane-producing archaeon found in the rumen of cattle. Methods. Methanobrevibacter ruminantium M1T (DSM 1093) was grown at 37°C for 30 days, and the amount of methane produced at different time points during this period was measured using gas chromatography. The archaeon was exposed to commercial hop extracts (tetra-hydro-iso-alpha acid and beta acid) and to aqueous hop extracts of a range of hop variants, and their effect on methane production was determined. Results. All of the extracts reduced the level of methane production of M. ruminantium over the 30-day period compared to the negative control (sterile distilled water). The commercial hop extracts were the most effective at inhibiting methane production over the course of the experiment in contrast to the aqueous extracts, which showed a gradual reduction of inhibition with time. Conclusions. Hops contain compounds which inhibit methane production. Given that hops can be safely fed to cattle, this raises the possibility of rationally designing a feed strategy which could reduce greenhouse gas emissions and protect against bovine tuberculosis. This study recommends that further research be undertaken to further identifying bioactive components from hops and their efficacy against a range of archaea

Critical Behavior of Random Bond Potts Models

The effect of quenched impurities on systems which undergo first-order phase transitions is studied within the framework of the q-state Potts model. For large q a mapping to the random field Ising model is introduced which provides a simple physical explanation of the absence of any latent heat in 2D, and suggests that in higher dimensions such systems should exhibit a tricritical point with a correlation length exponent related to the exponents of the random field model by \nu = \nu_RF / (2 - \alpha_RF - \beta_RF). In 2D we analyze the model using finite-size scaling and conformal invariance, and find a continuous transition with a magnetic exponent \beta / \nu which varies continuously with q, and a weakly varying correlation length exponent \nu \approx 1. We find strong evidence for the multiscaling of the correlation functions as expected for such random systems.Comment: 13 pages, RevTeX. 4 figures included. Submitted to Phys.Rev.Let

Cluster variation - Pade` approximants method for the simple cubic Ising model

The cluster variation - Pade` approximant method is a recently proposed tool, based on the extrapolation of low/high temperature results obtained with the cluster variation method, for the determination of critical parameters in Ising-like models. Here the method is applied to the three-dimensional simple cubic Ising model, and new results, obtained with an 18-site basic cluster, are reported. Other techniques for extracting non-classical critical exponents are also applied and their results compared with those by the cluster variation - Pade` approximant method.Comment: 8 RevTeX pages, 3 PostScript figure

Dynamic Critical Behavior of a Swendsen-Wang-Type Algorithm for the Ashkin-Teller Model

We study the dynamic critical behavior of a Swendsen-Wang-type algorithm for the Ashkin--Teller model. We find that the Li--Sokal bound on the autocorrelation time ($\tau_{{\rm int},{\cal E}} \ge {\rm const} \times C_H$) holds along the self-dual curve of the symmetric Ashkin--Teller model, and is almost but not quite sharp. The ratio $\tau_{{\rm int},{\cal E}} / C_H$ appears to tend to infinity either as a logarithm or as a small power ($0.05 \leq p \leq 0.12$). In an appendix we discuss the problem of extracting estimates of the exponential autocorrelation time.Comment: 59 pages including 3 figures, uuencoded g-compressed ps file. Postscript size = 799740 byte

Chorea-related mutations in PDE10A result in aberrant compartmentalization and functionality of the enzyme

A robust body of evidence supports the concept that phosphodiesterase 10A (PDE10A) activity in the basal ganglia orchestrates the control of coordinated movement in human subjects. Although human mutations in the PDE10A gene manifest in hyperkinetic movement disorders that phenocopy many features of early Huntington’s disease, characterization of the maladapted molecular mechanisms and aberrant signaling processes that underpin these conditions remains scarce. Recessive mutations in the GAF-A domain have been shown to impair PDE10A function due to the loss of striatal PDE10A protein levels, but here we show that this paucity is caused by irregular intracellular trafficking and increased PDE10A degradation in the cytosolic compartment. In contrast to GAF-A mutants, dominant mutations in the GAF-B domain of PDE10A induce PDE10A misfolding, a common pathological phenotype in many neurodegenerative diseases. These data demonstrate that the function of striatal PDE10A is compromised in disorders where disease-associated mutations trigger a reduction in the fidelity of PDE compartmentalization

Monte Carlo Renormalization of the 3-D Ising model: Analyticity and Convergence

We review the assumptions on which the Monte Carlo renormalization technique is based, in particular the analyticity of the block spin transformations. On this basis, we select an optimized Kadanoff blocking rule in combination with the simulation of a d=3 Ising model with reduced corrections to scaling. This is achieved by including interactions with second and third neighbors. As a consequence of the improved analyticity properties, this Monte Carlo renormalization method yields a fast convergence and a high accuracy. The results for the critical exponents are y_H=2.481(1) and y_T=1.585(3).Comment: RevTeX, 4 PostScript file

Computing the Roughening Transition of Ising and Solid-On-Solid Models by BCSOS Model Matching

We study the roughening transition of the dual of the 2D XY model, of the Discrete Gaussian model, of the Absolute Value Solid-On-Solid model and of the interface in an Ising model on a 3D simple cubic lattice. The investigation relies on a renormalization group finite size scaling method that was proposed and successfully tested a few years ago. The basic idea is to match the renormalization group flow of the interface observables with that of the exactly solvable BCSOS model. Our estimates for the critical couplings are $\beta_R^{XY}=1.1199(1)$, $K_R^{DG}=0.6653(2)$ and $K_R^{ASOS}=0.80608(2)$ for the XY-model, the Discrete Gaussian model and the Absolute Value Solid-On-Solid model, respectively. For the inverse roughening temperature of the Ising interface we find $K_R^{Ising}= 0.40758(1)$. To the best of our knowledge, these are the most precise estimates for these parameters published so far.Comment: 25 pages, LaTeX file, no figure

Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species’ soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53% of felled, 39% of drilled, and 28% of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1–82.8 %) and averaged 9% across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13% in trees 10–30 cm DBH to 54%in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7% relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation, but also that it strongly covaries with tree size, taxonomy, habitat association, and soil resources, underscoring the need to account for tree community composition and edaphic variation in estimating carbon storage in tropical forests