Diffusion-limited reactions on disordered surfaces with continuous distributions of binding energies

We study the steady state of a stochastic particle system on a two-dimensional lattice, with particle influx, diffusion and desorption, and the formation of a dimer when particles meet. Surface processes are thermally activated, with (quenched) binding energies drawn from a \emph{continuous} distribution. We show that sites in this model provide either coverage or mobility, depending on their energy. We use this to analytically map the system to an effective \emph{binary} model in a temperature-dependent way. The behavior of the effective model is well-understood and accurately describes key quantities of the system: Compared with discrete distributions, the temperature window of efficient reaction is broadened, and the efficiency decays more slowly at its ends. The mapping also explains in what parameter regimes the system exhibits realization dependence.Comment: 23 pages, 8 figures. Submitted to: Journal of Statistical Mechanics: Theory and Experimen

A General Limitation on Monte Carlo Algorithms of Metropolis Type

We prove that for any Monte Carlo algorithm of Metropolis type, the autocorrelation time of a suitable ``energy''-like observable is bounded below by a multiple of the corresponding ``specific heat''. This bound does not depend on whether the proposed moves are local or non-local; it depends only on the distance between the desired probability distribution $\pi$ and the probability distribution $\pi^{(0)}$ for which the proposal matrix satisfies detailed balance. We show, with several examples, that this result is particularly powerful when applied to non-local algorithms.Comment: 8 pages, LaTeX plus subeqnarray.sty (included at end), NYU-TH-93/07/01, IFUP-TH33/9

Asymptotic Scaling in the Two-Dimensional O(3)O(3) σ\sigma-Model at Correlation Length 10510^5

We carry out a high-precision Monte Carlo simulation of the two-dimensional $O(3)$-invariant $\sigma$-model at correlation lengths $\xi$ up to $\sim 10^5$. Our work employs a new and powerful method for extrapolating finite-volume Monte Carlo data to infinite volume, based on finite-size-scaling theory. We discuss carefully the systematic and statistical errors in this extrapolation. We then compare the extrapolated data to the renormalization-group predictions. The deviation from asymptotic scaling, which is $\approx 25\%$ at $\xi \sim 10^2$, decreases to $\approx 4\%$ at $\xi \sim 10^5$.Comment: 11 pages including 3 figures, 278964 bytes Postscript (changed storage format

Can Inhibitor-Resistant Substitutions in The Mycobacterium Tuberculosis β-Lactamase BlaC Lead to Clavulanate Resistance?: A Biochemical Rationale for The Use of β-Lactam–β-Lactamase Inhibitor Combinations

The current emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis calls for novel treatment strategies. Recently, BlaC, the principal β-lactamase of Mycobacterium tuberculosis, was recognized as a potential therapeutic target. The combination of meropenem and clavulanic acid, which inhibits BlaC, was found to be effective against even extensively drug-resistant M. tuberculosis strains when tested in vitro. Yet there is significant concern that drug resistance against this combination will also emerge. To investigate the potential of BlaC to evolve variants resistant to clavulanic acid, we introduced substitutions at important amino acid residues of M. tuberculosis BlaC (R220, A244, S130, and T237). Whereas the substitutions clearly led to in vitro clavulanic acid resistance in enzymatic assays but at the expense of catalytic activity, transformation of variant BlaCs into an M. tuberculosis H37Rv background revealed that impaired inhibition of BlaC did not affect inhibition of growth in the presence of ampicillin and clavulanate. From these data we propose that resistance to β-lactam–β-lactamase inhibitor combinations will likely not arise from structural alteration of BlaC, therefore establishing confidence that this therapeutic modality can be part of a successful treatment regimen against M. tuberculosis

Can Inhibitor-Resistant Substitutions in The Mycobacterium Tuberculosis β-Lactamase BlaC Lead to Clavulanate Resistance?: A Biochemical Rationale for The Use of β-Lactam–β-Lactamase Inhibitor Combinations

The current emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis calls for novel treatment strategies. Recently, BlaC, the principal β-lactamase of Mycobacterium tuberculosis, was recognized as a potential therapeutic target. The combination of meropenem and clavulanic acid, which inhibits BlaC, was found to be effective against even extensively drug-resistant M. tuberculosis strains when tested in vitro. Yet there is significant concern that drug resistance against this combination will also emerge. To investigate the potential of BlaC to evolve variants resistant to clavulanic acid, we introduced substitutions at important amino acid residues of M. tuberculosis BlaC (R220, A244, S130, and T237). Whereas the substitutions clearly led to in vitro clavulanic acid resistance in enzymatic assays but at the expense of catalytic activity, transformation of variant BlaCs into an M. tuberculosis H37Rv background revealed that impaired inhibition of BlaC did not affect inhibition of growth in the presence of ampicillin and clavulanate. From these data we propose that resistance to β-lactam–β-lactamase inhibitor combinations will likely not arise from structural alteration of BlaC, therefore establishing confidence that this therapeutic modality can be part of a successful treatment regimen against M. tuberculosis

A strong-coupling analysis of two-dimensional O(N) sigma models with N≥3N\geq 3 on square, triangular and honeycomb lattices

Recently-generated long strong-coupling series for the two-point Green's functions of asymptotically free ${\rm O}(N)$ lattice $\sigma$ models are analyzed, focusing on the evaluation of dimensionless renormalization-group invariant ratios of physical quantities and applying resummation techniques to series in the inverse temperature $\beta$ and in the energy $E$. Square, triangular, and honeycomb lattices are considered, as a test of universality and in order to estimate systematic errors. Large-$N$ solutions are carefully studied in order to establish benchmarks for series coefficients and resummations. Scaling and universality are verified. All invariant ratios related to the large-distance properties of the two-point functions vary monotonically with $N$, departing from their large-$N$ values only by a few per mille even down to $N=3$.Comment: 53 pages (incl. 5 figures), tar/gzip/uuencode, REVTEX + psfi

Multi-Grid Monte Carlo via XYXY Embedding. II. Two-Dimensional SU(3)SU(3) Principal Chiral Model

We carry out a high-precision simulation of the two-dimensional $SU(3)$ principal chiral model at correlation lengths $\xi$ up to $\sim 4 \times 10^5$, using a multi-grid Monte Carlo (MGMC) algorithm and approximately one year of Cray C-90 CPU time. We extrapolate the finite-volume Monte Carlo data to infinite volume using finite-size-scaling theory, and we discuss carefully the systematic and statistical errors in this extrapolation. We then compare the extrapolated data to the renormalization-group predictions. The deviation from asymptotic scaling, which is $\approx 12$ at $\xi \sim 25$, decreases to $\approx 2$ at $\xi \sim 4 \times 10^5$. We also analyze the dynamic critical behavior of the MGMC algorithm using lattices up to $256 \times 256$, finding the dynamic critical exponent $z_{int,{\cal M}^2} \approx 0.45 \pm 0.02$ (subjective 68% confidence interval). Thus, for this asymptotically free model, critical slowing-down is greatly reduced compared to local algorithms, but not completely eliminated.Comment: self-unpacking archive including .tex, .sty and .ps files; 126 pages including all figure

Health promotion networks in two districts in Bavaria, Germany: an exploratory case study mapping networks with respect to thematic agenda and location

IntroductionBuilding networks is an essential part of health promotion. However, network analysis remains relatively unexplored in this field. This study introduces a new technique that maps thematic agendas and geographical locations of health promotion actors.MethodsThis case study used elements of quantitative and qualitative methods to analyse network data. We used empirical data from two networks in Bavaria, a federal state of Germany.ResultsWe identified a total of 55 actors in the first network and 64 actors in the second. We categorized the thematic agenda of actors according to their main field of work: “healthy childhood development,” “healthy middle age phase,” “healthy ageing,” “health equity in all phases of life.” One network showed a significant surplus of actors that focus on “healthy ageing.” We combined and analysed data from both networks collectively. Two districts with no health promotion actors within their geographical borders were identified. To put geographical gaps into context, data about deprivation and age was included.DiscussionResults identified geographical areas with high need for support from health promotion actors. Through comparison of our results with existing literature, we derived potential network strategies for further successful networking. This study adds a new perspective to characterize health promotion networks by mapping them thematically and geographically. The concept can be used to give health promotion organisations relevant insight into network structures. This can improve decision-making processes concerning partnership strategy and finally lead to a positive health impact. Hence, our findings encourage further development of this technique and other networking methods in the field of health equity and health promotion