REinforcement learning based Adaptive samPling: REAPing Rewards by Exploring Protein Conformational Landscapes

One of the key limitations of Molecular Dynamics simulations is the computational intractability of sampling protein conformational landscapes associated with either large system size or long timescales. To overcome this bottleneck, we present the REinforcement learning based Adaptive samPling (REAP) algorithm that aims to efficiently sample conformational space by learning the relative importance of each reaction coordinate as it samples the landscape. To achieve this, the algorithm uses concepts from the field of reinforcement learning, a subset of machine learning, which rewards sampling along important degrees of freedom and disregards others that do not facilitate exploration or exploitation. We demonstrate the effectiveness of REAP by comparing the sampling to long continuous MD simulations and least-counts adaptive sampling on two model landscapes (L-shaped and circular), and realistic systems such as alanine dipeptide and Src kinase. In all four systems, the REAP algorithm consistently demonstrates its ability to explore conformational space faster than the other two methods when comparing the expected values of the landscape discovered for a given amount of time. The key advantage of REAP is on-the-fly estimation of the importance of collective variables, which makes it particularly useful for systems with limited structural information

Self-Diffusion in 2D Dusty Plasma Liquids: Numerical Simulation Results

We perform Brownian dynamics simulations for studying the self-diffusion in two-dimensional (2D) dusty plasma liquids, in terms of both mean-square displacement and velocity autocorrelation function (VAF). Super-diffusion of charged dust particles has been observed to be most significant at infinitely small damping rate $\gamma$ for intermediate coupling strength, where the long-time asymptotic behavior of VAF is found to be the product of $t^{-1}$ and $\exp{(-\gamma t)}$. The former represents the prediction of early theories in 2D simple liquids and the latter the VAF of a free Brownian particle. This leads to a smooth transition from super-diffusion to normal diffusion, and then to sub-diffusion with an increase of the damping rate. These results well explain the seemingly contradictory scattered in recent classical molecular dynamics simulations and experiments of dusty plasmas.Comment: 10 pages 5 figures, accepted by PR

Risk factors for acute exacerbations of COPD in a primary care population: A retrospective observational cohort study

Objectives: To evaluate risk factors associated with exacerbation frequency in primary care. Information on exacerbations of chronic obstructive pulmonary disease (COPD) has mainly been generated by secondary care-based clinical cohorts. Design: Retrospective observational cohort study. Setting: Electronic medical records database (England and Wales). Participants: 58 589 patients with COPD aged ≥40 years with COPD diagnosis recorded between 1 April 2009 and 30 September 2012, and with at least 365 days of follow-up before and after the COPD diagnosis, were identified in the Clinical Practice Research Datalink. Mean age: 69 years; 47% female; mean forced expiratory volume in 1s 60% predicted. Outcome measures: Data on moderate or severe exacerbation episodes defined by diagnosis and/or medication codes 12 months following cohort entry were retrieved, together with demographic and clinical characteristics. Associations between patient characteristics and odds of having none versus one, none versus frequent (≥2) and one versus frequent exacerbations over 12 months follow-up were evaluated using multivariate logistic regression models. Results: During follow-up, 23% of patients had evidence of frequent moderate-to-severe COPD exacerbations (24% one; 53% none). Independent predictors of increased odds of having exacerbations during the follow-up, either frequent episodes or one episode, included prior exacerbations, increasing dyspnoea score, increasing grade of airflow limitation, females and prior or current history of several comorbidities (eg, asthma, depression, anxiety, heart failure and cancer). Conclusions: Primary care-managed patients with COPD at the highest risk of exacerbations can be identified by exploring medical history for the presence of prior exacerbations, greater COPD disease severity and co-occurrence of other medical conditions

Hysteresis in the Random Field Ising Model and Bootstrap Percolation

We study hysteresis in the random-field Ising model with an asymmetric distribution of quenched fields, in the limit of low disorder in two and three dimensions. We relate the spin flip process to bootstrap percolation, and show that the characteristic length for self-averaging $L^*$ increases as $exp(exp (J/\Delta))$ in 2d, and as $exp(exp(exp(J/\Delta)))$ in 3d, for disorder strength $\Delta$ much less than the exchange coupling J. For system size $1 << L < L^*$, the coercive field $h_{coer}$ varies as $2J - \Delta \ln \ln L$ for the square lattice, and as $2J - \Delta \ln \ln \ln L$ on the cubic lattice. Its limiting value is 0 for L tending to infinity, both for square and cubic lattices. For lattices with coordination number 3, the limiting magnetization shows no jump, and $h_{coer}$ tends to J.Comment: 4 pages, 4 figure

GPU Acceleration of Image Convolution using Spatially-varying Kernel

Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution technique is used. Particularly suitable for large-scale images is a computationally intensive spatially-varying kernel. The underlying algorithm is inherently massively parallel due to unique kernel generation at every pixel location. The spatially-varying kernel cannot be efficiently computed through the Convolution Theorem, and thus does not lend itself to acceleration by Fast Fourier Transform (FFT). This work presents results of accelerated implementation of the spatially-varying kernel image convolution in multi-cores with OpenMP and graphic processing units (GPUs). Typical speedups over ANSI-C were a factor of 50 and a factor of 1000 over the initial IDL implementation, demonstrating that the techniques are a practical and high impact path to terabyte-per-night image pipelines and petascale processing.Comment: 4 pages. Accepted to IEEE-ICIP 201

A study of the dynamics of the Intertropical Convergence Zone (ITCZ) in a symmetric atmosphere-ocean model

A numerical model of the circulation of a coupled axisymmetric atmosphere-ocean system was constructed to investigate the physical factors governing the location and intensity of the Intertropical Convergence Zone (ITCZ) over oceans and over land. The results of several numerical integrations are presented to illustrate the interaction of the individual atmospheric and oceanic circulations. It is shown that the ITCA cannot be located at the equator because the atmosphere-ocean system is unstable for lateral displacements of the ITCA from an equilibrium position at the equator

Molecular Actuator: Redox-Controlled Clam-Like Motion in a Bichromophoric Electron Donor

The one-electron oxidation of tetramethoxydibenzobicyclo[4.4.1]undecane (4) prompts it to undergo a clam-like electromechanical actuation into a cofacially π-stacked conformer as established by (i) electrochemical analysis, (ii) by the observation of the intense charge-resonance transition in the near IR region in its cation radical spectrum, and (iii) by X-ray crystallographic characterization of the isolated cation radical salt (4+• SbCl6−)