From Small-Scale Dynamo to Isotropic MHD Turbulence

We consider the problem of incompressible, forced, nonhelical, homogeneous, isotropic MHD turbulence with no mean magnetic field. This problem is essentially different from the case with externally imposed uniform mean field. There is no scale-by-scale equipartition between magnetic and kinetic energies as would be the case for the Alfven-wave turbulence. The isotropic MHD turbulence is the end state of the turbulent dynamo which generates folded fields with small-scale direction reversals. We propose that the statistics seen in numerical simulations of isotropic MHD turbulence could be explained as a superposition of these folded fields and Alfven-like waves that propagate along the folds.Comment: kluwer latex, 7 pages, 7 figures; Proceedings of the International Workshop "Magnetic Fields and Star Formation: Theory vs. Observations", Madrid, 21-25 April 2003 -- published version (but the e-print is free of numerous typos introduced by the publisher

Usability evaluation of a research repository and collaboration website

This article reports results from an empirical usability evaluation of Human-Animal Bond Research Initiative Central as part of the effort to develop an open access research repository and collaboration platform for human-animal bond researchers. By repurposing and altering key features of the original HUBzero system, Human-Animal Bond Research Initiative Central hosts previously published materials from related disciplines and an extensive bibliography, in addition to traditional hub materials such as tools and datasets. Seven graduate students in the College of Veterinary Medicine at Purdue University participated in the usability evaluation. Tasks included exploring the system, finding an article in the repository, submitting an article to the repository, adding bibliographic information of an article to the repository, and using interaction features such as user groups. Participants also answered open questions regarding their overall experience and rated Human-Animal Bond Research Initiative Central\u27s usability using the System Usability Scale. Response measures included task successfulness, navigational steps, task time, participant comments, and behavior notes recorded by the researcher. Results of the evaluation showed that the overall user experience of Human-Animal Bond Research Initiative Central was satisfactory but also indicated a number of usability issues. Participants had difficulty inputting metadata such as resource type and author information when submitting an article to the repository. There were also interface design issues regarding layout and consistency. It is expected that findings from this study and the evaluation methodology can be extended to the development and evaluation of similar research repository systems

The onset of a small-scale turbulent dynamo at low magnetic Prandtl numbers

We study numerically the dependence of the critical magnetic Reynolds number Rmc for the turbulent small-scale dynamo on the hydrodynamic Reynolds number Re. The turbulence is statistically homogeneous, isotropic, and mirror--symmetric. We are interested in the regime of low magnetic Prandtl number Pm=Rm/Re<1, which is relevant for stellar convective zones, protostellar disks, and laboratory liquid-metal experiments. The two asymptotic possibilities are Rmc->const as Re->infinity (a small-scale dynamo exists at low Pm) or Rmc/Re=Pmc->const as Re->infinity (no small-scale dynamo exists at low Pm). Results obtained in two independent sets of simulations of MHD turbulence using grid and spectral codes are brought together and found to be in quantitative agreement. We find that at currently accessible resolutions, Rmc grows with Re with no sign of approaching a constant limit. We reach the maximum values of Rmc~500 for Re~3000. By comparing simulations with Laplacian viscosity, fourth-, sixth-, and eighth-order hyperviscosity and Smagorinsky large-eddy viscosity, we find that Rmc is not sensitive to the particular form of the viscous cutoff. This work represents a significant extension of the studies previously published by Schekochihin et al. 2004, PRL 92, 054502 and Haugen et al. 2004, PRE, 70, 016308 and the first detailed scan of the numerically accessible part of the stability curve Rmc(Re).Comment: 4 pages, emulateapj aastex, 2 figures; final version as published in ApJL (but with colour figures

MEPicides: Potent antimalarial prodrugs targeting isoprenoid biosynthesis

AbstractThe emergence of Plasmodium falciparum resistant to frontline therapeutics has prompted efforts to identify and validate agents with novel mechanisms of action. MEPicides represent a new class of antimalarials that inhibit enzymes of the methylerythritol phosphate (MEP) pathway of isoprenoid biosynthesis, including the clinically validated target, deoxyxylulose phosphate reductoisomerase (Dxr). Here we describe RCB-185, a lipophilic prodrug with nanomolar activity against asexual parasites. Growth of P. falciparum treated with RCB-185 was rescued by isoprenoid precursor supplementation, and treatment substantially reduced metabolite levels downstream of the Dxr enzyme. In addition, parasites that produced higher levels of the Dxr substrate were resistant to RCB-185. Notably, environmental isolates resistant to current therapies remained sensitive to RCB-185, the compound effectively treated sexually-committed parasites, and was both safe and efficacious in malaria-infected mice. Collectively, our data demonstrate that RCB-185 potently and selectively inhibits Dxr in P. falciparum, and represents a promising lead compound for further drug development.</jats:p

Cascade of Complexity in Evolving Predator-Prey Dynamics

We simulate an individual-based model that represents both the phenotype and genome of digital organisms with predator-prey interactions. We show how open-ended growth of complexity arises from the invariance of genetic evolution operators with respect to changes in the complexity, and that the dynamics which emerges is controlled by a non-equilibrium critical point. The mechanism is analogous to the development of the cascade in fluid turbulence.Comment: 5 pages, 3 figures; added comments on system size scaling and turbulence analogy, added error estimates of data collapse parameters. Slightly enhanced from the version which will appear in PR

Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation

The limited ability of Convolutional Neural Networks to generalize to images from previously unseen domains is a major limitation, in particular, for safety-critical clinical tasks such as dermoscopic skin cancer classification. In order to translate CNN-based applications into the clinic, it is essential that they are able to adapt to domain shifts. Such new conditions can arise through the use of different image acquisition systems or varying lighting conditions. In dermoscopy, shifts can also occur as a change in patient age or occurence of rare lesion localizations (e.g. palms). These are not prominently represented in most training datasets and can therefore lead to a decrease in performance. In order to verify the generalizability of classification models in real world clinical settings it is crucial to have access to data which mimics such domain shifts. To our knowledge no dermoscopic image dataset exists where such domain shifts are properly described and quantified. We therefore grouped publicly available images from ISIC archive based on their metadata (e.g. acquisition location, lesion localization, patient age) to generate meaningful domains. To verify that these domains are in fact distinct, we used multiple quantification measures to estimate the presence and intensity of domain shifts. Additionally, we analyzed the performance on these domains with and without an unsupervised domain adaptation technique. We observed that in most of our grouped domains, domain shifts in fact exist. Based on our results, we believe these datasets to be helpful for testing the generalization capabilities of dermoscopic skin cancer classifiers