VLA Observations of the Infrared Dark Cloud G19.30+0.07

We present Very Large Array observations of ammonia (NH3) (1,1), (2,2), and CCS (2_1-1_0) emission toward the Infrared Dark Cloud (IRDC) G19.30+0.07 at ~22GHz. The NH3 emission closely follows the 8 micron extinction. The NH3 (1,1) and (2,2) lines provide diagnostics of the temperature and density structure within the IRDC, with typical rotation temperatures of ~10 to 20K and NH3 column densities of ~10^15 cm^-2. The estimated total mass of G19.30+0.07 is ~1130 Msun. The cloud comprises four compact NH3 clumps of mass ~30 to 160 Msun. Two coincide with 24 micron emission, indicating heating by protostars, and show evidence of outflow in the NH3 emission. We report a water maser associated with a third clump; the fourth clump is apparently starless. A non-detection of 8.4GHz emission suggests that the IRDC contains no bright HII regions, and places a limit on the spectral type of an embedded ZAMS star to early-B or later. From the NH3 emission we find G19.30+0.07 is composed of three distinct velocity components, or "subclouds." One velocity component contains the two 24 micron sources and the starless clump, another contains the clump with the water maser, while the third velocity component is diffuse, with no significant high-density peaks. The spatial distribution of NH3 and CCS emission from G19.30+0.07 is highly anti-correlated, with the NH3 predominantly in the high-density clumps, and the CCS tracing lower-density envelopes around those clumps. This spatial distribution is consistent with theories of evolution for chemically young low-mass cores, in which CCS has not yet been processed to other species and/or depleted in high-density regions.Comment: 29 pages, 9 figures, accepted for publication by ApJ. Please contact the authors for higher resolution versions of the figure

Compact phases of polymers with hydrogen bonding

We propose an off-lattice model for a self-avoiding homopolymer chain with two different competing attractive interactions, mimicking the hydrophobic effect and the hydrogen bond formation respectively. By means of Monte Carlo simulations, we are able to trace out the complete phase diagram for different values of the relative strength of the two competing interactions. For strong enough hydrogen bonding, the ground state is a helical conformation, whereas with decreasing hydrogen bonding strength, helices get eventually destabilized at low temperature in favor of more compact conformations resembling $\beta$-sheets appearing in native structures of proteins. For weaker hydrogen bonding helices are not thermodynamically relevant anymore.Comment: 5 pages, 3 figures; revised version published in PR

What thermodynamic features characterize good and bad folders? Results from a simplified off-lattice protein model

The thermodynamics of the small SH3 protein domain is studied by means of a simplified model where each bead-like amino acid interacts with the others through a contact potential controlled by a 20x20 random matrix. Good folding sequences, characterized by a low native energy, display three main thermodynamical phases, namely a coil-like phase, an unfolded globule and a folded phase (plus other two phases, namely frozen and random coil, populated only at extremes temperatures). Interestingly, the unfolded globule has some regions already structured. Poorly designed sequences, on the other hand, display a wide transition from the random coil to a frozen state. The comparison with the analytic theory of heteropolymers is discussed

Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off

Bundling of graph edges (node-to-node connections) is a common technique to enhance visibility of overall trends in the edge structure of a large graph layout, and a large variety of bundling algorithms have been proposed. However, with strong bundling, it becomes hard to identify origins and destinations of individual edges. We propose a solution: we optimize edge coloring to differentiate bundled edges. We quantify strength of bundling in a flexible pairwise fashion between edges, and among bundled edges, we quantify how dissimilar their colors should be by dissimilarity of their origins and destinations. We solve the resulting nonlinear optimization, which is also interpretable as a novel dimensionality reduction task. In large graphs the necessary compromise is whether to differentiate colors sharply between locally occurring strongly bundled edges ("local bundles"), or also between the weakly bundled edges occurring globally over the graph ("global bundles"); we allow a user-set global-local tradeoff. We call the technique "peacock bundles". Experiments show the coloring clearly enhances comprehensibility of graph layouts with edge bundling.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

VLA Observations of the Infrared Dark Cloud G19.30+0.07

We present Very Large Array observations of ammonia (NH3) (1,1), (2,2), and CCS (2_1-1_0) emission toward the Infrared Dark Cloud (IRDC) G19.30+0.07 at ~22GHz. The NH3 emission closely follows the 8 micron extinction. The NH3 (1,1) and (2,2) lines provide diagnostics of the temperature and density structure within the IRDC, with typical rotation temperatures of ~10 to 20K and NH3 column densities of ~10^15 cm^-2. The estimated total mass of G19.30+0.07 is ~1130 Msun. The cloud comprises four compact NH3 clumps of mass ~30 to 160 Msun. Two coincide with 24 micron emission, indicating heating by protostars, and show evidence of outflow in the NH3 emission. We report a water maser associated with a third clump; the fourth clump is apparently starless. A non-detection of 8.4GHz emission suggests that the IRDC contains no bright HII regions, and places a limit on the spectral type of an embedded ZAMS star to early-B or later. From the NH3 emission we find G19.30+0.07 is composed of three distinct velocity components, or "subclouds." One velocity component contains the two 24 micron sources and the starless clump, another contains the clump with the water maser, while the third velocity component is diffuse, with no significant high-density peaks. The spatial distribution of NH3 and CCS emission from G19.30+0.07 is highly anti-correlated, with the NH3 predominantly in the high-density clumps, and the CCS tracing lower-density envelopes around those clumps. This spatial distribution is consistent with theories of evolution for chemically young low-mass cores, in which CCS has not yet been processed to other species and/or depleted in high-density regions.Comment: 29 pages, 9 figures, accepted for publication by ApJ. Please contact the authors for higher resolution versions of the figure

Analysis of strain and stacking faults in single nanowires using Bragg coherent diffraction imaging

Coherent diffraction imaging (CDI) on Bragg reflections is a promising technique for the study of three-dimensional (3D) composition and strain fields in nanostructures, which can be recovered directly from the coherent diffraction data recorded on single objects. In this article we report results obtained for single homogeneous and heterogeneous nanowires with a diameter smaller than 100 nm, for which we used CDI to retrieve information about deformation and faults existing in these wires. The article also discusses the influence of stacking faults, which can create artefacts during the reconstruction of the nanowire shape and deformation.Comment: 18 pages, 6 figures Submitted to New Journal of Physic

Multidimensional Borg-Levinson Theorem

We consider the inverse problem of the reconstruction of a Schr\"odinger operator on a unknown Riemannian manifold or a domain of Euclidean space. The data used is a part of the boundary $\Gamma$ and the eigenvalues corresponding to a set of impedances in the Robin boundary condition which vary on $\Gamma$. The proof is based on the analysis of the behaviour of the eigenfunctions on the boundary as well as in perturbation theory of eigenvalues. This reduces the problem to an inverse boundary spectral problem solved by the boundary control method

Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized

Understanding protein structure is of crucial importance in science, medicine and biotechnology. For about two decades, knowledge based potentials based on pairwise distances -- so-called "potentials of mean force" (PMFs) -- have been center stage in the prediction and design of protein structure and the simulation of protein folding. However, the validity, scope and limitations of these potentials are still vigorously debated and disputed, and the optimal choice of the reference state -- a necessary component of these potentials -- is an unsolved problem. PMFs are loosely justified by analogy to the reversible work theorem in statistical physics, or by a statistical argument based on a likelihood function. Both justifications are insightful but leave many questions unanswered. Here, we show for the first time that PMFs can be seen as approximations to quantities that do have a rigorous probabilistic justification: they naturally arise when probability distributions over different features of proteins need to be combined. We call these quantities reference ratio distributions deriving from the application of the reference ratio method. This new view is not only of theoretical relevance, but leads to many insights that are of direct practical use: the reference state is uniquely defined and does not require external physical insights; the approach can be generalized beyond pairwise distances to arbitrary features of protein structure; and it becomes clear for which purposes the use of these quantities is justified. We illustrate these insights with two applications, involving the radius of gyration and hydrogen bonding. In the latter case, we also show how the reference ratio method can be iteratively applied to sculpt an energy funnel. Our results considerably increase the understanding and scope of energy functions derived from known biomolecular structures

A Regularized Graph Layout Framework for Dynamic Network Visualization

Many real-world networks, including social and information networks, are dynamic structures that evolve over time. Such dynamic networks are typically visualized using a sequence of static graph layouts. In addition to providing a visual representation of the network structure at each time step, the sequence should preserve the mental map between layouts of consecutive time steps to allow a human to interpret the temporal evolution of the network. In this paper, we propose a framework for dynamic network visualization in the on-line setting where only present and past graph snapshots are available to create the present layout. The proposed framework creates regularized graph layouts by augmenting the cost function of a static graph layout algorithm with a grouping penalty, which discourages nodes from deviating too far from other nodes belonging to the same group, and a temporal penalty, which discourages large node movements between consecutive time steps. The penalties increase the stability of the layout sequence, thus preserving the mental map. We introduce two dynamic layout algorithms within the proposed framework, namely dynamic multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL). We apply these algorithms on several data sets to illustrate the importance of both grouping and temporal regularization for producing interpretable visualizations of dynamic networks.Comment: To appear in Data Mining and Knowledge Discovery, supporting material (animations and MATLAB toolbox) available at http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_201

Sports injuries in adults: overview of clinical examination and management

A wide variety of anatomical structures can be involved in a sports injury. To return to play as soon as possible is of utmost importance to an athlete, and in order to achieve this, a correct, all-inclusive diagnosis, a well-focused treatment plan, and a management plan that strives to offer protection are essential. This article aims to give an overview of acute and overuse (chronic) sports injuries in adults, the approach to an accurate diagnosis and the management strategies that are available. A literature review was conducted of scientific journals, text and internet material, including a Medline and PubMed search. Literature was selected for its in-depth data and well-researched information. Key search terms included "acute and overuse injuries", as well as "sports injuries diagnosis and management" to address current and relevant scientific data on the examination and management of sports injuries in adults. The literature review indicated that sports injuries (both acute and overuse) are increasing in number due to the growing interest in physical activity and sport, as well as the enhanced intensity of training programmes. Adults are vulnerable to both types of sports injuries, and the age of occurrence of overuse injuries varies in competitive and non-competitive athletes. The importance of making an accurate diagnosis cannot be overemphasised. To assist the clinician in making an accurate diagnosis, a comprehensive history, physical examination and appropriate special investigations are mandatory. Familiarity with the demands of the athlete's sport may also prove useful. The approach to the management of acute and overuse injuries differs, with the emphasis in acute injuries being on treating the effect (torn, broken, displaced) and in chronic injuries on treating the cause (intrinsic or extrinsic). There have been numerous advances in the management of sports injuries, however further research is still warranted in this area. Follow-up articles will focus more in-depth on specifics with regard to clinical examination, special investigations and management options