Density-based cluster algorithms for the identification of core sets

The core-set approach is a discretization method for Markov state models of complex molecular dynamics. Core-sets are disjoint metastable regions in the conformational space, which need to be known prior to the construction of the core-set model. We propose to use density-based cluster algorithms to identify the cores. We compare three different density-based cluster algorithms: the CNN, the DBSCAN and theJarvis-Patrick algorithm. While the core-set models based on the CNN and DBSCAN clustering are well-converged, constructing core-models based on the Jarvis-Patrick clustering cannot be recommended. In a well-converged core-set model, the number of core sets is up to an order of magnitude smaller than the number of states in a conventional Markov state model with comparable approximation error. Moreover, using the density-based clustering one can extend the core-set method to systems which are not strongly metastable. This is important for the practical application of the core-set method because most biologically interesting systems are only marginally metastable. The key point is to perform a hierarchical density-based clustering while monitoring the structure of metric matrix which appears in the core-set method. We test this approach on a molecular-dynamics simulation of a highly exible 14-residue peptide. The resulting core-set models have a high spatial resolution and can distinguish between conformationally similar yet chemically different structures, such as register-shifted hairpin structures

Effect of Dilution on Microstructure and Wear Resistance of a Fe-Based Hardfacing Alloy with a High Amount of Carbide-Forming Elements

Hardfacing is a widely diffused technique adopted to increase service life of parts for heavy-duty applications. Even though hardfacing alloys feature optimized chemistry and microstructure for specific service conditions, dilution with substrate modifies the resulting properties along a significant fraction of the deposit thickness. In particular, C and B diffusion to the substrate alters hypereutectic alloys reducing the carbide-forming ability andmodifying the solidification sequence. In the present paper, the effect of dilution on a hypereutectic Fe-C-B based alloy containing Cr and Mo was investigated. The effect of dilution on the reference alloy was studied by producing laboratory castings with an increased amount of Fe, up to 50 mass %. The obtained results were compared with the dilution of the hardfacing alloy cast on steel substrates. The microstructural evolution was analyzed by XRD (X-ray diffraction), differential scanning calorimetry (DSC), optical microscopy (OM), and scanning electron microscopy (SEM), whereas mechanical behaviour was evaluated by hardness measurements and wear resistance by pin-on-disc tests

A New Halocarbon Absorption Model Based on HITRAN Cross-Section Data and New Estimates of Halocarbon Instantaneous Clear-Sky Radiative Forcing

The article describes a new practical model for the infrared absorption of chlorofluorocarbons and other gases with dense spectra, based on high-resolution transmission molecular absorption database (HITRAN) absorption cross-sections. The model is very simple, consisting of frequency-dependent polynomial coefficients describing the pressure and temperature dependence of absorption. Currently it is implemented for the halocarbon species required by the Radiative Forcing Model Intercomparison Project. In cases where cross-section data is available at a range of different temperatures and pressures, this approach offers practical advantages compared to previously available options, and is traceable, since the polynomial coefficients follow directly from the laboratory spectra. The new model is freely available and has several important applications, notably in remote sensing and in developing advanced radiation schemes for global circulation models that include halocarbon absorption. For demonstration, the model is applied to the problem of computing instantaneous clear-sky halocarbon radiative efficiencies and present day radiative forcing. Results are in reasonable agreement with earlier assessments that were carried out with the less explicit Pinnock method, and thus broadly validate that method. Plain Language Summary Chlorofluorocarbons and other related gases have dense and complicated absorption spectra that can be measured in the laboratory. We bring such measurements to a form that can be used for simulations of the transfer of radiation through the atmosphere. Then we use the new model to calculate new estimates of the climate impact of these man-made gases. The results broadly validate earlier calculations that were done with a less explicit method

An infrared-submillimeter study of star-forming regions selected by the ISOSS 170um survey

Using the ISOPHOT Serendipity Survey (ISOSS) at 170um a sample of galactic star-forming regions exhibiting very cold dust temperatures (< 20 K) and high masses (> 100 M_sun) has been established. We characterise the star-forming content of five regions that were selected as potential sites for early stage high-mass star formation using SCUBA (JCMT) and Spitzer observations. In every region we identify one to four submillimeter clumps with projected sizes between 0.1 and 0.4 pc. The dust temperatures range from 11.6 to 21.3 K and the estimated clump masses are 2 to 166 M_sun. Towards the majority of submillimeter peaks we find point sources in the near- to mid-infrared. Most are interpreted as low-mass young stellar objects but we also detect very red sources. They probably represent very young and deeply embedded protostars that continue to accrete clump material and may reach higher masses. Several candidate intermediate-mass proto- or pre-main-sequence stars embedded in the clumps are identified. A subset of four clumps may be massive enough (> 100 M_sun) to form high-mass stars and accompanying clusters. The absence of stellar precursors with current masses in the high-mass regime leave the type of star formation occuring in the clumps unsettled. We confirm the presence of large fractions of cold material as derived from large-scale far-infrared measurements which dominates the emission of most clumps and suggests that the star-forming process will continue.Comment: 11 pages, 11 figures, accepted for publication in A&

Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology

Background: Monitoring spatial disease risk (e.g. identifying risk areas) is of great relevance in public health research, especially in cancer epidemiology. A common strategy uses case-control studies and estimates a spatial relative risk function (sRRF) via kernel density estimation (KDE). This study was set up to evaluate the sRRF estimation methods, comparing fixed with adaptive bandwidth-based KDE, and how they were able to detect ‘risk areas’ with case data from a population-based cancer registry. Methods: The sRRF were estimated within a defined area, using locational information on incident cancer cases and on a spatial sample of controls, drawn from a high-resolution population grid recognized as underestimating the resident population in urban centers. The spatial extensions of these areas with underestimated resident population were quantified with population reference data and used in this study as ‘true risk areas’. Sensitivity and specificity analyses were conducted by spatial overlay of the ‘true risk areas’ and the significant (α=.05) p-contour lines obtained from the sRRF. Results: We observed that the fixed bandwidth-based sRRF was distinguished by a conservative behavior in identifying these urban ‘risk areas’, that is, a reduced sensitivity but increased specificity due to oversmoothing as compared to the adaptive risk estimator. In contrast, the latter appeared more competitive through variance stabilization, resulting in a higher sensitivity, while the specificity was equal as compared to the fixed risk estimator. Halving the originally determined bandwidths led to a simultaneous improvement of sensitivity and specificity of the adaptive sRRF, while the specificity was reduced for the fixed estimator. Conclusion: The fixed risk estimator contrasts with an oversmoothing tendency in urban areas, while overestimating the risk in rural areas. The use of an adaptive bandwidth regime attenuated this pattern, but led in general to a higher false positive rate, because, in our study design, the majority of true risk areas were located in urban areas. However, there is a strong need for further optimizing the bandwidth selection methods, especially for the adaptive sRRF.<br