2,126 research outputs found
Elastic properties of 5d transition-metal carbides: An ab initio study
We have systematically studied the mechanical stability of group V transition
metal carbides TMC (TM = Hf, Ta, W, Re, Os, Ir, Pt, and Au) in the pyrite
and fluorite phase, by calculating their elastic constants within the density
functional theory scheme. It was found that all but ReC and OsC are
stable in pyrite phase. On the other hand, all metal carbides studied were
unstable in the fluorite phase.Comment: 7 pages, 4 figure
A direct primitive variable recovery scheme for hyperbolic conservative equations: the case of relativistic hydrodynamics
In this article we develop a Primitive Variable Recovery Scheme (PVRS) to
solve any system of coupled differential conservative equations. This method
obtains directly the primitive variables applying the chain rule to the time
term of the conservative equations. With this, a traditional finite volume
method for the flux is applied in order avoid violation of both, the entropy
and "Rankine-Hugoniot" jump conditions. The time evolution is then computed
using a forward finite difference scheme. This numerical technique evades the
recovery of the primitive vector by solving an algebraic system of equations as
it is often used and so, it generalises standard techniques to solve these kind
of coupled systems. The article is presented bearing in mind special
relativistic hydrodynamic numerical schemes with an added pedagogical view in
the appendix section in order to easily comprehend the PVRS. We present the
convergence of the method for standard shock-tube problems of special
relativistic hydrodynamics and a graphical visualisation of the errors using
the fluctuations of the numerical values with respect to exact analytic
solutions. The PVRS circumvents the sometimes arduous computation that arises
from standard numerical methods techniques, which obtain the desired primitive
vector solution through an algebraic polynomial of the charges.Comment: 19 pages, 6 figures, 2 tables. Accepted for publication in PLOS ON
Continuous Forest Fire Propagation in a Local Small World Network Model
This paper presents the development of a new continuous forest fire model
implemented as a weighted local small-world network approach. This new approach
was designed to simulate fire patterns in real, heterogeneous landscapes. The
wildland fire spread is simulated on a square lattice in which each cell
represents an area of the land's surface. The interaction between burning and
non-burning cells, in the present work induced by flame radiation, may be
extended well beyond nearest neighbors. It depends on local conditions of
topography and vegetation types. An approach based on a solid flame model is
used to predict the radiative heat flux from the flame generated by the burning
of each site towards its neighbors. The weighting procedure takes into account
the self-degradation of the tree and the ignition processes of a combustible
cell through time. The model is tested on a field presenting a range of slopes
and with data collected from a real wildfire scenario. The critical behavior of
the spreading process is investigated
Influence of biomaterial nanotopography on the adhesive and elastic properties of Staphylococcus aureus cells
Despite the well-known beneficial effects of biomaterial nanopatterning on host tissue integration, the influence of controlled nanoscale topography on bacterial colonisation and infection remains unknown. Therefore, the aim of the present study was to determine the nanoscale effect of surface nanopatterning on biomaterial colonisation by S. aureus, utilising AFM nanomechanics and single-cell force spectroscopy (SCFS). Nanoindentation of S. aureus bound to planar (PL) and nanopatterned (SQ) polycarbonate (PC) surfaces suggested two distinct areas of mechanical properties, consistent with a central bacterial cell surrounded by a capsullar component. Nevertheless, no differences in elastic moduli were found between bacteria bound to PL and SQ, suggesting a minor role of nanopatterning in bacterial cell elasticity. Furthermore, SCFS demonstrated increased adhesion forces and work between S. aureus and SQ surfaces at 0 s and 1 s contact times. Although WLC modelling showed similarities in contour lengths for attachment to both surfaces, Poisson analysis suggests increased short-range forces for the S. aureus–SQ interactions. In the case of S. aureus–PL, long-range forces were found to not only be dominant but also repulsive in nature, which may help explain the reduced adhesion forces observed during AFM probing. In conclusion, although surface nanopatterning does not significantly influence the elasticity of attached bacterial cells, it was found to promote the early-adhesion of S. aureus cells to the biomaterial surface
Cross-Scale Interactions Between Atmospheric and Hydrologic Processes in a Topographically Complex, Snow-Dominated Watershed as Revealed Through an Integrated Hydrologic Model
In much of the world, water for agricultural, domestic, and hydroelectric power generation uses are derived from snow-dominated mountain basins. In these regions, water management requires accurate and timely knowledge of runoff generation by snowmelt. This information is used to plan reservoir releases for downstream users and is generated by models of biophysical processes associated with varying degrees of fidelity to physical processes and/or spatial heterogeneities. The large variability in the characteristic spatial and temporal scales of atmospheric forcings, land-surface water and energy balance, and groundwater flow contribute to significant uncertainties in resolved hydrologic states and fluxes. Underlying sources of uncertainty in these models include difficulties in parameterizing nonlinear or unresolved processes, associated uncertainties in meteorological forcing data and parameters, as well as the large variability in characteristic spatial and temporal scales of atmospheric forcing, surface energy balance, and subsurface hydrological processes. These sources of uncertainty can introduce systematic biases when performing integrated atmospheric and hydrologic modeling. Reconciling these discrepancies while maintaining computational tractability remains a fundamental challenge in hydrologic modeling. This work investigates and quantifies the impacts of discrepancies in scales between distributed meteorological forcing data and modeled land surface and subsurface water flow at hillslope scales. In particular, we are interested in assessing hydrologic state variables and fluxes such as snow water equivalent, discharge, and soil water storage. Also, this work includes the evaluation of the outputs of integrated hydrologic models against observations for a particular set of environmental forcing data (i.e., spatially distributed, semi-distributed, and uniform). We also include an investigation of how the external forcings impact the estimation of snow prognostic and diagnostic variables, primarily snow water equivalent, by performing a global sensitivity analysis. Results of this work suggest that topography (e.g., slope, aspect and valley bottoms) is the primary physiographic variable that describes variations spatial patterns of snow water equivalent and soil water storage when hillslope-scale models are driven by atmospheric forcing characterized by a range of spatial resolutions. At the same time, simulations performed with spatially distributed and semi-distributed meteorological forcings revealed interesting interrelationships between different forcing variables during the snowmelt process. Of particular significance were relationships found between longwave radiation and other atmospheric forcings. Our global sensitivity analyses work allowed us to quantify the strength of first and second order interactions between forcing variables and the snowmelt process. This work has important implications for the use of atmospheric data and integrated hydrologic models in remote and ungauged areas and provides key insights regarding which forcing variables, if measured more precisely, may afford the most significant improvements in snowmelt predictions. In particular, this work has potential ramifications for the selection of forcing datasets for integrated hydrologic modeling experiment as well as for the design and development of observing system simulation experiments (OSSEs) in complex and snow-dominated landscapes
Detection of Anomalies and Novelties in Time Series with Self-Organizing Networks
This paper introduces the DANTE project: Detection of Anomalies and Novelties in Time sEries with self-organizing networks. The goal of this project is to evaluate several self-organizing networks in the detection of anomalies/novelties in dynamic data patterns. For this purpose, we first describe three standard clustering-based approaches which uses well-known self-organizing neural architectures, such as the SOM and the Fuzzy ART algorithms, and then present a novel approach based on the Operator Map (OPM) network. The OPM is a generalization of the SOM where neurons are regarded as temporal filters for dynamic patters. The OPM is used to build local adaptive filters for a given nonstationary time series. Non-parametric confidence intervals are then computed for the residuals of the local models and used as decision thresholds for detecting novelties/anomalies. Computer simulations are carried out to compare the performances of the aforementioned algorithms
Human Capital, Industry, Tourism and Economic Development of EU25 Regions
The role of human capital, industry and tourism in regional development is analysed by means of econometric models with data of both EU15 and the ten countries of the 2004's Enlargement. The study points to the need to improve economic policies at EU level, in order to increase production in the less developed regions and to get a higher degree of socio-economic convergence among EU regions. We analyse the main measures that have shown a positive impact on regional development during the last years
A new hydrodynamic spherical accretion exact solution and its quasi-spherical perturbations
We present an exact spherical accretion solution which modifies
the Bondi boundary condition of as to as . This change allows for simple power law solutions on the
density and infall velocity fields, ranging from a cold empty free-fall
condition where pressure tends to zero, to a hot hydrostatic equilibrium limit
with no infall velocity. As in the case of the Bondi solution, a maximum
accretion rate appears. As in the case of the Bondi solution, no
sonic radius appears, this time however, because the flow is always
characterised by a constant Mach number. This number equals 1 for the case of
the maximum accretion rate, diverges towards the cold empty state, and becomes
subsonic towards the hydrostatic equilibrium limit. It can be shown that in the
limit as { }, the Bondi solution tends to the new solution presented,
{ extending the validity of the Bondi accretion value to} cases where the
accretion density profile does not remain at a fixed constant value out to
infinity. We then explore small deviations from sphericity and the presence of
angular momentum through an analytic perturbative analysis. Such perturbed
solutions yield a rich phenomenology through density and velocity fields in
terms of Legendre polynomials, which we begin to explore for simple angular
velocity boundary conditions having zeros on the plane and pole. The new
solution presented provides complementary physical insight into accretion
problems in general.Comment: Accepted for publication in the ApJ. 10 figures, extended comparison
to observations and first numerical tests include
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