Comparison of Italian and Hungarian Black Spot Ranking

AbstractBlack spot ranking is an important tool for finding the sites with potential safety improvement on the road network. The EU Directive on Road Infrastructure Safety Management also demands the ranking of high accident concentration sites. This paper gives an introduction to localizing high accident concentration sites and the indicators used by Italy and Hungary. Accident and traffic volume data are gathered for motorway sections from both countries. Safety ranking is made using two conventional indicators, absolute number of accidents and accident rate. A more sophisticated ranking using the Empirical Bayes method is applied. Expected average crash frequency with Empirical Bayes adjustment is calculated. Based on the estimation of the crash frequency, the Critical Crash Rate (CCR) was added to identify and rank black spots. This additional performance measure is able to take into account traffic volume as required by the EU Directive. Results of the Empirical Bayes method are compared with the conventional procedures. It is concluded that the results are not comparable; inasmuch as there are modifications in the order of black spots. Based on the comparison of results recommendations are given to change the practice in both countries

Effects of surface modifications on molecular diffusion in mesoporous catalytic materials

In this work, we use pulsed-field gradient (PFG) NMR to probe molecular diffusion of liquids inside mesoporous structures and assess the influence of surface modifications, namely, deposition of palladium (Pd) nanoparticles over alumina (Al2O3) surfaces and passivation of titania (TiO2) surfaces with alkyl chains, on the diffusion pattern

Fixed-point elimination in the intuitionistic propositional calculus

It is a consequence of existing literature that least and greatest fixed-points of monotone polynomials on Heyting algebras-that is, the algebraic models of the Intuitionistic Propositional Calculus-always exist, even when these algebras are not complete as lattices. The reason is that these extremal fixed-points are definable by formulas of the IPC. Consequently, the $\mu$-calculus based on intuitionistic logic is trivial, every $\mu$-formula being equivalent to a fixed-point free formula. We give in this paper an axiomatization of least and greatest fixed-points of formulas, and an algorithm to compute a fixed-point free formula equivalent to a given $\mu$-formula. The axiomatization of the greatest fixed-point is simple. The axiomatization of the least fixed-point is more complex, in particular every monotone formula converges to its least fixed-point by Kleene's iteration in a finite number of steps, but there is no uniform upper bound on the number of iterations. We extract, out of the algorithm, upper bounds for such n, depending on the size of the formula. For some formulas, we show that these upper bounds are polynomial and optimal

Assortativity Decreases the Robustness of Interdependent Networks

It was recently recognized that interdependencies among different networks can play a crucial role in triggering cascading failures and hence system-wide disasters. A recent model shows how pairs of interdependent networks can exhibit an abrupt percolation transition as failures accumulate. We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the two interdependent networks significantly changes the critical density of failures that triggers the total disruption of the two-network system. Specifically, we find that the assortativity (i.e. the likelihood of nodes with similar degree to be connected) within a single network decreases the robustness of the entire system. The results of this study on the influence of assortativity may provide insights into ways of improving the robustness of network architecture, and thus enhances the level of protection of critical infrastructures

Statistical evolution of isotope composition of nuclear fragments

Calculations within the statistical multifragmentation model show that the neutron content of intermediate mass fragments can increase in the region of liquid-gas phase transition in finite nuclei. The model predicts also inhomogeneous distributions of fragments and their isospin in the freeze-out volume caused by an angular momentum and external long-range Coulomb field. These effects can take place in peripheral nucleus-nucleus collisions at intermediate energies and lead to neutron-rich isotopes produced in the midrapidity kinematic region.Comment: 14 pages with 4 figures. GSI preprint, Darmstadt, 200

Analysis of fragment yield ratios in the nuclear phase transition

The critical phenomena of the liquid-gas phase transition has been investigated in the reactions 78,86Kr+58,64Ni at beam energy of 35 MeV/nucleon using the Landau free energy approach with isospin asymmetry as an order parameter. Fits to the free energy of fragments showed three minima suggesting the system to be in the regime of a first order phase transition. The relation m =-{\partial}F/{\partial}H, which defines the order parameter and its conjugate field H, has been experimentally verified from the linear dependence of the mirror nuclei yield ratio data, on the isospin asymmetry of the source. The slope parameter, which is a measure of the distance from a critical temperature, showed a systematic decrease with increasing excitation energy of the source. Within the framework of the Landau free energy approach, isoscaling provided similar results as obtained from the analysis of mirror nuclei yield ratio data. We show that the external field is primarily related to the minimum of the free energy, which implies a modification of the source concentration \Delta used in isospin studies

Optimal interpolation of satellite and ground data for irradiance nowcasting at city scales

We use a Bayesian method, optimal interpolation, to improve satellite derived irradiance estimates at city-scales using ground sensor data. Optimal interpolation requires error covariances in the satellite estimates and ground data, which define how information from the sensor locations is distributed across a large area. We describe three methods to choose such covariances, including a covariance parameterization that depends on the relative cloudiness between locations. Results are computed with ground data from 22 sensors over a 75×80 km area centered on Tucson, AZ, using two satellite derived irradiance models. The improvements in standard error metrics for both satellite models indicate that our approach is applicable to additional satellite derived irradiance models. We also show that optimal interpolation can nearly eliminate mean bias error and improve the root mean squared error by 50%