Hard Core Component Research Articles

Outage in Motorway Multi-Lane VANETs With Hardcore Headway Distance Using Synthetic Traces

In this paper we analyze synthetic mobility traces generated for three-lane unidirectional motorway traffic to find that the locations of vehicles along a lane are better modeled by a hardcore point process instead of the widely-accepted Poisson point process (PPP). In order to capture the repulsion between successive vehicles while maintaining a level of analytical tractability, we make a simple extension to PPP: We model the inter-vehicle distance along a lane equal to the sum of a constant hardcore distance and an exponentially distributed random variable. We calculate the J-function and the Ripley's K-function for this hardcore point process. We fit its parameters to the available traces, and we illustrate that the higher the average speed along a lane, the more prominent the hardcore component becomes. In addition, we consider a transmitter-receiver link on the same lane, and we generate simple formulae for the moments of interference under reduced Palm measure for that lane, and without conditioning for other lanes. We illustrate that under Rayleigh fading a shifted-gamma approximation for the distribution of interference per lane provides a very good fit to the simulated outage probability using the synthetic traces, while the fit using the PPP is poor.

Progress on the Design Development for Hard Core Components for USDA Diagnostics at ITER

An ITER hard core component (HCC) is defined for each undesirable situation with cliff edge effect consequences. Such structure system components (SCCs) are designed to prevent these situations at nuclear power plants, as well as to return and maintain a safe state in the event such a situation occurs. Only two hard core situations can really lead to cliff edge effect unless HCCs are implemented to limit the consequences: extreme earthquake (SL-3) and multiples fire in tritium building initiated by SL-3. The equipment (window and/or shutter) that closes penetrations from both sides of gallery to outside (Diagnostic building, Tritium building, and Assembly building) are classified as HCCs and SIC-2. Design status of the HCC penetrations belong to US ITER diagnostic systems will be presented in this publication.

Hardcore smoking among continuing smokers in Canada 2004-2012.

Decline in adult smoking prevalence in Canada seems to have slowed, suggesting that smoking rate may have plateaued. It is unclear whether this, at least in part, can be interpreted as evidence that some groups or individuals are becoming less resistant to tobacco control measures. This study examined trends in the prevalence of hardcore smoking in Canada. A nationally representative sample of adult daily smokers was drawn from the Canadian Tobacco Use Monitoring Survey 2004 to 2012 (n = 13,861). Hardcore smokers were defined in two ways: Hardcore 1 comprised those that reported no quit attempt, no quit intention, and smoke their first cigarette within 30 min after awakening and hardcore 2 comprised hardcore 1 plus those smoking 15 or more cigarettes per day. Logistic regression was used to examine associations between hardcore measures and year and socio-demographic variables. Overall, there was no significant difference in hardcore smoking over time for the periods covered in this study. Analysis examining a single hardcore component, time-to-first cigarette (TTFC) after awakening as a measure of nicotine dependence showed similar results. A clear marked socioeconomic gradient in TTFC was found, those with university education (OR 0.46, 95 % CI 0.37-0.57), college (OR 0.51, 95 % CI 0.42-0.63), secondary (OR 0.68, 95 % CI 0.57-0.82) were significantly less likely to have TTFC ≤ 30 min compared with less than secondary education. This study does not support the hardening hypothesis when interpreted as the increase in hardcore smokers over time.

Why benzodiazepines are not going away

SummaryBenzodiazepines are still widely prescribed in psychiatry, mainly for the treatment of anxiety-related disorders. This is not because they are only taken by a hard core component of patients who are addicted and do not need them; it is because they remain the most effective and rapid acting of all drug treatments. Strategies for practitioners to use them more confidently are described.

The Use of Markov Chains to Estimate Destination Switching and Market Share

The Markov chain model provides researchers and policy makers with a means to predict travellers' choices of destination. This study predicts international tourist flows among three Asian countries and the USA, and provides a path for gauging the switching patterns of tourists from one country to another. Destination loyalty (hard core component) and the future market share for 2009 and 2010 were estimated. The findings provide necessary information to many interest groups, including government policy makers, travel companies, airline companies and researchers.

Forces between like-charged plates in electrolyte solution: ion-solvent packing versus electrostatic effects.

The anisotropic hypernetted-chain approximation is solved numerically for mixtures of neutral hard-sphere solvent particles and divalent counterions between charged plates. A detailed analysis of the different components of force acting between the plates is given. At separations of a few solvent diameters, it is shown that even at relatively high surface charge and moderate solvent density, the ionic contribution to the force tends to be dominated by the hard-core or packing component. If the ions and solvent particles are of equal size, then the net pressure between the plates can be reasonably well approximated by adding the pressures of pure one-component ionic and solvent systems. However, if the ion and solvent diameters are significantly different the pressure curve is more complex, and the simple superposition of the ionic and solvent pressures no longer works. For this case, we show that to a good approximation it is still possible to divide the pressure into electrostatic and hard-core components, but now the appropriate hard-core system must itself be a mixture of neutral hard spheres.

Bertlmann-Martin inequality for a weakly bound particle

The Bertlmann-Martin (BM) inequality for the rms radius is checked against the exact value in the case of a particle in a weak central potential having a single bound state. A number of usual potentials are considered in one and three dimensions. The BM inequality is poorly saturated but the correction factor needed to recover the exact rms radius is weakly depending on the shape of the potential, except for the Hulth?n potential. For potentials having a hard-core component, we found that , which depends on the bound-state energy, tends to a universal curve as the hard core radius increases.

Square-well and square-shoulder fluids: Simulation and equations of state

We explore the properties of a simple analytic equation of state, proposed by Heyes and Woodcock [D. M. Heyes and L. V. Woodcock, Mol. Phys. 59, 1369 (1986)] which is a development of the van der Waals equation of state, improved with an analytically simple yet accurate hard-core component for the compressibility factor. We call this the hard-sphere van der Waals (HSvdW) equation of state. We show, for the first time, that the HSvdW equation of state gives analytic values for the critical parameters and that it gives significantly more realistic values for the critical density than the van der Waals and other cubic equations of state. For single-component square wells of arbitrary well width, the HSvdW equation of state also produces a critical temperature and pressure in agreement with those from a recent Gibbs Monte Carlo simulation study. The chief advantage over a similar equation of state with an alternative form for the hard-core compressibility factor, such as Carnahan–Starling, is that it leads to more tractable analytic expressions for thermodynamic properties without loss of accuracy. Extensive Monte Carlo computer simulations of square-well (SW) and square-shoulder (SS) fluids with variable well width have been performed. We have calculated the compressibility factor, internal energy, pair distribution functions, and coordination number (average number of particles within the soft-shell interaction range). We have also determined the gas–liquid coexistence curve using the particle insertion chemical potential method for the square-well case, λ=1.5σ, where λ is the diameter of the soft interaction shell. This agrees well with the Gibbs ensemble simulation coexistence curve. For the purpose of improving the attractive component of the HSvdW equation of state, we have made use of the SW and SS simulation data and that of other workers to develop another new simple equation of state based on the quasichemical local coordination number approximation (QCA) which is a lattice model of a fluid. The QCA is improved to include the local coordination of the hard-sphere fluid. Present adaptations extend the range of earlier QCA models to arbitrary well width and sign of the well (either attractive well or repulsive shoulder). The simulation coordination numbers are reproduced well by the present model, although there is little improvement in the overall equation of state over the simpler HSvdW.

X-rays from Eta Carinae

X-ray observations of Eta Car obtained with the high-resolution imager and solid-state spectrometer of the Einstein observatory are reported and interpreted in terms of a two-shell model. A soft component with temperature 5 million K is located in the expanding outer shell, and the hard core component with temperature 80 million K is attributed to the interaction of a high-velocity stellar wind from the massive central object with the inner edge of a dust shell. Model calculations based on comparison with optical and IR data permit estimation of the mass of the outer shell (0.004 solar mass), the mass of the dust shell (3 solar mass), and the total shell expansion energy (less than 2 x 10 to the 49th ergs).

Poisson limits for a hard-core clustering model

Let X 1 n ,…, X > nn denote the locations of n points in a bounded, γ-dimensional, Euclidean region D n which has positive γ-dimensional Lebesgue measure μ( D n ). Let { Y n ( r): r > 0} be the interpoint distance process for these points where Y n ( r) is the number of pairs of points( X in , X in ) which with i < j have Euclidean distance ‖ X in − X > in ‖ < r. In this article we study the limiting distribution of Y n ( r) when n → ∞ and μ( D n ) → ∞, and the joint density of X 1 n ,…, X nn is of the form ƒ(x 1…x 1)= C n exp(vy n(r)) ify n(r 0)=0, 0 ify n(r 0)>0 where r 0 is a positive constant and C n is a normalizing constant. These joint densities modify the Strauss [11] clustering model densities by introducing a hard-core component (no two points can have ‖ X in − X in ‖ < r 0) found in the Matérn [4] models. In our main result we show that the interpoint distance process converges to a non-homogeneous Poisson process for r values in a bounded interval 0 < r 0 < r < r 00 provided sparseness conditions discussed by Saunders and Funk [9] hold. The sparseness conditions which require μ(D n) n 2 converges to a positive constant and the boundary of D n is negligible are essentially equivalent to requiring that although the number of points n is large the region is large enough so that the points are sparse in this region. That is, it is rare for a point to have another point close to it. These results extend results for v ⩽ 0 given by Saunders and Funk [9] where it is shown that without the hard core component such results do not hold for v > 0. Statistical applications are discussed.

Poisson limits for a hard-core clustering model

Abstract Let X1n,…,X>nn denote the locations of n points in a bounded, γ-dimensional, Euclidean region Dn which has positive γ-dimensional Lebesgue measure μ(Dn). Let {Yn(r): r > 0} be the interpoint distance process for these points where Yn(r) is the number of pairs of points(Xin, Xin) which with i in‖ ƒ(x 1 …x 1 )= C n exp (vy n (r)) if y n (r 0 )=0, 0 if y n (r 0 )>0 where r0 is a positive constant and Cn is a normalizing constant. These joint densities modify the Strauss [11] clustering model densities by introducing a hard-core component (no two points can have ‖Xin − Xin‖ μ(D n ) n 2 converges to a positive constant and the boundary of Dn is negligible are essentially equivalent to requiring that although the number of points n is large the region is large enough so that the points are sparse in this region. That is, it is rare for a point to have another point close to it. These results extend results for v ⩽ 0 given by Saunders and Funk [9] where it is shown that without the hard core component such results do not hold for v > 0. Statistical applications are discussed.