Theory of Flux-Flow Resistivity near Hc2H_{c2} for s-wave Type-II Superconductors

This paper presents a microscopic calculation of the flux-flow resistivity $\rho_{f}$ for s-wave type-II superconductors with arbitrary impurity concentrations near the upper critical field $H_{c2}$. It is found that, as the mean free path $l$ becomes longer, $\rho_{f}$ increases gradually from the dirty-limit result of Thompson [Phys. Rev. B{\bf 1}, 327 (1970)] and Takayama and Ebisawa [Prog. Theor. Phys. {\bf 44}, 1450 (1970)]. The limiting behaviors suggest that $\rho_{f}(H)$ at low temperatures may change from convex downward to upward as $l$ increases, thus deviating substantially from the linear dependence $\rho_{f}\propto H/H_{c2}$ predicted by the Bardeen-Stephen theory [Phys. Rev. {\bf 140}, A1197 (1965)]

Delayed maintenance modelling considering speed restriction for a railway section

The deterioration of track geometry depends on several factors of which the speed of the train is one. Imposing a speed restriction can slow down the track deterioration and allows a longer survival time before a serious condition is achieved. Preventive maintenance delays can be authorized during the survival time. However, speed restrictions also reduce the system throughput. On the other hand, a longer interval between preventive maintenance activities has a lower maintenance action cost and it also enables grouping the maintenance activities to save set-up costs as well as system down time. If the repair delay is too long, it may cause unacceptable conditions on the track and lead to higher maintenance costs and accidents. Therefore, it is interesting to assess the effect of a speed restriction on the delayed maintenance strategies for a railway track section. We want to solve a maintenance optimization problem to find the optimal tuning of the maintenance delay time and imposition of a speed restriction. To this aim, a delayed maintenance model is developed, in which track deterioration depends on the train speed and the number of passing trains. The model is used to determine an optimal speed restriction strategy and a preventive repair delay for the optimization of the system benefit and unavailability. Coloured Petri Nets (CPN) are adopted to model the maintenance and operation of the railway track section. The CPN model describes the gradual track deterioration as a stochastic process. Different speed restriction policies and maintenance delay strategies are modelled and activated by the observed component states. Monte Carlo simulations are carried out to estimate the maintenance cost, the system benefit and the system downtime under different policies. Numerical results show the maintenance decision variable trade-off

Entropy and Spin Susceptibility of s-wave Type-II Superconductors near Hc2H_{c2}

A theoretical study is performed on the entropy $S_{\rm s}$ and the spin susceptibility $\chi_{\rm s}$ near the upper critical field $H_{c2}$ of s-wave type-II superconductors with arbitrary impurity concentrations. The changes of these quantities through $H_{c2}$ may be expressed as $[S_{\rm s}(T,B)-S_{\rm s}(T,0)]/[S_{\rm n}(T)-S_{\rm s}(T,0)]=1-\alpha_{S}(1-B/H_{c2})\approx (B/H_{c2})^{\alpha_{S}}$, for example, where $B$ is the average flux density and $S_{\rm n}$ denotes entropy in the normal state. It is found that the slopes $\alpha_{S}$ and $\alpha_{\chi}$ at T=0 are identical, connected directly with the zero-energy density of states, and vary from 1.72 in the dirty limit to $0.5\sim 0.6$ in the clean limit. This mean-free-path dependence of $\alpha_{S}$ and $\alpha_{\chi}$ at T=0 is quantitatively the same as that of the slope $\alpha_{\rho}(T=0)$ for the flux-flow resistivity studied previously. The result suggests that $S_{\rm s}(B)$ and $\chi_{\rm s}(B)$ near T=0 are convex downward (upward) in the dirty (clean) limit, deviating substantially from the linear behavior $\propto B/H_{c2}$. The specific-heat jump at $H_{c2}$ also shows fairly large mean-free-path dependence.Comment: 8 pages, 5 figure

Core pinning by intragranular nanoprecipitates in polycrystalline MgCNi_3

The nanostructure and magnetic properties of polycrystalline MgCNi_3 were studied by x-ray diffraction, electron microscopy, and vibrating sample magnetometry. While the bulk flux-pinning force curve F_p(H) indicates the expected grain-boundary pinning mechanism just below T_c = 7.2 K, a systematic change to pinning by a nanometer-scale distribution of core pinning sites is indicated by a shift of F_p(H) with decreasing temperature. The lack of scaling of F_p(H) suggests the presence of 10 to 20% of nonsuperconducting regions inside the grains, which are smaller than the diameter of fluxon cores 2xi at high temperature and become effective with decreasing temperature when xi(T) approaches the nanostructural scale. Transmission electron microscopy revealed cubic and graphite nanoprecipitates with 2 to 5 nm size, consistent with the above hypothesis since xi(0) = 6 nm. High critical current densities, more than 10^6 A/cm^2 at 1 T and 4.2 K, were obtained for grain colonies separated by carbon. Dirty-limit behavior seen in previous studies may be tied to electron scattering by the precipitates, indicating the possibility that strong core pinning might be combined with a technologically useful upper critical field if versions of MgCNi_3 with higher T_c can be found.Comment: 5 pages, 6 figures, submitted to PR

Modelling prognostic factors in advanced pancreatic cancer

Pancreatic cancer is the fifth most common cause of cancer death. Identification of defined patient groups based on a prognostic index may improve the prediction of survival and selection of therapy. Many prognostic factors have been identified often based on retrospective, underpowered studies with unclear analyses. Data from 653 patients were analysed. Continuous variables are often simplified assuming a linear relationship with log hazard or introducing a step function (dichotomising). Misspecification may lead to inappropriate conclusions but has not been previously investigated in pancreatic cancer studies. Models based on standard assumptions were compared with a novel approach using nonlinear fractional polynomial (FP) transformations. The model based on FP-transformed covariates was most appropriate and confirmed five previously reported prognostic factors: albumin, CA19-9, alkaline phosphatase, LDH and metastases, and identified three additional factors not previously reported: WBC, AST and BUN. The effects of CA19-9, alkaline phosphatase, AST and BUN may go unrecognised due to simplistic assumptions made in statistical modelling. We advocate a multivariable approach that uses information contained within continuous variables appropriately. The functional form of the relationship between continuous covariates and survival should always be assessed. Our model should aid individual patient risk stratification and the design and analysis of future trials in pancreatic cancer

Modélisation de la géométrie d'une voie ferrée par un processus Gamma bivarié et application à la maintenance

ACTInternational audienceno abstrac

Modelling track geometry by a bivariate Gamma wear process, with application to maintenance

OSInternational audienceThis paper discusses the maintenance optimization of arailway track, based on the observation of two dependent randomlyincreasing deterioration indicators. These two indicators are mod-elled through a bivariate Gamma process constructed by trivariatereduction. Empirical and maximum likelihood estimators are givenfor the process parameters and tested on simulated data. The EMalgorithm is used to compute the maximum likelihood estimators. Abivariate Gamma process is then fitted to real data of railway trackdeterioration. Preventive maintenance scheduling is studied, ensuringthat the railway track keeps a good quality with a high probability.The results are compared to those based on both indicators takenseparately, and also on one single indicator (usually taken for currenttrack maintenance). The results based on the joined information areproved to be safer than the other ones, which shows the interest ofthe bivariate model