On distributionally regenerative processes

The paper is concerned with characterization results for distributional regeneration. It is shown that distributional regeneration is equivalent to renewal representation of the associated (shift) Markov operator. A sufficient condition for the distributional regeneration of the transfer operator in terms of variation is also formulated. Finally, a minorization condition is formulated and proved to be sufficient for recurrent co-Feller operators.     

Discrete and Continuous Time Modulated Random Walks with Heavy-Tailed Increments

We consider a modulated process S which, conditional on a background process X, has independent increments. Assuming that S drifts to −∞ and that its increments (jumps) are heavy-tailed (in a sense made precise in the paper), we exhibit natural conditions under which the asymptotics of the tail distribution of the overall maximum of S can be computed. We present results in discrete and in continuous time. In particular, in the absence of modulation, the process S in continuous time reduces to a Lévy process with heavy-tailed Lévy measure. A central point of the paper is that we make full use of the so-called “principle of a single big jump” in order to obtain both upper and lower bounds. Thus, the proofs are entirely probabilistic. The paper is motivated by queueing and Lévy stochastic networks.     

On the M/G/1 retrial queueing system with linear control policy

Summary This paper is concerned with the study of a newM/G/1 retrial queueing system in which the delays between retrials are exponentially distributed random variables with linear intensityg(n)=α+nμ, when there aren≥1 customers in the retrial group. This new retrial discipline will be calledlinear control policy. We carry out an extensive analysis of the model, including existence of stationary regime, stationary distribution of the embedded Markov chain at epochs of service completions, joint distribution of the orbit size and the server state in steady state and busy period. The results agree with known results for special cases.     

Performance of two-hop infrastructure based multi-antenna regenerative relaying in Rayleigh fading channel

Cooperative relaying is considered as an effective technique to enlarge the coverage area and enhance the system capacity for the future wireless systems. In this paper, an infrastructure based multi-antenna cooperative relay network has been investigated. Closed form expressions of outage probability and average error rate have been derived, when the relay and the destination perform selection combining of the signals. The relay is assumed to operate in the adaptive decode and forward mode. The effect of number of antennas installed on the relay and their placement has also been studied.     

Regenerative queueing processes and their qualitative and quantitative analysis

Recently developed methods of qualitative analysis for regenerative processes arising in queueing are presented. These methods are essentially qualitative and use notions such as coupling, probability metrics, etc. They are developed for studying various properties of regenerative models, including convergence rate to a stationary regime, continuity of their characteristics with respect to some parameters and first-occurrence time of an event such as queue overflowing. In spite of their qualitative nature they lead to good quantitative estimates of underlying properties with computer methods available to calculate them.     

Nonexistence of a class of variate generation schemes

Motivated by a problem arising in the regenerative analysis of discrete-event system simulation, we ask whether a certain class of random variate generation schemes exists or not. Under very reasonable conditions, we prove that such variate generation schemes do not exist. The implications of this result for regenerative steady-state simulation of discrete-event systems are discussed.     

大型回热换热器的降温实验

大型低温配件的降温试验复杂和多变,文中针对大型回热换热器的降温进行了研究。将回热换热器置于特制的冷箱内,利用液氮作为冷源,氦气做为载冷剂为换热器提供降温条件;隔膜压缩机为循环氦气提供循环压力。试验前将换热器上面布置9支传感器,传感器所采集的数据自动记录并保存在上位机内,同时绘制降温曲线,为大型回热换热器的降温研究提供了数据。     

Honest Importance Sampling With Multiple Markov Chains

Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π₁, is used to estimate an expectation with respect to another, π. The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asymptotic variance in the CLT, which makes for routine computation of standard errors. Importance sampling can also be used in the Markov chain Monte Carlo (MCMC) context. Indeed, if the random sample from π₁ is replaced by a Harris ergodic Markov chain with invariant density π₁, then the resulting estimator remains strongly consistent. There is a price to be paid, however, as the computation of standard errors becomes more complicated. First, the two simple moment conditions that guarantee a CLT in the iid case are not enough in the MCMC context. Second, even when a CLT does hold, the asymptotic variance has a complex form and is difficult to estimate consistently. In this article, we explain how to use regenerative simulation to overcome these problems. Actually, we consider a more general setup, where we assume that Markov chain samples from several probability densities, π₁, …, π_k, are available. We construct multiple-chain importance sampling estimators for which we obtain a CLT based on regeneration. We show that if the Markov chains converge to their respective target distributions at a geometric rate, then under moment conditions similar to those required in the iid case, the MCMC-based importance sampling estimator obeys a CLT. Furthermore, because the CLT is based on a regenerative process, there is a simple consistent estimator of the asymptotic variance. We illustrate the method with two applications in Bayesian sensitivity analysis. The first concerns one-way random effect models under different priors. The second involves Bayesian variable selection in linear regression, and for this application, importance sampling based on multiple chains enables an empirical Bayes approach to variable selection.     

Using the OSL single-aliquot regenerative-dose protocol with quartz extracted from building materials in retrospective dosimetry

We report on the application of the single-aliquot regenerative-dose (SAR) protocol to the optically stimulated luminescence signal from quartz extracted from fired bricks and unfired mortar in retrospective dosimetry. The samples came from a radioactive materials storage facility, with ambient dose rates of about 0.1 mGy/h. A detailed dose-depth profile was analysed from one brick, and compared with dose records from area TL dosemeters. Small-aliquot dose-distributions were analysed from the mortar samples; one associated with the exposed brick, and one from a remote site exposed only to background radiation. We conclude that unfired materials have considerable potential in retrospective dosimetry.     

Mechanisms of graphene influence on cell differentiation

The graphene family of nanomaterials (GFN) have a common carbon lattice base structure but represent a diverse range of materials with distinct chemical and physical characteristics. These characteristics are determined by the fabrication method and impart each material with specific chemical properties which govern interaction with cells and biomolecules, and physical properties that give unique nanotopography, stiffness, and electrical properties. Remarkably, members of the GFN have been shown to promote tissue formation and influence cell differentiation in a variety of tissue types, including neural, bone, and cardiac muscle, making them of high interest to the biomedical field. The diverse range of materials and experimental setups in the literature make uncovering the mechanism of action challenging. Nevertheless, it is becoming clear that the ability of GFN to form non-covalent interactions (π-π, hydrogen bonding, electrostatic) with biomolecules may increase their bioavailability via sequestering/concentration/conformation protection to induce cell differentiation. In addition to the chemical properties, the stimulation of mechanosensing pathways, cytoskeletal rearrangement, and enhanced electrical activity of cells on GFN substrates demonstrates the importance of the physical properties in directing cell differentiation. The understanding of the mechanism behind the ability of GFN to enhance cell differentiation will allow the design and selection of materials with the desired properties for tissue repair and regeneration.