Randomized observation periods for the compound Poisson risk model: Dividends

In the framework of the classical compound Poisson process in collective risk theory, we study a modification of the horizontal dividend barrier strategy by introducing random observation times at which dividends can be paid and ruin can be observed. This model contains both the continuous-time and the discrete-time risk model as a limit and represents a certain type of bridge between them which still enables the explicit calculation of moments of total discounted dividend payments until ruin. Numerical illustrations for several sets of parameters are given and the effect of random observation times on the performance of the dividend strategy is studied.

Optimal dividend strategies for a compound Poisson risk process under transaction costs and power utility

We characterize the value function of maximizing the total discounted utility of dividend payments for a compound Poisson insurance risk model when strictly positive transaction costs are included, leading to an impulse control problem. We illustrate that well known simple strategies can be optimal in the case of exponential claim amounts. Finally we develop a numerical procedure to deal with general claim amount distributions.

A risk model with an observer in a Markov environment

We consider a spectrally-negative Markov additive process as a model of a risk process in a random environment. Following recent interest in alternative ruin concepts, we assume that ruin occurs when an independent Poissonian observer sees the process as negative, where the observation rate may depend on the state of the environment. Using an approximation argument and spectral theory, we establish an explicit formula for the resulting survival probabilities in this general setting. We also discuss an efficient evaluation of the involved quantities and provide a numerical illustration.

Use of a human-like low-grade bacteremia model of experimental endocarditis to study the role of Staphylococcus aureus adhesins and platelet aggregation in early endocarditis.

Animal models of infective endocarditis (IE) induced by high-grade bacteremia revealed the pathogenic roles of Staphylococcus aureus surface adhesins and platelet aggregation in the infection process. In humans, however, S. aureus IE possibly occurs through repeated bouts of low-grade bacteremia from a colonized site or intravenous device. Here we used a rat model of IE induced by continuous low-grade bacteremia to explore further the contributions of S. aureus virulence factors to the initiation of IE. Rats with aortic vegetations were inoculated by continuous intravenous infusion (0.0017 ml/min over 10 h) with 10(6) CFU of Lactococcus lactis pIL253 or a recombinant L. lactis strain expressing an individual S. aureus surface protein (ClfA, FnbpA, BCD, or SdrE) conferring a particular adhesive or platelet aggregation property. Vegetation infection was assessed 24 h later. Plasma was collected at 0, 2, and 6 h postinoculation to quantify the expression of tumor necrosis factor (TNF), interleukin 1α (IL-1α), IL-1β, IL-6, and IL-10. The percentage of vegetation infection relative to that with strain pIL253 (11%) increased when binding to fibrinogen was conferred on L. lactis (ClfA strain) (52%; P = 0.007) and increased further with adhesion to fibronectin (FnbpA strain) (75%; P < 0.001). Expression of fibronectin binding alone was not sufficient to induce IE (BCD strain) (10% of infection). Platelet aggregation increased the risk of vegetation infection (SdrE strain) (30%). Conferring adhesion to fibrinogen and fibronectin favored IL-1β and IL-6 production. Our results, with a model of IE induced by low-grade bacteremia, resembling human disease, extend the essential role of fibrinogen binding in the initiation of S. aureus IE. Triggering of platelet aggregation or an inflammatory response may contribute to or promote the development of IE.

The optimal dividend barrier in the Gamma-Omega model

In the traditional actuarial risk model, if the surplus is negative, the company is ruined and has to go out of business. In this paper we distinguish between ruin (negative surplus) and bankruptcy (going out of business), where the probability of bankruptcy is a function of the level of negative surplus. The idea for this notion of bankruptcy comes from the observation that in some industries, companies can continue doing business even though they are technically ruined. Assuming that dividends can only be paid with a certain probability at each point of time, we derive closed-form formulas for the expected discounted dividends until bankruptcy under a barrier strategy. Subsequently, the optimal barrier is determined, and several explicit identities for the optimal value are found. The surplus process of the company is modeled by a Wiener process (Brownian motion).

Properties of a risk measure derived from ruin theory

This paper studies a risk measure inherited from ruin theory and investigates some of its properties. Specifically, we consider a value-at-risk (VaR)-type risk measure defined as the smallest initial capital needed to ensure that the ultimate ruin probability is less than a given level. This VaR-type risk measure turns out to be equivalent to the VaR of the maximal deficit of the ruin process in infinite time. A related Tail-VaR-type risk measure is also discussed.

Real-time monitoring of protein conformational changes using a nano-mechanical sensor.

Proteins can switch between different conformations in response to stimuli, such as pH or temperature variations, or to the binding of ligands. Such plasticity and its kinetics can have a crucial functional role, and their characterization has taken center stage in protein research. As an example, Topoisomerases are particularly interesting enzymes capable of managing tangled and supercoiled double-stranded DNA, thus facilitating many physiological processes. In this work, we describe the use of a cantilever-based nanomotion sensor to characterize the dynamics of human topoisomerase II (Topo II) enzymes and their response to different kinds of ligands, such as ATP, which enhance the conformational dynamics. The sensitivity and time resolution of this sensor allow determining quantitatively the correlation between the ATP concentration and the rate of Topo II conformational changes. Furthermore, we show how to rationalize the experimental results in a comprehensive model that takes into account both the physics of the cantilever and the dynamics of the ATPase cycle of the enzyme, shedding light on the kinetics of the process. Finally, we study the effect of aclarubicin, an anticancer drug, demonstrating that it affects directly the Topo II molecule inhibiting its conformational changes. These results pave the way to a new way of studying the intrinsic dynamics of proteins and of protein complexes allowing new applications ranging from fundamental proteomics to drug discovery and development and possibly to clinical practice.