state dependent parameters Research Articles (Page 1)

In mammals, the costs of reproduction are biased towards females. Lactation is particularly energetically expensive, and behavioral and physiological data indicate that maternal effort during lactation induces energetic stress. Another source of stress in females is male aggression directed towards them when they are cycling. Evaluating the costs of reproduction in wild and mobile animals can be a challenging task, and requires detailed information on state-dependent parameters such as hormone levels. Glucocorticoid (GC) levels are indicative of nutritional and social stress, and are widely used to assess the costs of reproduction. We investigated variation in urinary levels of cortisol, the main GC in female bonobos (Pan paniscus), between and within reproductive stages. Female chimpanzees (Pan troglodytes), the closest living relative of the bonobos, are often exposed to intense aggression from males, which causes a significant rise in their cortisol levels during the phase of their maximum fecundity. In bonobos, males compete for access to fertile females, but aggressive male mating strategies are absent in this species. Therefore, we expected that GC levels of cycling female bonobos would be lower than those of lactating females. Due to the long period of offspring care in bonobos, we expected that GC levels would remain elevated into the late stage of lactation, when immatures gain body weight but may still be nursed and carried by their mothers. We found elevated urinary GC levels only during the early stage of lactation. The GC levels of cycling females did not differ from those in the mid or late lactation stage. Behavioral strategies of female bonobos may allow them to compensate for the elevated energetic demands of lactation and prolonged maternal care.

Suboptimal Control of Nonlinear Dynamic System with Unlimited Transition Process Time

The forward premium puzzle and Markov-switching adaptive learning,

Extended State Dependent Parameter modelling with a Data-Based Mechanistic approach to nonlinear model structure identification

Control Design for Nonlinear Systems via Controller with Quasi-fixed Parameters

Very high resolution far infrared synchrotron radiation spectrum of methanol-D1 (CH2DOH) in the first three torsional-vibrational modes

Many optimization problems encountered in practice are multi-objective by nature, i.e., different objectives are conflicting and equally important. Many times, it is not desirable to drop some of them or to optimize them in a composite single objective or hierarchical manner. Furthermore, cost parameters change over time which makes optimization problems harder. For instance, in the transport sector, travel costs are a function of travel time which changes depending on the time of the day a vehicle is travelling (e.g., due to road congestion). Road congestion results in tremendous delays which lead to a decrease in the service quality and the responsiveness of logistic service providers. In Chapter 2, we develop a generic approach to deal with Multi-Objective Scheduling Problems (MOSPs) with State-Dependent Cost Parameters. The aim is to determine the set of Pareto solutions that capture the trade offs between the different conflicting objectives. Due to the complexity of MOSPs, an efficient approximation based on dynamic programming is developed. The approximation has a provable worse case performance guarantee. Even though the generated approximate Pareto front consist of fewer solutions, it still represents a good coverage of the true Pareto front. Furthermore, considerable gains in computation times are achieved. In Chapter 3, the developed methodology is validated on the multi-objective timedependent knapsack problem. In the classical knapsack problem, the input consists of a knapsack with a finite capacity and a set of items, each with a certain weight and a cost. A feasible solution to the knapsack problem is a selection of items such that their total weight does not exceed the knapsack capacity. The goal is to maximize the single objective function consisting of the total pro t of the selected items. We extend the classical knapsack problem in two ways. First, we consider time-dependent profits (e.g., in a retail environment profit depends on whether it is Christmas or not).

formula omitted]th moment exponential stochastic synchronization of coupled memristor-based neural networks with mixed delays via delayed impulsive control

This paper presents a very general option pricing formula incorporating both the Levy process methodology and the level dependent volatility approach. An approximate solution to the pricing problem is obtained throughout the construction of a parametrix by means of the pseudo differential calculus. Some examples are provided to illustrate the comprehensiveness of the framework. Finally, the implications in terms of the volatility smile are discussed.

Character of slip and stress due to interaction between fault segments along the dip direction of a subduction zone

Introducing the variation of advective time delay (ATD) to Transfer Function models

Discrete-time models with state-dependent parameters are derived for non-linear sampled-data systems. Velocity-based linearization of the continuous-time system followed by integration over the sampling interval is used to represent the sampled-data system by a discrete-time state-space model with state-dependent parameters. By reconstructing the state a quasi-ARX model is obtained, the parameters of which are functions of past inputs and outputs. As the velocity-based linearization procedure does not involve suppression of higher-order terms, the state-dependent state-space model and the quasi-ARX description give exact representations of the non-linear system.

In this paper we introduce and study functionals of the intensities of random measures modulated by a stochastic process ξ, which occur in applications to stochastic models and telecommunications. Modulation of a random measure by ξ is specified for marked Cox measures. Particular cases of modulation by ξ as semi‐Markov and semiregenerative processes enabled us to obtain explicit formulas for the named intensities. Examples in queueing (systems with state dependent parameters, Little′s and Campbell′s formulas) demonstrate the use of the results.