Enantioseparation of catechin and epicatechin in plant food by chiral capillary electrophoresis

The enantiomers of catechin and epicatechin were separated by chiral capillary electrophoresis using modified cyclodextrins as chiral selectors. Various conditions for the separation system were optimized, including the pH value and the concentration of the running buffer. A baseline separation of the catechin and epicatechin enantiomers could be achieved by using 0.1 mol l⁻¹ borate buffer (pH 8.5) with 12 mmol l⁻¹ (2-hydroxypropyl)-γ-cyclodextrin as chiral selector, a fused-silica capillary with 40 cm effective length (75 μm I.D.), +18 kV applied voltage, a temperature of 20 °C and direct UV detection at 280 nm. The method was applied to different plant food samples. (+)-Catechin and (−)-epicatechin could be verified as the most common flavan-3-ols. In the case of guaraná, however, we were able to identify all four enantiomers, both (+)- and (−)-catechin and (+)- and (−)-epicatechin, as naturally occurring compounds. This finding was verified by further isolation and purification of the flavan-3-ols and subsequent LC–MS analysis. This method allows for the identification of the authenticity of guaraná through the analysis of the catechin and epicatechin enantiomers, additionally to the conventional methods like HPLC.     

Scalable nonlinear dynamical systems for agent steering and crowd simulation

We present a new methodology for agent modeling that is scalable and efficient. It is based on the integration of nonlinear dynamical systems and kinetic data structures. The method consists of three layers, which together model 3D agent steering, crowds and flocks among moving and static obstacles. The first layer, the local layer employs nonlinear dynamical systems theory to models low-level behaviors. It is fast and efficient, and it does not depend on the total number of agents in the environment. This dynamical systems-based approach also allows us to establish continuous numerical parameters for modifying each agent's behavior. The second layer, a global environment layer consists of a specifically designed kinetic data structure to track efficiently the immediate environment of each agent and know which obstacles/agents are near or visible to the given agent. This layer reduces the complexity in the local layer. In the third layer, a global planning layer, the problem of target tracking is generalized in a way that allows navigation in maze-like terrains, avoidance of local minima and cooperation between agents. We implement this layer based on two approaches that are suitable for different applications: One approach is to track the closest single moving or static target; the second is to use a pre-specified vector field, which may be generated automatically (with harmonic functions, for example) or based on user input to achieve the desired output. We also discuss how hybrid systems concepts for global planning can capitalize on both our layered approach and the continuous, reactive nature of our agent steering.

We demonstrate the power of the approach through a series of experiments simulating single/multiple agents and crowds moving towards moving/static targets in complex environments.     

Separation of Steviol Glycosides by Hydrophilic Liquid Interaction Chromatography

Stevia rebaudiana Bertoni contains several steviol glycosides with sweet flavour. They all are sweeter than sucrose (up to factor 450). The various steviol glycosides are difficult to separate by reversed-phase chromatography. In this paper, five different hydrophilic liquid interaction chromatography columns are characterized using isocratic elution (5–20% water in acetonitrile with buffer or formic acid). Separation of the steviol glycosides is possible with all but one of the tested columns, but the robustness of the separation against changes of buffer concentration and percentage of water differ. Aqueous percentage and ion strength of the eluent are the main factors to be optimized in method development.     

Exact Reliability Formulas for Linear & Circular Consecutive-k-out-of-n:F Systems

A consecutive-k-out-of-n:F system, with n linearly or circularly arranged i.i.d. components is examined. The system reliability has an exact formula which is straight forward and more effective than those given elsewhere; the two formulas are given.     

Gentrifying the Rural? Planning and Market Processes in Rural Ireland

Rural gentrification represents an emerging research agenda in the context of social transformation of rural localities. Having as a case study the Republic of Ireland, which provides a case of a laissez-faire planning system, this paper first addresses supply-side factors that have provided key preconditions for gentrification to take place. Then, using survey data in case study localities, we examine the extent that gentrification is a factor in rural residential mobility. We argue that the changing rural condition of Ireland provides essential preconditions for gentrification to take place. However, the gentrification literature provides only a partial angle of rural residential mobility, given the nature of rural in-migration observed in our case studies (that is blue-collar and return rural in-migration) during a period of substantial rural housing growth.     

Reliability of a Consecutive-k-out-of-n:F System for Markov-Dependent Components

We examine a consecutive-k-out-of-n:F system, where the probability of failure of a component depends upon the state, (good or failed) of the preceding component; ie, the states of the components form a Markov chain. We compute the reliability of such a system, via a recurrence relation.     

On the Autocorrelation Properties of Long-Memory GARCH Processes

Abstract.  This paper derives the autocorrelation function of the squared values of long-memory GARCH processes. Such processes are of much interest as they can produce the long-memory conditional heteroskedasticity that many high-frequency financial time series exhibit. An empirical application illustrating the practical use of our results is also discussed.     

Prediction in ARMA Models with GARCH in Mean Effects

This paper considers forecasting the conditional mean and variance from an ARMA model with GARCH in mean effects. Expressions for the optimal predictors and their conditional and unconditional MSEs are presented. We also derive the formula for the covariance structure of the process and its conditional variance.
JEL. C22.     

Bounding the Distance between 2D Parametric Bézier Curves and their Control Polygon

Employing the techniques presented by Nairn, Peters and Lutterkort in [1], sharp bounds are firstly derived for the distance between a planar parametric Bézier curve and a parameterization of its control polygon based on the Greville abscissae. Several of the norms appearing in these bounds are orientation dependent. We next present algorithms for finding the optimal orientation angle for which two of these norms become minimal. The use of these bounds and algorithms for constructing polygonal envelopes of planar polynomial curves, is illustrated for an open and a closed composite Bézier curve.