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Time Dynamics (time + dynamics)

Distribution by Scientific Domains

Earth and Environmental Science	50%

Selected Abstracts

Physiological responses of Matricaria chamomilla to cadmium and copper excess

ENVIRONMENTAL TOXICOLOGY, Issue 1 2008
Jozef Ková
Abstract Physiological responses of Matricaria chamomilla plants exposed to cadmium (Cd) and copper (Cu) excess (3, 60, and 120 ,M for 7 days) with special emphasis on phenolic metabolism were studied. Cu at 120 ,M reduced chamomile growth, especially in the roots where it was more abundant than Cd. Notwithstanding the low leaf Cu amount (37.5 ,g g,1 DW) in comparison with Cd (237.8 ,g g,1 DW) at 120 ,M, it caused reduction of biomass accumulation, Fv/Fm ratio and soluble proteins. In combination with high accumulation of phenolics, strong reduction of proteins and high GPX activity in the roots, this supports severe redox Cu properties. In terms of leaf phenylalanine ammonia-lyase (PAL) activity, it seems that Cd had a stimulatory effect during the course of the experiment, whereas Cu was found to stimulate it after 7-day exposure. The opposite trend was visible in the roots, where Cd had a stimulatory effect at high doses but Cu mainly at the highest dose. This supports the assumption of different PAL time dynamics under Cd and Cu excess. A dose of 60 and 120 ,M Cu led to 2- and 3-times higher root lignin accumulation while the same Cd doses increased it by 33 and 68%, respectively. A Cu dose of 120 ,M can be considered as limiting for chamomile growth under conditions of present research, while resistance to high Cd doses was confirmed. However, PAL and phenolics seemed to play an important role in detoxification of Cd- and Cu-induced oxidative stress. © 2008 Wiley Periodicals, Inc. Environ Toxicol, 2008. [source]

Controllable Soluble Protein Concentration Gradients in Hydrogel Networks,

ADVANCED FUNCTIONAL MATERIALS, Issue 21 2008
Brian J. Peret
Abstract Here, controlled formation of sustained, soluble protein concentration gradients within hydrated polymer networks is reported. The approach involves spatially localizing proteins or biodegradable, protein-loaded microspheres within hydrogels to form a protein-releasing "depot." Soluble protein concentration gradients are then formed as the released protein diffuses away from the localized source. Control over key gradient parameters, including maximum concentration, gradient magnitude, slope, and time dynamics, is achieved by controlling the release of protein from the depot and subsequent transport through the hydrogel. Results demonstrate a direct relationship between the amount of protein released from the depot and the source concentration, gradient magnitude, and slope of the concentration gradient. In addition, an inverse relationship exists between the diffusion coefficient of protein within the hydrogel and the slope of the concentration gradient. The time dynamics of the concentration gradient profile can be directly correlated to protein release from the localized source, providing a mechanism for temporarily controlling gradient characteristics. Therefore, each key biologically relevant parameter associated with the protein concentration gradient can be controlled by defining protein release and diffusion. It is anticipated that the resulting materials may be useful in 3D cell culture systems, and in emerging tissue engineering approaches that aim to regenerate complex, functional tissues. [source]

Morphological development and nutritive value of herbage in five temperate grass species during primary growth: analysis of time dynamics

GRASS & FORAGE SCIENCE, Issue 2 2009

Abstract In a 2-year field experiment, morphological development and measures of the nutritive value of herbage for livestock during primary growth in Meadow foxtail, Tall oatgrass, Cocksfoot, Perennial ryegrass and Yorkshire fog were investigated. All measured variables were affected significantly by both species and sampling date, and their interaction (P < 0·001), in the period of primary growth. Changes with time in mean stage weight for Meadow foxtail and Cocksfoot were different from the other species due to their indeterminate growth habits. Mean stage weight of Tall oatgrass and Yorkshire fog increased more rapidly than that of Perennial ryegrass with time. Changes in mean stage weight with time were described by linear, parabolic and sigmoid relationships. Crude protein (CP) concentration of herbage was higher for Cocksfoot and Meadow foxtail than for Perennial ryegrass. A parabolic relationship of CP concentration with time was typical for all the species. Concentrations of neutral-detergent fibre (NDF) and acid-detergent fibre (ADF) in herbage of the species differed most during the mid-period of primary growth. Their increases with time showed curvilinear (sigmoid and parabolic) relationships. Perennial ryegrass had lower concentrations of both NDF and ADF in herbage than the other species. Differences between the in vitro dry matter (DM) digestibility among the grasses increased in mid- and late periods of primary growth. Perennial ryegrass had higher values for in vitro DM digestibility but the difference from other species was small in the early period of primary growth and from cocksfoot in the late period of primary growth. In vitro DM digestibility showed, in most cases, a sigmoid and, in others, a linear decrease with time. Principal component analysis showed that perennial ryegrass and meadow foxtail were the most distinctive of the species in characteristics relating to morphological development and the nutritive value of herbage to livestock. [source]

Modeling dependencies between rating categories and their effects on prediction in a credit risk portfolio

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 3 2008
Claudia Czado
Abstract The internal-rating-based Basel II approach increases the need for the development of more realistic default probability models. In this paper, we follow the approach taken in McNeil A and Wendin J 7 (J. Empirical Finance 2007) by constructing generalized linear mixed models for estimating default probabilities from annual data on companies with different credit ratings. The models considered, in contrast to McNeil A and Wendin J 7 (J. Empirical Finance 2007), allow parsimonious parametric models to capture simultaneously dependencies of the default probabilities on time and credit ratings. Macro-economic variables can also be included. Estimation of all model parameters are facilitated with a Bayesian approach using Markov chain Monte Carlo methods. Special emphasis is given to the investigation of predictive capabilities of the models considered. In particular, predictable model specifications are used. The empirical study using default data from Standard and Poor's gives evidence that the correlation between credit ratings further apart decreases and is higher than the one induced by the autoregressive time dynamics. Copyright © 2008 John Wiley & Sons, Ltd. [source]