The Influence of Cadmium on Fountain Grass Performance Correlates Closely with Metabolite Profiles.

The relationship between metabolite changes and biological endpoints in response to cadmium (Cd) stress remains unclear. Fountain grass has good Cd enrichment and tolerance abilities and is widely used in agriculture and landscaping. We analyzed the metabolic responses by detecting the metabolites through UPLC-MS and examined the relationships between metabolite changes and the characteristics of morphology and physiology to different Cd stress in fountain grass. Our results showed that under Cd stress, 102 differential metabolites in roots and 48 differential metabolites in leaves were detected, with 20 shared metabolites. Under Cd stress, most of the carbohydrates in leaves and roots decreased, which contributed to the lowered leaf/root length and fresh weight. In comparison, most of the differential amino acids and lipids decreased in the leaves but increased in the roots. Almost all the differential amino acids in the roots were negatively correlated with root length and root fresh weight, while they were positively correlated with malondialdehyde content. However, most of the differential amino acids in the leaves were positively correlated with leaf length and leaf fresh weight but negatively correlated with malondialdehyde content. Metabolic pathway analysis showed that Cd significantly affects seven and eight metabolic pathways in the leaves and roots, respectively, with only purine metabolism co-existing in the roots and leaves. Our study is the first statement on metabolic responses to Cd stress and the relationships between differential metabolites and biological endpoints in fountain grass. The coordination between various metabolic pathways in fountain grass enables plants to adapt to Cd stress. This study provides a comprehensive framework by explaining the metabolic plasticity and Cd tolerance mechanisms of plants.

Combining Metabolic Analysis With Biological Endpoints Provides a View Into the Drought Resistance Mechanism of Carex breviculmis.

Metabolomics is an effective tool to test the response of plants to environmental stress; however, the relationships between metabolites and biological endpoints remained obscure in response to drought stress. Carex breviculmis is widely used in forage production, turf management, and landscape application and it is particularly resistant to drought stress. We investigated the metabolomic responses of C. breviculmis to drought stress by imposing a 22-day natural soil water loss. The results showed that water-deficit restrained plant growth, reducing plant height, leaf fresh weight, and total weight, however, increasing soluble protein content and malondialdehyde content. In total, 129 differential metabolites in the leaves were detected between drought and control using the Ultrahigh Performance Liquid Chromatography-Mass Spectrometer (UPLC-MS) method. Drought enhanced most of the primary and secondary metabolites in the differential metabolites. Almost all the sugars, amino acids, organic acids, phytohormones, nucleotides, phenylpropanoids and polyketides in the differential metabolites were negatively correlated with plant height and leaf fresh weight, while they were positively correlated with soluble protein content and malondialdehyde content. Metabolic pathway analysis showed that drought stress significantly affected aminoacyl-tRNA biosynthesis, TCA cycling, starch and sucrose metabolism. Our study is the first statement on metabolomic responses to drought stress in the drought-enduring plant C. breviculmis. According to the result, the coordination between diverse metabolic pathways in C. breviculmis enables the plant to adapt to a drought environment. This study will provide a systematic framework for explaining the metabolic plasticity and drought tolerance mechanisms of C. breviculmis under drought stress.

Improved results on delay-interval-dependent robust stability criteria for uncertain neutral-type systems with time-varying delays.

In this paper, we consider the problem of delay-interval-dependent robust stability and stabilization of a class of linear uncertain neutral-type systems with time-varying delay. By constructing a candidate Lyapunov-Krasovskii functional (LKF), that takes into account the delay-range information appropriately, less conservative robust stability criteria are proposed in terms of linear matrix inequalities (LMIs) to compute the maximum allowable upper bounds (MAUB) for the delay-interval within which the uncertain neutral-type system under consideration remains asymptotically stable. The verifiable stabilizability conditions and memoryless state feedback control design are stated. Finally, numerical examples are also designated to demonstrate the effectiveness and reduced conservatism of the developed results.

Robust absolute stability criteria for uncertain Lurie interval time-varying delay systems of neutral type.

This study investigates the delay-dependent robust absolute stability analysis for uncertain Lurie systems with interval time-varying delays of neutral type. First, we divide the whole delay interval into two segmentations with an unequal width and checking the variation of the Lyapunov-Krasovskii functional (LKF) for each subinterval of delay, much less conservative delay-dependent absolute and robust stability criteria are derived. Second, a new delay-dependent robust stability condition for uncertain Lurie neutral systems with interval time-varying delays, which expressed in terms of quadratic forms of linear matrix inequalities (LMIs), and has been derived by constructing the LKF from the delayed decomposition approach (DDA) and integral inequality approach (IIA). Finally, three numerical examples are given to show the effectiveness of the proposed stability criteria.

Further improvement on delay-range-dependent robust absolute stability for Lur'e uncertain systems with interval time-varying delays.

This paper investigates improved delay-range-dependent robust absolute stability criteria for a class of Lur'e uncertain systems with interval time-varying delays. By using delayed decomposition approach (DDA), a tighter upper bound of the derivative of Lyapunov functional can be obtained, and thus the proposed criteria give results with less conservatism compared with some previous ones. An integral inequality approach (IIA) is proposed to reduce the conservativeness in computing the allowable maximum admissible upper bound (MAUB) of the time-delay. The developed stability condition is expressed in terms of linear matrix inequality (LMI) that manipulates fewer decision variables and requires reduced computational load. Finally, three numerical examples are given to show the effectiveness of the proposed stability criteria.

New results on delay-range-dependent stability analysis for interval time-varying delay systems with non-linear perturbations.

This paper studies the problem of the stability analysis of interval time-varying delay systems with nonlinear perturbations. Based on the Lyapunov-Krasovskii functional (LKF), a sufficient delay-range-dependent criterion for asymptotic stability is derived in terms of linear matrix inequality (LMI) and integral inequality approach (IIA) and delayed decomposition approach (DDA). Further, the delay range is divided into two equal segments for stability analysis. Both theoretical and numerical comparisons have been provided to show the effectiveness and efficiency of the present method. Two well-known examples are given to show less conservatism of our obtained results and the effectiveness of the proposed method.

Further improvement on delay-dependent robust stability criteria for neutral-type recurrent neural networks with time-varying delays.

This paper is concerned with the problem of improved delay-dependent robust stability criteria for neutral-type recurrent neural networks (NRNNs) with time-varying delays. Combining the Lyapunov-Krasovskii functional with linear matrix inequality (LMI) techniques and integral inequality approach (IIA), delay-dependent robust stability conditions for RNNs with time-varying delay, expressed in terms of quadratic forms of state and LMI, are derived. The proposed methods contain the least number of computed variables while maintaining the effectiveness of the robust stability conditions. Both theoretical and numerical comparisons have been provided to show the effectiveness and efficiency of the present method. Numerical examples are included to show that the proposed method is effective and can provide less conservative results.

Improved delay-range-dependent robust stability for uncertain systems with interval time-varying delay.

This paper is concerned with the improved delay-range-dependent stability and robust stability criteria for linear systems with time-varying delay and norm-bounded uncertainties. In order to obtain much less conservative criteria, a Lyapunov-Krasovskii functional (LKF), which makes use of the information of both the lower and upper bounds of the interval time-varying delay, is proposed to derive new stability criteria. By using delayed decomposition approach (DDA), a tighter upper bound of the derivative of Lyapunov functional can be obtained, and thus the proposed criteria give results with less conservatism compared with some previous ones. The resulting criteria have advantages over some previous ones in that it involves fewer matrix variables but has less conservatism, which are established theoretically. We show, by four well known examples, that our result overcomes the previous allowable maximum admissible upper bound (MAUB) of the time-delay and it is less conservative than the previous results having a relatively small upper bound in the derivative of time delay.

Further results on delay-range-dependent stability with additive time-varying delay systems.

In this paper, new conditions for the delay-range-dependent stability analysis of time-varying delay systems are proposed in a Lyapunov-Krasovskii framework. Time delay is considered to be time-varying and has lower and upper bounds. A new method is first presented for a system with two time delays, integral inequality approach (IIA) used to express relationships among terms of Leibniz-Newton formula. Constructing a novel Lyapunov-Krasovskii functional includes information belonging to a given range; new delay-range-dependent criterion is established in term of linear matrix inequality (LMI). The advantage of that criterion lies in its simplicity and less conservative. This paper also presents a new result of stability analysis for continuous systems with two additive time-variant components representing a general class of delay with strong application background in network-based control systems. Resulting criteria are then expressed in terms of convex optimization with LMI constraints, allowing for use of efficient solvers. Finally, three numerical examples show these methods reducing conservatism and improving maximal allowable delay.

Further improvement on delay-range-dependent stability results for linear systems with interval time-varying delays.

This paper provides an improved delay-range-dependent stability criterion for linear systems with interval time-varying delays. No model transformation and no slack matrix variable are introduced. Furthermore, overly bounding for some cross term is avoided. The resulting criterion has advantages over some previous ones in that it involves fewer matrix variables but has less conservatism, which is established theoretically. Finally, two numerical examples are given to show the effectiveness of the proposed results.

Improved delay-dependent stability of neutral type neural networks with distributed delays.

This paper deals with the problem of improved delay-dependent stability analysis of neutral type neural networks with distributed delays. These conditions are in terms of linear matrix inequality (LMI), easily checked by recently developed algorithms in solving linear matrix inequalities (LMIs). Finally, numerical examples demonstrate effectiveness of the proposed method.

Delay-dependent global exponential robust stability for delayed cellular neural networks with time-varying delay.

This paper investigates a class of delayed cellular neural networks (DCNN) with time-varying delay. Based on the Lyapunov-Krasovski functional and integral inequality approach (IIA), a uniformly asymptotic stability criterion in terms of only one simple linear matrix inequality (LMI) is addressed, which guarantees stability for such time-varying delay systems. This LMI can be easily solved by convex optimization techniques. Unlike previous methods, the upper bound of the delay derivative is taken into consideration, even if larger than or equal to 1. It is proven that results obtained are less conservative than existing ones. Four numerical examples illustrate efficacy of the proposed methods.

Robust stability analysis of genetic regulatory network with time delays.

The robust asymptotic stability problem of genetic regulatory networks with time delays is investigated by Lyapunov functional approach and linear matrix inequality techniques (LMIs). Stability criteria for the delayed genetic regulatory networks are expressed as a set of LMIs, yielding much less conservative analytic results. New criteria with reduced conservatism are obtained and they involve less matrix parameters than the existing ones. Finally, three numerical examples are presented to illustrate effectiveness and less conservative results.

New results on stability analysis for time-varying delay systems with non-linear perturbations.

The problem of stability for linear time-varying delay systems under nonlinear perturbation is discussed, with delay assumed as time-varying. Delay decomposition approach allows information of the delayed plant states to be fully considered. A less conservative delay-dependent robust stability condition is derived, using integral inequality approach to express the relationship of Leibniz-Newton formula terms in the within the framework of linear matrix inequalities (LMIs). Merits of the proposed results lie in lesser conservatism, which are realized by choosing different Lyapunov matrices in the decomposed integral intervals and estimating the upper bound of some cross term more exactly. Numerical examples are given to illustrate the effectiveness and lesser conservatism of the proposed method.

Improved delay-dependent robust stability criteria for recurrent neural networks with time-varying delays.

In this paper, the problem of improved delay-dependent robust stability criteria for recurrent neural networks (RNNs) with time-varying delays is investigated. Combining the Lyapunov-Krasovskii functional with linear matrix inequality (LMI) techniques and integral inequality approach (IIA), delay-dependent robust stability conditions for RNNs with time-varying delay, expressed in terms of quadratic forms of state and LMI, are derived. The proposed methods contain the least numbers of computed variables while maintaining the effectiveness of the stability conditions. Both theoretical and numerical comparisons have been provided to show the effectiveness and efficiency of the present method. Numerical examples are included to show that the proposed method is effective and can provide less conservative results.

A delay decomposition approach to robust stability analysis of uncertain systems with time-varying delay.

This paper is concerned with delay-dependent robust stability for uncertain systems with time-varying delays. The proposed method employs a suitable Lyapunov-Krasovskii's functional for new augmented system. Then, based on the Lyapunov method, a delay-dependent robust criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. By developing a delay decomposition approach, the information of the delayed plant states can be taken into full consideration, and new delay-dependent sufficient stability criteria are obtained in terms of linear matrix inequalities (LMIs) which can be easily solved by various optimization algorithms. Numerical examples are included to show that the proposed method is effective and can provide less conservative results.