Response Of Complex System Research Articles

Modular metabolic control analysis of large responses

Deciphering the laws that govern metabolic responses of complex systems is essential to understand physiological functioning, pathological conditions and the outcome of experimental manipulations of intact cells. To this aim, a theoretical and experimental sensitivity analysis, called modular metabolic control analysis (MMCA), was proposed. This field was previously developed under the assumptions of infinitesimal changes and/or proportionality between parameters and rates, which are usually not fulfilled in vivo. Here we develop a general MMCA for two modules, not relying on those assumptions. Control coefficients and elasticity coefficients for large changes are defined. These are subject to constraints: summation and response theorems, and relationships that allow calculating control from elasticity coefficients. We show how to determine the coefficients from top-down experiments, measuring the rates of the isolated modules as a function of the linking intermediate (there is no need to change parameters inside the modules). The novel formalism is applied to data of two experimental studies from the literature. In one of these, 40% increase in the activity of the supply module results in less than 4% increase in flux, while infinitesimal MMCA predicts more than 30% increase in flux. In addition, it is not possible to increase the flux by manipulating the activity of demand. The impossibility of increasing the flux by changing the activity of a single module is due to an abrupt decrease of the control of the modules when their corresponding activities are increased. In these cases, the infinitesimal approach can give highly erroneous predictions.

Assessment of seismic vulnerability of structures

The paper addresses the application of effective tools for investigating structural integrity under earthquake loading, namely experimental testing, computer analysis and field data collection, and their combination. In particular, the application of hybrid (experimental-analytical) distributed (using several sites) simulation, hereafter referred to as HDS, to investigate seismic response of complex systems is presented. After briefly reviewing and comparing approaches of field surveys, testing, analysis and hybrid simulation, the paper deals with five applications where at least two of the three tools have been successfully applied. The collapse of the I-880 (Cypress Viaduct) during the Loma Prieta (California) earthquake of 1989 was investigated analytically following field observation of the failure modes. A plausible mechanism was postulated based on advanced analysis and supported by field data. Analytical studies aimed at quantifying the demand imposed on steel moment frames in the Northridge (California) earthquake of 1994 pointed towards a possible contribution of vertical beam modes to the increased rotational demand imposed on connections, leading to their failure. Next, issues of irregularity and lack of seismic detailing in RC buildings, repeatedly observed to be a major contributor to damage, are studied at full scale using laboratory testing, supported by advanced analysis to steer the model design and tune the level of input motion. Reinforced concrete bridges are also studied, using advanced analysis and field observations to investigate the partial collapse of a ramp structure part of the Santa Monica Freeway (I-10). Finally, two examples of applications of hybrid distributed simulation (HDS) are presented, one of which is a continuation of the steel moment frames analytical investigation. It is emphasized that it is only through integrating the available investigation tools that the response of complex systems may be understood, leading to more economical and safer built environments in regions subjected to earthquakes.

Degrees of separation: Hillslope-channel coupling and the limits of palaeohydrological reconstruction

Qualitative analysis of hillslope-channel coupling conditions suggests that the internal configuration of a catchment has a strong influence on the transfer of water and sediment through the fluvial system. Consequently, similar climatic inputs into catchments with otherwise similar characteristics can result in very divergent responses. A cellular modelling approach has been used to evaluate the potential magnitude of this effect, and to investigate the implications for palaeohydrological investigations. Simple catchments with coupled and progressively uncoupled conditions (marked by the presence of one and two floodplain levels) were subjected to simulated climate change using a 740 ka proxy climate record. Dynamic flow and sediment routing were simulated, and vegetation and soils allowed to evolve in parallel. The results suggest that catchment configuration has a very strong effect producing a complex system response based on the output of sediment from the catchment and that there are no simple relationships between climate and catchment output. The complex response itself also evolves through time as the catchment dynamically reorganizes, implying that system trajectory and historical contingency are also significant factors. Although events may be captured in the sedimentary record, these events will often relate to pulses of sediment working their way through the system, rather than being directly related to climate changes or variability. The complex, non-equilibrium behaviour of the system suggests that climate proxies derived from even high-resolution palaeohydrological records should be treated with extreme caution.

Application of a Bayesian Approach to the Tomographic Analysis of Hopper Flow

AbstractThis paper presents a new approach to the analysis of data on powder flow from electrical capacitance tomography (ECT) using probability modelling and Bayesian statistics. The methodology is illustrated for powder flow in a hopper. The purpose, and special features, of this approach is that ‘high‐level’ statistical Bayesian modelling combined with a Markov chain Monte Carlo (MCMC) sampling algorithm allows direct estimation of control parameters of industrial processes in contrast to usually applied ‘low‐level’, pixel‐based methods of data analysis. This enables reliable recognition of key process features in a quantitative manner. The main difficulty when investigating hopper flow with ECT is due to the need to measure small differences in particle packing density. The MCMC protocol enables more robust identification of the responses of such complex systems. This paper demonstrates the feasibility of the approach for a simple case of particulate material flow during discharging of a hopper. It is concluded that these approaches can offer significant advantages for the analysis and control of some industrial powder and other multi‐phase flow processes.

Dynamic and reliability analysis of stochastic structure system using probabilistic finite element method

Industrial structure systems may have nonlinearity, and are also sometimes exposed to the danger of random excitation. This paper proposes a method to analyze response and reliability design of a complex nonlinear structure system under random excitation. The nonlinear structure system which is subjected to random process is modeled by finite element method. The nonlinear equations are expanded sequentially using the perturbation theory. Then, the perturbed equations are solved in probabilistic methods. Several statistical properties of random process that are of interest in random vibration applications are reviewed in accordance with the nonlinear stochastic problem.

The genomic response of skeletal muscle to methylprednisolone using microarrays: tailoring data mining to the structure of the pharmacogenomic time series.

High-throughput data collection using gene microarrays has great potential as a method for addressing the pharmacogenomics of complex biological systems. Similarly, mechanism-based pharmacokinetic/pharmacodynamic modeling provides a tool for formulating quantitative testable hypotheses concerning the responses of complex biological systems. As the response of such systems to drugs generally entails cascades of molecular events in time, a time series design provides the best approach to capturing the full scope of drug effects. A major problem in using microarrays for high-throughput data collection is sorting through the massive amount of data in order to identify probe sets and genes of interest. Due to its inherent redundancy, a rich time series containing many time points and multiple samples per time point allows for the use of less stringent criteria of expression, expression change and data quality for initial filtering of unwanted probe sets. The remaining probe sets can then become the focus of more intense scrutiny by other methods, including temporal clustering, functional clustering and pharmacokinetic/pharmacodynamic modeling, which provide additional ways of identifying the probes and genes of pharmacological interest.

Response of complex networks to stimuli.

We consider the response of complex systems to stimuli and argue for the importance of both sensitivity, the possibility of large response to small stimuli, and robustness, the possibility of small response to large stimuli. Using a dynamic attractor network model for switching of patterns of behavior, we show that the scale-free topologies often found in nature enable more sensitive response to specific changes than do random networks. This property may be essential in networks where appropriate response to environmental change is critical and may, in such systems, be more important than features, such as connectivity, often used to characterize network topologies. Phenomenologically observed exponents for functional scale-free networks fall in a range corresponding to the onset of particularly high sensitivities, while still retaining robustness.

Broadly altered gene expression in blood leukocytes in essential hypertension is absent during treatment.

We assessed whether large-scale expression profiling of leukocytes of patients with essential hypertension reflects characteristics of systemic disease and whether such changes are responsive to antihypertensive therapy. Total RNA from leukocytes were obtained from untreated (n=6) and treated (n=6) hypertensive patients without apparent end-organ damage and from normotensive controls (n=9). RNA was reverse-transcribed and labeled and gene expression analyzed using a 19-K oligonucleotide microarray using dye swaps. Samples of untreated and of treated patients were pooled for each sex and compared with age- and sex-matched controls. In untreated patients, 680 genes were differentially regulated (314 up and 366 down). In the treated patients, these changes were virtually absent (4 genes up, 3 genes down). A myriad of changes was observed in pathways involved in inflammation. Inflammation-dampening interleukin receptors were decreased in expression. Intriguingly, inhibitors of cytokine signaling (the PIAS family of proteins) were differentially expressed. The expression of several genes that are involved in regulation of blood pressure were also differentially expressed: angiotensin II type 1 receptor, ANP-A receptor, endothelin-2, and 3 of the serotonin receptors were increased, whereas endothelin-converting enzyme-1 was decreased. Strikingly, virtually no changes in gene expression could be detected in hypertensive patients who had become normotensive with treatment. This observation substantiates the long-standing idea that hypertension is associated with a complex systemic response involving inflammation-related genes. Furthermore, leukocytes display differential gene expression that is of importance in blood pressure control. Importantly, treatment of blood pressure to normal values can virtually correct such disturbances.

Well-conditioned model predictive control

Abstract Model-based predictive control is an advanced control strategy that uses a move suppression factor or constrained optimization methods for achieving satisfactory closed-loop dynamic responses of complex systems. While these approaches are suitable for many processes, they are formulated on the selection of certain parameters that are ambiguous and also computationally demanding which makes them less suited for tight control of fast processes. In this paper, a new dynamic matrix control (DMC) algorithm is proposed that reduces inherent ill-conditioning by allowing the process prediction time step to exceed the control time step. The main feature, that stands in contrast with current DMC approaches, is that the original open-loop data are used to evaluate a “shifting factor” m in the controller matrix where m replaces the move suppression coefficient. The new control algorithm is practically demonstrated on a fast reacting process with better control being realized in comparison with DMC using move suppression. The algorithm also gives improved closed-loop responses for control simulations on a multivariable nonlinear process having variable dead-time, and on other models found in the literature. The shifting factor m is generic and can be effectively applied for any control horizon.

Prediction of damped circular cylindrical shell vibration using energy flow analysis

Approximate energy prediction tools are gaining popularity in the field of engineering noise control because of the need to quickly predict the high frequency dynamic response of complex systems. One approximate energy prediction tool commonly used is statistical energy analysis. However, many problems encountered in the field of engineering noise control do not satisfy the assumptions of lightly damped, lightly coupled systems. A second method, energy flow analysis, has been proposed for the case of moderate damping and coupling. The application of energy flow analysis to plates and beams is well documented in the literature. However, applications of energy flow analysis to shells of curvature are limited and need to be addressed. Two approaches for modeling radial vibration of damped circular cylindrical shells using energy flow analysis are proposed and verified in this presentation. The formulations of the solutions are discussed. Qualitative and quantitative comparisons of the responses predicted by the energy flow models to analytical predictions are made. From the comparisons, it is concluded that energy flow analysis provides a valid method to model radial vibration of circular cylindrical shells subjected to a radial excitation both above and below the ring frequency of the cylinder.

Signaling Role of Hemocytes in Drosophila JAK/STAT-Dependent Response to Septic Injury

To characterize the features of JAK/STAT signaling in Drosophila immune response, we have identified totA as a gene that is regulated by the JAK/STAT pathway in response to septic injury. We show that septic injury triggers the hemocyte-specific expression of upd3, a gene encoding a novel Upd-like cytokine that is necessary for the JAK/STAT-dependent activation of totA in the Drosophila counterpart of the mammalian liver, the fat body. In addition, we demonstrate that totA activation also requires the NF-KB-like Relish pathway, indicating that fat body cells integrate the activity of NF-KB and JAK/STAT signaling pathways upon immune response. This study reveals that, in addition to the pattern recognition receptor-mediated NF-KB-dependent immune response, Drosophila undergoes a complex systemic response that is mediated by the production of cytokines in blood cells, a process that is similar to the acute phase response in mammals.

Validation of a medium-frequency computational method for the coupling between a plate and a water-filled cavity

The aim of this paper is the validation of a computation by a numerical method, normally adapted to the medium-frequency (MF) domain, of the strong coupling between an elastic structure (plate) and a cavity entirely filled with an internal acoustic viscous dense fluid (water). The method of computation does not lie in a modal approach (no need to extract the modal basis of the system) but it directly computes the frequency response of the system using a specific algorithm called the “Onera-MF method”. This method was developed to accurately calculate the response of complex systems in an MF broad band at a lower cost than standard modal method or direct step-by-step frequency method. The method can also be used for the low-frequency (LF) domain where modal densities of systems are low. The computation of the vibroacoustic response of the system lies in a finite element modelling of the overall system (structure and fluid) in which the coupling between the structure and the fluid (light or heavy) is directly taken into account within the formulation of the finite elements. A simple and well-known experimental case was chosen for validation: a parallelepipedic cavity entirely filled with water contained in a box defined by five rigid faces and closed at its end by an elastic clamped homogeneous plate. The validation is based on a comparison between measurement, the numerical computation and an analytical approach in the frequency band [0,5000 Hz] . Both the vibratory response of the plate and the acoustic pressure were compared. This study shows that the MF-method of computation used herein for this case also works in a modal domain.

Substructure analysis of complex systems using rigid body information of components

Frequency response function (FRF) based substructure analysis can predict the response of complex systems using the FRFs of substructures. It combines the FRFs of each substructure derived from finite element analysis or experiments depending on the situation. In general, the substructure with the excitation is separated from the others by rubber bushes to prevent the transmission of vibration from the source to the main structure. In this case, the substructure with the excitation shows rigid body motion up to the mid-frequency region. This paper presents a new FRF-based substructure analysis that uses the FRFs from the rigid body information not from the complex finite element model of the substructure with rigid body motion. The rigid body information including the mass, the moment of inertia and the coordinates of the mass centre comes from the computer-aided design data. Since the mechanism of this technique is very similar to the finite element formation, it can be applied to complex systems with ease. Through a simple example of a ladder structure and a practical example of the interior noise in a car, the accuracy and efficiency of this approach is proven.

Relaxation of dynamically correlated clusters

In the frame of a new probabilistic approach to relaxation, the scenario of relaxation leading to the Havriliak–Negami and Kohlrausch–Williams–Watts responses of complex systems is presented. In this approach the macroscopic laws are related to the micro/mesoscopic stochastic characteristics of the relaxing systems. This provides a rigorous formulation of the energy-criterion argument, introduced by Jonscher to explain the commonly observed high-frequency fractional power law. The presented considerations reinforce the physical significance of the empirically found forms of relaxation, and open a new line of analysis of relaxation phenomena.

Evaluation of the Koutecký–Koryta approximation for voltammetric currents generated by metal complex systems with various labilities

The voltammetric response of metal complex systems with various labilities is analyzed by rigorous numerical simulation with the Finite Element Method of the time-dependent concentration profiles of the different species. The ensuing exact fluxes and the corresponding currents are compared to those derived from the Koutecký–Koryta (KK) approximation which assumes a discontinuous transition in the concentration profiles from non-labile to labile behavior. The results indicate a relatively far-reaching correctness of the KK approximation in the complete kinetic range from non-labile to labile complexes, as long as the kinetic flux is computed from the effective concentration of the complex in the reaction layer. Some approximate analytical expressions for this concentration are provided. The KK approximation is shown to be applicable for any metal-to-ligand ratio, provided that the thickness of the reaction layer is expressed in terms of the ligand concentration at the electrode surface.

Linear response in complex systems: CTRW and the fractional Fokker–Planck equations

We consider the linear response of systems modelled by continuous-time random walks (CTRW) and by fractional Fokker–Planck equations under the influence of time-dependent external fields. We calculate the corresponding response functions explicitly. The CTRW curve exhibits aging, i.e., it is not translationally invariant in the time domain. This is different from what happens under fractional Fokker–Planck conditions.

Nonlinear Modal Analysis of Structural Systems Using Multi-Mode Invariant Manifolds

In this paper, an invariant manifold approach is introduced for the generationof reduced-order models for nonlinear vibrations of multi-degrees-of-freedomsystems. In particular, the invariant manifold approach for defining andconstructing nonlinear normal modes of vibration is extended to the case ofmulti-mode manifolds. The dynamic models obtained from this technique capture the essential coupling between modes of interest, while avoiding coupling fromother modes. Such an approach is useful for modeling complex systemresponses, and is essential when internal resonances exist between modes.The basic theory and a general, constructive methodology for the method arepresented. It is then applied to two example problems, one analytical andthe other finite-element based. Numerical simulation results are obtainedfor the full model and various types of reduced-order models, including theusual projection onto a set of linear modes, and the invariant manifoldapproach developed herein. The results show that the method is capable ofaccurately representing the nonlinear system dynamics with relatively fewdegrees of freedom over a range of vibration amplitudes.

Isovariant Dynamics Expand and Buffer the Responses of Complex Systems: The Diverse Plant Actin Gene Family

Isovariant Dynamics Expand and Buffer the Responses of Complex Systems: The Diverse Plant Actin Gene Family

Isovariant dynamics expand and buffer the responses of complex systems: the diverse plant actin gene family.

Most plant and animal genes are members of gene families that are differentially expressed and may encode diverse protein isovariants. With the recent explosion of information in plant genomics, researchers have become acutely aware that the gene families in plants are at least as diverse as their

Hysteresis in the temperature response of carbon dioxide and methane production in peat soils

The ability to predict the effects of climate change on trace gas fluxes requires a knowledge of microbial temperature responses. However, the response of a microbial community to temperature in a given substrate may be complicated by its thermal history. To examine the effect of sequentially changing temperature on methane and carbon dioxide production in different peat types, we incubated anaerobic peat samples from 3 types of northern peatlands, a bog, a sedge fen and a cedar swamp, in both rising and falling temperature regimes. Graphic and statistical comparisons of the different temperature regimes suggest hysteresis in microbial response to temperature, although the absolute rates at any given temperature often did not differ. Where regressions for temperature response (Arrhenius plots) were significant, they generally differed between temperature regimes. The greatest differences among treatments occurred during the first half of the 40-d incubation. Increases in carbon dioxide production were similar across all peat types, but methanogenesis varied widely: methane production was uniformly low in the bog peat but increased sharply with temperature in the other two peat types. The complicating effect of history or chronology on substrate responses to environmental stimuli may restrain our ability to model the responses of complex systems to changing conditions.