Chaotic transients in spatially extended systems

Different transient-chaos related phenomena of spatiotemporal systems are reviewed. Special attention is paid to cases where spatiotemporal chaos appears in the form of chaotic transients only. The asymptotic state is then spatially regular. In systems of completely different origins, ranging from fluid dynamics to chemistry and biology, the average lifetimes of these spatiotemporal transients are found, however, to grow rapidly with the system size, often in an exponential fashion. For sufficiently large spatial extension, the lifetime might turn out to be larger than any physically realizable time. There is increasing numerical and experimental evidence that in many systems such transients mask the real attractors. Attractors may then not be relevant to certain types of spatiotemporal chaos, or turbulence. The observable dynamics is governed typically by a high-dimensional chaotic saddle. We review the origin of exponential scaling of the transient lifetime with the system size, and compare this with a similar scaling with system parameters known in low-dimensional problems. The effect of weak noise on such supertransients is discussed. Different crisis phenomena of spatiotemporal systems are presented and fractal properties of the chaotic saddles underlying high-dimensional supertransients are discussed. The recent discovery according to which turbulence in pipe flows is a very long lasting transient sheds new light on chaotic transients in other spatially extended systems.     

Emergence of synchronized beating during the regrowth of eukaryotic flagella

A fundamental issue in the biology of eukaryotic flagella is the origin of synchronized beating observed in tissues and organisms containing multiple flagella. Recent studies of the biflagellate unicellular alga Chlamydomonas reinhardtii provided the first evidence that the interflagellar coupling responsible for synchronization is of hydrodynamic origin. To investigate this mechanism in detail, we study here synchronization in Chlamydomonas as its flagella slowly regrow after mechanically induced self-scission. The duration of synchronized intervals is found to be strongly dependent on flagellar length. Analysis within a stochastic model of coupled phase oscillators is used to extract the length dependence of the interflagellar coupling and the intrinsic beat frequencies of the two flagella. Physical and biological considerations that may explain these results are proposed.     

Magnetic field effects in proteins

ABSTRACT

Many animals can sense the geomagnetic field, which appears to aid in behaviours such as migration. The influence of man-made magnetic fields on biology, however, is potentially more sinister, with adverse health effects being claimed from exposure to fields from mobile phones or high voltage power lines. Do these phenomena have a common, biophysical origin, and is it even plausible that such weak fields can profoundly impact noisy biological systems? Radical pair intermediates are widespread in protein reaction mechanisms, and the radical pair mechanism has risen to prominence as perhaps the most plausible means by which even very weak fields might impact biology. In this New Views article, I will discuss the literature over the past 40 years that has investigated the topic of magnetic field effects in proteins. The lack of reproducible results has cast a shadow over the area. However, magnetic field and spin effects have proven to be useful mechanistic tools for radical mechanism in biology. Moreover, if a magnetic effect on a radical pair mechanism in a protein were to influence a biological system, the conditions necessary for it to do so appear increasing unlikely to have come about by chance.     

Advances in radiation biology: Radiosensitization in DNA and living cells

One fundamental goal of radiation biology is the evolution of concepts and methods for the elaboration of new approaches and protocols for the treatment of cancers. In this context, the use of fast ions as ionizing particles offers the advantage of optimizing cell killing inside the tumor whilst preserving the surrounding healthy tissues. One extremely promising strategy investigated recently is the addition of radiosensitizers in the targeted tissue. The optimization of radiotherapy with fast ions implies a multidisciplinary approach to ionizing radiation effects on complex living systems, ranging from studies on single molecules to investigations of entire organisms.In this article we review recent studies on ion induced damages in simple and complex biological systems, from DNA to living cells. The specific aspect of radiosensitization induced by metallic atoms is described. As a fundamental result, the addition of sensitizing compounds with ion irradiation may improve therapeutic index in cancer therapy. In conclusion, new perspectives are proposed based on the experience and contribution of different communities including Surface Sciences, to improve the development of radiation biology.     

Allometric scaling laws of metabolism

One of the most pervasive laws in biology is the allometric scaling, whereby a biological variable Y is related to the mass M of the organism by a power law, Y=Y₀M^b, where b is the so-called allometric exponent. The origin of these power laws is still a matter of dispute mainly because biological laws, in general, do not follow from physical ones in a simple manner. In this work, we review the interspecific allometry of metabolic rates, where recent progress in the understanding of the interplay between geometrical, physical and biological constraints has been achieved.

For many years, it was a universal belief that the basal metabolic rate (BMR) of all organisms is described by Kleiber's law (allometric exponent b=3/4). A few years ago, a theoretical basis for this law was proposed, based on a resource distribution network common to all organisms. Nevertheless, the 3/4-law has been questioned recently. First, there is an ongoing debate as to whether the empirical value of b is 3/4 or 2/3, or even nonuniversal. Second, some mathematical and conceptual errors were found these network models, weakening the proposed theoretical arguments. Another pertinent observation is that the maximal aerobically sustained metabolic rate of endotherms scales with an exponent larger than that of BMR. Here we present a critical discussion of the theoretical models proposed to explain the scaling of metabolic rates, and compare the predicted exponents with a review of the experimental literature. Our main conclusion is that although there is not a universal exponent, it should be possible to develop a unified theory for the common origin of the allometric scaling laws of metabolism.     

Self-similar scaling of density in complex real-world networks

Despite their diverse origin, networks of large real-world systems reveal a number of common properties including small-world phenomena, scale-free degree distributions and modularity. Recently, network self-similarity as a natural outcome of the evolution of real-world systems has also attracted much attention within the physics literature. Here we investigate the scaling of density in complex networks under two classical box-covering renormalizations–network coarse-graining–and also different community-based renormalizations. The analysis on over 50 real-world networks reveals a power-law scaling of network density and size under adequate renormalization technique, yet irrespective of network type and origin. The results thus advance a recent discovery of a universal scaling of density among different real-world networks [P.J. Laurienti, K.E. Joyce, Q.K. Telesford, J.H. Burdette, S. Hayasaka, Universal fractal scaling of self-organized networks, Physica A 390 (20) (2011) 3608–3613] and imply an existence of a scale-free density also within–among different self-similar scales of–complex real-world networks. The latter further improves the comprehension of self-similar structure in large real-world networks with several possible applications.     

The constructal unification of biological and geophysical design

Here we show that the emergence of scaling laws in inanimate (geophysical) flow systems is analogous to the emergence of allometric laws in animate (biological) flow systems, and that features of evolutionary “design” in nature can be predicted based on a principle of physics (the constructal law): “For a finite-size flow system to persist in time (to live) it must evolve in such a way that it provides easier and easier access to its currents”, meaning that the configuration and function of flow systems change over time in a predictable way that improves function, distributes imperfection, and creates geometries that best arrange high and low resistance areas or volumes. This theoretical unification of the phenomena of animate and inanimate flow design generation is illustrated with examples from biology (lung design, animal locomotion) and the physics of fluid flow (river basins, turbulent flow structure, self-lubrication). The place of this design-generation principle as a self-standing law in thermodynamics is discussed. Natural flow systems evolve by acquiring flow configuration in a definite direction in time: existing configurations are replaced by easier flowing configurations.     

Spatially resolved simulations of membrane reactions and dynamics: Multipolar reaction DPD

Biophysical chemistry of mesoscale systems and quantitative modeling in systems biology now require a simulation methodology unifying chemical reaction kinetics with essential collective physics. This will enable the study of the collective dynamics of complex chemical and structural systems in a spatially resolved manner with a combinatorially complex variety of different system constituents. In order to allow a direct link-up with experimental data (e.g. high-throughput fluorescence images) the simulations must be constructed locally, i.e. mesoscale phenomena have to emerge from local composition and interactions that can be extracted from experimental data. Under suitable conditions, the simulation of such local interactions must lead to processes such as vesicle budding, transport of membrane-bounded compartments and protein sorting, all of which result from a sophisticated interplay between chemical and mechanical processes and require the link-up of different length scales. In this work, we show that introducing multipolar interactions between particles in dissipative particle dynamics (DPD) leads to extended membrane structures emerging in a self-organized manner and exhibiting the necessary mechanical stability for transport, correct scaling behavior, and membrane fluidity so as to provide a two-dimensional self-organizing dynamic reaction environment for kinetic studies in the context of cell biology.     

Universality in food webs

Among recently studied real-world networks, food webs are particularly interesting since they provide an example of biological organization at the largest scale, namely that of ecological communities. Quite surprisingly, recent results reveal that food webs do not display those properties which are observed in almost all other networks, such as a scale-free degree distribution and a large clustering coefficient. However, when food webs are regarded from the point of view of trasportation networks, it is possible to uncover very interesting scaling properties which are displayed by other trasportation systems, namely vascular and river networks. While other topological properties appear to vary across different webs depending on specific aspects, such scaling relations are universal. An interpretation of these results in terms of the interplay of universal and nonuniversal mechanisms in food web evolution is suggested.Received: 26 December 2003, Published online: 14 May 2004PACS: 87.23.-n Ecology and evolution - 89.75.-k Complex systems - 05.65. + b Self-organized systems     

Dissipative Structures,Organisms and Evolution

Self-organization in nonequilibrium systems has been known for over 50 years. Under nonequilibrium conditions, the state of a system can become unstable and a transition to an organized structure can occur. Such structures include oscillating chemical reactions and spatiotemporal patterns in chemical and other systems. Because entropy and free-energy dissipating irreversible processes generate and maintain these structures, these have been called dissipative structures. Our recent research revealed that some of these structures exhibit organism-like behavior, reinforcing the earlier expectation that the study of dissipative structures will provide insights into the nature of organisms and their origin. In this article, we summarize our study of organism-like behavior in electrically and chemically driven systems. The highly complex behavior of these systems shows the time evolution to states of higher entropy production. Using these systems as an example, we present some concepts that give us an understanding of biological organisms and their evolution.     

Use and Abuse of Entropy in Biology: A Case for Caliber

Here, I discuss entropy and its use as a tool in fields of biology such as bioenergetics, ecology, and evolutionary biology. Statistical entropy concepts including Shannon’s diversity, configurational entropy, and informational entropy are discussed in connection to their use in describing the diversity, heterogeneity, and spatial patterning of biological systems. The use of entropy as a measure of biological complexity is also discussed, and I explore the extension of thermodynamic entropy principles to open, nonequilibrium systems operating in finite time. I conclude with suggestions for use of caliber, a metric similar to entropy but for time-dependent trajectories rather than static distributions, and propose the complementary notion of path information.     

Scaling laws and the modern city

The inter-relations and the complexity of modern urban spaces are difficult to analyse in a way that allows improving living conditions or help to ascertain optimal decisions for saving energy or improving sustainability. Carefully designed decisions and guidelines might produce unexpected results because of particularities, or complex sets of reactions from residents or economic counterparts. Complexity tends to increase with size, such as when, for instance, services tend to concentrate in large agglomerations, and transportation needs take on critical importance. Complex systems such as living organisms are known to follow approximate relationships as scaling laws between the variables that describe them. Some of these kinds of relationships are tested in relation to modern developed urban spaces, in which it is possible to find a reasonable continuity with the types of scales seen in living organisms, and some preliminary conclusions are drawn.     

Uncovering the underlying physical mechanisms of biological systems via quantification of landscape and flux

In this review, we explore the physical mechanisms of biological processes such as protein folding and recognition,ligand binding, and systems biology, including cell cycle, stem cell, cancer, evolution, ecology, and neural networks. Our approach is based on the landscape and flux theory for nonequilibrium dynamical systems. This theory provides a unifying principle and foundation for investigating the underlying mechanisms and physical quantification of biological systems.     

Scaling law of anomalous Hall effect in Fe/Cu bilayers

The scaling of anomalous Hall resistivity on longitudinal resistivity has been intensively studied in different magnetic systems, including multilayer and granular films, to examine whether a skew scattering or a side jump mechanism dominates in the origin of anomalous Hall effect (AHE). The scaling law is based on the premise that both resistivities are a consequence of electron scattering by the imperfections in the materials. By studying the anomalous Hall effect in the simple Fe/Cu bilayers, it was demonstrated that the measured anomalous Hall effect should not follow the scaling laws derived from skew scattering or side jump mechanism due to the short-circuit and shunting effects of the non-magnetic layers.     

X射线光谱技术在生物与生态环境中的应用进展

环境样品中元素的浓度、空间分布和赋存形态等是认识元素的生物功能和环境行为的关键。本文对近年来X射线光谱技术在生物与生态环境中的应用研究进展进行了评述,发现X射线荧光光谱技术可以提供活体植物中元素迁移与分布的定量数据,且微区X射线荧光光谱和X射线吸收谱技术的联用可深入认识生物与元素的相互作用,尤其是生物对元素的吸收、转运、贮存和细胞解毒机制,同时也能够揭示典型环境样品中元素的来源、演化和归趋等环境行为。然而,由于生物和环境样品基质的复杂性和多样性,仍存在一些技术难点与挑战,如X射线荧光自吸收效应的克服、低丰度（5%~10%）的元素形态的准确鉴定,以及对活体细胞中短暂的元素氧化还原反应的捕捉等。     

Femtosecond lasers in biology: nanoscale surgery with ultrafast optics

Femtosecond lasers are emerging as a powerful tool in basic biological research. The high peak light intensity generated by a tightly focused, ultrashort, pulse of infrared laser light enables versatile submicron ablation deep within biological samples. Recent studies have begun to exploit these capabilities to conduct meticulous laser surgery experiments within single cells, as well as within intact organisms. This review will discuss the basic physical mechanisms behind femtosecond laser ablation in biological samples. It will then examine a series of prominent applications in biology and how they are opening new possibilities in a range of research fields. The interface between physics and biology has been exceptionally fruitful over recent years and femtosecond laser ablation is proving to be another prime example of this.     

Effect of coarse-graining on detrended fluctuation analysis

Several studies have investigated the scaling behavior in naturally occurring biological and physical processes using techniques such as detrended fluctuation analysis (DFA). Data acquisition is an inherent part of these studies and maps the continuous process into digital data. The resulting digital data is discretized in amplitude and time, and shall be referred to as coarse-grained realization in the present study. Since coarse-graining precedes scaling exponent analysis, it is important to understand its effects on scaling exponent estimators such as DFA. In this brief communication, k-means clustering is used to generate coarse-grained realizations of data sets with different correlation properties, namely: anti-correlated noise, long-range correlated noise and uncorrelated noise. It is shown that the coarse-graining can significantly affect the scaling exponent estimates. It is also shown that scaling exponent can be reliably estimated even at low levels of coarse-graining and the number of the clusters required varies across the data sets with different correlation properties.     

The physical position neighbourhood evolving network model

Many social, technological, biological and economical systems are properly described by evolved network models. In this paper, a new evolving network model with the concept of physical position neighbourhood connectivity is proposed and studied. This concept exists in many real complex networks such as communication networks. The simulation results for network parameters such as the first nonzero eigenvalue and maximal eigenvalue of the graph Laplacian, clustering coefficients, average distances and degree distributions for different evolving parameters of this model are presented. The dynamical behaviour of each node on the consensus problem is also studied. It is found that the degree distribution of this new model represents a transition between power-law and exponential scaling, while the Barábasi-Albert scale-free model is only one of its special (limiting) cases. It is also found that the time to reach a consensus becomes shorter sharply with increasing of neighbourhood scale of the nodes.     

Growth of walled cells: from shells to vesicles

The growth of isolated walled cells is investigated. Examples of such cells range from bacteria to giant algae, and include cochlear hair, plant root hair, fungi, and yeast cells. They are modeled as elastic shells containing a liquid. Cell growth is driven by fluid pressure and is is similar to a plastic deformation of the wall. The requirement of mechanical equilibrium leads to two new scaling laws for cell size that are in quantitative agreement with the compiled biological data. Given these results, possible shapes for growing cells are computed by analogy with those of vesicle membranes.     

Coarsening in inhomogeneous systems

This article is a brief review of coarsening phenomena occurring in systems where quenched features—such as random field, varying coupling constants or lattice vacancies—spoil homogeneity. We discuss the current understanding of the problem in ferromagnetic systems with a non-conserved scalar order parameter by focusing primarily on the form of the growth law of the ordered domains and on the scaling properties.