- Published on 07 October 2020
Nature is full of nonlinearities that are responsible for a great variety of responses and, in some sense, define biodiversity characteristics. In this regard, a nonlinear dynamics perspective is of special interest for a proper understanding of natural rhythms that can represent the most striking manifestations of natural and biological system behaviors. Natural rhythms can be either periodic or irregular over time and space and each kind of dynamical behavior may be related to both normal and pathological functioning.
Nonlinear dynamics of biological systems have been investigated considering different approaches and perspectives, focused on different purposes. Accordingly, investigations can be related to the general comprehension of physiological functioning, pathologies, control and biomedical engineering applications. In this regard, it is of special importance the investigation of biological rhythms employing a nonlinear dynamics perspective.
Modeling, numerical and experimental approaches are all employed in the analysis of complex biological rhythms. We invite researchers to contribute original articles to the Special Issue Complex Bio Rhythms to show continuing efforts to understand nonlinear systems such as biological and biomedical systems, biomechanics and general natural systems. Distinct aspects as modeling, bifurcations, synchronization, control, parameter estimation and engineering applications are of interest.
- Published on 03 September 2020
Many of the real world systems are composed of several interacting subsystems and have several degrees of freedom. The complexity in such systems arises from the nonlinearity in the dynamics of the interacting sub systems, heterogeneity in the pattern of interactions among them and presence of multiple dynamical time scales among them.
These systems can undergo sudden changes in their dynamical states or “tip” from one emergent dynamical state to another. The threshold of such sudden transitions, called “tipping point” represent the critical values of one or more of the system parameters or state variables at which a perturbation can lead to sudden qualitative change in the state of the system. As such it is important to study methods of detecting and characterising this phenomenon with proper measures.
- Published on 13 July 2020
The fluids which do not obey the Newton's law of viscosity are called non-Newtonian fluids. In general, the viscosity of non-Newtonian fluids changes with shear stress and the shear rate non-linearly varies with shear stress. The non-Newtonian fluids are classified as viscoelastic, rheopectic, thixotropic, shear thickening, and shear thinning fluids. Examples of fluids that exhibit the viscoelastic nature are oils, liquid polymers, glycerine, some lubricants, and mucus.
Fluids that exhibit shear thinning nature are blood, motor oil, ketchup, nail polish, syrups, molasses, paper pulp in water, latex paint, and whipped cream. Shear thinning fluids are useful in lubricating fast-moving engine parts manufacture, polymer industries, and biomedical industries. In view of these applications, a number of mathematical models have been proposed to obtain thorough cognition of the mechanics of non-Newtonian fluid flows. The non-Newtonian fluid models include Bingham plastic, Burgers fluid, Carreau fluid, Casson fluid, Cross fluid, Eyring Powell fluid etc.
EPJ ST Special Issue: Circuit Application of Chaotic Systems: Modeling, Dynamical Analysis and Control
- Published on 17 June 2020
To be referred as an amazing physical phenomenon with the highly sensitivity to initial conditions, chaos is ubiquitous in natural world and human society. Numerous explorations have reported the broad engineering application potential of chaos on account of its excellent features. Nowadays, chaos theory has become an important frontier research field. It is valuable research to build chaotic systems for engineering purposes, to reveal the complex dynamic properties of chaotic systems via different theoretical and numerical analysis, to consider its different control objectives by applying some effective and feasible control techniques. We are keenly aware that there are still many challenging issues to be addressed on chaos study by considering the existing research work. That is why the chaos study can sustain vitality and exert important influence.
- Published on 19 May 2020
The idea of a cosmological constant which produces an accelerated universe has seen many ups and downs ever since it was introduced and then disowned by Einstein. A firm evidence of that our universe is accelerating came from the Luminosity vs redshift measurement of Type-I supernova by Riess eta al and Perlmutter et al in 1999 a discovery which earned them a Nobel prize in 2011. The recent examinations of supernova data however shows that not all is well with the standard LambdaCDM model of cosmology. The supernova evidence indicates that the cosmic acceleration is not isotropic which raises questions on our standard cosmological models that the universe is described by the Friedmann-Lemaitre-Robertson-Walker metric with small perturbations which were generated in a earlier epoch of accelerated expansion called Inflation. Apart from the supernova data the examination of data from large scale galaxy distribution and cosmic microwave anisotropy observations show that there are problems with the six-parameter ΛCDM model. The amplitude of the matter mower spectrum determined by the parameter called σ8 and Hubble expansion rate H0 show discrepancies between the determination from LSS observations and their determination from CMB. The resolution of these discrepancies my lie in the evolution of dark energy in time which then requires a well motivated model.
- Published on 08 May 2020
Theory of machine learning, deep learning in particular has been witnessing an implosion lately in deciphering the “black-box approaches”. Optimizing deep neural networks is largely thought to be an empirical process, requiring manual tuning of several parameters. Drawing insights into these parameters gained much attention lately. The special issue aims to focus on gaining theoretical insights in the computation and setting of these parameters and solicits original work reflecting the influence of such theoretical framework on experimental results on standard datasets and architectures. It also aims to garner valuable talking points from optimization studies, another aspect of deep learning architectures and experiments. It is in this spirit that the guest editors wish to bridge metaheuristic optimization methods with deep neural networks and solicit papers that focus on exploring alternatives to gradient descent/ascent types methods. Papers with theoretical insights and proofs are particularly sought after, with or without limited experimental validation. The guest editors would welcome cutting-edge research on aspects of deep learning theory used in the fields of artificial intelligence, statistics and data science, theoretical and numerical optimization.
EPJ ST Special Issue: Non-equilibrium phase transitions in heterogeneous systems: biophysical aspects
- Published on 11 February 2020
This special issue is devoted to the problems of experimental and theoretical studies, as well as computer simulations of physical features of structural and phase transitions in various biological systems (blood, cell cultures, biogels, metastable bioliquids) involved in external macroscopically non-equilibrium processes (hydrodynamic flows; alternating magnetic and electrical fields, stochastic forcing, etc.). Special attention is focused on a detailed study of internal transformations on macroscopic physical properties and the behavior of the systems under study.
- Published on 24 January 2020
Interaction of intense laser pulses with matter on various scales is a growing area of research using table-top femtosecond and sub-femtosecond laser pulses as well as large-scale free electron lasers spanning the photon energy range from the infrared to x-rays. The Nobel prize in Physics (2018) was awarded in part to the development of “light tools” or lasers delivering intense near-infrared laser pulses. This has burgeoned research in intense laser matter interaction to develop attosecond pulses in the soft x-ray region to super-intense pulses to generate relativistic plasmas. The large scale end of this research saw a concomitant development in accelerator based photon sources of intense short wavelength light pulses VUV, soft- and hard x-rays from free-electron laser pulses. This science has grown rapidly in the last few decades and calls for a review and a collection to gather its length and breadth.
- Published on 10 January 2020
The 40th Max Born Symposium – Three Days on Strong Correlations in Dense Matter – was organized jointly by the Institute of Theoretical Physics (University of Wroclaw), the Helmholtz International Centre for FAIR, and the Polish Academy of Science, Wroclaw Branch. It had an interdisciplinary character, addressing the questions related with the phase structure of hot and dense matter determined by strong correlations such as bound states and condensates which are studied in the theory and phenomenological applications to thermonuclear fusion and heavy-ion collision experiments as well as (exo)planets, supernovae explosions, neutron stars, and their mergers.