Vol. 46 No.4 - Highlights

Does knowing the opponent's strategy guarantee optimal play? (Vol. 46 No. 4)

Methods of statistical physics are proving indispensable for the study of evolutionary games in structured populations. The evolution of cooperation and the phase transitions leading to favorable evolutionary outcomes depend sensitively on the structure of the interaction network and the type of interactions, as well as on the number and type of competing strategies. Now, physicists have solved the puzzle of the availability of information in evolutionary games. In a new theoretical model, the authors answer whether knowing the strategy of an opponent is indeed the holy grail of optimal play in social dilemmas, or whether the situation is in fact more complex. It is indeed the latter, as final evolutionary outcomes depend sensitively not just on individual relations between the competitors as determined by payoff elements, but equally strongly on the spatiotemporal dynamics of defensive alliances that emerge spontaneously as a result of strategic complexity. Reentrant phase transitions highlight the fact that the viability of an alliance depends sharply on the invasion speeds between group members who cyclically dominate each other.

A. Szolnoki and M. Perc, Reentrant phase transitions and defensive alliances in social dilemmas with informed strategies, EPL, 110, 38003 (2015)
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Novel plasma diagnostics method (Vol. 46 No. 4)

Could the mundane action of switching on an energy saving light bulb still hold secrets? It does, at least for physicists. These bulbs are interesting because they contain low-temperature plasma—a gas containing charges from ions and electrons. Now, the authors have developed a method that could be used for measuring the increase in the plasma force on the inner side of such a light bulb when the light is switched on. These findings have implications for plasma diagnostics concerning plasma-wall interactions used in surface modification and the production of thin film solar cells and microchips. This could lead to a promising new kind of plasma diagnostics, providing insights into processes that conventional electrical probes can’t detect.

T. Trottenberg, T. Richter and H. Kersten,, Measurement of the force exerted on the surface of an object immersed in a plasma, Eur. Phys. J. D 69, 91 (2015)
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The importance of rheology in tissue development (Vol. 46 No. 4)

Our understanding of biomechanics increasingly improves through the use of physics models. There are some intriguing biological questions regarding the interplay between the behaviour of cells and the mechanics at the level of tissues. For example, how does a collective behaviour, not apparent at the cell scale, emerge at the tissue level? Or how can the mechanical state of a tissue affect the cell division rate or the orientation of cells undergoing division?

The authors think that the interplay between genes and mechanics is key to understanding how the adult shape emerges from a developing tissue.

They construct rheological diagrams based on insights concerning the mechanics of the biological tissue. One of the main insights is a distinction between intra-cellular and inter-cellular mechanism. The local rheological equations obtained allow to generate a complete spatial model expressed as a set of partial differential equations. This procedure is conducted not only in the case of small elastic deformations, but also in the relevant, less discussed, case of large elastic deformations. The authors provide a functional and versatile toolbox for tissue modelling and propose a framework for a tensorial treatment of heterogeneous tissues. Although the simplest applications concern in vitro experiments, the same approach may be used for many other living tissues including animal tissues during development, wound healing, or carcinogenesis.

S. Tlili, C. Gay, F. Graner, Ph. Marcq, F. Molino and P. Saramito, Colloquium: Mechanical formalisms for tissue dynamics, Eur. Phys. J. E, 38, 33 (2015)
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Self-imaging process at the near field of cylindrical convex gratings (Vol. 46 No. 4)

Diffraction gratings have become one of the most used optical elements. Their behaviour has been extensively analysed from many diverse points of view. From a general sight, diffraction gratings produce diffraction orders at the far field and self-images at the near field. The applicability of diffraction gratings is quite extensive. They can be found as fundamental parts of many different devices such as telescopes, spectrometers, optical encoders, etc.

One particular kind of optical encoder uses cylindrical convex gratings. The authors show the near-field diffraction of cylindrical convex gratings illuminated by a general source that can be punctual or finite, monochromatic or polychromatic. They analyse how the size and polychromatism of the source affect the self-imaging process of cylindrical convex gratings. A decrease in the self-images contrast is produced for finite non-punctual sources. On the other hand, polychromaticity of the source produces quasi-continuous diffraction fringes from a certain distance forward.

All the results have been proven by experiments and could be helpful in applications that include convex diffraction gratings.

F. J. Torcal-Milla, L. M. Sanchez-Brea and E. Bernabeu,, Near field diffraction of cylindrical convex gratings, J. Opt., 17, 035601 (2015)
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Fragmentation of random trees (Vol. 46 No. 4)

Networks are ubiquitous, appearing in the study of subjects as diverse as gene-protein interactions, power grids, and algorithms.

The function of a network is closely linked to its structure. For instance, in biochemical reaction networks, removal of a species or reaction can dramatically change the output of the system. Evolving networks often undergo degradation, making it important to understand how the structure breaks apart when components are randomly removed, also revealing how resilient a network is to attacks.

We studied the fragmentation of a random tree, a network formed by repeatedly attaching new nodes to an existing node chosen uniformly randomly.

We present exact equations governing the evolution of fragment sizes after a fraction of the nodes are removed at random, along with asymptotic solutions. For very large trees, fragment size distribution decays as a power law, with an exponent of 1+1/m, m being the fraction of remaining nodes. This implies that a few very large fragments coexist with many small ones (see figure).

Our findings reveal unusual fragmentation kinetics, where the fragment size distribution is characterized by a time-dependent exponent, and can provide insight into other fragmentation processes where dynamic parameters are observed.

Z. Kalay and E. Ben-Naim, Fragmentation of random trees, J. Phys. A, Math. Theor., 48, 045001 (2015)
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Organic nanoparticles, more lethal to tumours (Vol. 46 No. 4)

Carbon-based nanoparticles could be used to sensitize cancerous tumours to proton radiotherapy and induce more focused destruction of cancer cells, a new study shows.

Radiotherapy used in cancer treatment is a promising treatment method, albeit rather indiscriminate. Indeed, it affects neighbouring healthy tissues and tumours alike. Researchers have thus been exploring the possibilities of using various radio-sensitizers; these nanoscale entities focus the destructive effects of radiotherapy more specifically on tumour cells. In a study published recently, the authors have now shown that the production of low-energy electrons by radio-sensitizers made of carbon nanostructures hinges on a key physical mechanism referred to as plasmons—collective excitations of so-called valence electrons; a phenomenon already documented in rare metal sensitizers. This reseach may lead to the development of novel types of sensitizers composed of metallic and carbon-based parts.

A. Verkhovtsev, S. McKinnon, P. de Vera, E. Surdutovich, S. Guatelli, A. V. Korol, A. Rosenfeld and V. Solov’yov,, Comparative analysis of the secondary electron yield from carbon nanoparticles and pure water medium, Eur. Phys. J. D 69, 116 (2015)
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Does that “green” plasticiser make my PVC flexible enough for you? (Vol. 46 No. 4)

A study of an eco-friendly solvent helping to make PVC plastic more flexible reveals the molecular-level interaction of hydrogen bonds between the two ingredients.

What gives plastic objects their flexibility and reduces their brittleness is the concentration of plasticiser. For example, a chemical solvent of the phthalate family called DOP is often used. The trouble is there are concerns that phthalates present health risks. So there is a demand for more alternatives. Now, the authors have examined the effect of using DEHHP, a new eco-friendly plasticiser, used in combination with PVC. For a plasticiser to work, there has to be adequate hydrogen bonding with the plastic. By combining experiments and simulations, the team revealed why the polymer-solvent hydrogen bonding interaction's strength decreases with dilution at a molecular level—which is a phenomenon also observed in the DOP-PVC combination. These findings have been published in the present work.

Y. Liu, R. Zhang, X. Wang, P. Sun, W. Chen, J. Shen and G. Xue, Hydrogenation induced deviation of temperature and concentration dependences of polymer-solvent interactions in poly(vinyl chloride) and a new eco-friendly plasticizer, Eur. Phys. J. Plus 130, 116 (2015)
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Brain learning simulated via electronic replica memory (Vol. 46 No. 4)

A new study shows how a new way of controlling electronic systems endowed with a memory can provide insights into the way associative memories are formed by mimicking synapses.

Scientists are attempting to mimic the memory and learning functions of neurons found in the human brain. To do so, they investigated the electronic equivalent of the synapse, the bridge, making it possible for neurons to communicate with each other. Specifically, they rely on an electronic circuit simulating neural networks using memory resistors. Such devices, dubbed memristor, are well-suited to the task because they display a resistance, which depends on their past states, thus producing a kind of electronic memory. The authors have developed a novel adaptive-control approach for such neural networks, presented in this study. Potential applications are in pattern recognition as well as fields such as associative memories and associative learning.

H. Zhao, L. Li, H. Peng, J. Kurths, J. Xiao and Y. Yang, Anti-synchronization for stochastic memristor-based neural networks with non-modeled dynamics via adaptive control approach, Eur. Phys. J. B 88, 109 (2015)
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