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Study of internet file sizes shows that information growth is self-limited by the human mind. It is found here that it is the capacity of the human brain to process and record information –and not economic constraints – that may constitute the dominant limiting factor for the overall growth of globally stored information.

The authors first looked at the distribution of 633 public internet files by plotting the number of videos, audio and image files against the size of the files. They chose to focus on files hosted on domains pointing from the online encyclopaedia Wikipedia and the open web directory dmoz.

The absence of exponential tails for the graph representing the number of files indicates that economic costs were not the limiting factors for data production. Instead, it appears that underlying neurophysiological processes influence the brain’s ability to handle information. For example, when the individual attributes a subjective resolution to an image, their perception of the quality of that image matter. Their perception of the amount of information gained when increasing the resolution of a low-quality image is substantially higher then when increasing the resolution of a high-quality photo by the same degree.

The analysis shows that this relation, known as the Weber-Fechner law, is also obeyed by file-size distributions. This means that the total amount of information cannot grow faster than our ability to digest or handle it.

Collisions between slow highly charged ions and atoms are one of the most common fundamental processes in space. The consequent emitted light is used to diagnose the relative abundance of constituents in intergalactic clouds and comets. During the collision, the projectile-ions capture, in a highly excited-state, from one to many target-electrons. By a series of atomic cascades the electrons "tumble" from the very high atomic levels onto the ground state through multiple and complex pathways. These cascades lead to photon and/or electron emissions. The accurate analysis of the light (from UV to hard X) emitted during the interaction provides direct insights into the early stages of capture mechanisms.

Until now, for systems involving a large number of electrons, only low-resolution X-ray spectra recorded with solid state detectors were available. In the present work, the contribution of single-electron capture from multiple-capture processes in the X-ray emission have been successfully disentangled for an Ar¹⁷⁺ projectile colliding with N₂ or Ar gaseous target at v=0.53 a.u.

Thanks to an accurate calibration of the spectrometers and a complete determination of the ion beam-gas target overlap, absolute X-ray emission cross section has been extracted with a significant improvement in uncertainty. Using a mosaic crystal spectrometer, 2 orders of magnitude in resolving power have been reached. The whole He-like Ar¹⁶⁺ Lyman series from n = 2 to 10 has been resolved as well as the fine structure of 1s2l → 1s2 transitions. The role of single-electron capture, leading to transitions from n = 7 to 10 levels, has been clearly discriminated from multiple capture processes that populate lower lying states. Furthermore, a precise determination of the influence of metastable states emphasizes that transposition of the measurements via ’laboratory ion-atom collisions’ towards interpretation of astrophysical spectra should be made with caution.

Scientists aim at forecasting natural or economic disasters by identifying statistical anomalies in complex systems that deviate from behaviour obeying traditional power laws. This article and the special issue it comes from, present the many facets of Dragon Kings in a review alongside nineteen other contributions exploring to which extent this emerging field of statistical analysis could become further established.

Dragon Kings are events akin to catastrophes. They don’t belong to the same power law regime as the more standard events. For example, they can be found in financial market bubbles ending in crashes and neuron-firing cascades leading to epileptic seizures.

This review focuses on elucidating how Dragon Kings are created and can be detected. It also gives an overview of their empirical evidence in abnormal rainfall, hurricanes, and sudden events such as landslides and snow avalanches. The authors also outline the limitations of this sort of statistical analysis. For example, despite being sometimes interpreted as featuring characteristic events of Dragon Kings, great earthquakes may not be formally confirmed as such.

Finally, the authors share their views on the importance of devising prediction models that could become the basis for Dragon Kings simulators. These could be designed to help interpret the warning signs of complex systems evolving out of their safe equilibrium into extreme events such as the subprime crisis, and to steer them into sustainability and ultimately avoid such crisis.