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The dynamics of neuronal systems are characterized by hallmark features such as oscillations and synchrony. However, it has remained unclear whether these characteristics are epiphenomena or are exploited for computation. Due to the challenge of selectively interfering with oscillatory network dynamics in neuronal systems, we simulated recurrent networks of damped harmonic oscillators in which oscillatory activity is enforced in each node, a choice well supported by experimental findings. When trained on standard pattern recognition tasks, these harmonic oscillator recurrent networks (HORNs) outperformed nonoscillatory architectures with respect to learning speed, noise tolerance, and parameter efficiency. HORNs also reproduced a many characteristic features of neuronal systems, such as the cerebral cortex and the hippocampus. In trained HORNs, stimulus-induced interference patterns holistically represent the result of comparing sensory evidence with priors stored in recurrent connection weights, and learning-induced weight changes are compatible with Hebbian principles. Implementing additional features characteristic of natural networks, such as heterogeneous oscillation frequencies, inhomogeneous conduction delays, and network modularity, further enhanced HORN performance without requiring additional parameters. Taken together, our model allows us to give plausible a posteriori explanations for features of natural networks whose computational role has remained elusive. We conclude that neuronal systems are likely to exploit the unique dynamics of recurrent oscillator networks whose computational superiority critically depends on the oscillatory patterning of their nodal dynamics. Implementing the proposed computational principles in analog hardware is expected to enable the design of highly energy-efficient and self-adapting devices that could ideally complement existing digital technologies., Competing Interests: Competing interests statement:F.E. and W.S. have filed a patent application for the hardware implementation of the described network models at the European Patent Office, Application No. EP22183567.1.

Transport of energetic electrons in the flare loop is important to understanding nonthermal emissions in solar flares. In this work, we model the propagation of electrons by numerically solving the particle transport equation which includes the physics of magnetic mirroring and turbulent pitch-angle diffusion. We find that both the fractions of electrons trapped in the looptop and precipitating into the solar surface display a non-monotonic behavior with increasing scattering rate. In the moderate diffusion regime, the precipitation fraction is highest and we expect intense nonthermal HXR and microwave emissions at the footpoints. With no or weak pitch-angle scattering, the velocity space distribution can be highly anisotropic both in the looptop and loopleg regions. Different patterns of stripes with positive gradients in the perpendicular direction can drive the electron cyclotron maser instability with higher efficiency than the classical loss-cone distribution, facilitating the excitation of coherent solar radio bursts. Our simulation results highlight the effects of turbulent pitch-angle scattering on electron trap/precipitation and anisotropic distribution in solar flares, which may help us understand the precipitation of magnetospheric electrons accounting for the aurora as well. [ABSTRACT FROM AUTHOR]

In astrophysics, one significant challenge lies in understanding the acceleration of cosmic rays, which leads to the occurrence of a power law. In this article, momentum transport generated by the combined effects of pitch-angle diffusion and background flow velocity inhomogeneities is proposed to obtain a cosmic rays acceleration mechanism, starting from the well-known focused transport equation describing particle diffusion and acceleration. The inhomogeneities of background flow velocity are ubiquitous in the astrophysical environment. The equation for the isotropic part of the distribution function of charged energetic particles is derived, and its solution is obtained, demonstrating the form of momentum power laws of cosmic rays. In addition, if it is assumed that cosmic rays penetrate compressive MHD waves or turbulence, for quasi-steady states, the spectral index δ of the momentum power law spectrum of cosmic rays is found to be in the range [−5, −3], which includes the observed power law indices of galactic cosmic rays. The results obtained in this article demonstrate that the mechanism proposed in this article, along with shock acceleration, may also contribute to the acceleration of galactic cosmic rays. Furthermore, when momentum convection effect and higher-order momentum derivative terms are considered, the indices of power laws should be smaller than −5. This may explain the power laws of solar energetic particle events. [ABSTRACT FROM AUTHOR]

Cyanogenic glycosides form part of a binary plant defense system that, upon catabolism, detonates a toxic hydrogen cyanide bomb. In seed plants, the initial step of cyanogenic glycoside biosynthesis—the conversion of an amino acid to the corresponding aldoxime—is catalyzed by a cytochrome P450 from the CYP79 family. An evolutionary conundrum arises, as no CYP79s have been identified in ferns, despite cyanogenic glycoside occurrence in several fern species. Here, we report that a flavin-dependent monooxygenase (fern oxime synthase; FOS1), catalyzes the first step of cyanogenic glycoside biosynthesis in two fern species (Phlebodium aureum and Pteridium aquilinum), demonstrating convergent evolution of biosynthesis across the plant kingdom. The FOS1 sequence from the two species is near identical (98%), despite diversifying 140 MYA. Recombinant FOS1 was isolated as a catalytic active dimer, and in planta, catalyzes formation of an N-hydroxylated primary amino acid; a class of metabolite not previously observed in plants. Thodberg et al. report the first step of the synthesis of cyanogenic glycosides, a plant defense mechanism, by a Flavin-dependent monooxygenase (FOS1) in ferns, revealing convergent evolution of biosynthesis across the plant kingdom. The authors isolate FOS1 as a catalytically active dimer and demonstrate that it catalyzes the formation of N-hydroxylated amino acids. [ABSTRACT FROM AUTHOR]

Cosmic rays exhibit anomalous diffusion behaviors in the heliospheric environment that cannot be adequately described by classical diffusion models. In this paper, we develop a theoretical framework employing a fractional Fokker–Planck equation to model the anomalous transport of cosmic rays. This approach accounts for the observed non-Gaussian distributions, long-range correlations and memory effects in cosmic ray fluxes. We derive analytical solutions using the Adomian Decomposition Method and express them in terms of Mittag-Leffler functions and Lévy stable distributions. The model parameters, including the fractional orders α and μ and the entropic index q, are estimated by a short comparison between theoretical predictions and observational data from cosmic ray experiments. Our findings suggest that the integration of fractional calculus and non-extensive statistics can be employed for describing the cosmic ray propagation and the anomalous diffusion observed in the heliosphere. [ABSTRACT FROM AUTHOR]

In the research of new solvents for cellulose dissolution for textile fiber production, some ionic liquids offer high dissolving capacities making them attractive solvents for lyocell processes. One especially interesting group is superbase carboxylates. However, despite their excellent pulp dissolving abilities and good spinnability properties in a lyocell process, they have been lacking hydrolytic stability, which hinders their recyclability. In this article, a new type of superbase-based ionic liquid, [MTBNH][AcO], is aimed to provide higher hydrolytic stability than its structural relative predecessors. For evaluation of the hydrolysis behavior of [MTBNH][AcO], we have tested the ionic liquid in two sets of recycling experiments. The "blank-experiments" were applied to investigate hydrolytic behavior without the presence of pulp. These values were compared with the results from spinning trials with pulp. It was found that this new ionic liquid is not only more stable than its predecessor [MTBDH][AcO] in terms of hydrolysis but can also dissolve and spin cellulose at lower temperatures. The spun fibers were tested for their textile-physical properties and their performance was comparable to other lyocell fibers. [ABSTRACT FROM AUTHOR]

Data analysis is a major task for Computational Chemists. The diversity of modeling tools currently available in Computational Chemistry requires the development of flexible analysis tools that can adapt to different systems and output formats. As a contribution to this need, we report the implementation of goChem, a versatile open-source library for multiscale analysis of computational chemistry data. The library, written in and for the Go programming language, allows for easy integration of different levels of theory, in an easy-to-use API, allowing the development of both one-use and complex analysis programs in Go. We describe the library and detail some selected applications that illustrate the capabilities and potential of this tool. The library is available at http://gochem.org., (© 2025 Wiley Periodicals LLC.)