Asymmetric Twisting of Coronal Loops

The bright solar corona entirely consists of closed magnetic loops rooted in the photosphere. Photospheric motions are important drivers of magnetic stressing, which eventually leads to energy release into heat. These motions are chaotic and obviously different from one footpoint to the other, and in fact, there is strong evidence that loops are finely stranded. One may also expect strong transient variations along the field lines, but at a glance, coronal loops ever appear more or less uniformly bright from one footpoint to the other. We aim to understand how much coronal loops can preserve their own symmetry against asymmetric boundary motions that are expected to occur at loop footpoints. We investigate this issue by time-dependent 2.5D MHD modelling of a coronal loop, including its rooting and beta-variation in the photosphere. We assume that the magnetic flux tube is stressed by footpoint rotation but also that the rotation has a different pattern from one footpoint to the other. In this way, we force strong asymmetries because we expect independent evolution along different magnetic strands. We found that until the Alfven crossing-travel time relative to the entire loop length is much lower than the twisting period, the loop's evolution depends only on the relative velocity between the boundaries, and the symmetry is efficiently preserved. We conclude that the very high Alfven velocities that characterise the coronal environment can explain why coronal loops can maintain a very high degree of symmetry even when they are subjected to asymmetric photospheric motions for a long time

Solution of the two identical ion Penning trap final state

We have derived a closed form analytic expression for the asymptotic motion of a pair of identical ions in a high precision Penning trap. The analytic solution includes the effects of special relativity and the Coulomb interaction between the ions. The existence and physical relevance of such a final state is supported by a confluence of theoretical, experimental and numerical evidence.Comment: 5 pages and 2 figure

Coronal energy release by MHD avalanches. Effects on a structured, active region, multi-threaded coronal loop

A possible key element for large-scale energy release in the solar corona is an MHD kink instability in a single twisted magnetic flux tube. An initial helical current sheet fragments in a turbulent way into smaller-scale sheets, similarly to a nanoflare storm. As the loop expands in the radial direction during the relaxation process, an unstable loop can disrupt nearby stable loops and trigger an MHD avalanche. Exploratory investigations have been conducted in previous works with relatively simplified loop configurations. Here, we address a more realistic environment that comprehensively accounts for most of the physical effects involved in a stratified atmosphere, typical of an active region. The question is whether the avalanche process will be triggered, with what timescales, and how it will develop, as compared with the original, simpler approach. Three-dimensional MHD simulations describe the interaction of magnetic flux tubes, which have a stratified atmosphere, including chromospheric layers, the thin transition region to the corona, and the related transition from high-beta to low-beta regions. The model also includes the effects of thermal conduction and of optically thin radiation. Our simulations address the case where one flux tube among a few is twisted at the footpoints faster than its neighbours. We show that this flux tube becomes kink unstable first, in conditions in agreement with those predicted by analytical models. It rapidly involves nearby stable tubes, instigating significant magnetic reconnection and dissipation of energy as heat. The heating determines the development of chromospheric evaporation, while the temperature rises up to about 10 MK, close to microflares observations. This work confirms that avalanches are a viable mechanism for the storing and release of magnetic energy in plasma confined in closed coronal loops, as a result of photospheric motions.Comment: 16 pages, 16 figure

Epidemics in partially overlapped multiplex networks

Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nodes are present on every layer. To generate a more realistic scenario, we use a generalized multiplex network and assume that only a fraction $q$ of the nodes are shared by the layers. We develop a theoretical framework for a branching process to describe the spread of an epidemic on these partially overlapped multiplex networks. This allows us to obtain the fraction of infected individuals as a function of the effective probability that the disease will be transmitted $T$. We also theoretically determine the dependence of the epidemic threshold on the fraction $q > 0$ of shared nodes in a system composed of two layers. We find that in the limit of $q \to 0$ the threshold is dominated by the layer with the smaller isolated threshold. Although a system of two completely isolated networks is nearly indistinguishable from a system of two networks that share just a few nodes, we find that the presence of these few shared nodes causes the epidemic threshold of the isolated network with the lower propagating capacity to change discontinuously and to acquire the threshold of the other network.Comment: 13 pages, 4 figure

Characterization method of dielectric properties of free falling drops in a microwave processing cavity and its application in microwave internal gelation

[EN] Microwave internal gelation (MIG) is a chemical process proposed for the production of nuclear particle fuel. The internal gelation reaction is triggered by a temperature increase of aqueous droplets falling by gravity by means of non-contact microwave heating. Due to the short residence time of a solution droplet in a microwave heating cavity, a detailed knowledge of the interaction between microwaves and chemical solution (shaped in small drops) is required. This paper describes a procedure that enables the measurement of the dielectric properties of aqueous droplets that freely fall through a microwave cavity. These measurements provide the information to determine the optimal values of the parameters (such as frequency and power) that dictate the heating of such a material under microwaves.This work is a part of the PINE (Platform for Innovative Nuclear FuEls) project which targets the development of an advanced production method for Sphere-Pac fuel and is financed by the Swiss Competence Center for Energy and Mobility. The work has been also financed by the European Commission through contract no 295664 regarding the FP7 PELGRIMM Project, as well as contract no 295825 regarding the FP7-ASGARD Project. MC-S would like to thank the ITACA research team (UPV Valencia, Spain) and the EMPA Thun (Switzerland) for their support in the measurements and Carl Beard (PSI, Switzerland) for the help provided in respect with CST simulations. The work of FLP-F was supported by the Conselleria d'Educacio of the Generalitat Valenciana for economic support (BEST/2012/010).Cabanes Sempere, M.; Catalá Civera, JM.; Penaranda-Foix, FL.; Cozzo, C.; Vaucher, S.; Pouchon, MA. (2013). Characterization method of dielectric properties of free falling drops in a microwave processing cavity and its application in microwave internal gelation. Measurement Science and Technology. 24(9). https://doi.org/10.1088/0957-0233/24/9/095009S24

The physics of spreading processes in multilayer networks

The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of complex systems, which often include different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and be a major obstacle towards attempts to understand complex systems. The recent "multilayer" approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remain hidden when using ordinary graphs, the traditional network representation. Here we survey progress towards attaining a deeper understanding of spreading processes on multilayer networks, and we highlight some of the physical phenomena related to spreading processes that emerge from multilayer structure.Comment: 25 pages, 4 figure

Opinion formation in multiplex networks with general initial distributions

We study opinion dynamics over multiplex networks where agents interact with bounded confidence. Namely, two neighbouring individuals exchange opinions and compromise if their opinions do not differ by more than a given threshold. In literature, agents are generally assumed to have a homogeneous confidence bound. Here, we study analytically and numerically opinion evolution over structured networks characterised by multiple layers with respective confidence thresholds and general initial opinion distributions. Through rigorous probability analysis, we show analytically the critical thresholds at which a phase transition takes place in the long-term consensus behaviour, over multiplex networks with some regularity conditions. Our results reveal the quantitative relation between the critical threshold and initial distribution. Further, our numerical simulations illustrate the consensus behaviour of the agents in network topologies including lattices and, small-world and scale-free networks, as well as for structure-dependent convergence parameters accommodating node heterogeneity. We find that the critical thresholds for consensus tend to agree with the predicted upper bounds in Theorems 4 and 5 in this paper. Finally, our results indicate that multiplexity hinders consensus formation when the initial opinion configuration is within a bounded range and, provide insight into information diffusion and social dynamics in multiplex systems modeled by networks

Epidemic spreading on time-varying multiplex networks

Social interactions are stratified in multiple contexts and are subject to complex temporal dynamics. The systematic study of these two features of social systems has started only very recently, mainly thanks to the development of multiplex and time-varying networks. However, these two advancements have progressed almost in parallel with very little overlap. Thus, the interplay between multiplexity and the temporal nature of connectivity patterns is poorly understood. Here, we aim to tackle this limitation by introducing a time-varying model of multiplex networks. We are interested in characterizing how these two properties affect contagion processes. To this end, we study SIS epidemic models unfolding at comparable time-scale respect to the evolution of the multiplex network. We study both analytically and numerically the epidemic threshold as a function of the multiplexity and the features of each layer. We found that, higher values of multiplexity significantly reduce the epidemic threshold especially when the temporal activation patterns of nodes present on multiple layers are positively correlated. Furthermore, when the average connectivity across layers is very different, the contagion dynamics are driven by the features of the more densely connected layer. Here, the epidemic threshold is equivalent to that of a single layered graph and the impact of the disease, in the layer driving the contagion, is independent of the multiplexity. However, this is not the case in the other layers where the spreading dynamics are sharply influenced by it. The results presented provide another step towards the characterization of the properties of real networks and their effects on contagion phenomena

Inositol Phosphate Recycling Regulates Glycolytic and Lipid Metabolism That Drives Cancer Aggressiveness

Cancer cells possess fundamentally altered metabolism that supports their pathogenic features, which includes a heightened reliance on aerobic glycolysis to provide precursors for synthesis of biomass. We show here that inositol polyphosphate phosphatase 1 (INPP1) is highly expressed in aggressive human cancer cells and primary high-grade human tumors. Inactivation of INPP1 leads to a reduction in glycolytic intermediates that feed into the synthesis of the oncogenic signaling lipid lysophosphatidic acid (LPA), which in turn impairs LPA signaling and further attenuates glycolytic metabolism in a feed-forward mechanism to impair cancer cell motility, invasiveness, and tumorigenicity. Taken together these findings reveal a novel mode of glycolytic control in cancer cells that can serve to promote key oncogenic lipid signaling pathways that drive cancer pathogenicity