Plasma sheath tailoring by a magnetic field for three-dimensional plasma etching

Three-dimensional (3D) etching of materials by plasmas is an ultimate challenge in microstructuring applications. A method is proposed to reach a controllable 3D structure by using masks in front of the surface in a plasma etch reactor in combination with local magnetic fields to steer the incident ions in the plasma sheath region towards the surface to reach 3D directionality during etching and deposition. This effect can be controlled by modifying the magnetic field and/or plasma properties to adjust the relationship between sheath thickness and mask feature size. Since the guiding length scale is the plasma sheath thickness, which for typical plasma densities is at least 10s of microns or larger, controlled directional etching and deposition target the field of microstructuring, e.g. of solids for sensors, optics, or microfluidics. In this proof-of-concept study, it is shown that $\vec{E}\times\vec{B}$ drifts tailor the local sheath expansion, thereby controlling the plasma density distribution and the transport when the plasma penetrates the mask during an RF cycle. This modified local plasma creates a 3D etch profile. This is shown experimentally as well as using 2d3v Particle-In-Cell/Monte Carlo collisions simulation

Stochastic switching in delay-coupled oscillators

A delay is known to induce multistability in periodic systems. Under influence of noise, coupled oscillators can switch between coexistent orbits with different frequencies and different oscillation patterns. For coupled phase oscillators we reduce the delay system to a nondelayed Langevin equation, which allows us to analytically compute the distribution of frequencies and their corresponding residence times. The number of stable periodic orbits scales with the roundtrip delay time and coupling strength, but the noisy system visits only a fraction of the orbits, which scales with the square root of the delay time and is independent of the coupling strength. In contrast, the residence time in the different orbits is mainly determined by the coupling strength and the number of oscillators, and only weakly dependent on the coupling delay. Finally we investigate the effect of a detuning between the oscillators. We demonstrate the generality of our results with delay-coupled FitzHugh-Nagumo oscillators

SuperSAGE analysis of the Nicotiana attenuata transcriptome after fatty acid-amino acid elicitation (FAC): identification of early mediators of insect responses

<p>Abstract</p> <p>Background</p> <p>Plants trigger and tailor defense responses after perception of the oral secretions (OS) of attacking specialist lepidopteran larvae. Fatty acid-amino acid conjugates (FACs) in the OS of the <it>Manduca sexta </it>larvae are necessary and sufficient to elicit the herbivory-specific responses in <it>Nicotiana attenuata</it>, an annual wild tobacco species. How FACs are perceived and activate signal transduction mechanisms is unknown.</p> <p>Results</p> <p>We used SuperSAGE combined with 454 sequencing to quantify the early transcriptional changes elicited by the FAC <it>N</it>-linolenoyl-glutamic acid (18:3-Glu) and virus induced gene silencing (VIGS) to examine the function of candidate genes in the <it>M. sexta</it>-<it>N. attenuata </it>interaction. The analysis targeted mRNAs encoding regulatory components: rare transcripts with very rapid FAC-elicited kinetics (increases within 60 and declines within 120 min). From 12,744 unique Tag sequences identified (UniTags), 430 and 117 were significantly up- and down-regulated ≥ 2.5-fold, respectively, after 18:3-Glu elicitation compared to wounding. Based on gene ontology classification, more than 25% of the annotated UniTags corresponded to putative regulatory components, including 30 transcriptional regulators and 22 protein kinases. Quantitative PCR analysis was used to analyze the FAC-dependent regulation of a subset of 27 of these UniTags and for most of them a rapid and transient induction was confirmed. Six FAC-regulated genes were functionally characterized by VIGS and two, a putative lipid phosphate phosphatase (LPP) and a protein of unknown function, were identified as important mediators of the <it>M. sexta</it>-<it>N. attenuata </it>interaction.</p> <p>Conclusions</p> <p>The analysis of the early changes in the transcriptome of <it>N. attenuata </it>after FAC elicitation using SuperSAGE/454 has identified regulatory genes involved in insect-specific mediated responses in plants. Moreover, it has provided a foundation for the identification of additional novel regulators associated with this process.</p

Non-Universal Critical Behaviour of Two-Dimensional Ising Systems

Two conditions are derived for Ising models to show non-universal critical behaviour, namely conditions concerning 1) logarithmic singularity of the specific heat and 2) degeneracy of the ground state. These conditions are satisfied with the eight-vertex model, the Ashkin-Teller model, some Ising models with short- or long-range interactions and even Ising systems without the translational or the rotational invariance.Comment: 17 page

Strong and weak chaos in networks of semiconductor lasers with time-delayed couplings

Nonlinear networks with time-delayed couplings may show strong and weak chaos, depending on the scaling of their Lyapunov exponent with the delay time. We study strong and weak chaos for semiconductor lasers, either with time-delayed self-feedback or for small networks. We examine the dependence on the pump current and consider the question of whether strong and weak chaos can be identified from the shape of the intensity trace, the autocorrelations, and the external cavity modes. The concept of the sub-Lyapunov exponent λ0 is generalized to the case of two time-scale-separated delays in the system. We give experimental evidence of strong and weak chaos in a network of lasers, which supports the sequence of weak to strong to weak chaos upon monotonically increasing the coupling strength. Finally, we discuss strong and weak chaos for networks with several distinct sub-Lyapunov exponents and comment on the dependence of the sub-Lyapunov exponent on the number of a laser's inputs in a network

Understanding the enhanced synchronization of delay-coupled networks with fluctuating topology

We study the dynamics of networks with coupling delay, from which the connectivity changes over time. The synchronization properties are shown to depend on the interplay of three time scales: the internal time scale of the dynamics, the coupling delay along the network links and time scale at which the topology changes. Concentrating on a linearized model, we develop an analytical theory for the stability of a synchronized solution. In two limit cases the system can be reduced to an “effective” topology: In the fast switching approximation, when the network fluctuations are much faster than the internal time scale and the coupling delay, the effective network topology is the arithmetic mean over the different topologies. In the slow network limit, when the network fluctuation time scale is equal to the coupling delay, the effective adjacency matrix is the geometric mean over the adjacency matrices of the different topologies. In the intermediate regime the system shows a sensitive dependence on the ratio of time scales, and specific topologies, reproduced as well by numerical simulations. Our results are shown to describe the synchronization properties of fluctuating networks of delay-coupled chaotic maps

Neuropeptide S-Mediated Facilitation of Synaptic Transmission Enforces Subthreshold Theta Oscillations within the Lateral Amygdala

The neuropeptide S (NPS) receptor system modulates neuronal circuit activity in the amygdala in conjunction with fear, anxiety and the expression and extinction of previously acquired fear memories. Using in vitro brain slice preparations of transgenic GAD67-GFP (Δneo) mice, we investigated the effects of NPS on neural activity in the lateral amygdala as a key region for the formation and extinction of fear memories. We are able to demonstrate that NPS augments excitatory glutamatergic synaptic input onto both projection neurons and interneurons of the lateral amygdala, resulting in enhanced spike activity of both types of cells. These effects were at least in part mediated by presynaptic mechanisms. In turn, inhibition of projection neurons by local interneurons was augmented by NPS, and subthreshold oscillations were strengthened, leading to their shift into the theta frequency range. These data suggest that the multifaceted effects of NPS on amygdaloid circuitry may shape behavior-related network activity patterns in the amygdala and reflect the peptide's potent activity in various forms of affective behavior and emotional memory

Making translation work: Harmonizing cross-species methodology in the behavioural neuroscience of Pavlovian fear conditioning

Translational neuroscience bridges insights from specific mechanisms in rodents to complex functions in humans and is key to advance our general understanding of central nervous function. A prime example of translational research is the study of cross-species mechanisms that underlie responding to learned threats, by employing Pavlovian fear conditioning protocols in rodents and humans. Hitherto, evidence for (and critique of) these cross-species comparisons in fear conditioning research was based on theoretical viewpoints. Here, we provide a perspective to substantiate these theoretical concepts with empirical considerations of cross-species methodology. This meta-research perspective is expected to foster cross-species comparability and reproducibility to ultimately facilitate successful transfer of results from basic science into clinical applications

Reservoir computing with swarms

We study swarms as dynamical systems for reservoir computing (RC). By example of a modified Reynolds boids model, the specific symmetries and dynamical properties of a swarm are explored with respect to a nonlinear time-series prediction task. Specifically, we seek to extract meaningful information about a predator-like driving signal from the swarm's response to that signal. We find thatthe naïve implementation of a swarm for computation is very inefficient, as permutation symmetry of the individual agents reduces the computational capacity. To circumvent this, we distinguish between the computational substrate of the swarm and a separate observation layer, in which the swarm's response is measured for use in the task. We demonstrate the implementation of a radial basis-localized observation layer for this task. The behavior of the swarm is characterized by order parameters and measures of consistency and related to the performance of the swarm as a reservoir. The relationship between RC performance and swarm behavior demonstrates that optimal computational properties are obtained near a phase transition regime