Continuously wavelength-tunable high harmonic generation via soliton dynamics

We report generation of high harmonics in a gas-jet pumped by pulses self-compressed in a He-filled hollow-core photonic crystal fiber through the soliton effect. The gas-jet is placed directly at the fiber output. As the energy increases the ionization-induced soliton blue-shift is transferred to the high harmonics, leading to a emission bands that are continuously tunable from 17 to 45 eV

First-principles GW calculations for DNA and RNA nucleobases

On the basis of first-principles GW calculations, we study the quasiparticle properties of the guanine, adenine, cytosine, thymine, and uracil DNA and RNA nucleobases. Beyond standard G0W0 calculations, starting from Kohn-Sham eigenstates obtained with (semi)local functionals, a simple self-consistency on the eigenvalues allows to obtain vertical ionization energies and electron affinities within an average 0.11 eV and 0.18 eV error respectively as compared to state-of-the-art coupled-cluster and multi-configurational perturbative quantum chemistry approaches. Further, GW calculations predict the correct \pi -character of the highest occupied state, thanks to several level crossings between density functional and GW calculations. Our study is based on a recent gaussian-basis implementation of GW with explicit treatment of dynamical screening through contour deformation techniques.Comment: 5 pages, 3 figure

Gain control with A-type potassium current: IA as a switch between divisive and subtractive inhibition

Neurons process information by transforming barrages of synaptic inputs into spiking activity. Synaptic inhibition suppresses the output firing activity of a neuron, and is commonly classified as having a subtractive or divisive effect on a neuron's output firing activity. Subtractive inhibition can narrow the range of inputs that evoke spiking activity by eliminating responses to non-preferred inputs. Divisive inhibition is a form of gain control: it modifies firing rates while preserving the range of inputs that evoke firing activity. Since these two "modes" of inhibition have distinct impacts on neural coding, it is important to understand the biophysical mechanisms that distinguish these response profiles. We use simulations and mathematical analysis of a neuron model to find the specific conditions for which inhibitory inputs have subtractive or divisive effects. We identify a novel role for the A-type Potassium current (IA). In our model, this fast-activating, slowly- inactivating outward current acts as a switch between subtractive and divisive inhibition. If IA is strong (large maximal conductance) and fast (activates on a time-scale similar to spike initiation), then inhibition has a subtractive effect on neural firing. In contrast, if IA is weak or insufficiently fast-activating, then inhibition has a divisive effect on neural firing. We explain these findings using dynamical systems methods to define how a spike threshold condition depends on synaptic inputs and IA. Our findings suggest that neurons can "self-regulate" the gain control effects of inhibition via combinations of synaptic plasticity and/or modulation of the conductance and kinetics of A-type Potassium channels. This novel role for IA would add flexibility to neurons and networks, and may relate to recent observations of divisive inhibitory effects on neurons in the nucleus of the solitary tract.Comment: 20 pages, 11 figure

Gain Control With A-Type Potassium Current: IA As A Switch Between Divisive And Subtractive Inhibition

Neurons process and convey information by transforming barrages of synaptic inputs into spiking activity. Synaptic inhibition typically suppresses the output firing activity of a neuron, and is commonly classified as having a subtractive or divisive effect on a neuron’s output firing activity. Subtractive inhibition can narrow the range of inputs that evoke spiking activity by eliminating responses to non-preferred inputs. Divisive inhibition is a form of gain control: it modifies firing rates while preserving the range of inputs that evoke firing activity. Since these two “modes” of inhibition have distinct impacts on neural coding, it is important to understand the biophysical mechanisms that distinguish these response profiles. In this study, we use simulations and mathematical analysis of a neuron model to find the specific conditions (parameter sets) for which inhibitory inputs have subtractive or divisive effects. Significantly, we identify a novel role for the A-type Potassium current (IA). In our model, this fast-activating, slowly-inactivating outward current acts as a switch between subtractive and divisive inhibition. In particular, if IA is strong (large maximal conductance) and fast (activates on a time-scale similar to spike initiation), then inhibition has a subtractive effect on neural firing. In contrast, if IA is weak or insufficiently fast-activating, then inhibition has a divisive effect on neural firing. We explain these findings using dynamical systems methods (plane analysis and fast-slow dissection) to define how a spike threshold condition depends on synaptic inputs and IA. Our findings suggest that neurons can “self-regulate” the gain control effects of inhibition via combinations of synaptic plasticity and/or modulation of the conductance and kinetics of A-type Potassium channels. This novel role for IA would add flexibility to neurons and networks, and may relate to recent observations of divisive inhibitory effects on neurons in the nucleus of the solitary tract

Platelet-Activating Factor-Induced Reduction in Contact Hypersensitivity Responses Is Mediated by Mast Cells via Cyclooxygenase-2-Dependent Mechanisms

Platelet-activating factor (PAF) stimulates numerous cell types via activation of the G protein-coupled PAF receptor (PAFR). PAFR activation not only induces acute proinflammatory responses, but it also induces delayed systemic immunosuppressive effects by modulating host immunity. Although enzymatic synthesis and degradation of PAF are tightly regulated, oxidative stressors, such as UVB, chemotherapy, and cigarette smoke, can generate PAF and PAF-like molecules in an unregulated fashion via the oxidation of membrane phospholipids. Recent studies have demonstrated the relevance of the mast cell (MC) PAFR in PAFR-induced systemic immunosuppression. The current study was designed to determine the exact mechanisms and mediators involved in MC PAFR-mediated systemic immunosuppression. By using a contact hypersensitivity model, the MC PAFR was not only found to be necessary, but also sufficient to mediate the immunosuppressive effects of systemic PAF. Furthermore, activation of the MC PAFR induces MC-derived histamine and PGE2 release. Importantly, PAFR-mediated systemic immunosuppression was defective in mice that lacked MCs, or in MC-deficient mice transplanted with histidine decarboxylase- or cyclooxygenase-2-deficient MCs. Lastly, it was found that PGs could modulate MC migration to draining lymph nodes. These results support the hypothesis that MC PAFR activation promotes the immunosuppressive effects of PAF in part through histamine- and PGE2-dependent mechanisms

Memory, learning and language in autism spectrum disorder

Background and aims: The ‘dual-systems’ model of language acquisition has been used by Ullman and colleagues to explain patterns of strength and weakness in the language of higher-functioning people with autism spectrum disorder (ASD). Specifically, intact declarative/explicit learning is argued to compensate for a deficit in non-declarative/implicit procedural learning, constituting an example of the so-called ‘see-saw’ effect. Ullman and Pullman (2015) extended their argument concerning a see-saw effect on language in ASD to cover other perceived anomalies of behaviour, including impaired acquisition of social skills. The aim of this paper is to present a critique of Ullman and colleagues’ claims, and to propose an alternative model of links between memory systems and language in ASD. Main contribution: We argue that a 4-systems model of learning, in which intact semantic and procedural memory are used to compensate for weaknesses in episodic memory and perceptual learning, can better explain patterns of language ability across the autistic spectrum. We also argue that attempts to generalise the ‘impaired implicit learning/spared declarative learning’ theory to other behaviours in ASD are unsustainable. Conclusions: Clinically significant language impairments in ASD are under-researched, despite their impact on everyday functioning and quality of life. The relative paucity of research findings in this area lays it open to speculative interpretation which may be misleading. Implications: More research is need into links between memory/learning systems and language impairments across the spectrum. Improved understanding should inform therapeutic intervention, and contribute to investigation of the causes of language impairment in ASD with potential implications for prevention

Scale-free networks with tunable degree distribution exponents

We propose and study a model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent. The model represents a hybrid of the growing networks based on popularity-driven and fitness-driven preferential attachments. As the network grows, a newly added node establishes $m$ new links to existing nodes with a probability $p$ based on popularity of the existing nodes and a probability $1-p$ based on fitness of the existing nodes. An explicit form of the degree distribution $P(p,k)$ is derived within a mean field approach. For reasonably large $k$, $P(p,k) \sim k^{-\gamma(p)}{\cal F}(k,p)$, where the function ${\cal F}$ is dominated by the behavior of $1/\ln(k/m)$ for small values of $p$ and becomes $k$-independent as $p \to 1$, and $\gamma(p)$ is a model-dependent exponent. The degree distribution and the exponent $\gamma(p)$ are found to be in good agreement with results obtained by extensive numerical simulations.Comment: 12 pages, 2 figures, submitted to PR

Supercontinuum generation in the vacuum ultraviolet through dispersive-wave and soliton-plasma interaction in noble-gas-filled hollow-core photonic crystal fiber

We report on the generation of a three-octave-wide supercontinuum extending from the vacuum ultraviolet (VUV) to the near-infrared, spanning at least 113 to 1000 nm (i.e., 11 to 1.2 eV), in He-filled hollow-core kagome-style photonic crystal fiber. Numerical simulations confirm that the main mechanism is a novel and previously undiscovered interaction between dispersive-wave emission and plasma-induced blueshifted soliton recompression around the fiber zero dispersion frequency. The VUV part of the supercontinuum, which modeling shows to be coherent and possess a simple phase structure, has sufficient bandwidth to support single-cycle pulses of 500 attosecond duration. We also demonstrate, in the same system, the generation of narrower-band VUV pulses, through dispersive-wave emission, tunable from 120 to 200 nm with efficiencies exceeding 1% and VUV pulse energies in excess of 50 nJ.Comment: 7 pages, 5 figure

Disordered, stretched, and semiflexible biopolymers in two dimensions

We study the effects of intrinsic sequence-dependent curvature for a two dimensional semiflexible biopolymer with short-range correlation in intrinsic curvatures. We show exactly that when not subjected to any external force, such a system is equivalent to a system with a well-defined intrinsic curvature and a proper renormalized persistence length. We find the exact expression for the distribution function of the equivalent system. However, we show that such an equivalent system does not always exist for the polymer subjected to an external force. We find that under an external force, the effect of sequence-disorder depends upon the averaging order, the degree of disorder, and the experimental conditions, such as the boundary conditions. Furthermore, a short to moderate length biopolymer may be much softer or has a smaller apparent persistent length than what would be expected from the "equivalent system". Moreover, under a strong stretching force and for a long biopolymer, the sequence-disorder is immaterial for elasticity. Finally, the effect of sequence-disorder may depend upon the quantity considered

Force Distribution in a Granular Medium

We report on systematic measurements of the distribution of normal forces exerted by granular material under uniaxial compression onto the interior surfaces of a confining vessel. Our experiments on three-dimensional, random packings of monodisperse glass beads show that this distribution is nearly uniform for forces below the mean force and decays exponentially for forces greater than the mean. The shape of the distribution and the value of the exponential decay constant are unaffected by changes in the system preparation history or in the boundary conditions. An empirical functional form for the distribution is proposed that provides an excellent fit over the whole force range measured and is also consistent with recent computer simulation data.Comment: 6 pages. For more information, see http://mrsec.uchicago.edu/granula