How Chaotic is the Stadium Billiard? A Semiclassical Analysis

The impression gained from the literature published to date is that the spectrum of the stadium billiard can be adequately described, semiclassically, by the Gutzwiller periodic orbit trace formula together with a modified treatment of the marginally stable family of bouncing ball orbits. I show that this belief is erroneous. The Gutzwiller trace formula is not applicable for the phase space dynamics near the bouncing ball orbits. Unstable periodic orbits close to the marginally stable family in phase space cannot be treated as isolated stationary phase points when approximating the trace of the Green function. Semiclassical contributions to the trace show an $\hbar$ - dependent transition from hard chaos to integrable behavior for trajectories approaching the bouncing ball orbits. A whole region in phase space surrounding the marginal stable family acts, semiclassically, like a stable island with boundaries being explicitly $\hbar$-dependent. The localized bouncing ball states found in the billiard derive from this semiclassically stable island. The bouncing ball orbits themselves, however, do not contribute to individual eigenvalues in the spectrum. An EBK-like quantization of the regular bouncing ball eigenstates in the stadium can be derived. The stadium billiard is thus an ideal model for studying the influence of almost regular dynamics near marginally stable boundaries on quantum mechanics.Comment: 27 pages, 6 figures, submitted to J. Phys.

Rotational and Nuclear-Spin Level Dependent Photodissociation Dynamics of H₂S

The photodissociation dynamics of small molecules in the vacuum ultraviolet range can have key implications for astrochemical modelling, but revealing such dynamical details is a challenging task. Here the authors, combining high resolution experimental techniques, provide a detailed description of the fragmentation dynamics of selected rotational levels of a predissociated Rydberg state of H2S

Forward K+ production in subthreshold pA collisions at 1.0 GeV

K+ meson production in pA (A = C, Cu, Au) collisions has been studied using the ANKE spectrometer at an internal target position of the COSY-Juelich accelerator. The complete momentum spectrum of kaons emitted at forward angles, theta < 12 degrees, has been measured for a beam energy of T(p)=1.0 GeV, far below the free NN threshold of 1.58 GeV. The spectrum does not follow a thermal distribution at low kaon momenta and the larger momenta reflect a high degree of collectivity in the target nucleus.Comment: 4 pages, 3 figure

miR-132/212 knockout mice reveal roles for these miRNAs in regulating cortical synaptic transmission and plasticity

miR-132 and miR-212 are two closely related miRNAs encoded in the same intron of a small non-coding gene, which have been suggested to play roles in both immune and neuronal function. We describe here the generation and initial characterisation of a miR-132/212 double knockout mouse. These mice were viable and fertile with no overt adverse phenotype. Analysis of innate immune responses, including TLR-induced cytokine production and IFNβ induction in response to viral infection of primary fibroblasts did not reveal any phenotype in the knockouts. In contrast, the loss of miR-132 and miR-212, while not overtly affecting neuronal morphology, did affect synaptic function. In both hippocampal and neocortical slices miR-132/212 knockout reduced basal synaptic transmission, without affecting paired-pulse facilitation. Hippocampal long-term potentiation (LTP) induced by tetanic stimulation was not affected by miR-132/212 deletion, whilst theta burst LTP was enhanced. In contrast, neocortical theta burst-induced LTP was inhibited by loss of miR-132/212. Together these results indicate that miR-132 and/or miR-212 play a significant role in synaptic function, possibly by regulating the number of postsynaptic AMPA receptors under basal conditions and during activity-dependent synaptic plasticity

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

<p>Abstract</p> <p>Background</p> <p>RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments.</p> <p>Results</p> <p>We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene.</p> <p>Conclusions</p> <p>RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.</p