Consequences of wall stiffness for a beta-soft potential

Modifications of the infinite square well E(5) and X(5) descriptions of transitional nuclear structure are considered. The eigenproblem for a potential with linear sloped walls is solved. The consequences of the introduction of sloped walls and of a quadratic transition operator are investigated.Comment: RevTeX 4, 8 pages, as published in Phys. Rev.

Neutron Capture Cross Sections for the Weak s Process

In past decades a lot of progress has been made towards understanding the main s-process component that takes place in thermally pulsing Asymptotic Giant Branch (AGB) stars. During this process about half of the heavy elements, mainly between 90<=A<=209 are synthesized. Improvements were made in stellar modeling as well as in measuring relevant nuclear data for a better description of the main s process. The weak s process, which contributes to the production of lighter nuclei in the mass range 56<=A<=90 operates in massive stars (M>=8Msolar) and is much less understood. A better characterization of the weak s component would help disentangle the various contributions to element production in this region. For this purpose, a series of measurements of neutron-capture cross sections have been performed on medium-mass nuclei at the 3.7-MV Van de Graaff accelerator at FZK using the activation method. Also, neutron captures on abundant light elements with A<56 play an important role for s-process nucleosynthesis, since they act as neutron poisons and affect the stellar neutron balance. New results are presented for the (n,g) cross sections of 41K and 45Sc, and revisions are reported for a number of cross sections based on improved spectroscopic information

Heat Transfer from a Hemisphere-cylinder Equipped with Flow-separation Spikes

Average heat-transfer, temperature-recovery, and pressure-distribution measurements were obtained over the hemispherical nose of a body of revolution both with and without flow-separation spikes. The tests, conducted in a range of Reynolds numbers from 1.55 to 9.85 x 10(5) and from Mach number 0.12 to 5.04, indicated that in supersonic flow the addition of spikes approximately doubles the rate of heat transfer, regardless of spike length

Optimal control of circuit quantum electrodynamics in one and two dimensions

Optimal control can be used to significantly improve multi-qubit gates in quantum information processing hardware architectures based on superconducting circuit quantum electrodynamics. We apply this approach not only to dispersive gates of two qubits inside a cavity, but, more generally, to architectures based on two-dimensional arrays of cavities and qubits. For high-fidelity gate operations, simultaneous evolutions of controls and couplings in the two coupling dimensions of cavity grids are shown to be significantly faster than conventional sequential implementations. Even under experimentally realistic conditions speedups by a factor of three can be gained. The methods immediately scale to large grids and indirect gates between arbitrary pairs of qubits on the grid. They are anticipated to be paradigmatic for 2D arrays and lattices of controllable qubits.Comment: Published version

Aphasia in children: Suggestions for management and training

No abstract available

Quantized spin wave modes in magnetic tunnel junction nanopillars

We present an experimental and theoretical study of the magnetic field dependence of the mode frequency of thermally excited spin waves in rectangular shaped nanopillars of lateral sizes 60x100, 75x150, and 105x190 nm2, patterned from MgO-based magnetic tunnel junctions. The spin wave frequencies were measured using spectrally resolved electrical noise measurements. In all spectra, several independent quantized spin wave modes have been observed and could be identified as eigenexcitations of the free layer and of the synthetic antiferromagnet of the junction. Using a theoretical approach based on the diagonalization of the dynamical matrix of a system of three coupled, spatially confined magnetic layers, we have modeled the spectra for the smallest pillar and have extracted its material parameters. The magnetization and exchange stiffness constant of the CoFeB free layer are thereby found to be substantially reduced compared to the corresponding thin film values. Moreover, we could infer that the pinning of the magnetization at the lateral boundaries must be weak. Finally, the interlayer dipolar coupling between the free layer and the synthetic antiferromagnet causes mode anticrossings with gap openings up to 2 GHz. At low fields and in the larger pillars, there is clear evidence for strong non-uniformities of the layer magnetizations. In particular, at zero field the lowest mode is not the fundamental mode, but a mode most likely localized near the layer edges.Comment: 16 pages, 4 figures, (re)submitted to PR

Calculation of coincidence summing corrections for a specific small soil sample geometry

Previously, a system was developed at the INEL for measuring the {gamma}-ray emitting nuclides in small soil samples for the purpose of environmental monitoring. These samples were counted close to a {approx}20% Ge detector and, therefore, it was necessary to take into account the coincidence summing that occurs for some nuclides. In order to improve the technical basis for the coincidence summing corrections, the authors have carried out a study of the variation in the coincidence summing probability with position within the sample volume. A Monte Carlo electron and photon transport code (CYLTRAN) was used to compute peak and total efficiencies for various photon energies from 30 to 2,000 keV at 30 points throughout the sample volume. The geometry for these calculations included the various components of the detector and source along with the shielding. The associated coincidence summing corrections were computed at these 30 positions in the sample volume and then averaged for the whole source. The influence of the soil and the detector shielding on the efficiencies was investigated

Quadrupole Pairing Interaction and Signature Inversion

The signature inversion in the \pi h11/2 \otimes \nu h11/2 rotational bands of odd-odd Cs and La isotopes and the \pi h11/2 \otimes \nu i13/2 bands of odd-odd Tb, Ho and Tm nuclei is investigated using pairing and deformation self consistent mean field calculations. The model can rather satisfactorily account for the anomalous signature splitting, provided that spin assignments in som of the bands are revised. Our calculations show that signature inversioncan appear already at axially symmetric shapes. It is found that this is due to the contribution of the \lambda\mu=22 component of the quadrupole pairing interaction to the mean field potential.Comment: 17 pages, 14 figures, Nuclear Physics A in prin

DanceMoves: A Visual Analytics Tool for Dance Movement Analysis

Analyzing body movement as a means of expression is of interest in diverse areas, such as dance, sports, films, as well as anthropology or archaeology. In particular, in choreography, body movements are at the core of artistic expression. Dance moves are composed of spatial and temporal structures that are difficult to address without interactive visual data analysis tools. We present a visual analytics solution that allows the user to get an overview of, compare, and visually search dance move features in video archives. With the help of similarity measures, a user can compare dance moves and assess dance poses. We illustrate our approach through three use cases and an analysis of the performance of our similarity measures. The expert feedback and the experimental results show that 75% to 80% of dance moves can correctly be categorized. Domain experts recognize great potential in this standardized analysis. Comparative and motion analysis allows them to get detailed insights into temporal and spatial development of motion patterns and poses

Artificial intelligence methods enhance the discovery of RNA interactions

Understanding how RNAs interact with proteins, RNAs, or other molecules remains a challenge of main interest in biology, given the importance of these complexes in both normal and pathological cellular processes. Since experimental datasets are starting to be available for hundreds of functional interactions between RNAs and other biomolecules, several machine learning and deep learning algorithms have been proposed for predicting RNA-RNA or RNA-protein interactions. However, most of these approaches were evaluated on a single dataset, making performance comparisons difficult. With this review, we aim to summarize recent computational methods, developed in this broad research area, highlighting feature encoding and machine learning strategies adopted. Given the magnitude of the effect that dataset size and quality have on performance, we explored the characteristics of these datasets. Additionally, we discuss multiple approaches to generate datasets of negative examples for training. Finally, we describe the best-performing methods to predict interactions between proteins and specific classes of RNA molecules, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs), and methods to predict RNA-RNA or RNA-RBP interactions independently of the RNA type