Generation and development of small-amplitude disturbances in a laminar boundary layer in the presence of an acoustic field

A low-turbulence subsonic wind tunnel was used to study the influence of acoustic disturbances on the development of small sinusoidal oscillations (Tollmien-Schlichting waves) which constitute the initial phase of turbulent transition. It is found that acoustic waves propagating opposite to the flow generate vibrations of the model (plate) in the flow. Neither the plate vibrations nor the acoustic field itself have any appreciable influence on the stability of the laminar boundary layer. The influence of an acoustic field on laminar boundary layer disturbances is limited to the generation of Tollmien-Schlichting waves at the leading-edge of the plate

Tectonic asymmetry of the earth and other planets

The structures of Earth, Mars, Venus, and the Moon are examined and compared. Global tectonic characteristics are presented for each. A comparison of the tectonics reveals the structural asymetry of these planets and the moon. Tectonic asymmetry information for the group is used to interpret certain aspects of the earth's geological past

On the dichotomy of a system of linear differential equations with conditionally periodic coefficients

We show that a system of linear differential equations with conditionally periodic coefficients is exponentially dichotomous if and only if the spectrum of the monodromy operator does not meet the unit circle. © 2013 Pleiades Publishing, Ltd

Tectonics and volcanisms of Mars

Televised images of Mars transmitted from interplanetary stations are used to develop a theory of the structure and development of the planet. Crater chronology, the structure of planetary bodies in the Earth group, and a comparison of the Earth planetary bodies are among the factors included

Systematic limits on sin^2{2theta_{13}} in neutrino oscillation experiments with multi-reactors

Sensitivities to sin^2{2theta_{13}} without statistical errors (``systematic limit'') are investigated in neutrino oscillation experiments with multiple reactors. Using an analytical approach, we show that the systematic limit on sin^2{2theta_{13}} is dominated by the uncorrelated systematic error sigma_u of the detector. Even in an experiment with multi-detectors and multi-reactors, it turns out that most of the systematic errors including the one due to the nature of multiple sources is canceled as in the case with a single reactor plus two detectors, if the near detectors are placed suitably. The case of the KASKA plan (7 reactors and 3 detectors) is investigated in detail, and it is explicitly shown that it does not suffer from the extra uncertainty due to multiple reactors.Comment: 26 pages, 10 eps-files, revtex

Electron Transfer Across A Peptide-peptide Interface Within A Designed Metalloprotein

Mechanistic studies of biological electron-transfer (ET) reactions have involved the use of surface-derivatized proteins, protein−protein complexes, and polypeptide-bridged donor−acceptor compounds. These latter studies seek to use well-defined model systems to better define the role of the intervening protein matrix in mediating biological electron transfers. However, whereas many in vivo ET reactions occur across a noncovalent protein−protein interface, the primary role of the peptide spacers found in current model systems is to provide a covalent link between the donor and acceptor sites. As such, these systems are poorly suited to probe the mechanisms of ET reactions occurring across a peptide−peptide interface

Dynamical Susceptibility in KDP-type Crysals above and below Tc II

The path probability method (PPM) in the tetrahedron-cactus approximation is applied to the Slater-Takagi model with dipole-dipole interaction for KH2PO4-type hydrogen-bonded ferroelectric crystals in order to derive a small dip structure in the real part of dynamical susceptibility observed at the transition temperature Tc. The dip structure can be ascribed to finite relaxation times of electric dipole moments responsible for the first order transition with contrast to the critical slowing down in the second order transition. The light scattering intensity which is related to the imaginary part of dynamical susceptibility is also calculated above and below the transition temperature and the obtained central peak structure is consistent with polarization fluctuation modes in Raman scattering experiments.Comment: 8 pages, 11 figure

Relativistic many-body calculation of low-energy dielectronic resonances in Be-like carbon

We apply relativistic configuration-interaction method coupled with many-body perturbation theory (CI+MBPT) to describe low-energy dielectronic recombination. We combine the CI+MBPT approach with the complex rotation method (CRM) and compute the dielectronic recombination spectrum for Li-like carbon recombining into Be-like carbon. We demonstrate the utility and evaluate the accuracy of this newly-developed CI+MBPT+CRM approach by comparing our results with the results of the previous high-precision study of the CIII system [Mannervik et al., Phys. Rev. Lett. 81, 313 (1998)].Comment: 6 pages, 1 figure; v2,v3: fixed reference

A container-based workflow for distributed training of deep learning algorithms in HPC clusters

Deep learning has been postulated as a solution for numerous problems in different branches of science. Given the resource-intensive nature of these models, they often need to be executed on specialized hardware such graphical processing units (GPUs) in a distributed manner. In the academic field, researchers get access to this kind of resources through High Performance Computing (HPC) clusters. This kind of infrastructures make the training of these models difficult due to their multi-user nature and limited user permission. In addition, different HPC clusters may possess different peculiarities that can entangle the research cycle (e.g., libraries dependencies). In this paper we develop a workflow and methodology for the distributed training of deep learning models in HPC clusters which provides researchers with a series of novel advantages. It relies on udocker as containerization tool and on Horovod as library for the distribution of the models across multiple GPUs. udocker does not need any special permission, allowing researchers to run the entire workflow without relying on any administrator. Horovod ensures the efficient distribution of the training independently of the deep learning framework used. Additionally, due to containerization and specific features of the workflow, it provides researchers with a cluster-agnostic way of running their models. The experiments carried out show that the workflow offers good scalability in the distributed training of the models and that it easily adapts to different clusters