4,091 research outputs found

    Experimental study of ultracold neutron production in pressurized superfluid helium

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    We have investigated experimentally the pressure dependence of the production of ultracold neutrons (UCN) in superfluid helium in the range from saturated vapor pressure to 20bar. A neutron velocity selector allowed the separation of underlying single-phonon and multiphonon pro- cesses by varying the incident cold neutron (CN) wavelength in the range from 3.5 to 10{\AA}. The predicted pressure dependence of UCN production derived from inelastic neutron scattering data was confirmed for the single-phonon excitation. For multiphonon based UCN production we found no significant dependence on pressure whereas calculations from inelastic neutron scattering data predict an increase of 43(6)% at 20bar relative to saturated vapor pressure. From our data we conclude that applying pressure to superfluid helium does not increase the overall UCN production rate at a typical CN guide.Comment: 18 pages, 8 figures Version accepted for publication in PR

    The age of data-driven proteomics : how machine learning enables novel workflows

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    A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open modification searches. These workflows are all challenging because of ambiguity in the identification stage; they either expand the search space and thus increase the ambiguity of identifications, or, in the case of DIA, they generate data that is inherently more ambiguous. In this context, machine learning-based predictive models are now generating considerable excitement in the field of proteomics because these predictive models hold great potential to drastically reduce the ambiguity in the identification process of the above-mentioned workflows. Indeed, the field has already produced classical machine learning and deep learning models to predict almost every aspect of a liquid chromatography-mass spectrometry (LC-MS) experiment. Yet despite all the excitement, thorough integration of predictive models in these challenging LC-MS workflows is still limited, and further improvements to the modeling and validation procedures can still be made. In this viewpoint we therefore point out highly promising recent machine learning developments in proteomics, alongside some of the remaining challenges

    Pattern transfer of sub-micrometre-scaled structures into solid copper by laser embossing

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    Laser embossing allows the micron and submicron patterning of metal substrates that is of great interest in a wide range of applications. This replication process enables low-cost patterning of metallic materials by non-thermal, high-speed forming which is driven by laser-induced shock waves. In this study the surface topography characteristics as well as the material structure at laser embossing of sub-micrometre gratings into solid copper is presented. The topography of the laser-embossed copper pattern is analysed with atomic force microscopy (AFM) in comparison to the master surface. The height of the embossed structures and the replicated pattern fidelity increases up to a laser fluence of F ∼ 10 J/cm2. For higher laser fluences the height of the embossed structures saturates at 75% of the master pattern height and the shape is adequate to the master. Structural modifications in the copper mono crystals after the laser embossing process were investigated with transmission electron microscopy (TEM) and electron backscatter diffraction (EBSD). Almost no modifications were detected. The residual stress after laser embossing of 32 MPa (F = 30 J/cm2) has only a limited influence on the surface pattern formation

    LpL^p-Spectral theory of locally symmetric spaces with QQ-rank one

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    We study the LpL^p-spectrum of the Laplace-Beltrami operator on certain complete locally symmetric spaces M=Γ\XM=\Gamma\backslash X with finite volume and arithmetic fundamental group Γ\Gamma whose universal covering XX is a symmetric space of non-compact type. We also show, how the obtained results for locally symmetric spaces can be generalized to manifolds with cusps of rank one

    Is the Unitarity of the quark-mixing-CKM-matrix violated in neutron β\beta-decay?

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    We report on a new measurement of neutron β\beta-decay asymmetry. From the result \linebreak A0A_0 = -0.1189(7), we derive the ratio of the axial vector to the vector coupling constant λ\lambda = gA/gV{\it g_A/g_V} = -1.2739(19). When included in the world average for the neutron lifetime τ\tau = 885.7(7)s, this gives the first element of the Cabibbo-Kobayashi-Maskawa (CKM) matrix VudV_{ud} . With this value and the Particle Data Group values for VusV_{us} and VubV_{ub}, we find a deviation from the unitarity condition for the first row of the CKM matrix of Δ\Delta = 0.0083(28), which is 3.0 times the stated error

    Space Shuttle Program: Automatic rendezvous, proximity operations, and capture (category 3)

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    The NASA Johnson Space Center is actively pursuing the development and demonstration of capabilities for automatic rendezvous, proximity operations, and capture (AR&C) using the Space Shuttle as the active vehicle. This activity combines the technologies, expertise, tools, and facilities of the JSC Tracking and Communications Division (EE), Navigation, Control and Aeronautics Division (EG), Automation and Robotics Division (ER), and Structures and Mechanics Division (ES) of the Engineering Directorate and the Flight Design and Dynamics Division (DM) of the Mission Operations Directorate. Potential benefits of AR&C include more efficient and repeatable rendezvous, proximity operations, and capture operations; reduced impacts on the target vehicles (e.g., Orbiter RCS plume loads); reduced flight crew work loads; reduced ground support requirements; and reduced operational constraints. This paper documents the current JSC capabilities/tools/facilities for AR&C and describes a proposed plan for a progression of ground demonstrations and flight tests and demonstrations of AR&C capabilities. This plan involves the maturing of existing technologies in tracking and communications; guidance, navigation and control; mechanisms; manipulators; and systems management and integrating them into several evolutionary demonstration stages

    Low energy excitations in crystalline perovskite oxides: Evidence from noise experiments

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    In this paper we report measurements of 1/f noise in a crystalline metallic oxide with perovskite structure down to 4.2K. The results show existence of localized excitations with average activation energy ≈\approx 70-80 meV which produce peak in the noise at T ≈\approx 35-40K. In addition, it shows clear evidence of tunnelling type two-level-systems (as in glasses) which show up in noise measurements below 30K.Comment: 11 pages, 4 figures, to appear in Phys Rev B, vol 58, 1st Dec issu

    Construction and analysis of causally dynamic hybrid bond graphs

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    Engineering systems are frequently abstracted to models with discontinuous behaviour (such as a switch or contact), and a hybrid model is one which contains continuous and discontinuous behaviours. Bond graphs are an established physical modelling method, but there are several methods for constructing switched or ‘hybrid’ bond graphs, developed for either qualitative ‘structural’ analysis or efficient numerical simulation of engineering systems. This article proposes a general hybrid bond graph suitable for both. The controlled junction is adopted as an intuitive way of modelling a discontinuity in the model structure. This element gives rise to ‘dynamic causality’ that is facilitated by a new bond graph notation. From this model, the junction structure and state equations are derived and compared to those obtained by existing methods. The proposed model includes all possible modes of operation and can be represented by a single set of equations. The controlled junctions manifest as Boolean variables in the matrices of coefficients. The method is more compact and intuitive than existing methods and dispenses with the need to derive various modes of operation from a given reference representation. Hence, a method has been developed, which can reach common usage and form a platform for further study
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