Theory of the n=2 levels in muonic deuterium

The present knowledge of Lamb shift, fine- and hyperfine structure of the $\mathrm{2S}$ and $\mathrm{2P}$ states in muonic deuterium is reviewed in anticipation of the results of a first measurement of several $\mathrm{2S-2P}$ transition frequencies in muonic deuterium ($\mu\mathrm{d}$). A term-by-term comparison of all available sources reveals reliable values and uncertainties of the QED and nuclear structure-dependent contributions to the Lamb shift, which are essential for a determination of the deuteron rms charge radius from $\mu\mathrm{d}$. Apparent discrepancies between different sources are resolved, in particular for the difficult two-photon exchange contributions. Problematic single-sourced terms are identified which require independent recalculation.Comment: 26 pages, add missing feynman diagrams (Fig. 3), renumber items (Tab. IV), correct a sum (column 5, Tab. IV

Fast calibration of heliostats

We present the HelioPoint method - a fast airborne method for calibrating entire heliostat fields

Improved X-ray detection and particle identification with avalanche photodiodes

Avalanche photodiodes are commonly used as detectors for low energy x-rays. In this work we report on a fitting technique used to account for different detector responses resulting from photo absorption in the various APD layers. The use of this technique results in an improvement of the energy resolution at 8.2 keV by up to a factor of 2, and corrects the timing information by up to 25 ns to account for space dependent electron drift time. In addition, this waveform analysis is used for particle identification, e.g. to distinguish between x-rays and MeV electrons in our experiment.Comment: 6 pages, 6 figure

Cortico-muscular coherence is reduced acutely post-stroke and increases bilaterally during motor recovery: a pilot study

Motor recovery following stroke is believed to necessitate alteration in functional connectivity between cortex and muscle. Cortico-muscular coherence has been proposed as a potential biomarker for post-stroke motor deficits, enabling a quantification of recovery, as well as potentially indicating the regions of cortex involved in recovery of function. We recorded simultaneous EEG and EMG during wrist extension from healthy participants and patients following ischaemic stroke, evaluating function at three time points post-stroke. EEG–EMG coherence increased over time, as wrist mobility recovered clinically, and by the final evaluation, coherence was higher in the patient group than in the healthy controls. Moreover, the cortical distribution differed between the groups, with coherence involving larger and more bilaterally scattered areas of cortex in the patients than in the healthy participants. The findings suggest that EEG–EMG coherence has the potential to serve as a biomarker for motor recovery and to provide information about the cortical regions that should be targeted in rehabilitation therapies based on real-time EEG

Towards deep learning based airborne monitoring methods for heliostats in solar tower power plants

While deep learning methods have proven their superiority over conventional image processing techniques in many domains, their use in airborne heliostat monitoring remains limited. Our aim is to bridge this gap by developing models to improve and extend existing image-based measurement methods in this field. We use Blender and BlenderProc to generate synthetic image data, which grants us access to vast amounts of training data essential for developing effective deep learning models. The exemplary model we train can potentially solve the following tasks related to airborne heliostat field monitoring: detection of heliostats and detection of mirror facet corners. Our promising preliminary results demonstrate the applicability of our approach to use synthetic training data for the development of the intended deep learning models

Having a baby in the Isle of Man The analysis and interpretation of data collected as part of the European Longitudinal Study of Pregnancy and Childhood (ELSPAC)

Available from British Library Document Supply Centre-DSC:DXN007815 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Measuring the α-particle charge radius with muonic helium-4 ions

The energy levels of hydrogen-like atomic systems can be calculated with great precision. Starting from their quantum mechanical solution, they have been refined over the years to include the electron spin, the relativistic and quantum field effects, and tiny energy shifts related to the complex structure of the nucleus. These energy shifts caused by the nuclear structure are vastly magnified in hydrogen-like systems formed by a negative muon and a nucleus, so spectroscopy of these muonic ions can be used to investigate the nuclear structure with high precision. Here we present the measurement of two 2S–2P transitions in the muonic helium-4 ion that yields a precise determination of the root-mean-square charge radius of the α particle of 1.67824(83) femtometres. This determination from atomic spectroscopy is in excellent agreement with the value from electron scattering1, but a factor of 4.8 more precise, providing a benchmark for few-nucleon theories, lattice quantum chromodynamics and electron scattering. This agreement also constrains several beyond-standard-model theories proposed to explain the proton-radius puzzle2,3,4,5, in line with recent determinations of the proton charge radius6,7,8,9, and establishes spectroscopy of light muonic atoms and ions as a precise tool for studies of nuclear properties.ISSN:0028-0836ISSN:1476-468

Fast airborne calibration of entire solar fields of heliostats

We present a fast airborne method for calibrating entire heliostat fields