Semi-empirical analysis of leptons in gases in crossed electric and magnetic fields, Part II: Transverse compression of muon beams

This article employs fluid equations to analyse muon beams in gases subject to crossed electric and magnetic fields, focussing in particular on a scheme proposed by D. Taqqu in 2006, whereby transverse compression of the beam is achieved by creating a density gradient in the gas. A general criterion for maximising beam compression, derived from first principles, is then applied to determine optimal experimental conditions for {\mu ^ +} in helium gas. Although the calculations require input of transport data for ({\mu ^ +}, He), which are generally unavailable, this issue is circumvented by "aliasing" ({\mu ^ +}, He) with (H{^ +}, He), for which transport coefficient data are available

Weak-lensing shear measurement with machine learning: teaching artificial neural networks about feature noise

Cosmic shear is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe requires an extremely accurate measurement of the shapes of millions of galaxies based on imaging data. Crucially, the shear measurement must address and compensate for a range of interwoven nuisance effects related to the instrument optics and detector, noise, unknown galaxy morphologies, colors, blending of sources, and selection effects. This paper explores the use of supervised machine learning (ML) as a tool to solve this inverse problem. We present a simple architecture that learns to regress shear point estimates and weights via shallow artificial neural networks. The networks are trained on simulations of the forward observing process, and take combinations of moments of the galaxy images as inputs. A challenging peculiarity of this ML application is the combination of the noisiness of the input features and the requirements on the accuracy of the inverse regression. To address this issue, the proposed training algorithm minimizes bias over multiple realizations of individual source galaxies, reducing the sensitivity to properties of the overall sample of source galaxies. Importantly, an observational selection function of these source galaxies can be straightforwardly taken into account via the weights. We first introduce key aspects of our approach using toy-model simulations, and then demonstrate its potential on images mimicking Euclid data. Finally, we analyze images from the GREAT3 challenge, obtaining competitively low shear biases despite the use of a simple training set. We conclude that the further development of ML approaches is of high interest to meet the stringent requirements on the shear measurement in current and future surveys. A demonstration implementation of our technique is publicly available.Comment: 31 pages, 26 figures, minor changes to match the version published in A&A, code available at https://astro.uni-bonn.de/~mtewes/ml-shear-meas

Dynamic contrast in scanning microscopic OCT

While optical coherence tomography (OCT) provides a resolution down to 1 micrometer it has difficulties to visualize cellular structures due to a lack of scattering contrast. By evaluating signal fluctuations, a significant contrast enhancement was demonstrated using time-domain full-field OCT (FF-OCT), which makes cellular and subcellular structures visible. The putative cause of the dynamic OCT signal is ATP-dependent motion of cellular structures in a sub-micrometer range, which provides histology-like contrast. Here we demonstrate dynamic contrast with a scanning frequency-domain OCT (FD-OCT). Given the inherent sectional imaging geometry, scanning FD-OCT provides depth-resolved images across tissue layers, a perspective known from histopathology, much faster and more efficiently than FF-OCT. Both, shorter acquisition times and tomographic depth-sectioning reduce the sensitivity of dynamic contrast for bulk tissue motion artifacts and simplify their correction in post-processing. The implementation of dynamic contrast makes microscopic FD-OCT a promising tool for histological analysis of unstained tissues.Comment: 7 pages, 3 figures, 1 Video available on reques

The Effect of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Therapy on Skeletal Muscle Lipid Content in Obese and Nonobese Men.

Obstructive sleep apnea (OSA), independently of obesity (OBS), predisposes to insulin resistance (IR) for largely unknown reasons. Because OSA-related intermittent hypoxia triggers lipolysis, overnight increases in circulating free fatty acids (FFAs) including palmitic acid (PA) may lead to ectopic intramuscular lipid accumulation potentially contributing to IR. Using 3-T-1H-magnetic resonance spectroscopy, we therefore compared intramyocellular and extramyocellular lipid (IMCL and EMCL) in the vastus lateralis muscle at approximately 7 am between 26 male patients with moderate-to-severe OSA (17 obese, 9 nonobese) and 23 healthy male controls (12 obese, 11 nonobese). Fiber type composition was evaluated by muscle biopsies. Moreover, we measured fasted FFAs including PA, glycated hemoglobin A1c, thigh subcutaneous fat volume (ScFAT, 1.5-T magnetic resonance tomography), and maximal oxygen uptake (VO2max). Fourteen patients were reassessed after continuous positive airway pressure (CPAP) therapy. Total FFAs and PA were significantly (by 178% and 166%) higher in OSA patients vs controls and correlated with the apnea-hypopnea index (AHI) (r ≥ 0.45, P < .01). Moreover, IMCL and EMCL were 55% (P < .05) and 40% (P < .05) higher in OSA patients, that is, 114% and 103% in nonobese, 24.4% and 8.4% in obese participants (with higher control levels). Overall, PA, FFAs (minus PA), and ScFAT significantly contributed to IMCL (multiple r = 0.568, P = .002). CPAP significantly decreased EMCL (-26%) and, by trend only, IMCL, total FFAs, and PA. Muscle fiber composition was unaffected by OSA or CPAP. Increases in IMCL and EMCL are detectable at approximately 7 am in OSA patients and are partly attributable to overnight FFA excesses and high ScFAT or body mass index. CPAP decreases FFAs and IMCL by trend but significantly reduces EMCL

Polysialic acid promotes remyelination in cerebellar slice cultures by Siglec-E-dependent modulation of microglia polarization

Multiple sclerosis is an inflammatory demyelinating disease of the central nervous system. Spontaneous restoration of myelin after demyelination occurs, but its efficiency declines during disease progression. Efficient myelin repair requires fine-tuning inflammatory responses by brain-resident microglia and infiltrating macrophages. Accordingly, promising therapeutic strategies aim at controlling inflammation to promote remyelination. Polysialic acid (polySia) is a polymeric glycan with variable chain lengths, presented as a posttranslational modification on select protein carriers. PolySia emerges as a negative regulator of inflammatory microglia and macrophage activation and has been detected on oligodendrocyte precursors and reactive astrocytes in multiple sclerosis lesions. As shown recently, polySia-modified proteins can also be released by activated microglia, and the intrinsically released protein-bound and exogenously applied free polySia were equally able to attenuate proinflammatory microglia activation via the inhibitory immune receptor Siglec-E. In this study, we explore polySia as a candidate substance for promoting myelin regeneration by immunomodulation. Lysophosphatidylcholine-induced demyelination of organotypic cerebellar slice cultures was used as an experimental model to analyze the impact of polySia with different degrees of polymerization (DP) on remyelination and inflammation. In lysophosphatidylcholine-treated cerebellar slice cultures, polySia-positive cells were abundant during demyelination but largely reduced during remyelination. Based on the determination of DP24 as the minimal polySia chain length required for the inhibition of inflammatory BV2 microglia activation, pools with short and long polySia chains (DP8–14 and DP24–30) were generated and applied to slice cultures during remyelination. Unlike DP8–14, treatment with DP24–30 significantly improved remyelination, increased arginase-1-positive microglia ratios, and reduced the production of nitric oxide in wildtype, but not in Siglec-E-deficient slice cultures. In vitro differentiation of oligodendrocytes was not affected by DP24–30. Collectively, these results suggest a beneficial effect of exogenously applied polySia DP24–30 on remyelination by Siglec-E-dependent microglia regulation

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

NPHP4, a cilia-associated protein, negatively regulates the Hippo pathway

The cilia-associated protein NPHP4 is a negative regulator of Hippo signaling that modulates cell proliferation in mammals

Measurement of charged particle spectra in deep-inelastic ep scattering at HERA

Charged particle production in deep-inelastic ep scattering is measured with the H1 detector at HERA. The kinematic range of the analysis covers low photon virtualities, 5 LT Q(2) LT 100 GeV2, and small values of Bjorken-x, 10(-4) LT x LT 10(-2). The analysis is performed in the hadronic centre-of-mass system. The charged particle densities are measured as a function of pseudorapidity (n(*)) and transverse momentum (p(T)(*)) in the range 0 LT n(*) LT 5 and 0 LT p(T)(*) LT 10 GeV in bins of x and Q(2). The data are compared to predictions from different Monte Carlo generators implementing various options for hadronisation and parton evolutions