Dispersion monitoring for high-speed WDM networks via two-photon absorption in a semiconductor microcavity

Due to the continued demand for bandwidth, network operators have to increase the data rates at which individual wavelengths operate at. As these data rates will exceed 100 Gbit/s in the next 5-10 years, it will be crucial to be able to monitor and compensate for the amount of chromatic dispersion encountered by individual wavelength channels. This paper will focus on the use of the novel nonlinear optical-to-electrical conversion process of two-photon absorption (TPA) for dispersion monitoring. By incorporating a specially designed semiconductor microcavity, the TPA response becomes wavelength dependent, thus allowing simultaneous channel selection and monitoring without the need for external wavelength filterin

Editorial: The genetics of human Mendelian skin disorders

The skin is comprised of multiple types of cells that serve as a protective barrier. Mutations in the genes that are responsible for protecting the functional integrity of the skin are often found in many inherited skin diseases, more commonly known as the Mendelian human skin disorders. Advances in molecular techniques and sequencing technologies have enabled identification of novel pathogenic variants, which helps to provide insight into genotype–phenotype correlations and to define the genetic basis of these skin disorders. In this Research Topic, a total of ten articles are published, including those describing findings from case studies and original research, as well as a mini review of current genetic diagnosis strategies, novel gene variants, and genotype-phenotype correlations in human Mendelian skin disorders

Minimal immersions of closed surfaces in hyperbolic three-manifolds

We study minimal immersions of closed surfaces (of genus $g \ge 2$) in hyperbolic 3-manifolds, with prescribed data $(\sigma, t\alpha)$, where $\sigma$ is a conformal structure on a topological surface $S$, and $\alpha dz^2$ is a holomorphic quadratic differential on the surface $(S,\sigma)$. We show that, for each $t \in (0,\tau_0)$ for some $\tau_0 > 0$, depending only on $(\sigma, \alpha)$, there are at least two minimal immersions of closed surface of prescribed second fundamental form $Re(t\alpha)$ in the conformal structure $\sigma$. Moreover, for $t$ sufficiently large, there exists no such minimal immersion. Asymptotically, as $t \to 0$, the principal curvatures of one minimal immersion tend to zero, while the intrinsic curvatures of the other blow up in magnitude.Comment: 16 page

Cluster Editing: Kernelization based on Edge Cuts

Kernelization algorithms for the {\sc cluster editing} problem have been a popular topic in the recent research in parameterized computation. Thus far most kernelization algorithms for this problem are based on the concept of {\it critical cliques}. In this paper, we present new observations and new techniques for the study of kernelization algorithms for the {\sc cluster editing} problem. Our techniques are based on the study of the relationship between {\sc cluster editing} and graph edge-cuts. As an application, we present an ${\cal O}(n^2)$-time algorithm that constructs a $2k$ kernel for the {\it weighted} version of the {\sc cluster editing} problem. Our result meets the best kernel size for the unweighted version for the {\sc cluster editing} problem, and significantly improves the previous best kernel of quadratic size for the weighted version of the problem

Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation

Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat infiltration. These features are pivotal to measuring the state of muscle functional health and in tracking the response of the body to musculoskeletal and neuromusculoskeletal disorders. The gold standard approach to perform muscle segmentation requires manual processing of large numbers of images and is associated with significant operator repeatability issues and high time requirements. Deep learning-based techniques have been recently suggested to be capable of automating the process, which would catalyse research into the effects of musculoskeletal disorders on the muscular system. In this study, three convolutional neural networks were explored in their capacity to automatically segment twenty-three lower limb muscles from the hips, thigh, and calves from magnetic resonance images. The three neural networks (UNet, Attention UNet, and a novel Spatial Channel UNet) were trained independently with augmented images to segment 6 subjects and were able to segment the muscles with an average Relative Volume Error (RVE) between -8.6% and 2.9%, average Dice Similarity Coefficient (DSC) between 0.70 and 0.84, and average Hausdorff Distance (HD) between 12.2 and 46.5 mm, with performance dependent on both the subject and the network used. The trained convolutional neural networks designed, and data used in this study are openly available for use, either through re-training for other medical images, or application to automatically segment new T1-weighted lower limb magnetic resonance images captured with similar acquisition parameters

Electron-positron pair production in an arbitrary polarized ultrastrong laser field

Electron-positron pair production in an arbitrary polarized ultrastrong laser field is investigated in the first order perturbation approximation in which the Volkov states are used for convenient calculation of scattering amplitude and cross section. It is found surprisingly that the optimal pair production depends strongly on the polarization. For some cases of field parameters, the optimal field is elliptically polarized or evenly circularly polarized one, rather than the usual linear polarization as indicated by previous works. Some insights into pair generation are given and some interesting unexpected features are also discussed briefly.Comment: 20 pages, 10 figure

Cosmological model with interactions in the dark sector

A cosmological model is proposed for the current Universe consisted of non-interacting baryonic matter and interacting dark components. The dark energy and dark matter are coupled through their effective barotropic indexes, which are considered as functions of the ratio between their energy densities. It is investigated two cases where the ratio is asymptotically stable and their parameters are adjusted by considering best fits to Hubble function data. It is shown that the deceleration parameter, the densities parameters, and the luminosity distance have the correct behavior which is expected for a viable present scenario of the Universe.Comment: 6 pages, 8 figure

Rotating day and night disturb growth hormone secretion profiles, body energy metabolism, and insulin levels in mice

Background: Insulin and growth hormone (GH) - 2 vital metabolic regulatory hormones - regulate glucose, lipid, and energy metabolism. These 2 hormones determine substrate and energy metabolism under different living conditions. Shift of day and night affects the clock system and metabolism probably through altered insulin and GH secretion. Methods: Five-week-old male mice were randomly assigned to a rotating light (RL) group (3-day normal light/dark cycle followed by 4-day reversed light/dark cycle per week) and normal light (NL) group. Body weight and food intake were recorded every week. Series of blood samples were collected for pulsatile GH analysis, glucose tolerance test, and insulin tolerance test at 9, 10, and 11 weeks from the start of intervention, respectively. Indirect calorimetric measurement was performed, and body composition was tested at 12 weeks. Expressions of energy and substrate metabolism-related genes were evaluated in pituitary and liver tissues at the end of 12-week intervention. Results: The RL group had an increased number of GH pulsatile bursts and reduced GH mass/burst. RL also disturbed the GH secretion regularity and mode. It suppressed insulin secretion, which led to a disturbed insulin/GH balance. It was accompanied by the reduced metabolic flexibility and modified gene expression involved in energy balance and substrate metabolism. Indirect calorimeter recording revealed that RL decreased the respiratory exchange ratio (RER) and oxygen consumption at the dark phase, which resulted in an increase in fat mass and free fatty acid levels in circulation. Conclusion: RL disturbed pulsatile GH secretion and decreased insulin secretion in male mice with significant impairment in energy, substrate metabolism, and body composition.Diabetes mellitus: pathophysiological changes and therap

A Systematic Study on Energy Dependence of Quasi-Periodic Oscillation Frequency in GRS 1915+105

Systematically studying all the RXTE/PCA observations for GRS 1915+105 before November 2010, we have discovered three additional patterns in the relation between Quasi-Periodic Oscillation (QPO) frequency and photon energy, extending earlier outcomes reported by Qu et al. (2010). We have confirmed that as QPO frequency increases, the relation evolves from the negative correlation to positive one. The newly discovered patterns provide new constraints on the QPO models