Optical Coherence Tomography for Examination of Parchment Degradation

A novel application of Optical Coherence Tomography utilizing infrared light of 830 nm central wavelength for non invasive examination of the structure of parchment, some covered with iron gall ink, is presented. It is shown that both the parchment and the ink applied are sufficiently transparent to light of this wavelength. In the study, Spectral OCT (SOCT) as well as Polarisation Sensitive OCT (PS-OCT) techniques were used to obtain cross-sectional images of samples of parchment based on scattering properties. The second technique was additionally employed to recover the birefringence properties and the optical axis orientations of the sample. It was shown that freshly produced parchment exhibits a degree of birefringence. However, this property declines with ageing, and samples of old parchment completely depolarise the incident light

A planar dielectric antenna for directional single-photon emission and near-unity collection efficiency

Single emitters have been considered as sources of single photons in various contexts such as cryptography, quantum computation, spectroscopy, and metrology. The success of these applications will crucially rely on the efficient directional emission of photons into well-defined modes. To accomplish a high efficiency, researchers have investigated microcavities at cryogenic temperatures, photonic nanowires, and near-field coupling to metallic nano-antennas. However, despite an impressive progress, the existing realizations substantially fall short of unity collection efficiency. Here we report on a theoretical and experimental study of a dielectric planar antenna, which uses a layered structure for tailoring the angular emission of a single oriented molecule. We demonstrate a collection efficiency of 96% using a microscope objective at room temperature and obtain record detection rates of about 50 MHz. Our scheme is wavelength-insensitive and can be readily extended to other solid-state emitters such as color centers and semiconductor quantum dots

Controlled coupling of counterpropagating whispering-gallery modes by a single Rayleigh scatterer: a classical problem in a quantum optical light

We present experiments where a single subwavelength scatterer is used to examine and control the back-scattering induced coupling between counterpropagating high-Q modes of a microsphere resonator. Our measurements reveal the standing wave character of the resulting symmetric and antisymmetric eigenmodes, their unbalanced intensity distributions, and the coherent nature of their coupling. We discuss our findings and the underlying classical physics in the framework common to quantum optics and provide a particularly intuitive explanation of the central processes.Comment: accepted for publication in Pysical Review Letter

Quantum Degenerate Exciton-Polaritons in Thermal Equilibrium

We study the momentum distribution and relaxation dynamics of semiconductor microcavity polaritons by angle-resolved and time-resolved spectroscopy. Above a critical pump level, the thermalization time of polaritons at positive detunings becomes shorter than their lifetime, and the polaritons form a quantum degenerate Bose-Einstein distribution in thermal equilibrium with the lattice.Comment: Updated with the published versio

RoSA: A Framework for Modeling Self-Awareness in Cyber-Physical Systems

The role of smart and autonomous systems is becoming vital in many areas of industry and society. Expectations from such systems continuously rise and become more ambitious: long lifetime, high reliability, high performance, energy efficiency, and adaptability, particularly in the presence of changing environments. Computational self-awareness promises a comprehensive assessment of the system state for sensible and well-informed actions and resource management. Computational self-awareness concepts can be used in many applications such as automated manufacturing plants, telecommunication systems, autonomous driving, traffic control, smart grids, and wearable health monitoring systems. Developing self-aware systems from scratch for each application is the most common practice currently, but this is highly redundant, inefficient, and uneconomic. Hence, we propose a framework that supports modeling and evaluation of various self-aware concepts in hierarchical agent systems, where agents are made up of self-aware functionalities. This paper presents the Research on Self-Awareness (RoSA) framework and its design principles. In addition, self-aware functionalities abstraction, data reliability, and confidence, which are currently provided by RoSA, are described. Potential use cases of RoSA are discussed. Capabilities of the proposed framework are showcased by case studies from the fields of healthcare and industrial monitoring. We believe that RoSA is capable of serving as a common framework for self-aware modeling and applications and thus helps researchers and engineers in exploring the vast design space of hierarchical agent-based systems with computational self-awareness

FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography

Spectral-domain optical coherence tomography (SD-OCT) provides volumetric images of retinal structures with unprecedented detail. Accurate segmentation algorithms and feature quantification in these images, however, are needed to realize the full potential of SD-OCT. The fully automated segmentation algorithm, FloatingCanvas, serves this purpose and performs a volumetric segmentation of retinal tissue layers in three-dimensional image volume acquired around the optic nerve head without requiring any pre-processing. The reconstructed layers are analysed to extract features such as blood vessels and retinal nerve fibre layer thickness. Findings from images obtained with the RTVue-100 SD-OCT (Optovue, Fremont, CA, USA) indicate that FloatingCanvas is computationally efficient and is robust to the noise and low contrast in the images. The FloatingCanvas segmentation demonstrated good agreement with the human manual grading. The retinal nerve fibre layer thickness maps obtained with this method are clinically realistic and highly reproducible compared with time-domain StratusOCT™

Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: insights from an experimental catchment

This study presents quantitative and qualitative insights into the time scale dependencies of hydrological parameters, predictions and their uncertainties, and examines the impact of the time resolution of the calibration data on the identifiable system complexity. Data from an experimental basin (Weierbach, Luxembourg) is used to analyze four conceptual models of varying complexity, over time scales of 30 min to 3 days, using several combinations of numerical implementations and inference equations. Large spurious time scale trends arise in the parameter estimates when unreliable time-stepping approximations are employed and/or when the heteroscedasticity of the model residual errors is ignored. Conversely, the use of robust numerics and more adequate (albeit still clearly imperfect) likelihood functions markedly stabilizes and, in many cases, reduces the time scale dependencies and improves the identifiability of increasingly complex model structures. Parameters describing slow flow remained essentially constant over the range of subhourly to daily scales considered here, while parameters describing quick flow converged toward increasingly precise and stable estimates as the data resolution approached the characteristic time scale of these faster processes. These results are consistent with theoretical expectations based on numerical error analysis and dataaveraging considerations. Additional diagnostics confirmed the improved ability of the more complex models to reproduce distinct signatures in the observed data. More broadly, this study provides insights into the information content of hydrological data and, by advocating careful attention to robust numericostatistical analysis and stringent processoriented diagnostics, furthers the utilization of dense-resolution data and experimental insights to advance hypothesis-based hydrological modeling at the catchment scale.Dmitri Kavetski, Fabrizio Fenicia and Martyn P. Clar

COVID-19 in children and adolescents in Europe: a multinational, multicentre cohort study

Background To date, few data on paediatric COVID-19 have been published, and most reports originate from China. This study aimed to capture key data on children and adolescents with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection across Europe to inform physicians and health-care service planning during the ongoing pandemic. Methods This multicentre cohort study involved 82 participating health-care institutions across 25 European countries, using a well established research network—the Paediatric Tuberculosis Network European Trials Group (ptbnet)—that mainly comprises paediatric infectious diseases specialists and paediatric pulmonologists. We included all individuals aged 18 years or younger with confirmed SARS-CoV-2 infection, detected at any anatomical site by RT-PCR, between April 1 and April 24, 2020, during the initial peak of the European COVID-19 pandemic. We explored factors associated with need for intensive care unit (ICU) admission and initiation of drug treatment for COVID-19 using univariable analysis, and applied multivariable logistic regression with backwards stepwise analysis to further explore those factors significantly associated with ICU admission. Findings 582 individuals with PCR-confirmed SARS-CoV-2 infection were included, with a median age of 5·0 years (IQR 0·5–12·0) and a sex ratio of 1·15 males per female. 145 (25%) had pre-existing medical conditions. 363 (62%) individuals were admitted to hospital. 48 (8%) individuals required ICU admission, 25 (4%) mechanical ventilation (median duration 7 days, IQR 2–11, range 1–34), 19 (3%) inotropic support, and one (<1%) extracorporeal membrane oxygenation. Significant risk factors for requiring ICU admission in multivariable analyses were being younger than 1 month (odds ratio 5·06, 95% CI 1·72–14·87; p=0·0035), male sex (2·12, 1·06–4·21; p=0·033), pre-existing medical conditions (3·27, 1·67–6·42; p=0·0015), and presence of lower respiratory tract infection signs or symptoms at presentation (10·46, 5·16–21·23; p<0·0001). The most frequently used drug with antiviral activity was hydroxychloroquine (40 [7%] patients), followed by remdesivir (17 [3%] patients), lopinavir–ritonavir (six [1%] patients), and oseltamivir (three [1%] patients). Immunomodulatory medication used included corticosteroids (22 [4%] patients), intravenous immunoglobulin (seven [1%] patients), tocilizumab (four [1%] patients), anakinra (three [1%] patients), and siltuximab (one [<1%] patient). Four children died (case-fatality rate 0·69%, 95% CI 0·20–1·82); at study end, the remaining 578 were alive and only 25 (4%) were still symptomatic or requiring respiratory support. Interpretation COVID-19 is generally a mild disease in children, including infants. However, a small proportion develop severe disease requiring ICU admission and prolonged ventilation, although fatal outcome is overall rare. The data also reflect the current uncertainties regarding specific treatment options, highlighting that additional data on antiviral and immunomodulatory drugs are urgently needed. Funding ptbnet is supported by Deutsche Gesellschaft für Internationale Zusammenarbeit