GREGOR Fabry-Perot Interferometer - status report and prospects

The GREGOR Fabry-Perot Interferometer (GFPI) is one of three first-light instruments of the German 1.5-meter GREGOR solar telescope at the Observatorio del Teide, Tenerife, Spain. The GFPI allows fast narrow-band imaging and post-factum image restoration. The retrieved physical parameters will be a fundamental building block for understanding the dynamic Sun and its magnetic field at spatial scales down to 50 km on the solar surface. The GFPI is a tunable dual-etalon system in a collimated mounting. It is designed for spectropolarimetric observations over the wavelength range from 530-860 nm with a theoretical spectral resolution of R ~ 250,000. The GFPI is equipped with a full-Stokes polarimeter. Large-format, high-cadence CCD detectors with powerful computer hard- and software enable the scanning of spectral lines in time spans equivalent to the evolution time of solar features. The field-of-view of 50" x 38" covers a significant fraction of the typical area of active regions. We present the main characteristics of the GFPI including advanced and automated calibration and observing procedures. We discuss improvements in the optical design of the instrument and show first observational results. Finally, we lay out first concrete ideas for the integration of a second FPI, the Blue Imaging Solar Spectrometer, which will explore the blue spectral region below 530 nm.Comment: 18 pages, 9 Figures, 4 Tables, "Astronomical Telescopes and Instrumentation", Amsterdam, 1-6 July 2012, SPIE Proc. 8446-276, in pres

Echo State Networks as Novel Approach for Low-Cost Myoelectric Control

Prahm C, Schulz A, Paaßen B, Aszmann O, Hammer B, Dorffner G. Echo State Networks as Novel Approach for Low-Cost Myoelectric Control. In: ten Telje A, Popow C, Holmes JH, Sacchi L, eds. Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017). Lecture Notes in Computer Science. Vol 10259. Springer; 2017: 338--342.Myoelectric signals or muscle signals provide an intuitive and rapid interface for controlling technical devices, in particular bionic arm prostheses. However, inferring the intended movement from a surface myoelectric recording is a non-trivial pattern recognition task, especially if myoelectric data stems from low-cost sensors. At the same time, overly complex models are prohibited by strict speed, data parsimonity and robustness requirements. As a compromise between high accuracy and strict requirements we propose to apply Echo State Networks (ESNs), which can be seen as an extension of standard linear regression with 1) a memory and 2) nonlinearity. We find that both features, memory and nonlinearity, independently as well as in conjunction, improve the prediction accuracy on simultaneous movements in two degrees of freedom (hand opening/closing as well as pronation/supination) recorded from four able-bodied participants using a low-cost myoelectric sensor. However, we also find that the model is still not sufficiently resistant to external disturbances such as electrode shift

Highly Selective PTK2 Proteolysis Targeting Chimeras to Probe Focal Adhesion Kinase Scaffolding Functions

Focal adhesion tyrosine kinase (PTK2) is often overexpressed in human hepatocellular carcinoma (HCC), and several reports have linked PTK2 depletion and/or pharmacological inhibition to reduced tumorigenicity. However, the clinical relevance of targeting PTK2 still remains to be proven. Here, we present two highly selective and functional PTK2 proteolysis-targeting chimeras utilizing von Hippel–Lindau and cereblon ligands to hijack E3 ligases for PTK2 degradation. BI-3663 (cereblon-based) degrades PTK2 with a median DC₅₀ of 30 nM to >80% across a panel of 11 HCC cell lines. Despite effective PTK2 degradation, these compounds did not phenocopy the reported antiproliferative effects of PTK2 depletion in any of the cell lines tested. By disclosing these compounds, we hope to provide valuable tools for the study of PTK2 degradation across different biological systems

Monatsschrift Kinderheilkunde / „Cyberbullying“ unter Jugendlichen : Daten, Trends und Möglichkeiten der Prävention

Cyberbullying, die missbräuchliche Verwendung elektronischer Kommunikationsmedien mit dem Ziel, andere zu verletzen, zu demütigen oder einzuschüchtern, führt zu langfristigen Traumatisierungen mit schwerwiegenden, z.T. lebensbedrohlichen Konsequenzen. Im Durchschnitt ist etwa ein Viertel aller Jugendlichen von diesem Problem betroffen. Der vorliegende Beitrag gibt einen Überblick über Phänomenologie, Symptome, Hintergründe, Konsequenzen und Präventionsmöglichkeiten, um zur aussichtsreichen Bekämpfung gegen dieses bisher praktisch völlig vernachlässigte Phänomen aufzurufen. Ziele sind die Einführung flächendeckender Maßnahmen zur Prävention von Cyberbullying sowie das Erkennen bereits eingetretener Folgen und ihre Behandlung.(VLID)365282

Monitoring and Therapy Planning without Effective Data Validation are Ineffective

Systems for monitoring and therapy planning, which receive their data from computer-based patient records and on-line monitoring equipment, require reliable data. Reasoning on faulty data can cause unexplainable and lifethreatening conclusions. Effective and efficient data validation methods are needed to arrive at reliable conclusions. We distinguished four categories of data validation and repair based on their underlying temporal ontologies: time-point-, time-interval-, trend-based, and time-independent validation and repair. Observing single measurements is not effective to arrive at trustable data. Therefore we take into account the behavior of parameters in the past as well as knowledge derived from domain experts. Examples from VIE-VENT, a knowledge-based monitoring and therapy-planning system for artificially-ventilated newborns, demonstrate the applicability of these methods. 1 Introduction In the last years, several sophisticated knowledge-based monitoring and therapy-plann..

Metaphor graphics to visualize ICU data over time

The time-oriented analysis of electronic patient records at a (neonatal) intensive care unit is a tedious and time-consuming task. The vast amount of data available makes it hard for the physician to recognize the essential changes over time. VIEVISU is a data visualization system which uses multiples to present the change in the patient's status over time in graphic form. Metaphor graphics is used to sketch the parameters most relevant in characterizing the situation of a patient. 1 Introduction The intensive care unit (ICU) is a data rich environment. On-line monitoring produces a set of patient data every second. Moreover, clinical data (patient's state, lab values, diagnoses, medication, other therapeutic and nursing actions) are collected manually at various time intervals. A computer based patient data management system (PDMS) stores both types of data, on-line collected and manually entered data within a time frame. Even if these electronic patient records are complete and corre..