TY - JOUR A1 - Kralemann, Bjoern A1 - Pikovskij, Arkadij A1 - Rosenblum, Michael T1 - Reconstructing effective phase connectivity of oscillator networks from observations JF - New journal of physics : the open-access journal for physics N2 - We present a novel approach for recovery of the directional connectivity of a small oscillator network by means of the phase dynamics reconstruction from multivariate time series data. The main idea is to use a triplet analysis instead of the traditional pairwise one. Our technique reveals an effective phase connectivity which is generally not equivalent to a structural one. We demonstrate that by comparing the coupling functions from all possible triplets of oscillators, we are able to achieve in the reconstruction a good separation between existing and non-existing connections, and thus reliably reproduce the network structure. KW - network reconstruction KW - coupled oscillators KW - connectivity KW - data analysis Y1 - 2014 U6 - https://doi.org/10.1088/1367-2630/16/8/085013 SN - 1367-2630 VL - 16 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Verma, Meetu A1 - Kummerow, P. A1 - Denker, Carsten T1 - On the extent of the moat flow in axisymmetric sunspots JF - Astronomische Nachrichten = Astronomical notes N2 - Unipolar, axisymmetric sunspots are figuratively called “theoretician's sunspots” because their simplicity supposedly makes them more suitable for theoretical descriptions or numerical models. On November 18, 2013, a very large specimen (active region NOAA 11899) crossed the central meridian of the sun. The moat flow associated with this very large spot is quantitatively compared to that of a medium and a small sunspot to determine the extent of the moat flow in different environments. We employ continuum images and magnetograms of the Helioseismic and Magnetic Imager (HMI) as well as extreme ultraviolet (EUV) images at λ160 nm of the Atmospheric Imaging Assembly (AIA), both on board the Solar Dynamics Observatory (SDO), to measure horizontal proper motions with Local Correlation Tracking (LCT) and flux transport velocities with the Differential Affine Velocity Estimator (DAVE). We compute time-averaged flow maps (±6 hr around meridian passage) and radial averages of photometric, magnetic, and flow properties. Flow fields of a small- and a medium-sized axisymmetric sunspot provide the context for interpreting the results. All sunspots show outward moat flow and the advection of moving magnetic features (MMFs). However, the extent of the moat flow varies from spot to spot, and a correlation of flow properties with size is tenuous, if at all present. The moat flow is asymmetric and predominantly in the east–west direction, whereby deviations are related to the tilt angle of the sunspot group as well as to the topology and activity level of the trailing plage. KW - activity KW - data analysis KW - image processing KW - photosphere KW - sunspots Y1 - 2018 U6 - https://doi.org/10.1002/asna.201813482 SN - 0004-6337 SN - 1521-3994 VL - 339 IS - 4 SP - 268 EP - 276 PB - Wiley-VCH CY - Weinheim ER - TY - JOUR A1 - Topçu, Çağdaş A1 - Frühwirth, Matthias A1 - Moser, Maximilian A1 - Rosenblum, Michael A1 - Pikovskij, Arkadij T1 - Disentangling respiratory sinus arrhythmia in heart rate variability records JF - Physiological Measurement N2 - Objective: Several different measures of heart rate variability, and particularly of respiratory sinus arrhythmia, are widely used in research and clinical applications. For many purposes it is important to know which features of heart rate variability are directly related to respiration and which are caused by other aspects of cardiac dynamics. Approach: Inspired by ideas from the theory of coupled oscillators, we use simultaneous measurements of respiratory and cardiac activity to perform a nonlinear disentanglement of the heart rate variability into the respiratory-related component and the rest. Main results: The theoretical consideration is illustrated by the analysis of 25 data sets from healthy subjects. In all cases we show how the disentanglement is manifested in the different measures of heart rate variability. Significance: The suggested technique can be exploited as a universal preprocessing tool, both for the analysis of respiratory influence on the heart rate and in cases when effects of other factors on the heart rate variability are in focus. KW - respiratory sinus arrhythmia KW - heart rate variability KW - coupled oscillators model KW - phase dynamics KW - data analysis Y1 - 2018 U6 - https://doi.org/10.1088/1361-6579/aabea4 SN - 0967-3334 SN - 1361-6579 VL - 39 IS - 5 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Adnan, Hassan Sami A1 - Srsic, Amanda A1 - Venticich, Pete Milos A1 - Townend, David M.R. T1 - Using AI for mental health analysis and prediction in school surveys JF - European journal of public health N2 - Background: Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper- based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models. Methods: For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases. Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning can then be deployed to classify specific behaviour and mental health patterns. Results: We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project. Conclusions: This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns of unknown effects. KW - ethics KW - artificial intelligence KW - adolescent KW - child KW - confidentiality KW - health personnel KW - mental disorders KW - mental health KW - personal satisfaction KW - privacy KW - school (environment) KW - statutes and laws KW - public health medicine KW - surveillance KW - medical KW - prevention KW - datasets KW - machine learning KW - supervised machine learning KW - data analysis Y1 - 2020 U6 - https://doi.org/10.1093/eurpub/ckaa165.336 SN - 1101-1262 SN - 1464-360X VL - 30 SP - V125 EP - V125 PB - Oxford Univ. Press CY - Oxford [u.a.] ER - TY - JOUR A1 - Dineva, Ekaterina A1 - Pearson, Jeniveve A1 - Ilyin, Ilya A1 - Verma, Meetu A1 - Diercke, Andrea A1 - Strassmeier, Klaus A1 - Denker, Carsten T1 - Characterization of chromospheric activity based on Sun-as-a-star spectral and disk-resolved activity indices JF - Astronomische Nachrichten = Astronomical notes N2 - The strong chromospheric absorption lines Ca ii H & K are tightly connected to stellar surface magnetic fields. Only for the Sun, spectral activity indices can be related to evolving magnetic features on the solar disk. The Solar Disk-Integrated (SDI) telescope feeds the Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) of the Large Binocular Telescope (LBT) at Mt. Graham International Observatory, Arizona, U.S.A. We present high-resolution, high-fidelity spectra that were recorded on 184 & 82 days in 2018 & 2019 and derive the Ca ii H & K emission ratio, that is, the S-index. In addition, we compile excess brightness and area indices based on full-disk Ca ii K-line-core filtergrams of the Chromospheric Telescope (ChroTel) at Observatorio del Teide, Tenerife, Spain and full-disk ultraviolet (UV) 1600 angstrom images of the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO). Thus, Sun-as-a-star spectral indices are related to their counterparts derived from resolved images of the solar chromosphere. All indices display signatures of rotational modulation, even during the very low magnetic activity in the minimum of Solar Cycle 24. Bringing together different types of activity indices has the potential to join disparate chromospheric datasets yielding a comprehensive description of chromospheric activity across many solar cycles. KW - astronomical databases KW - miscellaneous KW - methods KW - data analysis KW - activity KW - Sun KW - atmosphere KW - chromosphere KW - techniques KW - spectroscopic Y1 - 2022 U6 - https://doi.org/10.1002/asna.20223996 SN - 0004-6337 SN - 1521-3994 VL - 343 IS - 5 PB - Wiley-VCH CY - Weinheim ER -