A Modular Mobile Device for Real-Time 3D Streaming

In recent years, 3D movies and streaming films have become increasingly popular. Even mobile devices, such as mobile phones and tablet computers, are becoming more popular, more powerful and have better multimedia capabilities. Nevertheless, compact mobile devices to broadcast live 3D videos in real time are barely available. In this article, we provide a modular and mobile solution that allows 3D video streaming in real time at 25 frames per second and with a resolution of 1280 × 720 pixels (720p). As operating system, we use standard hardware components combined with Android. Furthermore, we will describe the restraints of the development, and how they were solved.In den letzten Jahren sind 3D-Filme und das Streamen von Filmen immer populärer geworden. Auch mobile Endgeräte, wie Smartphones oder Tablet Computer, nehmen an Verbreitung zu, werden leistungsstärker und verfügen über verbesserte Multimediafähigkeiten. Trotzdem gibt es kaum kompakte mobile Geräte, um live 3D-Videos in Echtzeit zu übertragen. In diesem Artikel stellen wir eine modulare und mobile Lösung vor, die es ermöglicht, 3D-Videos in Echtzeit, bei 25 Bildern pro Sekunde und mit einer Auflösung von 1280 × 720 Pixeln (720p) zu senden. Dabei verwenden wir Standard-Hardware-Komponenten und nutzen Android als Betriebssystem. Des Weiteren beschreiben wir, welche Schwierigkeiten bei der Entwicklung auftraten und wie diese gelöst wurden

Beyond IQ: A latent state-trait analysis of general intelligence, dynamic decision making, and implicit learning

The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed two standard intelligence tests, two dynamic decision making tasks, and two implicit learning tasks at two measurement occasions each. We used structural equation models to test latent state-trait measurement models and the relation between constructs. The results suggest that dynamic decision making and implicit learning are substantially related with general intelligence. Furthermore, general intelligence is the best predictor for income, social status, and educational attainment. Dynamic decision making can predict supervisor ratings even beyond general intelligence

Development and Validation of Targeted Next-Generation Sequencing Panels for Detection of Germline Variants in Inherited Diseases.

Context.-The number of targeted next-generation sequencing (NGS) panels for genetic diseases offered by clinical laboratories is rapidly increasing. Before an NGS-based test is implemented in a clinical laboratory, appropriate validation studies are needed to determine the performance characteristics of the test. Objective.-To provide examples of assay design and validation of targeted NGS gene panels for the detection of germline variants associated with inherited disorders. Data Sources.-The approaches used by 2 clinical laboratories for the development and validation of targeted NGS gene panels are described. Important design and validation considerations are examined. Conclusions.-Clinical laboratories must validate performance specifications of each test prior to implementation. Test design specifications and validation data are provided, outlining important steps in validation of targeted NGS panels by clinical diagnostic laboratories

TUNER-compliant error estimation for MIPAS: methodology

This paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties of the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile as well as persistent gain calibration uncertainties, offset calibration and spectral calibration uncertainties and their impact through propagated calibration-related temperature and pointing uncertainties are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used inthe retrieval, also related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty of the final data product via multiple pathways, i.e., on the one hand directly, and on the other hand via errors caused in a preceding retrieval step. These errors tend to partly compensate each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered as the major limitations of the MIPAS error estimation

TUNER-compliant error estimation for MIPAS

This paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties of the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile as well as persistent gain calibration uncertainties, offset calibration and spectral calibration uncertainties and their impact through propagated calibration-related temperature and pointing uncertainties are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used inthe retrieval, also related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty of the final data product via multiple pathways, i.e., on the one hand directly, and on the other hand via errors caused in a preceding retrieval step. These errors tend to partly compensate each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered as the major limitations of the MIPAS error estimation

MIPAS IMK/IAA Carbon Tetrachloride (CCl4) Retrieval and First Comparison With Other Instruments

MIPAS thermal limb emission measurements were used to derive vertically resolved profiles of carbon tetrachloride (CCl4). Level-1b data versions MIPAS/5.02 to MIPAS/5.06 were converted into volume mixing ratio profiles using the level-2 processor developed at Karlsruhe Institute of Technology (KIT) Institute of Meteorology and Climate Research (IMK) and Consejo Superior de Investigaciones Cientificas (CSIC), Instituto de Astrofisica de Andalucia (IAA). Consideration of peroxyacetyl nitrate (PAN) as an interfering species, which is jointly retrieved, and CO2 line mixing is crucial for reliable retrievals. Parts of the CO2 Q-branch region that overlap with the CCl4 signature were omitted, since large residuals were still found even though line mixing was considered in the forward model. However, the omitted spectral region could be narrowed noticeably when line mixing was accounted for. A new CCl4 spectro-scopic data set leads to slightly smaller CCl4 volume mixing ratios. In general, latitude-altitude cross sections show the expected CCl4 features with highest values of around 90 pptv at altitudes at and below the tropical tropopause and values decreasing with altitude and latitude due to stratospheric decomposition. Other patterns, such as subsidence in the polar vortex during winter and early spring, are also visible in the distributions. The decline in CCl4 abundance during the MI-PAS Envisat measurement period (July 2002 to April 2012) is clearly reflected in the altitude-latitude cross section of trends estimated from the entire retrieved data set