Take it personally - A Python library for data enrichment for infometrical applications

Like every other social sphere, science is influenced by individual characteristics of researchers. However, for investigations on scientific networks, only little data about the social background of researchers, e.g. social origin, gender, affiliation etc., is available. This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata. The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientific knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientific publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities

ORCID for Wikidata. Data enrichment for scientometric applications

Due to its numerous bibliometric entries of scholarly articles and connected information Wikidata can serve as an open and rich source for deep scientometrical analyses. However, there are currently certain limitations: While 31.5% of all Wikidata entries represent scientific articles, only 8.9% are entries describing a person and the number of entries researcher is accordingly even lower. Another issue is the frequent absence of established relations between the scholarly article item and the author item although the author is already listed in Wikidata. To fill this gap and to improve the content of Wikidata in general, we established a workflow for matching authors and scholarly publications by integrating data from the ORCID (Open Researcher and Contributor ID) database. By this approach we were able to extend Wikidata by more than 12k author-publication relations and the method can be transferred to other enrichments based on ORCID data. This is extension is beneficial for Wikidata users performing bibliometrical analyses or using such metadata for other purposes

BAT (Berry Analysis Tool): A high-throughput image interpretation tool to acquire the number, diameter, and volume of grapevine berries

QTL-analysis (quantitative trait loci) and marker development rely on efficient phenotyping techniques. Objectivity and precision of a phenotypic data evaluation is crucial but time consuming. In the present study a high-throughput image interpretation tool was developed to acquire automatically number, size, and volume of grape berries from RGB (red-green-blue) images. Individual berries of one cluster were placed on a black construction (300 x 300 mm) to take a RGB image from the top. The image interpretation of one dataset with an arbitrary number of images runs automatically using the BAT (Berry-Analysis-Tool) developed in MATLAB. For validation of results, the number of berries was counted and their size was measured using a digital calliper. A measuring cylinder was used to determine reliably the berry volume by displacement of water. All placed berries could be counted by BAT 100 % correctly. Manual ratings compared with BAT ratings showed strong correlation of r = 0.96 for mean berry diameter/image and r = 0.98 for cluster volume.

Initial steps for high-throughput phenotyping in vineyards

The evaluation of phenotypic characters of grapevines is required directly in vineyards and is strongly limited by time, costs and the subjectivity of person in charge. Sensor-based techniques are prerequisite in order to allow non-invasive phenotyping of individual plant traits, to increase the quantity of object records and to reduce error variation. Thus, a Prototype-Image-Acquisition-System (PIAS) was developed for semi-automated capture of geo-referenced images in an experimental vineyard. Different strategies were tested for image interpretation using MATLAB®. The interpretation of images from the vineyard with real background is more practice-oriented but requires the calculation of depth maps. Different image analysis tools were verified in order to enable contactless and non-invasive detection of bud burst and quantification of shoots at an early developmental stage (BBCH 10) and enable fast and accurate determination of the grapevine berry size at BBCH 89. Depending on the time of image acquisition at BBCH 10 up to 94 % of green shoots were visible in images. The mean berry size (BBCH 89) was recorded non-invasively with a precision of 1 mm.

Electron g-Factor Anisotropy in Symmetric (110)-oriented GaAs Quantum Wells

We demonstrate by spin quantum beat spectroscopy that in undoped symmetric (110)-oriented GaAs/AlGaAs single quantum wells even a symmetric spatial envelope wavefunction gives rise to an asymmetric in-plane electron Land\'e-g-factor. The anisotropy is neither a direct consequence of the asymmetric in-plane Dresselhaus splitting nor of the asymmetric Zeeman splitting of the hole bands but is a pure higher order effect that exists as well for diamond type lattices. The measurements for various well widths are very well described within 14 x 14 band k.p theory and illustrate that the electron spin is an excellent meter variable to map out the internal -otherwise hidden- symmetries in two dimensional systems. Fourth order perturbation theory yields an analytical expression for the strength of the g-factor anisotropy, providing a qualitative understanding of the observed effects

The ICON-1.2 hydrostatic atmospheric dynamical core on triangular grids – Part 1: Formulation and performance of the baseline version

Abstract. As part of a broader effort to develop next-generation models for numerical weather prediction and climate applications, a hydrostatic atmospheric dynamical core is developed as an intermediate step to evaluate a finite-difference discretization of the primitive equations on spherical icosahedral grids. Based on the need for mass-conserving discretizations for multi-resolution modelling as well as scalability and efficiency on massively parallel computing architectures, the dynamical core is built on triangular C-grids using relatively small discretization stencils. This paper presents the formulation and performance of the baseline version of the new dynamical core, focusing on properties of the numerical solutions in the setting of globally uniform resolution. Theoretical analysis reveals that the discrete divergence operator defined on a single triangular cell using the Gauss theorem is only first-order accurate, and introduces grid-scale noise to the discrete model. The noise can be suppressed by fourth-order hyper-diffusion of the horizontal wind field using a time-step and grid-size-dependent diffusion coefficient, at the expense of stronger damping than in the reference spectral model. A series of idealized tests of different complexity are performed. In the deterministic baroclinic wave test, solutions from the new dynamical core show the expected sensitivity to horizontal resolution, and converge to the reference solution at R2B6 (35 km grid spacing). In a dry climate test, the dynamical core correctly reproduces key features of the meridional heat and momentum transport by baroclinic eddies. In the aqua-planet simulations at 140 km resolution, the new model is able to reproduce the same equatorial wave propagation characteristics as in the reference spectral model, including the sensitivity of such characteristics to the meridional sea surface temperature profile. These results suggest that the triangular-C discretization provides a reasonable basis for further development. The main issues that need to be addressed are the grid-scale noise from the divergence operator which requires strong damping, and a phase error of the baroclinic wave at medium and low resolutions

Surface velocity fields of active rock glaciers and ice-debris complexes in the Central Andes of Argentina

Rock glaciers and transitional ice-debris complexes predominate the Central Andean landform assemblage, yet regional studies on their state of activity and their kinematics remain sparse. Here we utilize the national glacier inventory of Argentina to quantify surface velocity fields of 244 rock glaciers and 51 ice-debris complexes, located in the Cordón del Plata range, Argentina. Applying a feature-tracking approach to repeated RapidEye satellite imagery acquired between 2010 and 2017/18, we find mean displacement rates between 0.37 and 2.61 m year−1 for 149 landforms, while for the remaining 146 features, surface movement remains below our level of detection. We compare our satellite-derived velocity fields with ground-truth data from two local field sites and find closely matching results in magnitude and spatial distribution. With average displacement of one-third of the active rock glaciers and ice-debris complexes exceeding 1 m year−1, the region hosts an exceptional number of fast-flowing periglacial landforms, compared to other mountain belts. Using a random forest model, we test the predictive power of 25 morphometric and topoclimatic candidate predictors for modelling the state of activity of rock glaciers and ice-debris complexes on two different scales. For entire landforms and individual landform segments, constructed along displacement centrelines, we can predict the state of activity with overall accuracies of 70.08% (mean AUROC = 0.785) and 74.86% (mean AUROC = 0.753), respectively. While topoclimatic parameters such as solar radiation and elevation are most important for entire landforms, geometric parameters become more important at the scale of landform segments. Despite tentative correlations between local slope and surface kinematics, our results point to factors integrating slope and distance to the source to govern local deformation. We conclude that feature tracking in optical imagery is feasible for regional studies in remote regions and provides valuable insight into the current state of the Andean cryosphere.Fil: Blöthe, Jan Henrik. Universitat Bonn; AlemaniaFil: Halla, Christian. Universitat Bonn; AlemaniaFil: Schwalbe, Ellen. Technische Universität Dresden; AlemaniaFil: Bottegal, Estefania Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Trombotto, Dario Tomas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Schrott, Lothar. Universitat Bonn; Alemani

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust

Tensor voting for robust color edge detection

The final publication is available at Springer via http://dx.doi.org/10.1007/978-94-007-7584-8_9This chapter proposes two robust color edge detection methods based on tensor voting. The first method is a direct adaptation of the classical tensor voting to color images where tensors are initialized with either the gradient or the local color structure tensor. The second method is based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to robust edge detection in color images. In this case, three tensors are used to encode local CIELAB color channels and edginess, while the voting process propagates both color and edginess by applying perception-based rules. Unlike the classical tensor voting, the second method considers the context in the voting process. Recall, discriminability, precision, false alarm rejection and robustness measurements with respect to three different ground-truths have been used to compare the proposed methods with the state-of-the-art. Experimental results show that the proposed methods are competitive, especially in robustness. Moreover, these experiments evidence the difficulty of proposing an edge detector with a perfect performance with respect to all features and fields of application.This research has been supported by the Swedish Research Council under the project VR 2012-3512