@article{AbdallaAdamAharonianetal.2020,
  author    = {Abdalla, H. and Adam, R. and Aharonian, Felix A. and Benkhali, F. Ait and Ang{\"u}ner, Ekrem Oǧuzhan and Arcaro, C. and Armand, C. and Armstrong, T. and Ashkar, H. and Backes, M. and Baghmanyan, V. and Martins, V. Barbosa and Barnacka, A. and Barnard, M. and Becherini, Y. and Berge, D. and Bernlohr, K. and Bi, B. and Bottcher, M. and Boisson, C. and Bolmont, J. and de Lavergne, M. de Bony and Bordas, Pol and Breuhaus, M. and Brun, F. and Brun, P. and Bryan, M. and Buchele, M. and Bulik, T. and Bylund, T. and Caroff, S. and Carosi, A. and Casanova, Sabrina and Chand, T. and Chandra, S. and Chen, A. and Cotter, G. and Curylo, M. and Mbarubucyeye, J. Damascene and Davids, I. D. and Davies, J. and Deil, C. and Devin, J. and deWilt, P. and Dirson, L. and Djannati-Atai, A. and Dmytriiev, A. and Donath, A. and Doroshenko, V. and Duffy, C. and Dyks, J. and Egberts, Kathrin and Eichhorn, F. and Einecke, S. and Emery, G. and Ernenwein, J. -P. and Feijen, K. and Fegan, S. and Fiasson, A. and de Clairfontaine, G. Fichet and Fontaine, G. and Funk, S. and Fussling, Matthias and Gabici, S. and Gallant, Y. A. and Giavitto, G. and Giunti, L. and Glawion, D. and Glicenstein, J. F. and Gottschall, D. and Grondin, M. -H. and Hahn, J. and Haupt, M. and Hermann, G. and Hinton, J. A. and Hofmann, W. and Hoischen, Clemens and Holch, T. L. and Holler, M. and Horbe, M. and Horns, D. and Huber, D. and Jamrozy, M. and Jankowsky, D. and Jankowsky, F. and Jardin-Blicq, A. and Joshi, V. and Jung-Richardt, I. and Kasai, E. and Kastendieck, M. A. and Katarzynski, K. and Katz, U. and Khangulyan, D. and Khelifi, B. and Klepser, S. and Kluzniak, W. and Komin, Nu. and Konno, R. and Kosack, K. and Kostunin, D. and Kreter, M. and Lamanna, G. and Lemiere, A. and Lemoine-Goumard, M. and Lenain, J. -P. and Levy, C. and Lohse, T. and Lypova, I. and Mackey, J. and Majumdar, J. and Malyshev, D. and Malyshev, D. and Marandon, V. and Marchegiani, P. and Marcowith, Alexandre and Mares, A. and Marti-Devesa, G. and Marx, R. and Maurin, G. and Meintjes, P. J. and Meyer, M. and Mitchell, A. and Moderski, R. and Mohamed, M. and Mohrmann, L. and Montanari, A. and Moore, C. and Morris, P. and Moulin, Emmanuel and Muller, J. and Murach, T. and Nakashima, K. and Nayerhoda, A. and de Naurois, M. and Ndiyavala, H. and Niederwanger, F. and Niemiec, J. and Oakes, L. and O'Brien, Patrick and Odaka, H. and Ohm, S. and Olivera-Nieto, L. and Wilhelmi, E. de Ona and Ostrowski, M. and Oya, I. and Panter, M. and Panny, S. and Parsons, R. D. and Peron, G. and Peyaud, B. and Piel, Q. and Pita, S. and Poireau, V. and Noel, A. Priyana and Prokhorov, D. A. and Prokoph, H. and Puhlhofer, G. and Punch, M. and Quirrenbach, A. and Raab, S. and Rauth, R. and Reichherzer, P. and Reimer, A. and Reimer, O. and Remy, Q. and Renaud, M. and Rieger, F. and Rinchiuso, L. and Romoli, C. and Rowell, G. and Rudak, B. and Ruiz-Velasco, E. and Sahakian, V. and Sailer, S. and Sanchez, D. A. and Santangelo, Andrea and Sasaki, M. and Scalici, M. and Schussler, F. and Schutte, H. M. and Schwanke, U. and Schwemmer, S. and Seglar-Arroyo, M. and Senniappan, M. and Seyffert, A. S. and Shafi, N. and Shiningayamwe, K. and Simoni, R. and Sinha, A. and Sol, H. and Specovius, A. and Spencer, S. and Spir-Jacob, M. and Stawarz, L. and Sun, L. and Steenkamp, R. and Stegmann, C. and Steinmassl, S. and Steppa, C. and Takahashi, T. and Tavernier, T. and Taylor, A. M. and Terrier, R. and Tiziani, D. and Tluczykont, M. and Tomankova, L. and Trichard, C. and Tsirou, M. and Tuffs, R. and Uchiyama, Y. and van der Walt, D. J. and van Eldik, C. and van Rensburg, C. and van Soelen, B. and Vasileiadis, G. and Veh, J. and Venter, C. and Vincent, P. and Vink, J. and Volk, H. J. and Vuillaume, T. and Wadiasingh, Z. and Wagner, S. J. and Watson, J. and Werner, F. and White, R. and Wierzcholska, A. and Wong, Yu Wun and Yusafzai, A. and Zacharias, M. and Zanin, R. and Zargaryan, D. and Zdziarski, A. A. and Zech, Alraune and Zhu, S. J. and Ziegler, A. and Zorn, J. and Zouari, S. and Zywucka, N.},
  title     = {An extreme particle accelerator in the Galactic plane},
  series = {Astronomy and astrophysics : an international weekly journal},
  volume    = {644},
  journal   = {Astronomy and astrophysics : an international weekly journal},
  publisher = {EDP Sciences},
  address   = {Les Ulis},
  organization    = {HESS Collaboration},
  issn      = {0004-6361},
  doi       = {10.1051/0004-6361/202038851},
  pages     = {8},
  year      = {2020},
  abstract  = {The unidentified very-high-energy (VHE; E > 0.1 TeV) gamma -ray source, HESS J1826-130, was discovered with the High Energy Stereoscopic System (HESS) in the Galactic plane. The analysis of 215 h of HESS data has revealed a steady gamma -ray flux from HESS J1826-130, which appears extended with a half-width of 0.21 degrees +/- 0.02 <br /> (stat)degrees <br /> stat degrees +/- 0.05 <br /> (sys)degrees sys degrees . The source spectrum is best fit with either a power-law function with a spectral index Gamma = 1.78 +/- 0.10(stat) +/- 0.20(sys) and an exponential cut-off at 15.2 <br /> (+5.5)(-3.2) -3.2+5.5 TeV, or a broken power-law with Gamma (1) = 1.96 +/- 0.06(stat) +/- 0.20(sys), Gamma (2) = 3.59 +/- 0.69(stat) +/- 0.20(sys) for energies below and above E-br = 11.2 +/- 2.7 TeV, respectively. The VHE flux from HESS J1826-130 is contaminated by the extended emission of the bright, nearby pulsar wind nebula, HESS J1825-137, particularly at the low end of the energy spectrum. Leptonic scenarios for the origin of HESS J1826-130 VHE emission related to PSR J1826-1256 are confronted by our spectral and morphological analysis. In a hadronic framework, taking into account the properties of dense gas regions surrounding HESS J1826-130, the source spectrum would imply an astrophysical object capable of accelerating the parent particle population up to greater than or similar to 200 TeV. Our results are also discussed in a multiwavelength context, accounting for both the presence of nearby supernova remnants, molecular clouds, and counterparts detected in radio, X-rays, and TeV energies.},
  language  = {en}
}
@article{AbdallaAdamAharonianetal.2020,
  author    = {Abdalla, Hassan E. and Adam, Remi and Aharonian, Felix A. and Benkhali, Faical Ait and Ang{\"u}ner, Ekrem Oǧuzhan and Arakawa, Masanori and Arcaro, C and Armand, Catherine and Armstrong, T. and Egberts, Kathrin},
  title     = {Very high energy γ-ray emission from two blazars of unknown redshift and upper limits on their distance},
  series = {Monthly Notices of the Royal Astronomical Society},
  volume    = {494},
  journal   = {Monthly Notices of the Royal Astronomical Society},
  number    = {4},
  publisher = {Wiley-Blackwell},
  address   = {Oxford},
  pages     = {13},
  year      = {2020},
  abstract  = {We report on the detection of very high energy (VHE; E > 100 GeV) gamma-ray emission from the BL Lac objects KUV 00311-1938 and PKS 1440-389 with the High Energy Stereoscopic System (H.E.S.S.). H.E.S.S. observations were accompanied or preceded by multiwavelength observations with Fermi/LAT, XRT and UVOT onboard the Swift satellite, and ATOM. Based on an extrapolation of the Fermi/LAT spectrum towards the VHE gamma-ray regime, we deduce a 95 per cent confidence level upper limit on the unknown redshift of KUV 00311-1938 of z < 0.98 and of PKS 1440-389 of z < 0.53. When combined with previous spectroscopy results, the redshift of KUV 00311-1938 is constrained to 0.51 <= z < 0.98 and of PKS 1440-389 to 0.14 (sic) z < 0.53.},
  language  = {en}
}
@article{AbdirashidLenhard2020,
  author    = {Abdirashid, Hashim and Lenhard, Michael},
  title     = {Say it with double flowers},
  series = {Journal of experimental botany},
  volume    = {71},
  journal   = {Journal of experimental botany},
  number    = {9},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0022-0957},
  doi       = {10.1093/jxb/eraa109},
  pages     = {2469 -- 2471},
  year      = {2020},
  abstract  = {Every year, lovers world-wide rely on mutants to show their feelings on Valentine's Day. This is because many of the most popular ornamental flowering plants have been selected to form extra petals at the expense of reproductive organs to enhance their attractiveness and aesthetic value to humans. This so-called 'double flower' (DF) phenotype, first described more than 2000 years ago (Meyerowitz et al., 1989) is present, for example, in many modern roses, carnations, peonies, and camellias. Gattolin et al. (2020) now identify a unifying explanation for the molecular basis of many of these DF cultivars.},
  language  = {en}
}
@article{Abromeit2020,
  author    = {Abromeit, Wolfgang},
  title     = {Digitalisierung des Gemeinwesens},
  series = {KWI Schriften},
  journal   = {KWI Schriften},
  number    = {12},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-486-9},
  issn      = {1867-951X},
  doi       = {10.25932/publishup-48518},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-485181},
  pages     = {15 -- 27},
  year      = {2020},
  language  = {de}
}
@article{AdamElsner2020,
  author    = {Adam, Maurits and Elsner, Birgit},
  title     = {The impact of salient action effects on 6-, 7-, and 11-month-olds' goal-predictive gaze shifts for a human grasping action},
  series = {PLOS ONE},
  volume    = {15},
  journal   = {PLOS ONE},
  number    = {10},
  publisher = {Public Library of Science},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0240165},
  pages     = {18},
  year      = {2020},
  abstract  = {When infants observe a human grasping action, experience-based accounts predict that all infants familiar with grasping actions should be able to predict the goal regardless of additional agency cues such as an action effect. Cue-based accounts, however, suggest that infants use agency cues to identify and predict action goals when the action or the agent is not familiar. From these accounts, we hypothesized that younger infants would need additional agency cues such as a salient action effect to predict the goal of a human grasping action, whereas older infants should be able to predict the goal regardless of agency cues. In three experiments, we presented 6-, 7-, and 11-month-olds with videos of a manual grasping action presented either with or without an additional salient action effect (Exp. 1 and 2), or we presented 7-month-olds with videos of a mechanical claw performing a grasping action presented with a salient action effect (Exp. 3). The 6-month-olds showed tracking gaze behavior, and the 11-month-olds showed predictive gaze behavior, regardless of the action effect. However, the 7-month-olds showed predictive gaze behavior in the action-effect condition, but tracking gaze behavior in the no-action-effect condition and in the action-effect condition with a mechanical claw. The results therefore support the idea that salient action effects are especially important for infants' goal predictions from 7 months on, and that this facilitating influence of action effects is selective for the observation of human hands.},
  language  = {en}
}
@article{Adelmann2020,
  author    = {Adelmann, Dieter},
  title     = {Der Begriff „Zeugung / Erzeugung" bei H. Steinthal dargestellt im Hinblick auf die Logik der reinen Erkenntnis von Hermann Cohen},
  volume    = {2020},
  number    = {4},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-487-6},
  doi       = {10.25932/publishup-47729},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-477299},
  pages     = {19 -- 114},
  year      = {2020},
  language  = {de}
}
@article{AdnanMatthewsHackletal.2020,
  author    = {Adnan, Hassan Sami and Matthews, Sam and Hackl, M. and Das, P. P. and Manaswini, Manisha and Gadamsetti, S. and Filali, Maroua and Owoyele, Babajide and Santuber, Joaqu{\´i}n and Edelman, Jonathan},
  title     = {Human centered AI design for clinical monitoring and data management},
  series = {European journal of public health : official journal of the European Health Association},
  volume    = {30},
  journal   = {European journal of public health : official journal of the European Health Association},
  number    = {5},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {1101-1262},
  doi       = {10.1093/eurpub/ckaa165.225},
  pages     = {V86 -- V86},
  year      = {2020},
  abstract  = {In clinical settings, significant resources are spent on data collection and monitoring patients' health parameters to improve decision-making and provide better care. With increased digitization, the healthcare sector is shifting towards implementing digital technologies for data management and in administration. New technologies offer better treatment opportunities and streamline clinical workflow, but the complexity can cause ineffectiveness, frustration, and errors. To address this, we believe digital solutions alone are not sufficient. Therefore, we take a human-centred design approach for AI development, and apply systems engineering methods to identify system leverage points. We demonstrate how automation enables monitoring clinical parameters, using existing non-intrusive sensor technology, resulting in more resources toward patient care. Furthermore, we provide a framework on digitization of clinical data for integration with data management.},
  language  = {en}
}
@article{AdnanSrsicVenticichetal.2020,
  author    = {Adnan, Hassan Sami and Srsic, Amanda and Venticich, Pete Milos and Townend, David M.R.},
  title     = {Using AI for mental health analysis and prediction in school surveys},
  series = {European journal of public health},
  volume    = {30},
  journal   = {European journal of public health},
  publisher = {Oxford Univ. Press},
  address   = {Oxford [u.a.]},
  issn      = {1101-1262},
  doi       = {10.1093/eurpub/ckaa165.336},
  pages     = {V125 -- V125},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@article{AgaBarfknechtHallahanGottmannetal.2020,
  author    = {Aga-Barfknecht, Heja and Hallahan, Nicole and Gottmann, Pascal and J{\"a}hnert, Markus and Osburg, Sophie and Schulze, Gunnar and Kamitz, Anne and Arends, Danny and Brockmann, Gudrun and Schallschmidt, Tanja and Lebek, Sandra and Chadt, Alexandra and Al-Hasani, Hadi and Joost, Hans-Georg and Sch{\"u}rmann, Annette and Vogel, Heike},
  title     = {Identification of novel potential type 2 diabetes genes mediating beta-cell loss and hyperglycemia using positional cloning},
  series = {Frontiers in genetics},
  volume    = {11},
  journal   = {Frontiers in genetics},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {1664-8021},
  doi       = {10.3389/fgene.2020.567191},
  pages     = {11},
  year      = {2020},
  abstract  = {Type 2 diabetes (T2D) is a complex metabolic disease regulated by an interaction of genetic predisposition and environmental factors. To understand the genetic contribution in the development of diabetes, mice varying in their disease susceptibility were crossed with the obese and diabetes-prone New Zealand obese (NZO) mouse. Subsequent whole-genome sequence scans revealed one major quantitative trait loci (QTL),Nidd/DBAon chromosome 4, linked to elevated blood glucose and reduced plasma insulin and low levels of pancreatic insulin. Phenotypical characterization of congenic mice carrying 13.6 Mbp of the critical fragment of DBA mice displayed severe hyperglycemia and impaired glucose clearance at week 10, decreased glucose response in week 13, and loss of beta-cells and pancreatic insulin in week 16. To identify the responsible gene variant(s), further congenic mice were generated and phenotyped, which resulted in a fragment of 3.3 Mbp that was sufficient to induce hyperglycemia. By combining transcriptome analysis and haplotype mapping, the number of putative responsible variant(s) was narrowed from initial 284 to 18 genes, including gene models and non-coding RNAs. Consideration of haplotype blocks reduced the number of candidate genes to four (Kti12,Osbpl9,Ttc39a, andCalr4) as potential T2D candidates as they display a differential expression in pancreatic islets and/or sequence variation. In conclusion, the integration of comparative analysis of multiple inbred populations such as haplotype mapping, transcriptomics, and sequence data substantially improved the mapping resolution of the diabetes QTLNidd/DBA. Future studies are necessary to understand the exact role of the different candidates in beta-cell function and their contribution in maintaining glycemic control.},
  language  = {en}
}
@article{AgarwalMarwanMaheswaranetal.2020,
  author    = {Agarwal, Ankit and Marwan, Norbert and Maheswaran, Rathinasamy and {\"O}zt{\"u}rk, Ugur and Kurths, J{\"u}rgen and Merz, Bruno},
  title     = {Optimal design of hydrometric station networks based on complex network analysis},
  series = {Hydrology and Earth System Sciences},
  volume    = {24},
  journal   = {Hydrology and Earth System Sciences},
  number    = {5},
  publisher = {Copernicus Publ.},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-24-2235-2020},
  pages     = {2235 -- 2251},
  year      = {2020},
  abstract  = {Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure - the weighted degree-betweenness (WDB) measure - to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.},
  language  = {en}
}