@misc{RepkeKrestelEddingetal.2018,
  author    = {Repke, Tim and Krestel, Ralf and Edding, Jakob and Hartmann, Moritz and Hering, Jonas and Kipping, Dennis and Schmidt, Hendrik and Scordialo, Nico and Zenner, Alexander},
  title     = {Beacon in the Dark},
  series = {Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
  journal   = {Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  isbn      = {978-1-4503-6014-2},
  doi       = {10.1145/3269206.3269231},
  pages     = {1871 -- 1874},
  year      = {2018},
  abstract  = {The large amount of heterogeneous data in these email corpora renders experts' investigations by hand infeasible. Auditors or journalists, e.g., who are looking for irregular or inappropriate content or suspicious patterns, are in desperate need for computer-aided exploration tools to support their investigations. We present our Beacon system for the exploration of such corpora at different levels of detail. A distributed processing pipeline combines text mining methods and social network analysis to augment the already semi-structured nature of emails. The user interface ties into the resulting cleaned and enriched dataset. For the interface design we identify three objectives expert users have: gain an initial overview of the data to identify leads to investigate, understand the context of the information at hand, and have meaningful filters to iteratively focus onto a subset of emails. To this end we make use of interactive visualisations based on rearranged and aggregated extracted information to reveal salient patterns.},
  language  = {en}
}
@misc{WippertPuschmannDriessleinetal.2017,
  author    = {Wippert, Pia-Maria and Puschmann, Anne-Katrin and Drießlein, David and Arampatzis, Adamantios and Banzer, Winfried and Beck, Heidrun and Schiltenwolf, Marcus and Schmidt, Hendrik and Schneider, Christian and Mayer, Frank},
  title     = {Development of a risk stratification and prevention index for stratified care in chronic low back pain. Focus: yellow flags (MiSpEx network)},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-403424},
  pages     = {11},
  year      = {2017},
  abstract  = {Introduction: Chronic low back pain (LBP) is a major cause of disability; early diagnosis and stratification of care remain challenges. Objectives: This article describes the development of a screening tool for the 1-year prognosis of patients with high chronic LBP risk (risk stratification index) and for treatment allocation according to treatment-modifiable yellow flag indicators (risk prevention indices, RPI-S). Methods: Screening tools were derived from a multicentre longitudinal study (n = 1071, age >18, intermittent LBP). The greatest prognostic predictors of 4 flag domains ("pain," "distress," "social-environment," "medical care-environment") were determined using least absolute shrinkage and selection operator regression analysis. Internal validity and prognosis error were evaluated after 1-year follow-up. Receiver operating characteristic curves for discrimination (area under the curve) and cutoff values were determined. Results: The risk stratification index identified persons with increased risk of chronic LBP and accurately estimated expected pain intensity and disability on the Pain Grade Questionnaire (0-100 points) up to 1 year later with an average prognosis error of 15 points. In addition, 3-risk classes were discerned with an accuracy of area under the curve = 0.74 (95\% confidence interval 0.63-0.85). The RPI-S also distinguished persons with potentially modifiable prognostic indicators from 4 flag domains and stratified allocation to biopsychosocial treatments accordingly. Conclusion: The screening tools, developed in compliance with the PROGRESS and TRIPOD statements, revealed good validation and prognostic strength. These tools improve on existing screening tools because of their utility for secondary preventions, incorporation of exercise effect modifiers, exact pain estimations, and personalized allocation to multimodal treatments.},
  language  = {en}
}
@article{MeierKriegelMotschmannetal.2014,
  author    = {Meier, Patrick and Kriegel, Hendrik and Motschmann, Uwe and Schmidt, J{\"u}rgen and Spahn, Frank and Hill, Thomas W. and Dong, Yaxue and Jones, Geraint H.},
  title     = {A model of the spatial and size distribution of Enceladus' dust plume},
  series = {Planetary and space science},
  volume    = {104},
  journal   = {Planetary and space science},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0032-0633},
  doi       = {10.1016/j.pss.2014.09.016},
  pages     = {216 -- 233},
  year      = {2014},
  language  = {en}
}
@article{MeierMotschmannSchmidtetal.2015,
  author    = {Meier, Patrick and Motschmann, Uwe and Schmidt, Jurgen and Spahn, Frank and Hill, Thomas W. and Dong, Yaxue and Jones, Geraint H. and Kriegel, Hendrik},
  title     = {Modeling the total dust production of Enceladus from stochastic charge equilibrium and simulations},
  series = {Planetary and space science},
  volume    = {119},
  journal   = {Planetary and space science},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0032-0633},
  doi       = {10.1016/j.pss.2015.10.002},
  pages     = {208 -- 221},
  year      = {2015},
  language  = {en}
}
@book{SchwarzerWeissSaoumiKitteletal.2023,
  author    = {Schwarzer, Ingo and Weiß-Saoumi, Said and Kittel, Roland and Friedrich, Tobias and Kaynak, Koraltan and Durak, Cemil and Isbarn, Andreas and Diestel, J{\"o}rg and Knittel, Jens and Franz, Marquart and Morra, Carlos and Stahnke, Susanne and Braband, Jens and Dittmann, Johannes and Griebel, Stephan and Krampf, Andreas and Link, Martin and M{\"u}ller, Matthias and Radestock, Jens and Strub, Leo and Bleeke, Kai and Jehl, Leander and Kapitza, R{\"u}diger and Messadi, Ines and Schmidt, Stefan and Schwarz-R{\"u}sch, Signe and Pirl, Lukas and Schmid, Robert and Friedenberger, Dirk and Beilharz, Jossekin Jakob and Boockmeyer, Arne and Polze, Andreas and R{\"o}hrig, Ralf and Sch{\"a}be, Hendrik and Thiermann, Ricky},
  title     = {RailChain},
  number    = {152},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-550-7},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-57740},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-577409},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {140},
  year      = {2023},
  abstract  = {The RailChain project designed, implemented, and experimentally evaluated a juridical recorder that is based on a distributed consensus protocol. That juridical blockchain recorder has been realized as distributed ledger on board the advanced TrainLab (ICE-TD 605 017) of Deutsche Bahn. For the project, a consortium consisting of DB Systel, Siemens, Siemens Mobility, the Hasso Plattner Institute for Digital Engineering, Technische Universit{\"a}t Braunschweig, T{\"U}V Rheinland InterTraffic, and Spherity has been formed. These partners not only concentrated competencies in railway operation, computer science, regulation, and approval, but also combined experiences from industry, research from academia, and enthusiasm from startups. Distributed ledger technologies (DLTs) define distributed databases and express a digital protocol for transactions between business partners without the need for a trusted intermediary. The implementation of a blockchain with real-time requirements for the local network of a railway system (e.g., interlocking or train) allows to log data in the distributed system verifiably in real-time. For this, railway-specific assumptions can be leveraged to make modifications to standard blockchains protocols. EULYNX and OCORA (Open CCS On-board Reference Architecture) are parts of a future European reference architecture for control command and signalling (CCS, Reference CCS Architecture - RCA). Both architectural concepts outline heterogeneous IT systems with components from multiple manufacturers. Such systems introduce novel challenges for the approved and safety-relevant CCS of railways which were considered neither for road-side nor for on-board systems so far. Logging implementations, such as the common juridical recorder on vehicles, can no longer be realized as a central component of a single manufacturer. All centralized approaches are in question. The research project RailChain is funded by the mFUND program and gives practical evidence that distributed consensus protocols are a proper means to immutably (for legal purposes) store state information of many system components from multiple manufacturers. The results of RailChain have been published, prototypically implemented, and experimentally evaluated in large-scale field tests on the advanced TrainLab. At the same time, the project showed how RailChain can be integrated into the road-side and on-board architecture given by OCORA and EULYNX. Logged data can now be analysed sooner and also their trustworthiness is being increased. This enables, e.g., auditable predictive maintenance, because it is ensured that data is authentic and unmodified at any point in time.},
  language  = {en}
}
@article{WippertPuschmannDriessleinetal.2017,
  author    = {Wippert, Pia-Maria and Puschmann, Anne-Katrin and Drießlein, David and Arampatzis, Adamantios and Banzer, Winfried and Beck, Heidrun and Schiltenwolf, Marcus and Schmidt, Hendrik and Schneider, Christian and Mayer, Frank},
  title     = {Development of a risk stratification and prevention index for stratified care in chronic low back pain. Focus: yellow flags (MiSpEx network)},
  series = {Pain reports},
  volume    = {9},
  journal   = {Pain reports},
  publisher = {Wolters Kluwer Health},
  address   = {Riverwoods, IL},
  doi       = {10.1097/PR9.0000000000000623},
  pages     = {1 -- 11},
  year      = {2017},
  abstract  = {Introduction: Chronic low back pain (LBP) is a major cause of disability; early diagnosis and stratification of care remain challenges. Objectives: This article describes the development of a screening tool for the 1-year prognosis of patients with high chronic LBP risk (risk stratification index) and for treatment allocation according to treatment-modifiable yellow flag indicators (risk prevention indices, RPI-S). Methods: Screening tools were derived from a multicentre longitudinal study (n = 1071, age >18, intermittent LBP). The greatest prognostic predictors of 4 flag domains ("pain," "distress," "social-environment," "medical care-environment") were determined using least absolute shrinkage and selection operator regression analysis. Internal validity and prognosis error were evaluated after 1-year follow-up. Receiver operating characteristic curves for discrimination (area under the curve) and cutoff values were determined. Results: The risk stratification index identified persons with increased risk of chronic LBP and accurately estimated expected pain intensity and disability on the Pain Grade Questionnaire (0-100 points) up to 1 year later with an average prognosis error of 15 points. In addition, 3-risk classes were discerned with an accuracy of area under the curve = 0.74 (95\% confidence interval 0.63-0.85). The RPI-S also distinguished persons with potentially modifiable prognostic indicators from 4 flag domains and stratified allocation to biopsychosocial treatments accordingly. Conclusion: The screening tools, developed in compliance with the PROGRESS and TRIPOD statements, revealed good validation and prognostic strength. These tools improve on existing screening tools because of their utility for secondary preventions, incorporation of exercise effect modifiers, exact pain estimations, and personalized allocation to multimodal treatments.},
  language  = {en}
}