Refine
Year of publication
- 2020 (1711) (remove)
Document Type
- Article (1711) (remove)
Keywords
- random point processes (18)
- statistical mechanics (18)
- stochastic analysis (18)
- climate change (17)
- machine learning (10)
- Germany (9)
- dynamics (9)
- model (9)
- Franconia (8)
- Franken (8)
Institute
- Institut für Physik und Astronomie (177)
- Institut für Biochemie und Biologie (156)
- Institut für Geowissenschaften (140)
- Institut für Chemie (107)
- Historisches Institut (83)
- Institut für Mathematik (75)
- Department Psychologie (73)
- Institut für Umweltwissenschaften und Geographie (63)
- Department Sport- und Gesundheitswissenschaften (59)
- Department Linguistik (58)
Der Beitrag setzt sich würdigend und kritisch mit Michael Zürns Arbeiten zur internationalen Autorität auseinander. Dessen potenziell autoritatives Autoritätskonzept weist mehrere Vorzüge auf: Erstens bietet es eine Erklärung für ein Paradox. Warum sollten souveräne Staaten die Kompetenz Externer anerkennen, ihnen Ratschläge zu geben bzw. Forderungen an sie zu richten, und zudem noch bereit sein, diesen zu folgen? Zweitens konkretisiert es die u.a. bei Hannah Arendt angelegte Idee der fraglosen Anerkennung, indem es Autoritätsadressaten zugesteht, bestimmte Qualitäten der Autorität zu prüfen. Drittens entkoppelt es Legitimität und Autorität, ohne die Legitimationsbedürftigkeit von Autorität zu opfern. Dies anerkennend plädiert der Beitrag aber dafür, die Legitimationsbedürftigkeit internationaler Autorität nicht auf formal institutionalisierte Beziehungen zu reduzieren, sondern diese auch weiterhin auf informellere, d.h. der Praxis entstammende, Anerkennung und Folgebereitschaft innerhalb von Autoritätsbeziehungen zu beziehen. Die überzeugende begründungstheoretische Fundierung von Autorität sollte zudem nicht dazu verführen, Sozialisationsprozesse in Autoritätsbeziehungen zu übersehen, zumal deren Legitimität kritisch hinterfragbar ist.
How do people decide which risks they want to get informed about? The present study examines the role of the availability and affect heuristics on these decisions. Participants (N= 100, aged 19-72 years) selected for which of 23 cancers they would like to receive an information brochure, reported the number of occurrences of each type of cancer in their social circle (availability), and rated their dread reaction to each type of cancer (affect); they also made relative judgments about which of 2 cancers was more common in Germany (judged risk). Participants tended to choose information brochures for those cancers for which they indicated a higher availability within their social networks as well as for cancers they dreaded. Mediation analyses suggested that the influence of availability and affect on information choice was only partly mediated by judged risk. The results demonstrate the operation of 2 key judgment heuristics (availability and affect), previously studied in risk perception, also in decisions about information choice. We discuss how our findings can be used to identify which risks are likely to fall from people's radar.
Electroencephalographic (EEG) research indicates changes in adults' low frequency bands of frontoparietal brain areas executing different balance tasks with increasing postural demands. However, this issue is unsolved for adolescents when performing the same balance task with increasing difficulty. Therefore, we examined the effects of a progressively increasing balance task difficulty on balance performance and brain activity in adolescents. Thirteen healthy adolescents aged 16-17 year performed tests in bipedal upright stance on a balance board with six progressively increasing levels of task difficulty. Postural sway and cortical activity were recorded simultaneously using a pressure sensitive measuring system and EEG. The power spectrum was analyzed for theta (4-7 Hz) and alpha-2 (10-12 Hz) frequency bands in pre-defined frontal, central, and parietal clusters of electrocortical sources. Repeated measures analysis of variance (rmANOVA) showed a significant main effect of task difficulty for postural sway (p < 0.001; d = 6.36). Concomitantly, the power spectrum changed in frontal, bilateral central, and bilateral parietal clusters. RmANOVAs revealed significant main effects of task difficulty for theta band power in the frontal (p < 0.001, d = 1.80) and both central clusters (left: p < 0.001, d = 1.49; right: p < 0.001, d = 1.42) as well as for alpha-2 band power in both parietal clusters (left: p < 0.001, d = 1.39; right: p < 0.001, d = 1.05) and in the central right cluster (p = 0.005, d = 0.92). Increases in theta band power (frontal, central) and decreases in alpha-2 power (central, parietal) with increasing balance task difficulty may reflect increased attentional processes and/or error monitoring as well as increased sensory information processing due to increasing postural demands. In general, our findings are mostly in agreement with studies conducted in adults. Similar to adult studies, our data with adolescents indicated the involvement of frontoparietal brain areas in the regulation of postural control. In addition, we detected that activity of selected brain areas (e.g., bilateral central) changed with increasing postural demands.
Die konservative Revolution in Polen hat ihre Thinktanks, Intellektuellen und ihre Literatur. Jarosław Marek Rymkiewicz genießt in rechten Kreisen den Status eines Nationaldichters. Bereits in den frühen 1990ern schloss sich Rymkiewicz den radikalen Kritikern der polnischen Transformation an. Er gehört zu den prominenten Unterstützern der PiS. Sein literarisch fesselndes und politisch brisantes Spätwerk übt großen Einfluss auf die Radikalkonservativen in Polen aus.
Barite scales in geothermal installations are a highly unwanted effect of circulating deep saline fluids. They build up in the reservoir if supersaturated fluids are re-injected, leading to irreversible loss of injectivity. A model is presented for calculating the total expected barite precipitation. To determine the related injectivity decline over time, the spatial precipitation distribution in the subsurface near the injection well is assessed by modelling barite growth kinetics in a radially diverging Darcy flow domain. Flow and reservoir properties as well as fluid chemistry are chosen to represent reservoirs subject to geothermal exploration located in the North German Basin (NGB) and the Upper Rhine Graben (URG) in Germany. Fluids encountered at similar depths are hotter in the URG, while they are more saline in the NGB. The associated scaling amount normalised to flow rate is similar for both regions. The predicted injectivity decline after 10 years, on the other hand, is far greater for the NGB (64%) compared to the URG (24%), due to the temperature- and salinity-dependent precipitation rate. The systems in the NGB are at higher risk. Finally, a lightweight score is developed for approximating the injectivity loss using the Damkohler number, flow rate and total barite scaling potential. This formula can be easily applied to geothermal installations without running complex reactive transport simulations.
Organic solar cells are currently experiencing a second golden age thanks to the development of novel non-fullerene acceptors (NFAs). Surprisingly, some of these blends exhibit high efficiencies despite a low energy offset at the heterojunction. Herein, free charge generation in the high-performance blend of the donor polymer PM6 with the NFA Y6 is thoroughly investigated as a function of internal field, temperature and excitation energy. Results show that photocurrent generation is essentially barrierless with near-unity efficiency, regardless of excitation energy. Efficient charge separation is maintained over a wide temperature range, down to 100 K, despite the small driving force for charge generation. Studies on a blend with a low concentration of the NFA, measurements of the energetic disorder, and theoretical modeling suggest that CT state dissociation is assisted by the electrostatic interfacial field which for Y6 is large enough to compensate the Coulomb dissociation barrier.
Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy
(2020)
An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model-based predictions of therapy outcomes. Current Bayesian forecasting tools typically rely only on the most probable model parameters (maximum a posteriori (MAP) estimate). This MAP-based approach, however, does neither necessarily predict the most probable outcome nor does it quantify the risks of treatment inefficacy or toxicity. Bayesian data assimilation (DA) methods overcome these limitations by providing a comprehensive uncertainty quantification. We compare DA methods with MAP-based approaches and show how probabilistic statements about key markers related to chemotherapy-induced neutropenia can be leveraged for more informative decision support in individualized chemotherapy. Sequential Bayesian DA proved to be most computationally efficient for handling interoccasion variability and integrating TDM data. For new digital monitoring devices enabling more frequent data collection, these features will be of critical importance to improve patient care decisions in various therapeutic areas.
Bayesian geomorphology
(2020)
The rapidly growing amount and diversity of data are confronting us more than ever with the need to make informed predictions under uncertainty. The adverse impacts of climate change and natural hazards also motivate our search for reliable predictions. The range of statistical techniques that geomorphologists use to tackle this challenge has been growing, but rarely involves Bayesian methods. Instead, many geomorphic models rely on estimated averages that largely miss out on the variability of form and process. Yet seemingly fixed estimates of channel heads, sediment rating curves or glacier equilibrium lines, for example, are all prone to uncertainties. Neighbouring scientific disciplines such as physics, hydrology or ecology have readily embraced Bayesian methods to fully capture and better explain such uncertainties, as the necessary computational tools have advanced greatly. The aim of this article is to introduce the Bayesian toolkit to scientists concerned with Earth surface processes and landforms, and to show how geomorphic models might benefit from probabilistic concepts. I briefly review the use of Bayesian reasoning in geomorphology, and outline the corresponding variants of regression and classification in several worked examples.