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The promise of algorithmic decision-making (ADM) lies in its capacity to support or replace human decision-making based on a superior ability to solve specific cognitive tasks. Applications have found their way into various domains of decision-making—and even find appeal in the realm of politics. Against the backdrop of widespread dissatisfaction with politicians in established democracies, there are even calls for replacing politicians with machines. Our discipline has hitherto remained surprisingly silent on these issues. The present article argues that it is important to have a clear grasp of when and how ADM is compatible with political decision-making. While algorithms may help decision-makers in the evidence-based selection of policy instruments to achieve pre-defined goals, bringing ADM to the heart of politics, where the guiding goals are set, is dangerous. Democratic politics, we argue, involves a kind of learning that is incompatible with the learning and optimization performed by algorithmic systems.
We propose a universal method for the evaluation of generalized standard materials that greatly simplifies the material law implementation process. By means of automatic differentiation and a numerical integration scheme, AutoMat reduces the implementation effort to two potential functions. By moving AutoMat to the GPU, we close the performance gap to conventional evaluation routines and demonstrate in detail that the expression level reverse mode of automatic differentiation as well as its extension to second order derivatives can be applied inside CUDA kernels. We underline the effectiveness and the applicability of AutoMat by integrating it into the FFT-based homogenization scheme of Moulinec and Suquet and discuss the benefits of using AutoMat with respect to runtime and solution accuracy for an elasto-viscoplastic example.
Heterocystous Cyanobacteria of the genus Nodularia form major blooms in brackish waters, while terrestrial Nostoc species occur worldwide, often associated in biological soil crusts. Both genera, by virtue of their ability to fix N2 and conduct oxygenic photosynthesis, contribute significantly to global primary productivity. Select Nostoc and Nodularia species produce the hepatotoxin nodularin and whether its production will change under climate change conditions needs to be assessed. In light of this, the effects of elevated atmospheric CO2 availability on growth, carbon and N2 fixation as well as nodularin production were investigated in toxin and non-toxin producing species of both genera. Results highlighted the following:
Biomass and volume specific biological nitrogen fixation (BNF) rates were respectively almost six and 17 fold higher in the aquatic Nodularia species compared to the terrestrial Nostoc species tested, under elevated CO2 conditions.
There was a direct correlation between elevated CO2 and decreased dry weight specific cellular nodularin content in a diazotrophically grown terrestrial Nostoc species, and the aquatic Nodularia species, regardless of nitrogen availability.
Elevated atmospheric CO2 levels were correlated to a reduction in biomass specific BNF rates in non-toxic Nodularia species.
Nodularin producers exhibited stronger stimulation of net photosynthesis rates (NP) and growth (more positive Cohen’s d) and less stimulation of dark respiration and BNF per volume compared to non-nodularin producers under elevated CO2 levels.
This study is the first to provide information on NP and nodularin production under elevated atmospheric CO2 levels for Nodularia and Nostoc species under nitrogen replete and diazotrophic conditions.
When considering complex systems, identifying the most important actors is often of relevance. When the system is modeled
as a network, centrality measures are used which assign each node a value due to its position in the network. It is often
disregarded that they implicitly assume a network process flowing through a network, and also make assumptions of how
the network process flows through the network. A node is then central with respect to this network process (Borgatti in Soc
Netw 27(1):55–71, 2005, https ://doi.org/10.1016/j.socne t.2004.11.008). It has been shown that real-world processes often
do not fulfill these assumptions (Bockholt and Zweig, in Complex networks and their applications VIII, Springer, Cham,
2019, https ://doi.org/10.1007/978-3-030-36683 -4_7). In this work, we systematically investigate the impact of the measures’
assumptions by using four datasets of real-world processes. In order to do so, we introduce several variants of the betweenness
and closeness centrality which, for each assumption, use either the assumed process model or the behavior of the real-world
process. The results are twofold: on the one hand, for all measure variants and almost all datasets, we find that, in general,
the standard centrality measures are quite robust against deviations in their process model. On the other hand, we observe a
large variation of ranking positions of single nodes, even among the nodes ranked high by the standard measures. This has
implications for the interpretability of results of those centrality measures. Since a mismatch of the behaviour of the real
network process and the assumed process model does even affect the highly-ranked nodes, resulting rankings need to be
interpreted with care.
A Strained Partnership: Krise und Resilienz in den transatlantischen Beziehungen 20 Jahre nach 9/11
(2021)
2021 lieferte aus transatlantischer Perspektive gleich mehrere Zäsuren. Im Januar wurde US-Präsident Donald Trump, dessen disruptive Politik diverse Konflikte mit Europa provozierte, durch Joseph R. Biden abgelöst. Im August endete in Afghanistan der längste Einsatz in der Geschichte der NATO mit einem chaotischen Abzug und der Machtübernahme der Taliban, fast 20 Jahre nach dem Beginn des Krieges. Und schließlich läuteten die Bundestagswahlen im September das Ende der Amtszeit Angela Merkels ein, die als Bundeskanzlerin in 16 Regierungsjahren auf vier US-Präsidenten traf. Diese Zäsuren bieten Anlass genug, eine Bilanz der transatlantischen Beziehungen seit 9/11 zu ziehen.
Weber, Daniel ; Kirsch, Benjamin ; Chighizola, Christopher R. ; D'Elia, Christopher R. ; Linke, Barbara S. ; Hill, Michael R. ; Aurich, Jan C.
Machining-induced residual stresses (MIRS) are a main driver for distortion of thin-walled monolithic aluminum workpieces. Before one can develop compensation techniques to minimize distortion, the effect of machining on the MIRS has to be fully understood. This means that not only an investigation of the effect of different process parameters on the MIRS is important. In addition, the repeatability of the MIRS resulting from the same machining condition has to be considered. In past research, statistical confidence of MIRS of machined samples was not focused on. In this paper, the repeatability of the MIRS for different machining modes, consisting of a variation in feed per tooth and cutting speed, is investigated. Multiple hole-drilling measurements within one sample and on different samples, machined with the same parameter set, were part of the investigations. Besides, the effect of two different clamping strategies on the MIRS was investigated. The results show that an overall repeatability for MIRS is given for stable machining (between 16 and 34% repeatability standard deviation of maximum normal MIRS), whereas instable machining, detected by vibrations in the force signal, has worse repeatability (54%) independent of the used clamping strategy. Further experiments, where a 1-mm-thick wafer was removed at the milled surface, show the connection between MIRS and their distortion. A numerical stress analysis reveals that the measured stress data is consistent with machining-induced distortion across and within different machining modes. It was found that more and/or deeper MIRS cause more distortion.
Analysis of dimensional accuracy for micro-milled areal material measures with kinematic simulation
(2021)
The calibration of areal surface topography measuring instruments is of high relevance to estimate the measurement uncertainty and to guarantee the traceability of the measurement results. Calibration structures for optical measuring instruments must be sufficiently small to determine the limits of the instruments.
Besides other methods, micro-milling is a suitable process for manufacturing areal material measures. For the manufacturing by micro-milling with ball end mills, the tool radius (effective cutter radius) is the corresponding limiting factor: if the tool radius is too large to penetrate the concave profile details without removing the surrounding material, deviations from the target geometry will occur. These deviations can be detected and excluded before experimental manufacturing with the aid of a kinematic simulation.
In this study, a kinematic simulation model for the prediction of the dimensional accuracy of micro-milled areal material measures is developed and validated. Subsequently, a radius study is conducted to determine how the tool radius r of the tool influences the dimensional accuracy of an areal crossed sinusoidal (ACS) geometry according to ISO 25178-70 [1] with a defined amplitude d and period length p. The resulting theoretical surface texture parameters are evaluated and compared to the target values. It was shown that the surface texture parameters deviate from the nominal values depending on the effective cutter radius used. Based on the results of the study, it can be determined with which effective tool radius the measurands Sa and Sq of the material measures are best met. The ideal effective radius for the application considered is between 50 and 75 μm.
Adaptive numerical integration of exponential finite elements for a phase field fracture model
(2021)
Phase field models for fracture are energy-based and employ a continuous field variable, the phase field, to indicate cracks. The width of the transition zone of this field variable between damaged and intact regions is controlled by a regularization parameter. Narrow transition zones are required for a good approximation of the fracture energy which involves steep gradients of the phase field. This demands a high mesh density in finite element simulations if 4-node elements with standard bilinear shape functions are used. In order to improve the quality of the results with coarser meshes, exponential shape functions derived from the analytic solution of the 1D model are introduced for the discretization of the phase field variable. Compared to the bilinear shape functions these special shape functions allow for a better approximation of the fracture field. Unfortunately, lower-order Gauss-Legendre quadrature schemes, which are sufficiently accurate for the integration of bilinear shape functions, are not sufficient for an accurate integration of the exponential shape functions. Therefore in this work, the numerical accuracy of higher-order Gauss-Legendre formulas and a double exponential formula for numerical integration is analyzed.
Without actors, there is no action: How interpersonal interactions help to explain routine dynamics
(2020)
In this paper, we argue that it is important to gain a better understanding on how people interact with each other to explain routine dynamics. Thus, we propose to focus on the interpersonal interactions of actors which is not only the fact that actors interact with each other but that the manner and quality of these interactions is important to understand routine dynamics. By drawing on social exchange theory, we propose a framework that seeks to explain routine dynamics based on different relationships between actors. Building on this framework, we provide different process models indicating how routine performing and patterning is enacted due to the respective relationship of actors. Our insights contribute to research on routine dynamics by arguing (1) that actions of patterning are dependent on the relationship of actors; (2) that trust works as an enabler for creating new patterns of actions; (3) that distrust functions as an enhancer for interrupting and dissolving patterns of actions.
Meyer, Robert ; Mutter, Andreas ; Umstätter, Philipp ; Schünemann, Volker ; Beck, Tilmann ; Smaga, Marek ; Urbassek, Herbert M.
Defects change the phonon spectrum and also the magnetic properties of bcc-Fe. Using molecular dynamics simulation, the influence of defects – vacancies, dislocations, and grain boundaries – on the phonon spectra and magnetic properties of bcc-Fe is determined. It is found that the main influence of defects consists in a decrease of the amplitude of the longitudinal peak, PL, at around 37 meV. While the change in phonon spectra shows only little dependence on the defect type, the quantitative decrease of PL is proportional to the defect concentration. Local magnetic moments can be determined from the local atomic volumes. Again, the changes in the magnetic moments of a defective crystal are linear in the defect concentrations. In addition, the change of the phonon density of states and the magnetic moments under homogeneous uniaxial strain are investigated.