Social preferences across contexts

Over the past decades, the behavior of people who do not maximize their payoff but instead seem to be other-regarding has received much attention in the (behavioral) economics literature. Many different social preference models that ideally explain such other-regarding behavior across a large span of contexts have been proposed and tested. Building on this literature, this dissertation studies social preferences in different contexts and expressions across three manuscripts. The first manuscript examines the behavior of people who avoid a situation that allows them to express social preferences. Drawing on psychological game theory, we tested whether guilt-aversion or self-image concerns could better explain this behavior. It was found that guilt-aversion, but not self-image concerns, can explain the behavior of these people. The second manuscript made use of crowdfunding donations data and showed that the reversal of the compassion fade effect when going from a separate to a joint evaluation condition extends from the lab to the field. Social preferences can also manifest themselves through people donating their time. The third manuscript examines how the severity of a catastrophe (i.e., the COVID-19 pandemic) affects the provision of catastrophe-related voluntary labor. We found a concave relationship between the weekly COVID-19-related death numbers and the amount of voluntary work provided by individuals. Thus, by drawing on prosocial behavior expressed in three different environments, this dissertation extends the current literature by studying how social preferences are influenced by the context in which they are carried out

Power and its Logic: Mastering Politics

Power is the essence of politics. Whoever seeks to understand and master it must understand its logic. Drawing on two decades of international experience in political consulting, Dominik Meier and Christian Blum give profound and honest insights into the inner workings of power. Introducing their Power Leadership Approach, the authors provide a conceptual analysis of power and present the tools to successfully exercise it in the political domain. "Power and its Logic" is a guidebook for politicians, business leaders, civil society pioneers, public affairs consultants and for every citizen who wants to understand the unwritten rules of politics

Power and its Logic

Power is the essence of politics. Whoever seeks to understand and master it must understand its logic. Drawing on two decades of international experience in political consulting, Dominik Meier and Christian Blum give profound and honest insights into the inner workings of power. Introducing their Power Leadership Approach, the authors provide a conceptual analysis of power and present the tools to successfully exercise it in the political domain. "Power and its Logic" is a guidebook for politicians, business leaders, civil society pioneers, public affairs consultants and for every citizen who wants to understand the unwritten rules of politics

Designing and evaluating an online reinforcement learning agent for physical exercise recommendations in N-of-1 trials

Personalized adaptive interventions offer the opportunity to increase patient benefits, however, there are challenges in their planning and implementation. Once implemented, it is an important question whether personalized adaptive interventions are indeed clinically more effective compared to a fixed gold standard intervention. In this paper, we present an innovative N-of-1 trial study design testing whether implementing a personalized intervention by an online reinforcement learning agent is feasible and effective. Throughout, we use a new study on physical exercise recommendations to reduce pain in endometriosis for illustration. We describe the design of a contextual bandit recommendation agent and evaluate the agent in simulation studies. The results show that adaptive interventions add complexity to the design and implementation process, but have the potential to improve patients' benefits even if only few observations are available. In order to quantify the expected benefit, data from previous interventional studies is required. We expect our approach to be transferable to other interventions and clinical interventions

Stochasticity from function -- why the Bayesian brain may need no noise

An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encoding scheme for probabilistic computing. Since the precise statistical properties of neural activity are important in this context, many models assume an ad-hoc source of well-behaved, explicit noise, either on the input or on the output side of single neuron dynamics, most often assuming an independent Poisson process in either case. However, these assumptions are somewhat problematic: neighboring neurons tend to share receptive fields, rendering both their input and their output correlated; at the same time, neurons are known to behave largely deterministically, as a function of their membrane potential and conductance. We suggest that spiking neural networks may, in fact, have no need for noise to perform sampling-based Bayesian inference. We study analytically the effect of auto- and cross-correlations in functionally Bayesian spiking networks and demonstrate how their effect translates to synaptic interaction strengths, rendering them controllable through synaptic plasticity. This allows even small ensembles of interconnected deterministic spiking networks to simultaneously and co-dependently shape their output activity through learning, enabling them to perform complex Bayesian computation without any need for noise, which we demonstrate in silico, both in classical simulation and in neuromorphic emulation. These results close a gap between the abstract models and the biology of functionally Bayesian spiking networks, effectively reducing the architectural constraints imposed on physical neural substrates required to perform probabilistic computing, be they biological or artificial

Corneal absorption spectra in the deep UV range.

SIGNIFICANCE Refractive surgery in ophthalmology uses pulsed lasers at 193, 210, or 213 nm. The reason is that most molecular constituents of cornea absorb strongly in this wavelength range. Precise refractive surgery via ablation requires an accurate knowledge of the absorption coefficient at the relevant wavelengths. Yet, the absorption coefficients of corneal tissue reported in literature vary by almost an order of magnitude; moreover, they were measured mostly at the wavelengths mentioned earlier. AIM By measuring the corneal absorption coefficient of intact eyeballs stored at different environmental conditions, prepared by following different procedures, and as a function of postmortem time, we determine the absorption coefficient for the entire wavelength range between 185 and 250 nm for as close as possible to in-vivo conditions. APPROACH We use a specially designed UV ellipsometer to measure refractive index and absorption coefficient. Specifically, we investigate the temporal evolution of refractive index and absorption coefficient after enucleation of the eyeballs under different environmental conditions and preparation procedures. RESULTS Our measurements provide accurate values for refractive index as well as absorption coefficient of cornea in the wavelength range between 185 and 250 nm. We find that the absorption coefficient decreases with time and that neither storage conditions nor preparation procedures but a continuous degeneration of the cornea is responsible for the observed time evolution. We use the measured time evolution to extrapolate refractive index and absorption coefficient to in-vivo conditions. CONCLUSION Our measurements of the close to in-vivo absorption coefficient of cornea between 185 and 250 nm allow for a better understanding and modeling of refractive cornea surgery, also at other than the three commonly used wavelengths. In the future, this may be relevant when new pulsed laser sources with other wavelengths become available

Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction

Reconstructing 3D objects from 2D images is both challenging for our brains and machine learning algorithms. To support this spatial reasoning task, contextual information about the overall shape of an object is critical. However, such information is not captured by established loss terms (e.g. Dice loss). We propose to complement geometrical shape information by including multi-scale topological features, such as connected components, cycles, and voids, in the reconstruction loss. Our method uses cubical complexes to calculate topological features of 3D volume data and employs an optimal transport distance to guide the reconstruction process. This topology-aware loss is fully differentiable, computationally efficient, and can be added to any neural network. We demonstrate the utility of our loss by incorporating it into SHAPR, a model for predicting the 3D cell shape of individual cells based on 2D microscopy images. Using a hybrid loss that leverages both geometrical and topological information of single objects to assess their shape, we find that topological information substantially improves the quality of reconstructions, thus highlighting its ability to extract more relevant features from image datasets.Comment: Accepted at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI

A bibliometric analysis of orthogeriatric care: top 50 articles.

BACKGROUND Population is ageing and orthogeriatric care is an emerging research topic. PURPOSE This bibliometric review aims to provide an overview, to investigate the status and trends in research in the field of orthogeriatric care of the most influential literature. METHODS From the Core Collection databases in the Thomson Reuters Web of Knowledge, the most influential original articles with reference to orthogeriatric care were identified in December 2020 using a multistep approach. A total of 50 articles were included and analysed in this bibliometric review. RESULTS The 50 most cited articles were published between 1983 and 2017. The number of total citations per article ranged from 34 to 704 citations (mean citations per article: n = 93). Articles were published in 34 different journals between 1983 and 2017. In the majority of publications, geriatricians (62%) accounted for the first authorship, followed by others (20%) and (orthopaedic) surgeons (18%). Articles mostly originated from Europe (76%), followed by Asia-pacific (16%) and Northern America (8%). Key countries (UK, Sweden, and Spain) and key topic (hip fracture) are key drivers in the orthogeriatric research. The majority of articles reported about therapeutic studies (62%). CONCLUSION This bibliometric review acknowledges recent research. Orthogeriatric care is an emerging research topic in which surgeons have a potential to contribute and other topics such as intraoperative procedures, fractures other than hip fractures or elective surgery are related topics with the potential for widening the field to research