2,683 research outputs found
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 213Â 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 250Â 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 250Â 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 250Â 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
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