Continuois Time Contests

This paper introduces a contest model in which each player decides when to stop a privately observed Brownian motion with drift and incurs costs depending on his stopping time. The player who stops his process at the highest value wins a prize. Applications of the model include procurement contests and competitions for grants. We prove existence and uniqueness of the Nash equilibrium outcome, even if players have to choose bounded stopping times. We derive the equilibrium distribution in closed form. If the noise vanishes, the equilibrium outcome converges to - and thus selects - the symmetric equilibrium outcome of an all-pay auction. For two players and constant costs, each player’s profits increase if costs for both players increase, variance increases, or drift decreases. Intuitively, patience becomes a more important factor for contest success, which reduces informational rents

Gambling in Contests

This paper presents a strategic model of risk-taking behavior in contests. Formally, we analyze an n-player winner-take-all contest in which each player decides when to stop a privately observed Brownian Motion with drift. A player whose process reaches zero has to stop. The player with the highest stopping point wins. Contrary to the explicit cost for a higher stopping time in a war of attrition, here, higher stopping times are riskier, because players can go bankrupt. We derive a closed-form solution of the unique Nash equilibrium outcome of the game. In equilibrium, the trade-off between risk and reward causes a non-monotonicity: highest expected losses occur if the process decreases only slightly in expectation

Magnetic Field-Induced Lattice Effects in a Quasi-2D Organic Conductor Close to the Mott Metal-Insulator Transition

We present ultra-high-resolution dilatometric studies in magnetic fields on a quasi-two-dimensional organic conductor $\kappa$-(D8-BEDT-TTF)$_{2}$Cu[N(CN)$_{2}$]Br, which is located close to the Mott metal-insulator (MI) transition. The obtained thermal expansion coefficient, $\alpha(T)$, reveals two remarkable features: (i) the Mott MI transition temperature $T_{MI}$ = (13.6 $\pm$ 0.6)\,K is insensitive to fields up to 10\,T, the highest applied field; (ii) for fields along the interlayer \emph{b}-axis, a magnetic-field-induced (FI) phase transition at $T_{FI}$ = (9.5 $\pm$ 0.5)\,K is observed above a threshold field $H_c \sim$ 1 T, indicative of a spin reorientation with strong magneto-elastic coupling.Comment: 5 pages, 4 figure

'A net for everyone': fully personalized and unsupervised neural networks trained with longitudinal data from a single patient

With the rise in importance of personalized medicine, we trained personalized neural networks to detect tumor progression in longitudinal datasets. The model was evaluated on two datasets with a total of 64 scans from 32 patients diagnosed with glioblastoma multiforme (GBM). Contrast-enhanced T1w sequences of brain magnetic resonance imaging (MRI) images were used in this study. For each patient, we trained their own neural network using just two images from different timepoints. Our approach uses a Wasserstein-GAN (generative adversarial network), an unsupervised network architecture, to map the differences between the two images. Using this map, the change in tumor volume can be evaluated. Due to the combination of data augmentation and the network architecture, co-registration of the two images is not needed. Furthermore, we do not rely on any additional training data, (manual) annotations or pre-training neural networks. The model received an AUC-score of 0.87 for tumor change. We also introduced a modified RANO criteria, for which an accuracy of 66% can be achieved. We show that using data from just one patient can be used to train deep neural networks to monitor tumor change

Pleasure and the Control of Food Intake: An Embodied Cognition Approach to Consumer Self‐Regulation

Consumers try to avoid temptation when exposed to appetizing foods by diverting their attention away from their senses (e.g., sight, smell, mouthfeel) and bodily states (e.g., state of arousal, salivation) in order to focus on their longer term goals (e.g., eating healthily, achieving an ideal body weight). However, when not including sensations in their decision‐making processes, consumers risk depleting their self‐regulatory resources, potentially leading to unhealthy food choices. Conversely, based on the concept of “embodied self‐regulation,” the suggestion is made that considering bodily states may help consumers regulate their food choices more effectively. A new model is proposed that facilitates understanding observed consumer behavior and the success or failure of self‐control in food intake. It is argued that bodily states and sensory information should be considered when modeling consumer behavior and developing health‐related advocacy and communication campaigns. The model proposed here leads to new perspectives on consumer consumption behavior and health policy research and strategies

When language gets emotional: irony and the embodiment of affect in discourse

Although there is increasing evidence to suggest that language is grounded in perception and action, the relationship between language and emotion is less well understood. We investigate the grounding of language in emotion using a novel approach that examines the relationship between the comprehension of a written discourse and the performance of affect-related motor actions (hand movements towards and away from the body). Results indicate that positively and negatively valenced words presented in context influence motor responses (Experiment 1), whilst valenced words presented in isolation do not (Experiment 3). Furthermore, whether discourse context indicates that an utterance should be interpreted literally or ironically can influence motor responding, suggesting that the grounding of language in emo- tional states can be influenced by discourse-level factors (Experiment 2). In addition, the finding of affect-related motor responses to certain forms of ironic language, but not to non-ironic control sentences, suggests that phrasing a message ironically may influence the emotional response that is elicited

Adaptive Evolution of the Lactose Utilization Network in Experimentally Evolved Populations of Escherichia coli

Adaptation to novel environments is often associated with changes in gene regulation. Nevertheless, few studies have been able both to identify the genetic basis of changes in regulation and to demonstrate why these changes are beneficial. To this end, we have focused on understanding both how and why the lactose utilization network has evolved in replicate populations of Escherichia coli. We found that lac operon regulation became strikingly variable, including changes in the mode of environmental response (bimodal, graded, and constitutive), sensitivity to inducer concentration, and maximum expression level. In addition, some classes of regulatory change were enriched in specific selective environments. Sequencing of evolved clones, combined with reconstruction of individual mutations in the ancestral background, identified mutations within the lac operon that recapitulate many of the evolved regulatory changes. These mutations conferred fitness benefits in environments containing lactose, indicating that the regulatory changes are adaptive. The same mutations conferred different fitness effects when present in an evolved clone, indicating that interactions between the lac operon and other evolved mutations also contribute to fitness. Similarly, changes in lac regulation not explained by lac operon mutations also point to important interactions with other evolved mutations. Together these results underline how dynamic regulatory interactions can be, in this case evolving through mutations both within and external to the canonical lactose utilization network