Unveiling the underlying mechanism for the matching effect between construal level and message frames: how and why do matches between gain versus loss frames and construal level enhance persuasion?

different weighting functions for gains and for losses. Two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting functions. A review of the experimental evidence and the results of a new experiment confirm a

Abstract. Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while taking the empirically best action as often as possible. A popular measure of a policy’s success in addressing

and generalists, and significantly advances our understanding of the dynamics of job gain and loss. Simple and very useful examples are often presented to clarify measurement concepts, thus increasing the accessibility of the results and the

effects of difficulty and gain versus loss on vocal

violate the marginal condition.2 Thus we expect a market solution to be suboptimal. However, a much more precise structure must be put on the problem if we are to understand the nature of the bias involved. It is useful to think of the question as one of quantity versus diversity. With scale economies

received the transmission. This deferred choice gives each transmission multiple opportunities to make progress. As a result ExOR can use long radio links with high loss rates, which would be avoided by traditional routing. ExOR increases a connection’s throughput while using no more network capacity than

then show through experiments on an emulated network that current DHT implementations cannot handle such churn rates. Next, we identify and explore three factors affecting DHT performance under churn: reactive versus periodic failure recovery, message timeout calculation, and proximity neighbor selection

on several real-world sensor-network data sets, taking into account the real measured data and communication quality, demonstrating that our model-based approach provides a high-fidelity representation of the real phenomena and leads to significant performance gains versus traditional data acquisition

, for each definition, different correlation models and channel information assumptions that we consider. We first provide a comprehensive summary of ergodic and capacity versus outage results for single-user MIMO channels. These results indicate that the capacity gain obtained from multiple antennas heavily