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There is substantial evidence from behavioral economics and decision sciences demonstrating that in the context of decision-making under uncertainty, the carriers of value behind actions are gains and losses defined relative to a reference point (e.g. pre-action expectations), rather than the absolute final outcomes. Also, the capability of early predicting session-level search decisions and user experience is essential for developing reactive and proactive search recommendations. To address these research gaps, our study aims to 1) develop reference dependence features based on a series of simulated user expectations or reference points in first query segments of sessions, and 2) examine the extent to which we can enhance the performance of early predicting session behavior and user satisfaction by constructing and employing reference dependence features. Based on the experimental results on three datasets of varying types, we found that incorporating reference dependent features developed in first query segments into prediction models achieves better performance than using baseline cost-benefit features only in early predicting three key session metrics (user satisfaction score, session clicks, and session dwell time). Also, when running simulations by varying the search time expectation and rate of user satisfaction decay, the results demonstrate that users tended to expect to complete their search within a minute and showed a rapid rate of satisfaction decay in a logarithmic fashion once surpassing the estimated expectation points. By factoring in a user's search time expectation and measuring their behavioral response once the expectation is not met, we can further improve the performance of early prediction models and enhance our understanding of users' behavioral patterns. 

Apidaecin (Api), an unmodified 18-amino-acid-long proline-rich antibacterial peptide produced by bees, has been recently described as a specific inhibitor of translation termination. It invades the nascent peptide exit tunnel of the postrelease ribosome and traps the release factors preventing their recycling. Api binds in the exit tunnel in an extended conformation that matches the placement of a nascent polypeptide and establishes multiple contacts with ribosomal RNA (rRNA) and ribosomal proteins. Which of these interactions are critical for Api’s activity is unknown. We addressed this problem by analyzing the activity of all possible single-amino-acid substitutions of the Api variants synthesized in the bacterial cell. By conditionally expressing the engineeredapigene, we generated Api directly in the bacterial cytosol, thereby bypassing the need for importing the peptide from the medium. The endogenously expressed Api, as well as its N-terminally truncated mutants, retained the antibacterial properties and the mechanism of action of the native peptide. Taking advantage of the Api expression system and next-generation sequencing, we mapped in one experiment all the single-amino-acid substitutions that preserve or alleviate the on-target activity of the Api mutants. Analysis of the inactivating mutations made it possible to define the pharmacophore of Api involved in critical interactions with the ribosome, transfer RNA (tRNA), and release factors. We also identified the Api segment that tolerates a variety of amino acid substitutions; alterations in this segment could be used to improve the pharmacological properties of the antibacterial peptide.