The existence of rational expectations equilibrium: a retrospective

This paper provides a selective review of theoretical research on the consistency of rational expectations equilibrium and its properties in microeconomic models. The general equilibrium framework is emphasized throughout the paper. After defining rational expectations equilibrium for a pure exchange economy, the paper presents a simple counterexample to illustrate that rational expectations equilibria need not exist. Results are summarized for the generic existence of fully revealing rational expectations equilibria in smooth economies satisfying additional dimensionality assumptions. Then the rational expectations equilibrium existence problem is related to earlier analysis of informationally decentralized allocation mechanisms. Next the efficiency properties of rational expectations equilibrium allocations are examined. Finally, the possibilities for partially revealing rational expectations equilibria are discussed.Equilibrium (Economics) - Mathematical models ; Rational expectations (Economic theory)

Reducing Risky Driving Behavior: The Impact of an Adolescent Driver Intervention Program With and Without Mandatory Parental Attendance

The United States is a vehicle-dependent society and allows adolescents to obtain driver’s licenses at age 16 or younger. This study examined the impacts of a driver intervention program on reducing risky driving behaviors among youths who had received their first traffic citation, as well as parental management of driving practices. Participants consisted of 243 youths ages 16 and 17 who were court-ordered to attend the Ohio 4-H CARTEENS (CAR = Caution and Responsibility and TEENS = Teens who volunteer as teachers) program with and without parents. Results indicated that risky driving behavior decreased significantly for both groups after the intervention program. Parental management practices, however, increased only for youths attending without parents. Regression analysis indicated that risky driving behavior at Time 1 and levels of parental management (parental control) at Time 2 predicted risky driving behavior after completion of the program. Implications of this study include the importance of adolescent driver intervention and prevention programs to teach youths about unsafe driving practices before licensure

Automated Ecological Assessment of Physical Activity: Advancing Direct Observation.

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) of bias/difference values, and intraclass correlation coefficients (ICC) assessed the criterion validity compared to accelerometry separately for each camera. The number and proportion of participants sedentary and in moderate-to-vigorous physical activity (MVPA) had small biases (within 20% of the criterion mean) and the ICCs were excellent (0.82-0.98). Total MET-minutes were slightly underestimated by 9.3-17.1% and the ICCs were good (0.68-0.79). The standard deviations of the bias estimates were moderate-to-large relative to the means. The computer vision algorithms appeared to have acceptable sample-level validity (i.e., across a sample of time intervals) and are promising for automated ecological assessment of activity in open outdoor settings, but further development and testing is needed before such tools can be used in a diverse range of settings

Analysis of the role of Ser1/Ser2/Thr9 phosphorylation on myosin II assembly and function in live cells

<p>Abstract</p> <p>Background</p> <p>Phosphorylation of non-muscle myosin II regulatory light chain (RLC) at Thr18/Ser19 is well established as a key regulatory event that controls myosin II assembly and activation, both in vitro and in living cells. RLC can also be phosphorylated at Ser1/Ser2/Thr9 by protein kinase C (PKC). Biophysical studies show that phosphorylation at these sites leads to an increase in the Km of myosin light chain kinase (MLCK) for RLC, thereby indirectly inhibiting myosin II activity. Despite unequivocal evidence that PKC phosphorylation at Ser1/Ser2/Thr9 can regulate myosin II function in vitro, there is little evidence that this mechanism regulates myosin II function in live cells.</p> <p>Results</p> <p>The purpose of these studies was to investigate the role of Ser1/Ser2/Thr9 phosphorylation in live cells. To do this we utilized phospho-specific antibodies and created GFP-tagged RLC reporters with phosphomimetic aspartic acid substitutions or unphosphorylatable alanine substitutions at the putative inhibitory sites or the previously characterized activation sites. Cell lines stably expressing the RLC-GFP constructs were assayed for myosin recruitment during cell division, the ability to complete cell division, and myosin assembly levels under resting or spreading conditions. Our data shows that manipulation of the activation sites (Thr18/Ser19) significantly alters myosin II function in a number of these assays while manipulation of the putative inhibitory sites (Ser1/Ser2/Thr9) does not.</p> <p>Conclusions</p> <p>These studies suggest that inhibitory phosphorylation of RLC is not a substantial regulatory mechanism, although we cannot rule out its role in other cellular processes or perhaps other types of cells or tissues in vivo.</p

General N-and O-linked glycosylation of lipoproteins in mycoplasmas and role of exogenous oligosaccharide

The lack of a cell wall, flagella, fimbria, and other extracellular appendages and the possession of only a single membrane render the mycoplasmas structurally simplistic and ideal model organisms for the study of glycoconjugates. Most species have genomes of about 800 kb and code for few proteins predicted to have a role in glycobiology. The murine pathogens Mycoplasma arthritidis and Mycoplasma pulmonis have only a single gene annotated as coding for a glycosyltransferase but synthesize glycolipid, polysaccharide and glycoproteins. Previously, it was shown that M. arthritidis glycosylated surface lipoproteins through O-linkage. In the current study, O-linked glycoproteins were similarly found in M. pulmonis and both species of mycoplasma were found to also possess N-linked glycans at residues of asparagine and glutamine. Protein glycosylation occurred at numerous sites on surface-exposed lipoproteins with no apparent amino acid sequence specificity. The lipoproteins of Mycoplasma pneumoniae also are glycosylated. Glycosylation was dependent on the glycosidic linkages from host oligosaccharides. As far as we are aware, N-linked glycoproteins have not been previously described in Gram-positive bacteria, the organisms to which the mycoplasmas are phylogenetically related. The findings indicate that the mycoplasma cell surface is heavily glycosylated with implications for the modulation of mycoplasma-host interactions

Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics

An inherent problem of reinforcement learning is performing exploration of an environment through random actions, of which a large portion can be unproductive. Instead, exploration can be improved by initializing the learning policy with an existing (previously learned or hard-coded) oracle policy, offline data, or demonstrations. In the case of using an oracle policy, it can be unclear how best to incorporate the oracle policy's experience into the learning policy in a way that maximizes learning sample efficiency. In this paper, we propose a method termed Critic Confidence Guided Exploration (CCGE) for incorporating such an oracle policy into standard actor-critic reinforcement learning algorithms. More specifically, CCGE takes in the oracle policy's actions as suggestions and incorporates this information into the learning scheme when uncertainty is high, while ignoring it when the uncertainty is low. CCGE is agnostic to methods of estimating uncertainty, and we show that it is equally effective with two different techniques. Empirically, we evaluate the effect of CCGE on various benchmark reinforcement learning tasks, and show that this idea can lead to improved sample efficiency and final performance. Furthermore, when evaluated on sparse reward environments, CCGE is able to perform competitively against adjacent algorithms that also leverage an oracle policy. Our experiments show that it is possible to utilize uncertainty as a heuristic to guide exploration using an oracle in reinforcement learning. We expect that this will inspire more research in this direction, where various heuristics are used to determine the direction of guidance provided to learning.Comment: Under review at TML

Self-Serving Bias in Performance Goal Achievement Appraisals: Evidence From Long-Distance Runners

While working with a long-distance running event organizer, the authors of this study observed considerable differences between event participants’ official finish time (i.e., bib time) and their self-reported finish time in the post-event survey. Drawing on the notion of self-serving bias, we aim to explore the source of this disparity and how such psychological bias influences participants’ event experience at long-distance running events. Using evidence of 1,320 marathon runners, we demonstrated how people are more likely to be subject to a biased self-assessment contingent upon achieving their best finish time at the event. The study samples were split into record-high-achieved and record-high-missed groups, and the self-serving biases of each group were explored. Results from the t-test comparing record-high-achieved and -missed groups showed that runners in the record-high-missed group were significantly more likely to report a positively biased finish time than runners in the record-high-achieved group (p \u3c 0.01). Additionally, results from logistic regression showed that as runners missed their best finish time by a wider margin, the probability of reporting a positively biased incorrect finish time increased. Lastly, we conducted an additional t-test and revealed that runners who are subject to self-serving bias showed a lower level of overall event satisfaction. The current study suggests one way to bypass the adverse effects of participant sport event participants’ worse-than-expected athletic performance. We specifically suggest that the event organizers target runners who had worse-than-expected performance and make extra efforts on non-race service attributes (e.g., finish line experience, rest and recovery area, and transportation after the event) because these runners are more likely to be unsatisfied with the event