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Increasingly colleges and universities use survey results to make decisions, inform research, and shape public opinion. Given the large number of surveys distributed on campuses, can researchers reasonably expect that busy respondents will diligently answer each and every question? Less serious respondents may 'satisfice,' i.e., take short-cuts to conserve effort, in a number of ways-choosing the same response every time, skipping items, rushing through the instrument, or quitting early. In this paper we apply this satisficing framework to demonstrate analytic options for assessing respondents' conscientiousness in giving high fidelity survey answers. Specifically, we operationalize satisficing as a series of measurable behaviors and compute a satisficing index for each survey respondent. Using data from two surveys administered in university contexts, we find that the majority of respondents engaged in satisficing behaviors, that single-item results can be significantly impacted by satisficing, and that scale reliabilities and correlations can be altered by satisficing behaviors. We conclude with a discussion of the importance of identifying satisficers in routine survey analysis in order to verify data quality prior to using results for decision-making, research, or public dissemination of findings

The long term discount rate is critically dependent upon projections of future growth rates that are fuzzier in proportion to the remoteness of the time horizon. This paper models such increasing fuzziness as an evolving hidden-state stochastic process. The underlying trend growth rate is an unobservable random walk hidden by noisy transitory shocks and recoverable only as a probability distribution via Bayesian updating. A simple expression is derived for the time-declining Ramsey discount rate. The components of this hidden-state Ramsey discounting formula are then analyzed, followed by a few remarks about possible implications and applications, Economics

Swarm robotics utilizes a large number of simple robots to accomplish a task, instead of a single complex robot. Communications constraints often force these systems to be distributed and leaderless, placing restrictions on the types of algorithms which can be executed by the swarm. The performance of a swarm algorithm is affected by the environment in which the swarm operates. Different environments may call for different algorithms to be chosen, but often no single robot has enough information to make this decision. In this paper, we focus on foraging as a multi-robot task and present two distributed foraging algorithms, each of which performs best for different food locations. We then present a third adaptive algorithm in which the swarm as a whole is able to choose the best algorithm for the given situation by combining individual-level and distributed colony-level algorithm switching. We show that this adaptive method combines the bene ts of the other methods, and yields the best overall performance., Engineering and Applied Sciences

Clinical teachers often observe interactions that may contribute to health care disparities, yet may hesitate to teach about them. A pedagogical model could help faculty structure teaching about health care disparities in the clinical setting, but to our knowledge, none have been adapted for this purpose. In this paper, we adapt an established model, Time-Effective Strategies for Teaching (TEST), to the teaching of health care disparities. We use several case scenarios to illustrate the core components of the model: diagnose the learner, teach rapidly to the learner’s need, and provide feedback. The TEST model is straightforward, easy to use, and enables the incorporation of teaching about health care disparities into routine clinical teaching.

We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that they ignore the impact of their reports on the profit they might garner from future trades. In this paper, we analyze non-myopic strategies and examine what information structures lead to truthful betting by traders. Specifically, we analyze the behavior of risk-neutral traders with incomplete information playing in a dynamic game. We consider finite-stage and infinite-stage game models. For each model, we study the logarithmic market scoring rule (LMSR) with two different information structures: conditionally independent signals and (unconditionally) independent signals. In the finite-stage model, when signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE). Moreover, it is the unique Weak Perfect Bayesian Equilibrium (WPBE) of the game. In contrast, when signals of traders are unconditionally independent, truthful betting is not a WPBE. In the infinite-stage model with unconditionally independent signals, there does not exist an equilibrium in which all information is revealed in a finite amount of time. We propose a simple discounted market scoring rule that reduces the opportunity for bluffing strategies. We show that in any WPBE for the infinite-stage market with discounting, the market price converges to the fully-revealing price, and the rate of convergence can be bounded in terms of the discounting parameter. When signals are conditionally independent, truthful betting is the unique WPBE for the infinite-stage market with and without discounting., Engineering and Applied Sciences

Attention-deficit/hyperactivity disorder, ADHD, is a common and highly heritable neuropsychiatric disorder that is seen in children and adults. Although heritability is estimated at around 76%, it has been hard to find genes underlying the disorder. ADHD is a multifactorial disorder, in which many genes, all with a small effect, are thought to cause the disorder in the presence of unfavorable environmental conditions. Whole genome linkage analyses have not yet lead to the identification of genes for ADHD, and results of candidate gene-based association studies have been able to explain only a tiny part of the genetic contribution to disease, either. A novel way of performing hypothesis-free analysis of the genome suitable for the identification of disease risk genes of considerably smaller effect is the genome-wide association study (GWAS). So far, five GWAS have been performed on the diagnosis of ADHD and related phenotypes. Four of these are based on a sample set of 958 parent–child trio’s collected as part of the International Multicentre ADHD Genetics (IMAGE) study and genotyped with funds from the Genetic Association Information Network (GAIN). The other is a pooled GWAS including adult patients with ADHD and controls. None of the papers reports any associations that are formally genome-wide significant after correction for multiple testing. There is also very limited overlap between studies, apart from an association with CDH13, which is reported in three of the studies. Little evidence supports an important role for the ‘classic’ ADHD genes, with possible exceptions for SLC9A9, NOS1 and CNR1. There is extensive overlap with findings from other psychiatric disorders. Though not genome-wide significant, findings from the individual studies converge to paint an interesting picture: whereas little evidence—as yet—points to a direct involvement of neurotransmitters (at least the classic dopaminergic, noradrenergic and serotonergic pathways) or regulators of neurotransmission, some suggestions are found for involvement of ‘new’ neurotransmission and cell–cell communication systems. A potential involvement of potassium channel subunits and regulators warrants further investigation. More basic processes also seem involved in ADHD, like cell division, adhesion (especially via cadherin and integrin systems), neuronal migration, and neuronal plasticity, as well as related transcription, cell polarity and extracellular matrix regulation, and cytoskeletal remodeling processes. In conclusion, the GWAS performed so far in ADHD, though far from conclusive, provide a first glimpse at genes for the disorder. Many more (much larger studies) will be needed. For this, collaboration between researchers as well as standardized protocols for phenotyping and DNA-collection will become increasingly important.

Informational visualization tools, such as commercial charting packages, provide a standard set of visualizations for tabular data, including bar charts, scatter plots, pie charts, and the like. For some combinations of data and task, these are suitable visualizations. For others, however, novel visualizations over multiple variables would be preferred but are unavailable in the fixed list of standard options. To allow for these cases, we introduce a declarative language for specifying visualizations on the basis of the first principles on which (a subset of) informational graphics are built. The functionality we aim to provide with this language is presented by way of example, from simple scatter plots to versions of two quite famous visualizations: Minard’s depiction of troop strength during Napoleon’s march on Moscow and a map of the early ARPAnet from the ancient history of the Internet. Benefits of our approach include flexibility and expressiveness for specifying a range of visualizations that cannot be rendered with standard commercial systems., Engineering and Applied Sciences

The pathogenesis of migraine headache is poorly understood but the trigeminovascular system seems to play an important role in it. The trigeminal nucleus caudalis is sensitised by noxious sensory stimuli, often from convergent afferents originating from a variety of tissues. In this paper, we review evidence to support the view that the cervical muscles play a role in the pathogenesis of the migraine headache as well by facilitating the mechanism of central sensitisation.