Incentivizing Exploration with Heterogeneous Value of Money

Recently, Frazier et al. proposed a natural model for crowdsourced exploration of different a priori unknown options: a principal is interested in the long-term welfare of a population of agents who arrive one by one in a multi-armed bandit setting. However, each agent is myopic, so in order to incentivize him to explore options with better long-term prospects, the principal must offer the agent money. Frazier et al. showed that a simple class of policies called time-expanded are optimal in the worst case, and characterized their budget-reward tradeoff. The previous work assumed that all agents are equally and uniformly susceptible to financial incentives. In reality, agents may have different utility for money. We therefore extend the model of Frazier et al. to allow agents that have heterogeneous and non-linear utilities for money. The principal is informed of the agent's tradeoff via a signal that could be more or less informative. Our main result is to show that a convex program can be used to derive a signal-dependent time-expanded policy which achieves the best possible Lagrangian reward in the worst case. The worst-case guarantee is matched by so-called "Diamonds in the Rough" instances; the proof that the guarantees match is based on showing that two different convex programs have the same optimal solution for these specific instances. These results also extend to the budgeted case as in Frazier et al. We also show that the optimal policy is monotone with respect to information, i.e., the approximation ratio of the optimal policy improves as the signals become more informative.Comment: WINE 201

The biological origin of linguistic diversity

In contrast with animal communication systems, diversity is characteristic of almost every aspect of human language. Languages variously employ tones, clicks, or manual signs to signal differences in meaning; some languages lack the noun-verb distinction (e.g., Straits Salish), whereas others have a proliferation of fine-grained syntactic categories (e.g., Tzeltal); and some languages do without morphology (e.g., Mandarin), while others pack a whole sentence into a single word (e.g., Cayuga). A challenge for evolutionary biology is to reconcile the diversity of languages with the high degree of biological uniformity of their speakers. Here, we model processes of language change and geographical dispersion and find a consistent pressure for flexible learning, irrespective of the language being spoken. This pressure arises because flexible learners can best cope with the observed high rates of linguistic change associated with divergent cultural evolution following human migration. Thus, rather than genetic adaptations for specific aspects of language, such as recursion, the coevolution of genes and fast-changing linguistic structure provides the biological basis for linguistic diversity. Only biological adaptations for flexible learning combined with cultural evolution can explain how each child has the potential to learn any human language

Rapid cultural adaptation can facilitate the evolution of large-scale cooperation

Over the past several decades, we have argued that cultural evolution can facilitate the evolution of large-scale cooperation because it often leads to more rapid adaptation than genetic evolution, and, when multiple stable equilibria exist, rapid adaptation leads to variation among groups. Recently, Lehmann, Feldman, and colleagues have published several papers questioning this argument. They analyze models showing that cultural evolution can actually reduce the range of conditions under which cooperation can evolve and interpret these models as indicating that we were wrong to conclude that culture facilitated the evolution of human cooperation. In the main, their models assume that rates of cultural adaption are not strong enough compared to migration to maintain persistent variation among groups when payoffs create multiple stable equilibria. We show that Lehmann et al. reach different conclusions because they have made different assumptions. We argue that the assumptions that underlie our models are more consistent with the empirical data on large-scale cultural variation in humans than those of Lehmann et al., and thus, our models provide a more plausible account of the cultural evolution of human cooperation in large groups

Applying human factors methods to explore ‘Work as Imagined’ and ‘Work as Done’ in the Emergency Department’s response to chemical, biological, radiological, and nuclear events

The Emergency Department (ED) is a complex, hectic, and high-pressured environment. Chemical, Biological, Radiological, and Nuclear (CBRN) events are multi-faceted emergencies and present numerous challenges to ED staff (first receivers) with large scale trauma, consequently requiring a combination of complex responses. Human Factors and Ergonomics (HF/E) methods such as Hierarchical Task Analysis (HTA) have been used in healthcare research. However, HF/E methods and theory have not been combined to understand how the ED responds to CBRN events. This study aimed to compare Work as Imagined (WAI) and Work as Done (WAD) in the ED CBRN response in a UK based hospital. WAI was established by carrying out document analyses on a CBRN plan and WAD by exploring first receivers response to CBRN scenario cards. The responses were converted to HTAs and compared. The WAI HTAs showed 4-8 phases of general organizational responsibilities during a CBRN event. WAD HTAs placed emphasis on diagnosing and treating presenting conditions. A comparison of WAI and WAD HTAs highlighted common actions and tasks. This study has identified three key differences between WAI and WAD in the ED CBRN response: 1) documentation of the CBRN event 2) treating the patient and 3) diagnosing the presenting complaint. Findings from this study provide an evidence base which can be used to inform future clinical policy and practice in providing safe and high quality care during CBRN events in the ED

The Salmonella Genomic Island 1 Is Specifically Mobilized In Trans by the IncA/C Multidrug Resistance Plasmid Family

BACKGROUND: The Salmonella genomic island 1 (SGI1) is a Salmonella enterica-derived integrative mobilizable element (IME) containing various complex multiple resistance integrons identified in several S. enterica serovars and in Proteus mirabilis. Previous studies have shown that SGI1 transfers horizontally by in trans mobilization in the presence of the IncA/C conjugative helper plasmid pR55. METHODOLOGY/PRINCIPAL FINDINGS: Here, we report the ability of different prevalent multidrug resistance (MDR) plasmids including extended-spectrum β-lactamase (ESBL) gene-carrying plasmids to mobilize the multidrug resistance genomic island SGI1. Through conjugation experiments, none of the 24 conjugative plasmids tested of the IncFI, FII, HI2, I1, L/M, N, P incompatibility groups were able to mobilize SGI1 at a detectable level (transfer frequency <10(-9)). In our collection, ESBL gene-carrying plasmids were mainly from the IncHI2 and I1 groups and thus were unable to mobilize SGI1. However, the horizontal transfer of SGI1 was shown to be specifically mediated by conjugative helper plasmids of the broad-host-range IncA/C incompatibility group. Several conjugative IncA/C MDR plasmids as well as the sequenced IncA/C reference plasmid pRA1 of 143,963 bp were shown to mobilize in trans SGI1 from a S. enterica donor to the Escherichia coli recipient strain. Depending on the IncA/C plasmid used, the conjugative transfer of SGI1 occurred at frequencies ranging from 10(-3) to 10(-6) transconjugants per donor. Of particular concern, some large IncA/C MDR plasmids carrying the extended-spectrum cephalosporinase bla(CMY-2) gene were shown to mobilize in trans SGI1. CONCLUSIONS/SIGNIFICANCE: The ability of the IncA/C MDR plasmid family to mobilize SGI1 could contribute to its spread by horizontal transfer among enteric pathogens. Moreover, the increasing prevalence of IncA/C plasmids in MDR S. enterica isolates worldwide has potential implications for the epidemic success of the antibiotic resistance genomic island SGI1 and its close derivatives

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery – Part II: an illustrative example

<p>Abstract</p> <p>Background</p> <p>Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example.</p> <p>Methods</p> <p>Eight models were developed: Bayes linear and quadratic models, <it>k</it>-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively.</p> <p>Results</p> <p>Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and <it>k</it>-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, <it>k</it>-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results.</p> <p>Conclusion</p> <p>Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.</p

Cardiosphere-derived cells suppress allogeneic lymphocytes by production of PGE2 acting via the EP4 receptor

derived cells (CDCs) are a cardiac progenitor cell population, which have been shown to possess cardiac regenerative properties and can improve heart function in a variety of cardiac diseases. Studies in large animal models have predominantly focussed on using autologous cells for safety, however allogeneic cell banks would allow for a practical, cost-effective and efficient use in a clinical setting. The aim of this work was to determine the immunomodulatory status of these cells using CDCs and lymphocytes from 5 dogs. CDCs expressed MHC I but not MHC II molecules and in mixed lymphocyte reactions demonstrated a lack of lymphocyte proliferation in response to MHC-mismatched CDCs. Furthermore, MHC-mismatched CDCs suppressed lymphocyte proliferation and activation in response to Concanavalin A. Transwell experiments demonstrated that this was predominantly due to direct cell-cell contact in addition to soluble mediators whereby CDCs produced high levels of PGE2 under inflammatory conditions. This led to down-regulation of CD25 expression on lymphocytes via the EP4 receptor. Blocking prostaglandin synthesis restored both, proliferation and activation (measured via CD25 expression) of stimulated lymphocytes. We demonstrated for the first time in a large animal model that CDCs inhibit proliferation in allo-reactive lymphocytes and have potent immunosuppressive activity mediated via PGE2

The associations between body and knee height measurements and knee joint structure in an asymptomatic cohort

<p>Abstract</p> <p>Background</p> <p>It has been suggested that knee height is a determinant of knee joint load. Nonetheless, no study has directly examined the relationship between anthropometric measures of height and knee joint structures, such as cartilage.</p> <p>Methods</p> <p>89 asymptomatic community-based adults aged 25-62 with no diagnosed history of knee arthropathy were recruited. Anthropometric data (knee height and body height) were obtained by standard protocol, while tibial cartilage volume and defects, as well as bone area were determined from magnetic resonance imaging. Static knee alignment was measured from the joint radiograph.</p> <p>Results</p> <p>All anthropometric height measures were associated with increasing compartmental tibial bone area (<it>p </it>≤ 0.05). Although knee height was associated with tibial cartilage volume (e.g. β = 27 mm³95% CI 7- 48; <it>p </it>= 0.009 for the medial compartment), these relationship no longer remained significant when knee height as a percentage of body height was analysed. Knee height as a percentage of body height was associated with a reduced risk of medial tibial cartilage defects (odds ratio 0.6; 95% confidence interval 0.4 - 1.0; <it>p </it>= 0.05).</p> <p>Conclusion</p> <p>The association between increased anthropometric height measures and increased tibial bone area may reflect inherently larger bony structures. However the beneficial associations demonstrated with cartilage morphology suggest that an increased knee height may confer a beneficial biomechanical environment to the chondrocyte of asymptomatic adults.</p