The Liking Gap in Conversations: Do People Like Us More Than We Think?

Having conversations with new people is an important and rewarding part of social life. Yet conversations can also be intimidating and anxiety provoking, and this makes people wonder and worry about what their conversation partners really think of them. Are people accurate in their estimates? We found that following interactions, people systematically underestimated how much their conversation partners liked them and enjoyed their company, an illusion we call the liking gap. We observed the liking gap as strangers got acquainted in the laboratory, as first-year college students got to know their dorm mates, and as formerly unacquainted members of the general public got to know each other during a personal development workshop. The liking gap persisted in conversations of varying lengths and even lasted for several months, as college dorm mates developed new relationships. Our studies suggest that after people have conversations, they are liked more than they know

Cardiovascular disease risk assessment and reduction: summary of updated NICE guidance

NICE recommendations are based on systematic reviews of the best available evidence and explicit consideration of cost effectiveness. When minimal evidence is available, recommendations are based on the guideline committee's (GC's) experience and opinion of what constitutes good practice. Evidence levels for the recommendations are given in italic in square brackets. Definitions of evidence certainty are given in box 1

Causal connectivity of evolved neural networks during behavior

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics

Use of re-randomized data in meta-analysis

BACKGROUND: Outcomes collected in randomized clinical trials are observations of random variables that should be independent and identically distributed. However, in some trials, the patients are randomized more than once thus violating both of these assumptions. The probability of an event is not always the same when a patient is re-randomized; there is probably a non-zero covariance coming from observations on the same patient. This is of particular importance to the meta-analysts. METHODS: We developed a method to estimate the relative error in the risk differences with and without re-randomization of the patients. The relative error can be estimated by an expression depending on the percentage of the patients who were re-randomized, multipliers (how many times more likely it is to repeat an event) for the probability of reoccurrences, and the ratio of the total events reported and the initial number of patients entering the trial. RESULTS: We illustrate our methods using two randomized trials testing growth factors in febrile neutropenia. We showed that under some circumstances the relative error of taking into account re-randomized patients was sufficiently small to allow using the results in the meta-analysis. Our findings indicate that if the study in question is of similar size to other studies included in the meta-analysis, the error introduced by re-randomization will only minimally affect meta-analytic summary point estimate. We also show that in our model the risk ratio remains constant during the re-randomization, and therefore, if a meta-analyst is concerned about the effect of re-randomization on the meta-analysis, one way to sidestep the issue and still obtain reliable results is to use risk ratio as the measure of interest. CONCLUSION: Our method should be helpful in the understanding of the results of clinical trials and particularly helpful to the meta-analysts to assess if re-randomized patient data can be used in their analyses

Tracking Target Signal Strengths on a Grid using Sparsity

Multi-target tracking is mainly challenged by the nonlinearity present in the measurement equation, and the difficulty in fast and accurate data association. To overcome these challenges, the present paper introduces a grid-based model in which the state captures target signal strengths on a known spatial grid (TSSG). This model leads to \emph{linear} state and measurement equations, which bypass data association and can afford state estimation via sparsity-aware Kalman filtering (KF). Leveraging the grid-induced sparsity of the novel model, two types of sparsity-cognizant TSSG-KF trackers are developed: one effects sparsity through $\ell_1$-norm regularization, and the other invokes sparsity as an extra measurement. Iterative extended KF and Gauss-Newton algorithms are developed for reduced-complexity tracking, along with accurate error covariance updates for assessing performance of the resultant sparsity-aware state estimators. Based on TSSG state estimates, more informative target position and track estimates can be obtained in a follow-up step, ensuring that track association and position estimation errors do not propagate back into TSSG state estimates. The novel TSSG trackers do not require knowing the number of targets or their signal strengths, and exhibit considerably lower complexity than the benchmark hidden Markov model filter, especially for a large number of targets. Numerical simulations demonstrate that sparsity-cognizant trackers enjoy improved root mean-square error performance at reduced complexity when compared to their sparsity-agnostic counterparts.Comment: Submitted to IEEE Trans. on Signal Processin

Capturing egocentric biases in reference reuse during collaborative dialogue

Words that are produced aloud—and especially self-produced ones—are remembered better than words that are not, a phenomenon labeled the production effect in the field of memory research. Two experiments were conducted to determine whether this effect can be generalized to dialogue, and how it might affect dialogue management. Triads (Exp. 1) or dyads (Exp. 2) of participants interacted to perform a collaborative task. Analyzing reference reuse during the interaction revealed that the participants were more likely to reuse the references that they had presented themselves, on the one hand, and those that had been accepted through verbatim repetition, on the other. Analyzing reference recall suggested that the greater accessibility of self-presented references was only transient. Moreover, among partner-presented references, those discussed while the participant had actively taken part in the conversation were more likely to be recalled than those discussed while the participant had been inactive. These results contribute to a better understanding of how individual memory processes might contribute to collaborative dialogue

Clinical and cost effectiveness of mechanical support for severe ankle sprains: design of a randomised controlled trial in the emergency department [ISRCTN 37807450]

Background The optimal management for severe sprains (Grades II and III) of the lateral ligament complex of the ankle is unclear. The aims of this randomised controlled trial are to estimate (1) the clinical effectiveness of three methods of providing mechanical support to the ankle (below knee cast, Aircast® brace and Bledsoe® boot) in comparison to Tubigrip®, and (2) to compare the cost of each strategy, including subsequent health care costs. Methods/design Six hundred and fifty people with a diagnosis of severe sprain are being identified through emergency departments. The study has been designed to complement routine practice in the emergency setting. Outcomes are recovery of mobility (primary outcome) and usual activity, residual symptoms and need for further medical, rehabilitation or surgical treatment. Parallel economic and qualitative studies are being conducted to aid interpretation of the results and to evaluate the cost-effectiveness of the interventions. Discussion This paper highlights the design, methods and operational aspects of a clinical trial of acute injury management in the emergency department

Collaborative Gaze Channelling for Improved Cooperation During Robotic Assisted Surgery

The use of multiple robots for performing complex tasks is becoming a common practice for many robot applications. When different operators are involved, effective cooperation with anticipated manoeuvres is important for seamless, synergistic control of all the end-effectors. In this paper, the concept of Collaborative Gaze Channelling (CGC) is presented for improved control of surgical robots for a shared task. Through eye tracking, the fixations of each operator are monitored and presented in a shared surgical workspace. CGC permits remote or physically separated collaborators to share their intention by visualising the eye gaze of their counterparts, and thus recovers, to a certain extent, the information of mutual intent that we rely upon in a vis-à-vis working setting. In this study, the efficiency of surgical manipulation with and without CGC for controlling a pair of bimanual surgical robots is evaluated by analysing the level of coordination of two independent operators. Fitts' law is used to compare the quality of movement with or without CGC. A total of 40 subjects have been recruited for this study and the results show that the proposed CGC framework exhibits significant improvement (p<0.05) on all the motion indices used for quality assessment. This study demonstrates that visual guidance is an implicit yet effective way of communication during collaborative tasks for robotic surgery. Detailed experimental validation results demonstrate the potential clinical value of the proposed CGC framework. © 2012 Biomedical Engineering Society.link_to_subscribed_fulltex

The time-dependent expression of keratins 5 and 13 during the reepithelialization of human skin wounds

The time-dependent reepithelialization of 55 human surgical skin wounds with a wound age between 8h and more than 2 months was investigated by the immunohistochemical localization of cytokeratins 5 and 13. A complete, rebuilt epidermal layer over the wound area was first detectable in a 5-day-old wound, while all wounds of more than 18 days duration contained a completely reepithelialized wound area. Between 5 and 18 days the basal layer of keratinocytes showed — in contrast to normal skin — only some cells positive for cytokeratin 5. In some, but not all lesions with a wound age of 13 days or more, a basal cell layer completely staining for cytokeratin 5 was demonstrable. This staining pattern was found in all skin wounds with a wound age of more than 23 days. The immunohistochemical detection of cytokeratin 13 which can be observed regularly in non-cornifying squamous epithelia provides no information for the time-estimation of human skin wounds, since no significant temporary expression of this polypeptide seems to occur during the healing of human skin wounds