Attachment preference in auditory German sentences: Individual differences and pragmatic strategy

Relative clauses modify a preceding element, but as this element can be flexibly located, the point of attachment is sometimes ambiguous. Preference for this attachment can vary within languages such as German, yet explanations for differences in attachment preference related to cognitive strategies or constraints have been conflicting in the current literature. The present study aimed to assess the preference for relative clause attachment among German listeners and whether these preferences could be explained by strategy or individual differences in working memory or musical rhythm ability. We performed a sentence completion experiment, conducted post hoc interviews, and measured working memory and rhythm abilities with diagnostic tests. German listeners had no homogeneous attachment preference, although participants consistently completed individual sentences across trials according to the general preference that they reported offline. Differences in attachment preference were moreover not linked to individual differences in either working memory or musical rhythm ability. However, the pragmatic content of individual sentences sometimes overrode the general syntactic preference in participants with lower rhythm ability. Our study makes an important contribution to the field of psycholinguistics by validating offline self-reports as a reliable diagnostic for an individual’s online relative clause attachment preference. The link between pragmatic strategy and rhythm ability is an interesting direction for future research

A Mobile App to Aid Smoking Cessation: Preliminary Evaluation of SmokeFree28

Background: Little is known about the effectiveness of mobile apps in aiding smoking cessation or their validity for automated collection of data on smoking cessation outcomes. Objective: We conducted a preliminary evaluation of SF28 (SF28 is the name of the app, short for SmokeFree28)—an app aimed at helping smokers to be smoke-free for 28 days. / Methods: Data on sociodemographic characteristics, smoking history, number of logins, and abstinence at each login were uploaded to a server from SF28 between August 2012 and August 2013. Users were included if they were aged 16 years or over, smoked cigarettes at the time of registration, had set a quit date, and used the app at least once on or after their quit date. Their characteristics were compared with data from a representative sample of smokers trying to stop smoking in England. The percentage of users recording 28 days of abstinence was compared with a value of 15% estimated for unaided quitting. Correlations were assessed between recorded abstinence for 28 days and well-established abstinence predictors. / Results: A total of 1170 users met the inclusion criteria. Compared with smokers trying to quit in England, they had higher consumption, and were younger, more likely to be female, and had a non-manual rather than manual occupation. In total, 18.9% (95% CI 16.7-21.1) were recorded as being abstinent from smoking for 28 days or longer. The mean number of logins was 8.5 (SD 9.0). The proportion recording abstinence for 28 days or longer was higher in users who were older, in a non-manual occupation, and in those using a smoking cessation medication. / Conclusions: The recorded 28-day abstinence rates from the mobile app, SF28, suggest that it may help some smokers to stop smoking. Further evaluation by means of a randomized trial appears to be warranted

Prospective cohort study of the effectiveness of varenicline versus nicotine replacement therapy for smoking cessation in the "real world"

It is important to know the comparative effectiveness of varenicline and nicotine replacement therapy (NRT) for smoking cessation when prescribed under routine circumstances and in the general population. Previous estimates relied on cross-sectional data. The objective of the current study was to use longitudinal data to compare the abstinence rates of smokers trying to stop having used varenicline versus NRT on prescription (Rx) when provided with minimal professional support in the general population while adjusting for key potential confounders

The ensemble of random Markov matrices

The ensemble of random Markov matrices is introduced as a set of Markov or stochastic matrices with the maximal Shannon entropy. The statistical properties of the stationary distribution pi, the average entropy growth rate $h$ and the second largest eigenvalue nu across the ensemble are studied. It is shown and heuristically proven that the entropy growth-rate and second largest eigenvalue of Markov matrices scale in average with dimension of matrices d as h ~ log(O(d)) and nu ~ d^(-1/2), respectively, yielding the asymptotic relation h tau_c ~ 1/2 between entropy h and correlation decay time tau_c = -1/log|nu| . Additionally, the correlation between h and and tau_c is analysed and is decreasing with increasing dimension d.Comment: 12 pages, 6 figur

Dynamic Facial Expressions Prime the Processing of Emotional Prosody

Evidence suggests that emotion is represented supramodally in the human brain. Emotional facial expressions, which often precede vocally expressed emotion in real life, can modulate event-related potentials (N100 and P200) during emotional prosody processing. To investigate these cross-modal emotional interactions, two lines of research have been put forward: cross-modal integration and cross-modal priming. In cross-modal integration studies, visual and auditory channels are temporally aligned, while in priming studies they are presented consecutively. Here we used cross-modal emotional priming to study the interaction of dynamic visual and auditory emotional information. Specifically, we presented dynamic facial expressions (angry, happy, neutral) as primes and emotionally-intoned pseudo-speech sentences (angry, happy) as targets. We were interested in how prime-target congruency would affect early auditory event-related potentials, i.e., N100 and P200, in order to shed more light on how dynamic facial information is used in cross-modal emotional prediction. Results showed enhanced N100 amplitudes for incongruently primed compared to congruently and neutrally primed emotional prosody, while the latter two conditions did not significantly differ. However, N100 peak latency was significantly delayed in the neutral condition compared to the other two conditions. Source reconstruction revealed that the right parahippocampal gyrus was activated in incongruent compared to congruent trials in the N100 time window. No significant ERP effects were observed in the P200 range. Our results indicate that dynamic facial expressions influence vocal emotion processing at an early point in time, and that an emotional mismatch between a facial expression and its ensuing vocal emotional signal induces additional processing costs in the brain, potentially because the cross-modal emotional prediction mechanism is violated in case of emotional prime-target incongruency

Characteristics of Vehicular Traffic Flow at a Roundabout

We construct a stochastic cellular automata model for the description of vehicular traffic at a roundabout designed at the intersection of two perpendicular streets. The vehicular traffic is controlled by a self-organized scheme in which traffic lights are absent. This controlling method incorporates a yield-at-entry strategy for the approaching vehicles to the circulating traffic flow in the roundabout. Vehicular dynamics is simulated within the framework of the probabilistic cellular automata and the delay experienced by the traffic at each individual street is evaluated for specified time intervals. We discuss the impact of the geometrical properties of the roundabout on the total delay. We compare our results with traffic-light signalisation schemes, and obtain the critical traffic volume over which the intersection is optimally controlled through traffic light signalisation schemes.Comment: 10 pages, 17 eps figures. arXiv admin note: text overlap with arXiv:cond-mat/040107

Characterising University WLANs within Eduroam Context

The eduroam initiative is assuming an ever growing relevance in providing a secure, worldwide roaming access within the university WLAN context. Although several studies have focused on educational WLAN traffic characterisation, the increasing variety of devices, mobility scenarios and user applications, motivate assessing the effective use of eduroam in order to sustain consistent network planning and deployment. Based on recent WLAN traffic traces collected at the University of Minho (Portugal) and University of Vigo (Spain), the present work contributes for identifying and characterising patterns of user behaviour regarding, for instance, the location and activity sector of users. The results of data analysis quantify the impact of network access location on the number of associated users, on the number and duration of sessions and corresponding traffic volumes. The results also illustrate to what extent users take advantage of mobility in the WLAN. Complementing the analysis on a monthly basis, a fine grain study of WLAN traffic is provided through the identification of users' behaviour and patterns in small timescales

Characterising smoking cessation smartphone applications in terms of behaviour change techniques, engagement and ease-of-use features

The aim of this study was to assess whether or not behaviour change techniques (BCTs) as well as engagement and ease-of-use features used in smartphone applications (apps) to aid smoking cessation can be identified reliably. Apps were coded for presence of potentially effective BCTs, and engagement and ease-of-use features. Inter-rater reliability for this coding was assessed. Inter-rater agreement for identifying presence of potentially effective BCTs ranged from 66.8 to 95.1 % with ‘prevalence and bias adjusted kappas’ (PABAK) ranging from 0.35 to 0.90 (p 50 % for rewarding abstinence. The average proportions of specified engagement and ease-of-use features included in the apps were 69 and 83 %, respectively. The study found that it is possible to identify potentially effective BCTs, and engagement and ease-of-use features in smoking cessation apps with fair to high inter-rater reliability

Statistical mixing and aggregation in Feller diffusion

We consider Feller mean-reverting square-root diffusion, which has been applied to model a wide variety of processes with linearly state-dependent diffusion, such as stochastic volatility and interest rates in finance, and neuronal and populations dynamics in natural sciences. We focus on the statistical mixing (or superstatistical) process in which the parameter related to the mean value can fluctuate - a plausible mechanism for the emergence of heavy-tailed distributions. We obtain analytical results for the associated probability density function (both stationary and time dependent), its correlation structure and aggregation properties. Our results are applied to explain the statistics of stock traded volume at different aggregation scales.Comment: 16 pages, 3 figures. To be published in Journal of Statistical Mechanics: Theory and Experimen