Perception and Imitation of Vocally Expressed Emotion in Individuals with Autism Spectrum Disorder

Perception and Imitation of Vocally Expressed Emotion in Individuals with Autism Spectrum Disorder Prior research has shown that individuals with Autism Spectrum Disorder (ASD) have deficits in areas of pitch processing and mimicry. The ability to track linguistic pitch contours is an essential component of emotion perception and communication. This research examines the perception of vocally expressed emotion and vocal mimicry abilities in individuals with ASD. People generally engage in behavioral mimicry in situations in which there is a need to affiliate with a conversational partner. Vocal pitch contour mimicry is one form of mimicry that has been largely neglected, so there isn’t any normative data on this or data from individuals with ASD. College-aged students with ASD were recruited along with age-matched typically developing (TD) participants. The participants were tested for their ability to correctly identify emotion in semantically-controlled vocal expressions of happiness, anger, and sadness in a three-alternative-choice task. In a separate block, participants were also asked to listen to each stimulus and then vocally imitate it to the best of their ability. These vocalizations were recorded. A separate group of raters were asked to evaluate how well each participant mimicked each vocal expression. The results of this study will address whether individuals with ASD have deficits identifying vocal expressions of emotion relative to TD individuals. Additionally, the results will address whether individuals with ASD are able to accurately imitate the vocalizations of others. Keywords: Vocal expression of emotion, Mimicry, Prosody, Pitch perception, Autism Spectrum Disorder

Measuring the Angular Momentum Distribution in Core-Collapse Supernova Progenitors with Gravitational Waves

The late collapse, core bounce, and the early postbounce phase of rotating core collapse leads to a characteristic gravitational wave (GW) signal. The precise shape of the signal is governed by the interplay of gravity, rotation, nuclear equation of state (EOS), and electron capture during collapse. We explore the dependence of the signal on total angular momentum and its distribution in the progenitor core by means of a large set of axisymmetric general-relativistic core collapse simulations in which we vary the initial angular momentum distribution in the core. Our simulations include a microphysical finite-temperature EOS, an approximate electron capture treatment during collapse, and a neutrino leakage scheme for the postbounce evolution. We find that the precise distribution of angular momentum is relevant only for very rapidly rotating cores with T/|W|>~8% at bounce. We construct a numerical template bank from our baseline set of simulations, and carry out additional simulations to generate trial waveforms for injection into simulated advanced LIGO noise at a fiducial galactic distance of 10 kpc. Using matched filtering, we show that for an optimally-oriented source and Gaussian noise, advanced Advanced LIGO could measure the total angular momentum to within ~20%, for rapidly rotating cores. For most waveforms, the nearest known degree of precollapse differential rotation is correctly inferred by both our matched filtering analysis and an alternative Bayesian model selection approach. We test our results for robustness against systematic uncertainties by injecting waveforms from simulations using a different EOS and and variations in the electron fraction in the inner core. The results of these tests show that these uncertainties significantly reduce the accuracy with which the total angular momentum and its precollapse distribution can be inferred from observations.Comment: 22 pages, 16 figure

Genetic Algorithm Guidance of a Constraint Programming Solver for the Multiple Traveling Salesman Problem

This project developed a metaheuristic approach to the Multiple Traveling Salesman Problem that pairs a custom genetic algorithm with a conventional combinatorial optimization solver. This combined approach was used to build an optimal route for two popular radio show hosts to visit each of the 37 Atlanta area Jersey Mike\u27s Subs in one day. This supported a fundraising eort to send children with chronic and terminal illnesses to Disney World through an organization called Bert\u27s Big Adventure. Atlanta-area Jersey Mike\u27s locations donated 100% of proceeds earned on this Day of Giving to Bert\u27s Big Adventure. With the suggested route developed through our approach, the radio hosts successfully visited all 37 Jersey Mike\u27s in one day, a task Bert\u27s Big Adventure staff members had not been able to complete in previous years

Why We Read Wikipedia

Wikipedia is one of the most popular sites on the Web, with millions of users relying on it to satisfy a broad range of information needs every day. Although it is crucial to understand what exactly these needs are in order to be able to meet them, little is currently known about why users visit Wikipedia. The goal of this paper is to fill this gap by combining a survey of Wikipedia readers with a log-based analysis of user activity. Based on an initial series of user surveys, we build a taxonomy of Wikipedia use cases along several dimensions, capturing users' motivations to visit Wikipedia, the depth of knowledge they are seeking, and their knowledge of the topic of interest prior to visiting Wikipedia. Then, we quantify the prevalence of these use cases via a large-scale user survey conducted on live Wikipedia with almost 30,000 responses. Our analyses highlight the variety of factors driving users to Wikipedia, such as current events, media coverage of a topic, personal curiosity, work or school assignments, or boredom. Finally, we match survey responses to the respondents' digital traces in Wikipedia's server logs, enabling the discovery of behavioral patterns associated with specific use cases. For instance, we observe long and fast-paced page sequences across topics for users who are bored or exploring randomly, whereas those using Wikipedia for work or school spend more time on individual articles focused on topics such as science. Our findings advance our understanding of reader motivations and behavior on Wikipedia and can have implications for developers aiming to improve Wikipedia's user experience, editors striving to cater to their readers' needs, third-party services (such as search engines) providing access to Wikipedia content, and researchers aiming to build tools such as recommendation engines.Comment: Published in WWW'17; v2 fixes caption of Table

Young professionals for health development: the Kenyan experience in combating non-communicable diseases

Young individuals (below 35 years) comprise an estimated 60% of the global population. Not only are these individuals currently experiencing chronic, non-communicable diseases (NCDs), either living with or at risk for these conditions, but will also experience the long-term repercussions of the current NCD policy implementations. It is thus imperative that they meaningfully contribute to the global discourse and responses for NCDs at the local level. Here, we profile one example of meaningful engagement: the Young Professionals Chronic Disease Network (YPCDN). The YPCDN is a global online network that provides a platform for young professionals to deliberate new and innovative methods of approaching the NCD challenges facing our societies. We provide a case study of the 2-year experiences of a country chapter (Kenya) of the YPCDN to demonstrate the significance and impact of emerging leaders in addressing the new global health agenda of the 21st century

Fluid and Diffusion Limits for Bike Sharing Systems

Bike sharing systems have rapidly developed around the world, and they are served as a promising strategy to improve urban traffic congestion and to decrease polluting gas emissions. So far performance analysis of bike sharing systems always exists many difficulties and challenges under some more general factors. In this paper, a more general large-scale bike sharing system is discussed by means of heavy traffic approximation of multiclass closed queueing networks with non-exponential factors. Based on this, the fluid scaled equations and the diffusion scaled equations are established by means of the numbers of bikes both at the stations and on the roads, respectively. Furthermore, the scaling processes for the numbers of bikes both at the stations and on the roads are proved to converge in distribution to a semimartingale reflecting Brownian motion (SRBM) in a $N^{2}$-dimensional box, and also the fluid and diffusion limit theorems are obtained. Furthermore, performance analysis of the bike sharing system is provided. Thus the results and methodology of this paper provide new highlight in the study of more general large-scale bike sharing systems.Comment: 34 pages, 1 figure

User-Based Solutions for Increasing Level of Service in Bike-Sharing Transportation Systems

International audienceBike-sharing transportation systems have been well studied from a top-down viewpoint, either for an optimal conception of the system , or for a better statistical understanding of their working mechanisms in the aim of the optimization of the management strategy. Yet bottom-up approaches that could include behavior of users have not been well studied so far. We propose an agent-based model for the short time evolution of a bike-sharing system, with a focus on two strategical parameters that are the role of the quantity of information users have on the all system and the propensity of user to walk after having dropped their bike. We implement the model in a general way so it is applicable to every system as soon as data are available in a certain format. The model of simulation is parametrized and calibrated on processed real time-series of bike movements for the system of Paris. After showing the robustness of the simulations by validating internally and externally the model, we are able to test different user-based strategies for an increase of the level of service. In particular, we show that an increase of user information can have significant impact on the homogeneity of repartition of bikes in docking stations, and, what is important for a future implementation of the strategy, that an action on only 30% of regular users is enough to obtain most of the possible amelioration

Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from the age of 6 to 11 years

Background: Child and adolescent overweight and obesity has increased globally, and can be associated with significant short- and longterm health consequences. This is an update of a Cochrane Review published first in 2003, and updated previously in 2009. However, the update has now been split into six reviews addressing different childhood obesity treatments at different ages. Objectives: To assess the effects of diet, physical activity and behavioural interventions (behaviour-changing interventions) for the treatment of overweight or obese children aged 6 to 11 years. Search methods: We searched CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, LILACS as well as trial registers ClinicalTrials.gov and RsdI1401 Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from th... 2 / 499 ICTRP Search Portal. We checked references of studies and systematic reviews. We did not apply any language restrictions. The date of the last search was July 2016 for all databases. Selection criteria: We selected randomised controlled trials (RCTs) of diet, physical activity, and behavioural interventions (behaviour-changing interventions) for treating overweight or obese children aged 6 to 11 years, with a minimum of six months' follow-up. We excluded interventions that specifically dealt with the treatment of eating disorders or type 2 diabetes, or included participants with a secondary or syndromic cause of obesity. Data collection and analysis Two review authors independently screened references, extracted data, assessed risk of bias, and evaluated the quality of the evidence using the GRADE instrument. We contacted study authors for additional information. We carried out metaanalyses according to the statistical guidelines in the Cochrane Handbook for Systematic Reviews of Interventions. Main results: We included 70 RCTs with a total of 8461 participants randomised to either the intervention or control groups. The number of participants per trial ranged from 16 to 686. Fifty-five trials compared a behaviour-changing intervention with no treatment/usual care control and 15 evaluated the effectiveness of adding an additional component to a behaviour-changing intervention. Sixty-four trials were parallel RCTs, and four were cluster RCTs. Sixty-four trials were multicomponent, two were diet only and four were physical activity only interventions. Ten trials had more than two arms. The overall quality of the evidence was low or very low and 62 trials had a high risk of bias for at least one criterion. Total duration of trials ranged from six months to three years. The median age of participants was 10 years old and the median BMI z score was 2.2. Primary analyses demonstrated that behaviour-changing interventions compared to no treatment/usual care control at longest follow-up reduced BMI, BMI z score and weight. Mean difference (MD) in BMI was -0.53 kg/m2 (95% confidence interval (CI) -0.82 to -0.24); P < 0.00001; 24 trials; 2785 participants; low-quality evidence. MD in BMI z score was -0.06 units (95% CI -0.10 to -0.02); P = 0.001; 37 trials; 4019 participants; low-quality evidence and MD in weight was -1.45 kg (95% CI -1.88 to -1.02); P < 0.00001; 17 trials; 1774 participants; low-quality evidence. Thirty-one trials reported on serious adverse events, with 29 trials reporting zero occurrences RR 0.57 (95% CI 0.17 to 1.93); P = 0.37; 4/2105 participants in the behaviour-changing intervention groups compared with 7/1991 participants in the comparator groups). Few trials reported health-related quality of life or behaviour change outcomes, and none of the analyses demonstrated a substantial difference in these outcomes between intervention and control. In two trials reporting on minutes per day of TV viewing, a small reduction of 6.6 minutes per day (95% CI -12.88 to -0.31), P = 0.04; 2 trials; 55 participants) was found in favour of the intervention. No trials reported on all-cause mortality, morbidity or socioeconomic effects, and few trials reported on participant views; none of which could be meta-analysed. As the meta-analyses revealed substantial heterogeneity, we conducted subgroup analyses to examine the impact of type of comparator, type of intervention, risk of attrition bias, setting, duration of post-intervention follow-up period, parental involvement and baseline BMI z score. No subgroup effects were shown for any of the subgroups on any of the outcomes. Some data indicated that a reduction in BMI immediately post-intervention was no longer evident at follow-up at less than six months, which has to be investigated in further trials. Authors' conclusions: Multi-component behaviour-changing interventions that incorporate diet, physical activity and behaviour change may be beneficial in achieving small, short-term reductions in BMI, BMI z score and weight in children aged 6 to 11 years. The evidence suggests a very low occurrence of adverse events. The quality of the evidence was low or very low. The heterogeneity observed across all outcomes was not explained by subgrouping. Further research is required of behaviourchanging interventions in lower income countries and in children from different ethnic groups; also on the impact of behaviour-changing interventions on health-related quality of life and comorbidities. The sustainability of reduction in BMI/BMI z score and weight is a key consideration and there is a need for longer-term follow-up and further research on the most appropriate forms of post-intervention maintenance in order to ensure intervention benefits are sustained over the longer term