Children ranging from 3 to 5 years were introduced to two anthropomorphic robots that provided them with information about unfamiliar animals. Children treated the robots as interlocutors. They supplied information to the robots and retained what the robots told them. Children also treated the robots as informants from whom they could seek information. Consistent with studies of children's early sensitivity to an interlocutor's non‐verbal signals, children were especially attentive and receptive to whichever robot displayed the greater non‐verbal contingency. Such selective information seeking is consistent with recent findings showing that although young children learn from others, they are selective with respect to the informants that they question or endorse.

Prior research with preschool children has established that dialogic or active book reading is an effective method for expanding young children’s vocabulary. In this exploratory study, we asked whether similar benefits are observed when a robot engages in dialogic reading with preschoolers. Given the established effectiveness of active reading, we also asked whether this effectiveness was critically dependent on the expressive characteristics of the robot. For approximately half the children, the robot’s active reading was expressive; the robot’s voice included a wide range of intonation and emotion (Expressive). For the remaining children, the robot read and conversed with a flat voice, which sounded similar to a classic text-to-speech engine and had little dynamic range (Flat). The robot’s movements were kept constant across conditions. We performed a verification study using Amazon Mechanical Turk (AMT) to confirm that the Expressive robot was viewed as significantly more expressive, more emotional, and less passive than the Flat robot. We invited 45 preschoolers with an average age of 5 years who were either English Language Learners (ELL), bilingual, or native English speakers to engage in the reading task with the robot. The robot narrated a story from a picture book, using active reading techniques and including a set of target vocabulary words in the narration. Children were post-tested on the vocabulary words and were also asked to retell the story to a puppet. A subset of 34 children performed a second story retelling 4–6 weeks later. Children reported liking and learning from the robot a similar amount in the Expressive and Flat conditions. However, as compared to children in the Flat condition, children in the Expressive condition were more concentrated and engaged as indexed by their facial expressions; they emulated the robot’s story more in their story retells; and they told longer stories during their delayed retelling. Furthermore, children who responded to the robot’s active reading questions were more likely to correctly identify the target vocabulary words in the Expressive condition than in the Flat condition. Taken together, these results suggest that children may benefit more from the expressive robot than from the flat robot.

Atmospheric CO2 observations reveal a decrease in Arctic ecosystem carbon residence time over the past four decades.

[1] This study investigates the changes in winter cold extreme events over East Asia in the present and future climates. Two distinct terms to indicate cold extreme events are analyzed: "cold day," which describes a temperature below a certain threshold value (e.g., simply cold weather), and "cold surge," which describes an abrupt temperature drop (e.g., relatively colder weather than a previous day). We analyze both observations and long-term climate simulations from 13 atmospheric and oceanic coupled global climate models (CGCMs). The geographical distribution of sea level pressure corresponding to a cold day (cold surge) is represented by a dipole (wave train) feature. Although cold day and cold surge show similar patterns of surface air temperature, they are induced by the out-of-phase sea level pressures. From the results of our analysis of a series of future projections for the mid and late twenty-first century using the 13 CGCMs, cold day occurrences clearly decrease with an increasing mean temperature (a correlation coefficient of −0.49), but the correlation between cold surge occurrences and the mean temperature is insignificant (a correlation coefficient of 0.08), which is supported by the same results in recent observation periods . Thus, it is anticipated that cold surge occurrences will remain frequent even in future warmer climate. This deduction is based on the future projections in which the change in the day-to-day temperature variability is insignificant, although the mean temperature shows significant increase. The present results suggest that living things in the future, having acclimatized to a warmer climate, would suffer the strong impact of cold surges, and hence the issue of vulnerability to cold surges should be treated seriously in the future.

BACKGROUND AND OBJECTIVES: Social robots (SRs) are increasingly present in medical and educational contexts, but their use in inpatient pediatric settings has not been demonstrated in studies. In this study, we aimed to (1) describe the introduction of SR technology into the pediatric inpatient setting through an innovative partnership among a pediatric teaching hospital, robotics development, and computational behavioral science laboratories and (2) present feasibility and acceptability data. METHODS: Fifty-four children ages 3 to 10 years were randomly exposed to 1 of 3 interventions: (1) interactive SR teddy bear; (2) tablet-based avatar version of the bear; or (3) plush teddy bear with human presence. We monitored intervention enrollment and completion patterns, obtained qualitative feedback on acceptability of SR use from child life–specialist stakeholders, and assessed children’s positive and negative affect, anxiety, and pain intensity pre- and postintervention. RESULTS: The intervention was well received and appeared feasible, with 93% of those enrolled completing the study (with 80% complete parent data). Children exposed to the SR reported more positive affect relative to those who received a plush animal. SR interactions were characterized by greater levels of joyfulness and agreeableness than comparison interventions. Child life specialist stakeholders reported numerous potential benefits of SR technology in the pediatric setting. CONCLUSIONS: The SR appears to be an engaging tool that may provide new ways to address the emotional needs of hospitalized children, potentially increasing access to emotionally targeted interventions. Rigorous development and validation of SR technology in pediatrics could ultimately lead to scalable and cost-effective tools to improve the patient care experience.

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Children and their parents may undergo challenging experiences when admitted for inpatient care at pediatric hospitals. While most hospitals make efforts to provide socio-emotional support for patients and their families during care, gaps still exist between human resource supply and demand. The Huggable project aims to close this gap by creating a social robot able to mitigate stress, anxiety, and pain in pediatric patients by engaging them in playful interactive activities. In this paper, we introduce a larger experimental design to compare the effects of the Huggable robot to a virtual character on a screen and a plush teddy bear, and provide initial qualitative analyses of patients' and parents' behaviors during intervention sessions collected thus far. We demonstrate preliminarily that children are more eager to emotionally connect with and be physically activated by a robot than a virtual character, illustrating the potential of social robots to provide socio-emotional support during inpatient pediatric care.