Flexible Lithium-Ion Batteries with High Areal Capacity Enabled by Smart Conductive Textiles.

Increasing demand for flexible devices in various applications, such as smart watches, healthcare, and military applications, requires the development of flexible energy-storage devices, such as lithium-ion batteries (LIBs) with high flexibility and capacity. However, it is difficult to ensure high capacity and high flexibility simultaneously through conventional electrode preparation processes. Herein, smart conductive textiles are employed as current collectors for flexible LIBs owing to their inherent flexibility, fibrous network, rough surface for better adhesion, and electrical conductivity. Conductivity and flexibility are further enhanced by nanosizing lithium titanate oxide (LTO) and lithium iron phosphate (LFP) active materials, and hybridizing them with a flexible 2D graphene template. The resulting LTO/LFP full cells demonstrate high areal capacity and flexibility with tolerance to mechanical fatigue. The battery achieves a capacity of 1.2 mA h cm-2 while showing excellent flexibility. The cells demonstrate stable open circuit voltage retention under repeated flexing for 1000 times at a bending radius of 10 mm. The discharge capacity of the unflexed battery is retained in cells subjected to bending for 100 times at bending radii of 30, 20, and 10 mm, respectively, confirming that the suggested electrode configuration successfully prevents structural damage (delamination or cracking) upon repeated deformation.

Monitoring heavy metals, residual agricultural chemicals and sulfites in traditional herbal decoctions.

BACKGROUND: Asian traditional herbal preparations are frequently considered for the contamination with undeclared toxic or hazardous substances. The aim of this study was to determine the toxic heavy metals, pesticides and sulfur dioxide in decoctions that is a common form of final utilization in Korea. METHODS: A total of 155 decoctions composed of multi-ingredient traditional herbs were randomly sampled from Seoul in Korea between 2013 and 2014. For each decoction, the concentrations of four heavy metals (arsenic, cadmium, lead and mercury), 33 pesticides and sulfur dioxide were analyzed using inductively coupled plasma mass spectrometry (ICP-MS), mercury analyzer, gas chromatography/nitrogen phosphorous detector (GC/NPD), gas chromatography/micro electron capture detector (GC/µECD), and Monier-Williams method respectively. RESULTS: One hundred fifty-two of One hundred fifty-five decoctions (98.1%) contained one of three heavy metals (96.1% for As, 97.4% for Cd, and 90.3% for Pb, 0.0% for Hg). Their average concentrations (77.0 ± 79.7 ug/kg for As, 20.4 ± 23.7 ug/kg for Cd, and 68.8 ± 76.5 ug/kg for Pb) were approximately 20% of the maximum allowable limits of vegetable or ginseng beverage described in the Korean Food Standard Codex while their 95th percentile concentrations were below than the guideline for them. None of 33 pesticides was detected in 155 decoction samples, and only one sample showed over limit of detection for residual sulfites. CONCLUSIONS: This study support that the contained status of toxic heavy metals, pesticides and sulfur dioxide in herbal decoctions are currently within safe level in Korea, and provide a reference data for the further studies focused on the safety herbal preparations.

Pre-operative CT predictors associated with 30-day adverse events in patients with appendiceal inflammatory masses who underwent immediate appendectomies.

PURPOSE: To retrospectively evaluate pre-operative CT predictors that are associated with 30-day adverse events in patients who underwent immediate appendectomies for appendiceal inflammatory masses. METHODS: This retrospective study was approved by our institutional review board, and the requirement for informed consent was waived. One hundred forty-four consecutive patients who underwent immediate appendectomies and were diagnosed with appendiceal inflammatory masses by pre-operative CT from January 2005 to December 2013 at a tertiary hospital were included. The main outcome measure was 30-day adverse events. Patient demographics and data for inflammatory markers including leukocyte counts, segmented neutrophils, and C-reactive protein levels were collected by a single radiologist. Pre- and post-operative CT findings were evaluated for features of appendiceal inflammatory masses, associated findings, and post-operative adverse events by two radiologists in a blinded fashion with consensus to assess surgical and pathologic results, post-operative outcomes, and original CT interpretations. Appendiceal inflammatory masses were defined as complicated appendicitis with a phlegmon or an abscess that was identified on pre-operative CT exam. Factors associated with 30-day adverse events were assessed using logistic regression analysis. RESULTS: A total of 22 (15%) of the 144 patients (mean age [±SD] 44.6 ± 22.0 years, range 3-97 years) experienced 30-day adverse events: ten intra-abdominal abscesses, three wound infections, two cases of peritonitis, two small bowel obstructions, two intra-abdominal abscesses with peritonitis, one intra-abdominal abscess with wound infection, one intra-abdominal abscess with small bowel obstruction, and one case of peritonitis with small bowel obstruction. In univariate analysis, the presence of appendicolith (odds ratio [OR] 2.49, p = 0.048) and high-grade obstruction (OR 3.79; p = 0.01) were associated with adverse events. High-grade obstruction (adjusted OR 3.05; p = 0.04) was the only independent pre-operative predictor associated with 30-day adverse events in patients with appendiceal inflammatory masses. CONCLUSIONS: High-grade obstruction was an independent pre-operative CT predictor associated with 30-day adverse events in patients who underwent immediate appendectomies for appendiceal inflammatory masses.

Preoperative prediction model for conversion of laparoscopic to open cholecystectomy in patient with acute cholecystitis: based on clinical, laboratory, and CT parameters.

OBJECTIVE: To identify preoperative computed tomography (CT) predictors associated with conversion from laparoscopic to open cholecystectomy and to propose the risk scoring model for prediction of conversion by integrating clinical, laboratory, and CT parameters. METHODS: The institutional review board approved this retrospective study, and informed consent was waived. One hundred eighty-three patients who underwent a laparoscopic cholecystectomy for acute cholecystitis were evaluated for clinical, laboratory, and CT parameters. Associations between conversion and these parameters were assessed by using univariate and multivariate logistic regression analysis. The risk scoring model was devised using a regression coefficient-based scoring method. RESULTS: Conversion to open cholecystectomy was performed in 30 patients (17%). Multivariate analysis identified age older than 60 years, male, and pericholecystic fluid as independent predictors of conversion. The preoperative prediction model to calculate the risk score for conversion showed sensitivity of 83% and specificity of 72%, with an area under the receiver operator curve of 0.83. CONCLUSIONS: Pericholecystic fluid collection was the only CT parameter with clinical parameters of age older than 60 years and male in prediction for conversion in acute cholecystitis. The preoperative prediction model using these 3 parameters can be adapted easily in clinical practice with a good discrimination.

Differentiation of early perforated from nonperforated appendicitis: MDCT findings, MDCT diagnostic performance, and clinical outcome.

To determine the CT findings and assess their diagnostic performance in differentiating early perforated appendicitis from nonperforated appendicitis, and to compare therapeutic approaches and clinical outcomes between two types of appendicitis. Our retrospective study was approved by our institutional review board and informed consent was waived. From July 2012 to July 2013, 339 patients [mean age 40.8 years; age range 19-80 years; 183 male (mean age 40.5 years; age range 19-79 years) and 156 female (mean age 41.2 years; age range 19-80 years)] who underwent appendectomy with preoperative CT examination for suspected acute appendicitis were included, with exclusion of 37 patients with specific CT findings for advanced perforated appendicitis. And they were categorized into nonperforated and early perforated appendicitis groups according to surgical and pathologic reports. The following CT findings were evaluated by two radiologists blinded to pathologic and surgical findings: transverse diameter of the appendix, thickness of the appendiceal wall, the depth of intraluminal appendiceal fluid, appendiceal wall enhancement, presence or absence of focal defect in the appendiceal wall, intraluminal appendiceal air, appendicolith/fecalith, periappendiceal changes, cecal wall thickening, and free fluid. The type of surgical procedures, performance of surgical drainage, and the length of hospital stay were recorded. Univariate and multivariate logistic regression analysis were used to determine the CT findings for differentiating early perforated appendicitis from nonperforated appendicitis, a total of 75 (22%) of the 339 patients was diagnosed with early perforated appendicitis. Focal wall defect [adjusted odds ratio (aOR), 23.40; p < 0.001], circumferential periappendiceal changes (aOR, 5.63; p < 0.001), appendicoliths/fecaliths (aOR, 2.47; p = 0.015), and transverse diameter of the appendix (aOR, 1.22; p = 0.003) were independently differentiating variables for early perforated appendicitis. The transverse diameter of the appendix (≥11 mm) had the highest sensitivity (62.7%) and focal wall defect in the appendiceal wall showed the highest specificity (98.8%). The prevalence of surgical drainage was higher (p = 0.001) and the mean hospital stay was approximately one day longer (p < 0.001) in the early perforated group than nonperforated group. CT can be helpful in differentiating early perforated appendicitis from nonperforated appendicitis, although the sensitivity of the evaluated findings was somewhat limited.

Promising directions for human-robot interactions defined by older adults.

Introduction: Older adults are engaging more and more with voice-based agent and social robot technologies, and roboticists are increasingly designing interactions for these systems with older adults in mind. Older adults are often not included in these design processes, yet there are many opportunities for older adults to collaborate with design teams to design future robot interactions and help guide directions for robot development. Methods: Through a year-long co-design project, we collaborated with 28 older adults to understand the key focus areas that older adults see promise in for older adult-robot interaction in their everyday lives and how they would like these interactions to be designed. This paper describes and explores the robot-interaction guidelines and future directions identified by older adults, specifically investigating the change and trajectory of these guidelines through the course of the co-design process from the initial interview to the design guideline generation session to the final interview. Results were analyzed through an adapted ethnographic decision tree modeling approach to understand older adults' decision making surrounding the various focus areas and guidelines for social robots. Results: Overall, over the course of the co-design process between the beginning and end, older adults developed a better understanding of the robot that translated to them being more certain of their attitudes of how they would like a robot to engage with them in their lives. Older adults were more accepting of transactional functions such as reminders and scheduling and less open to functions that would involve sharing sensitive information and tracking and/or monitoring of them, expressing concerns around surveillance. There was some promise in robot interactions for connecting with others, body signal monitoring, and emotional wellness, though older adults brought up concerns around autonomy, privacy, and naturalness of the interaction with a robot that need to be further explored. Discussion: This work provides guidance for future interaction development for robots that are being designed to interact with older adults and highlights areas that need to be further investigated with older adults to understand how best to design for user concerns.

Empathy Toward Artificial Intelligence Versus Human Experiences and the Role of Transparency in Mental Health and Social Support Chatbot Design: Comparative Study.

BACKGROUND: Empathy is a driving force in our connection to others, our mental well-being, and resilience to challenges. With the rise of generative artificial intelligence (AI) systems, mental health chatbots, and AI social support companions, it is important to understand how empathy unfolds toward stories from human versus AI narrators and how transparency plays a role in user emotions. OBJECTIVE: We aim to understand how empathy shifts across human-written versus AI-written stories, and how these findings inform ethical implications and human-centered design of using mental health chatbots as objects of empathy. METHODS: We conducted crowd-sourced studies with 985 participants who each wrote a personal story and then rated empathy toward 2 retrieved stories, where one was written by a language model, and another was written by a human. Our studies varied disclosing whether a story was written by a human or an AI system to see how transparent author information affects empathy toward the narrator. We conducted mixed methods analyses: through statistical tests, we compared user's self-reported state empathy toward the stories across different conditions. In addition, we qualitatively coded open-ended feedback about reactions to the stories to understand how and why transparency affects empathy toward human versus AI storytellers. RESULTS: We found that participants significantly empathized with human-written over AI-written stories in almost all conditions, regardless of whether they are aware (t196=7.07, P<.001, Cohen d=0.60) or not aware (t298=3.46, P<.001, Cohen d=0.24) that an AI system wrote the story. We also found that participants reported greater willingness to empathize with AI-written stories when there was transparency about the story author (t494=-5.49, P<.001, Cohen d=0.36). CONCLUSIONS: Our work sheds light on how empathy toward AI or human narrators is tied to the way the text is presented, thus informing ethical considerations of empathetic artificial social support or mental health chatbots.

A Robotic Companion for Psychological Well-being: A Long-term Investigation of Companionship and Therapeutic Alliance.

Social support plays a crucial role in managing and enhancing one's mental health and well-being. In order to explore the role of a robot's companion-like behavior on its therapeutic interventions, we conducted an eight-week-long deployment study with seventy participants to compare the impact of (1) a control robot with only assistant-like skills, (2) a coach-like robot with additional instructive positive psychology interventions, and (3) a companion-like robot that delivered the same interventions in a peer-like and supportive manner. The companion-like robot was shown to be the most effective in building a positive therapeutic alliance with people, enhancing participants' well-being and readiness for change. Our work offers valuable insights into how companion AI agents could further enhance the efficacy of the mental health interventions by strengthening their therapeutic alliance with people for long-term mental health support.

Deploying a robotic positive psychology coach to improve college students' psychological well-being.

Despite the increase in awareness and support for mental health, college students' mental health is reported to decline every year in many countries. Several interactive technologies for mental health have been proposed and are aiming to make therapeutic service more accessible, but most of them only provide one-way passive contents for their users, such as psycho-education, health monitoring, and clinical assessment. We present a robotic coach that not only delivers interactive positive psychology interventions but also provides other useful skills to build rapport with college students. Results from our on-campus housing deployment feasibility study showed that the robotic intervention showed significant association with increases in students' psychological well-being, mood, and motivation to change. We further found that students' personality traits were associated with the intervention outcomes as well as their working alliance with the robot and their satisfaction with the interventions. Also, students' working alliance with the robot was shown to be associated with their pre-to-post change in motivation for better well-being. Analyses on students' behavioral cues showed that several verbal and nonverbal behaviors were associated with the change in self-reported intervention outcomes. The qualitative analyses on the post-study interview suggest that the robotic coach's companionship made a positive impression on students, but also revealed areas for improvement in the design of the robotic coach. Results from our feasibility study give insight into how learning users' traits and recognizing behavioral cues can help an AI agent provide personalized intervention experiences for better mental health outcomes.

Agile and versatile climbing on ferromagnetic surfaces with a quadrupedal robot.

A climbing robot that can rapidly move on diverse surfaces such as floors, walls, and ceilings will have an enlarged operational workspace compared with other terrestrial robots. However, the climbing skill of robots in such environments has been limited to low speeds or simple locomotion tasks. Here, we present an untethered quadrupedal climbing robot called MARVEL (magnetically adhesive robot for versatile and expeditious locomotion), capable of agile and versatile climbing locomotion in ferromagnetic environments. MARVEL excels over prior climbing robots in terms of climbing speed and ability to execute various motions. It demonstrates the fastest vertical and inverted walking speed, whereas its versatile locomotion ability enables the highest number of gaits and locomotion tasks. The key innovations are an integrated foot design using electropermanent magnets and magnetorheological elastomers that provide large adhesion and traction forces, torque control actuators, and a model predictive control framework adapted for stable climbing. In experiments, the robot achieved locomotion on ceilings and vertical walls up to 0.5 meter (1.51 body lengths) per second and 0.7 meter (2.12 body lengths) per second, respectively. Furthermore, the robot exhibited complex behaviors such as stepping over 10-centimeter-wide gaps; overcoming 5-centimeter-high obstacles; and making transitions between floors, walls, and ceilings. We also show that MARVEL could climb on a curved surface of a storage tank covered with up to 0.3-millimeter-thick paint with rust and dust.

Monitoring Cellular Immune Responses after Consumption of Selected Probiotics in Immunocompromised Mice.

Probiotics are currently considered as one of tools to modulate immune responses under specific clinical conditions. The purpose of this study was to evaluate whether oral administration of three different probiotics (Lactiplantibacillus plantarum CJLP243, CJW55-10, and CJLP475) could evoke a cell-mediated immunity in immunodeficient mice. Before conducting in vivo experiments, we examined the in vitro potency of these probiotics for macrophage activation. After co-culture with these probiotics, bone marrow derived macrophages (BMDMs) produced significant amounts of proinflammatory cytokines including interleukin-6 (IL-6), IL-12, and tumor necrosis factor-α (TNF-α). Levels of inducible nitric oxide synthase (inos) and co-stimulatory molecules (CD80 and CD86) were also upregulated in BMDMs after treatment with some of these probiotics. To establish an immunocompromised animal model, we intraperitoneally injected mice with cyclophosphamide on day 0 and again on day 2. Starting day 3, we orally administered probiotics every day for the last 15 d. After sacrificing experimental mice on day 18, splenocytes were isolated and co-cultured with these probiotics for 3 d to measure levels of several cytokines and immune cell proliferation. Results clearly indicated that the consumption of all three probiotic strains promoted secretion of interferon-γ (IFN-γ), IL-1ß, IL-6, IL-12, and TNF-α. NK cell cytotoxicity and proliferation of immune cells were also increased. Taken together, our data strongly suggest that consumption of some probiotics might induce cell-mediated immune responses in immunocompromised mice.

Social Robots as Creativity Eliciting Agents.

Can robots help children be more creative? In this work, we posit social robots as creativity support tools for children in collaborative interactions. Children learn creative expressions and behaviors through social interactions with others during playful and collaborative tasks, and socially emulate their peers' and teachers' creativity. Social robots have a unique ability to engage in social and emotional interactions with children that can be leveraged to foster creative expression. We focus on two types of social interactions: creativity demonstration, where the robot exhibits creative behaviors, and creativity scaffolding, where the robot poses challenges, suggests ideas, provides positive reinforcement, and asks questions to scaffold children's creativity. We situate our research in three playful and collaborative tasks - the Droodle Creativity game (that affords verbal creativity), the MagicDraw game (that affords figural creativity), and the WeDo construction task (that affords constructional creativity), that children play with Jibo, a social robot. To evaluate the efficacy of the robot's social behaviors in enhancing creative behavior and expression in children, we ran three randomized controlled trials with 169 children in the 5-10 yr old age group. In the first two tasks, the robot exhibited creativity demonstration behaviors. We found that children who interacted with the robot exhibiting high verbal creativity in the Droodle game and high figural creativity in the MagicDraw game also exhibited significantly higher creativity than a control group of participants who interacted with a robot that did not express creativity (p < 0.05*). In the WeDo construction task, children who interacted with the robot that expressed creative scaffolding behaviors (asking reflective questions, generating ideas and challenges, and providing positive reinforcement) demonstrated higher creativity than participants in the control group by expressing a greater number of ideas, more original ideas, and more varied use of available materials (p < 0.05*). We found that both creativity demonstration and creativity scaffolding can be leveraged as social mechanisms for eliciting creativity in children using a social robot. From our findings, we suggest design guidelines for pedagogical tools and social agent interactions to better support children's creativity.

Lifelong Personalization via Gaussian Process Modeling for Long-Term HRI.

Across a wide variety of domains, artificial agents that can adapt and personalize to users have potential to improve and transform how social services are provided. Because of the need for personalized interaction data to drive this process, long-term (or longitudinal) interactions between users and agents, which unfold over a series of distinct interaction sessions, have attracted substantial research interest. In recognition of the expanded scope and structure of a long-term interaction, researchers are also adjusting the personalization models and algorithms used, orienting toward "continual learning" methods, which do not assume a stationary modeling target and explicitly account for the temporal context of training data. In parallel, researchers have also studied the effect of "multitask personalization," an approach in which an agent interacts with users over multiple different tasks contexts throughout the course of a long-term interaction and learns personalized models of a user that are transferrable across these tasks. In this paper, we unite these two paradigms under the framework of "Lifelong Personalization," analyzing the effect of multitask personalization applied to dynamic, non-stationary targets. We extend the multi-task personalization approach to the more complex and realistic scenario of modeling dynamic learners over time, focusing in particular on interactive scenarios in which the modeling agent plays an active role in teaching the student whose knowledge the agent is simultaneously attempting to model. Inspired by the way in which agents use active learning to select new training data based on domain context, we augment a Gaussian Process-based multitask personalization model with a mechanism to actively and continually manage its own training data, allowing a modeling agent to remove or reduce the weight of observed data from its training set, based on interactive context cues. We evaluate this method in a series of simulation experiments comparing different approaches to continual and multitask learning on simulated student data. We expect this method to substantially improve learning in Gaussian Process models in dynamic domains, establishing Gaussian Processes as another flexible modeling tool for Long-term Human-Robot Interaction (HRI) Studies.

Personal Narratives in Technology Design: The Value of Sharing Older Adults' Stories in the Design of Social Robots.

The storytelling lens in human-computer interaction has primarily focused on personas, design fiction, and other stories crafted by designers, yet informal personal narratives from everyday people have not been considered meaningful data, such as storytelling from older adults. Storytelling may provide a clear path to conceptualize how technologies such as social robots can support the lives of older or disabled individuals. To explore this, we engaged 28 older adults in a year-long co-design process, examining informal stories told by older adults as a means of generating and expressing technology ideas and needs. This paper presents an analysis of participants' stories around their prior experience with technology, stories shaped by social context, and speculative scenarios for the future of social robots. From this analysis, we present suggestions for social robot design, considerations of older adults' values around technology design, and promotion of participant stories as sources for design knowledge and shifting perspectives of older adults and technology.

Speed Dating with Voice User Interfaces: Understanding How Families Interact and Perceive Voice User Interfaces in a Group Setting.

As voice-user interfaces (VUIs), such as smart speakers like Amazon Alexa or social robots like Jibo, enter multi-user environments like our homes, it is critical to understand how group members perceive and interact with these devices. VUIs engage socially with users, leveraging multi-modal cues including speech, graphics, expressive sounds, and movement. The combination of these cues can affect how users perceive and interact with these devices. Through a set of three elicitation studies, we explore family interactions (N = 34 families, 92 participants, ages 4-69) with three commercially available VUIs with varying levels of social embodiment. The motivation for these three studies began when researchers noticed that families interacted differently with three agents when familiarizing themselves with the agents and, therefore, we sought to further investigate this trend in three subsequent studies designed as a conceptional replication study. Each study included three activities to examine participants' interactions with and perceptions of the three VUIS in each study, including an agent exploration activity, perceived personality activity, and user experience ranking activity. Consistent for each study, participants interacted significantly more with an agent with a higher degree of social embodiment, i.e., a social robot such as Jibo, and perceived the agent as more trustworthy, having higher emotional engagement, and having higher companionship. There were some nuances in interaction and perception with different brands and types of smart speakers, i.e., Google Home versus Amazon Echo, or Amazon Show versus Amazon Echo Spot between the studies. In the last study, a behavioral analysis was conducted to investigate interactions between family members and with the VUIs, revealing that participants interacted more with the social robot and interacted more with their family members around the interactions with the social robot. This paper explores these findings and elaborates upon how these findings can direct future VUI development for group settings, especially in familial settings.

Effect of Different Rheological Models on the Distress Prediction of Composite Pavement.

In this paper, three different rheological models including a newly developed formulation based on the current Christensen Anderson and Marateanu (CAM) model, named sigmoidal CAM model (SCM), are used to estimate the evolution of roughness, rutting, and reflective cracking in a typical composite pavement structure currently widely adopted in South Korea. Three different asphalt mixtures were prepared and dynamic modulus tests were performed. Then, the mechanistic-empirical pavement design guide (MEPDG) was used for predicting the progression of the pavement distress and to estimate the effect of the three different models on such phenomena. It is found that the three different mathematical models provide lower and upper limits for roughness, rutting, and reflective cracking. While the CAM model may not be entirely reliable due to its inability in fitting the data in the high-temperature domain, SCM might result in moderately more conservative pavement design.

Development and experiments of a bio-inspired robot with multi-mode in aerial and terrestrial locomotion.

This paper introduces a new multi-modal robot capable of terrestrial and aerial locomotion, aiming to operate in a wider range of environments. The robot was built to achieve two locomotion modes of walking and gliding while preventing one modality hindering the other. To achieve this goal, we found the solution from Pteromyini, commonly known as the flying squirrel. Pteromyini utilizes its flexible membrane to glide in the air, and it shows agile movements on the ground. We studied Pteromyini to mimic the key features that allow Pteromyini to perform aerial and terrestrial locomotion. We adopted the flexible membrane and gliding strategy of Pteromyini to the robot. Through dynamics analysis and simulations, the overall design was determined. The flexibility of the membrane was also chosen considering the robot's performance in the air and on the ground. The leg was optimized to perform with regulated motor torques in both walking and gliding. From gliding tests, the robot showed an average gliding ratio of 1.88. Inspired by Pteromyini, controlling the robot's angle of attack with leg and tail movement was also adopted and tested. Different gait patterns and changing walking directions were tested to demonstrate the robot's terrestrial performance. The average walking speed was 13.38 cm s-1. The experimental results demonstrated the robot's functionality in aerial and terrestrial locomotion.

Growing Growth Mindset with a Social Robot Peer.

Mindset has been shown to have a large impact on people's academic, social, and work achievements. A growth mindset, i.e., the belief that success comes from effort and perseverance, is a better indicator of higher achievements as compared to a fixed mindset, i.e., the belief that things are set and cannot be changed. Interventions aimed at promoting a growth mindset in children range from teaching about the brain's ability to learn and change, to playing computer games that grant brain points for effort rather than success. This work explores a novel paradigm to foster a growth mindset in young children where they play a puzzle solving game with a peer-like social robot. The social robot is fully autonomous and programmed with behaviors suggestive of it having either a growth mindset or a neutral mindset as it plays puzzle games with the child. We measure the mindset of children before and after interacting with the peer-like robot, in addition to measuring their problem solving behavior when faced with a challenging puzzle. We found that children who played with a growth mindset robot 1) self-reported having a stronger growth mindset and 2) tried harder during a challenging task, as compared to children who played with the neutral mindset robot. These results suggest that interacting with peer-like social robot with a growth mindset can promote the same mindset in children.

Impact of high-grade obstruction on outcomes in patients with appendiceal inflammatory masses managed by nonoperative treatment.

PURPOSE: To retrospectively assess the impact of high-grade obstructions identified on initial CT on outcomes of patients with appendiceal inflammatory masses managed by nonoperative treatment. METHODS: Institutional Review Boards approved this retrospective study and informed consent was waived. Included were 52 consecutive patients diagnosed with appendiceal inflammatory masses by CT scan and managed by nonoperative treatment. The main outcome measure was treatment failure and secondary outcomes were complications and initial and total hospital stay. Patient demographics, inflammatory markers, and CT findings for presence of an appendiceal inflammatory mass and high-grade obstruction were assessed. Patients with and without high-grade obstruction were compared for patient characteristics and outcomes using Fisher exact test and Student t-test. RESULTS: Among 52 patients, 14 (27%) had high-grade obstruction on CT examination at presentation. No significant differences were observed in patient characteristics (P > 0.05), treatment failure (P = 0.33), complications (P = 0.29), or initial (P = 0.73) or total (P = 0.72) hospitalization between patients with and without high-grade obstruction. CONCLUSION: For patients who were managed by nonoperative treatment for appendiceal inflammatory masses, the presence of high-grade obstruction identified on initial CT scan did not significantly affect outcomes of treatment failure, complications, and initial and total hospitalization.

Focal hepatic solid lesions incidentally detected on initial ultrasonography in 542 asymptomatic patients.

PURPOSE: The purpose of this study is to evaluate the clinical significance of focal hepatic solid lesions incidentally detected on initial ultrasonography in asymptomatic patients. METHODS: From January 2009 to December 2009, 2670 initial ultrasonographies were performed in asymptomatic population. Of these 2670 initial examinations, 681 focal hepatic solid lesions in 542 patients (mean 39.4 years, range 23-73 years) were detected. Clinical information, ultrasonography features, and the outcome of these lesions were analyzed. RESULTS: Six hundred and seventy four lesions (99.0%) in 539 patients (99.4%) were benign, while seven lesions (1.0%) in three patients (0.6%) proved to be malignant. Risk factors significantly associated with malignant focal hepatic solid lesions were known history of malignancy, history of hepatitis, a positive result for the hepatitis B surface antigen, and abnormally elevated tumor markers. No malignancy was identified in patients without any one of these four risk factors. Ultrasonographic features of internal heterogeneous echotexture with peripheral hypoechoic rim showed significant associations with malignancy. CONCLUSIONS: Focal hepatic solid lesions incidentally detected on initial ultrasonography were rarely malignant, especially in patients without these risk factors. Therefore, the knowledge of these risk factors and US features is important in order to make a differential diagnosis between benign and malignant focal hepatic lesions.