These log files are then analyzed using machine learning techniques (k-means clustering) in order to extract different patterns in the creation of the sequences and extract various problem-solving pathways performed by students. The difference between problem-solving pathways with respect to an indicator of early achievement is studied.For effective virtual realities, "presence," the feeling of "being there" in a virtual environment (VR), is deemed an essential prerequisite. Several studies have assessed the effect of the (non-)availability of auditory stimulation on presence, but due to differences in study design (e.g., virtual realities used, types of sounds included, rendering technologies employed), generalizing the results and estimating the effect of the auditory component is difficult. In two experiments, the influence of an ambient nature soundscape and movement-triggered step sounds were investigated regarding their effects on presence. In each experiment, approximately forty participants walked on a treadmill, thereby strolling through a virtual park environment reproduced via a stereoscopic head-mounted display (HMD), while the acoustical environment was delivered via noise-canceling headphones. In Experiment 1, conditions with the ambient soundscape and the step sounds either present or absent were combined in a 2 × 2 within-suial effects on subscales of presence, in that both affected overall presence and realism, while involvement was improved and distraction reduced by the ambient soundscape only.This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations of the swarm. These should be taken into account when designing swarm behaviors in order to maximize the utility of the group. At the lowest level, each MAV should operate safely. Robustness is often hailed as a pillar of swarm robotics, and a minimum level of local reliability is needed for it to propagate to the global level. An MAV must be capable of autonomous navigation within an environment with sufficient trustworthiness before the system can be scaled up. Once the operations of the single MAV are sufficiently secured for a task, the subsequent challenge is to allow the MAVs to sense one another within a neighborhood of interest. Relative localization of neighbors is a fundamental part of self-organizing roand safety. Taking these local limitations into account when designing a global swarm behavior is key in order to take full advantage of the system, enabling local limitations to become true strengths of the swarm.This study examines the coiling and uncoiling motions of a soft pneumatic actuator inspired by the awn tissue of Erodium cicutarium. These tissues have embedded cellulose fibers distributed in a tilted helical pattern, which induces hygroscopic coiling and uncoiling in response to the daily changes in ambient humidity. Such sophisticated motions can eventually "drill" the seed at the tip of awn tissue into the soil a drill bit in the plant kingdom.  https://www.selleckchem.com/products/leupeptin-hemisulfate.html  Through finite element simulation and experimental testing, this study examines a soft pneumatic actuator that has a similar reinforcing fiber layout to the Erodium plant tissue. This actuator, in essence, is a thin-walled elastomeric cylinder covered by tilted helical Kevlar fibers. Upon internal pressurization, it can exhibit a coiling motion by a combination of simultaneous twisting, bending, and extension. Parametric analyses show that the coiling motion characteristics are directly related to the geometry of tilted helical fibers. Notably, a moderate tilt in the reinforcing helical fiber leads to many coils of small radius, while a significant tilt gives fewer coils of larger radius. The results of this study can offer guidelines for constructing plant-inspired robotic manipulators that can achieve complicated motions with simple designs.The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is outlined in a simplified setup.The emergence and development of cognitive strategies for the transition from exploratory actions towards intentional problem-solving in children is a key question for the understanding of the development of human cognition. Researchers in developmental psychology have studied cognitive strategies and have highlighted the catalytic role of the social environment. However, it is not yet adequately understood how this capacity emerges and develops in biological systems when they perform a problem-solving task in collaboration with a robotic social agent. This paper presents an empirical study in a human-robot interaction (HRI) setting which investigates children's problem-solving from a developmental perspective. In order to theoretically conceptualize children's developmental process of problem-solving in HRI context, we use principles based on the intuitive theory and we take into consideration existing research on executive functions with a focus on inhibitory control. We considered the paradigm of the Tower of Hanoi and we conducted an HRI behavioral experiment to evaluate task performance. We designed two types of robot interventions, "voluntary" and "turn-taking"-manipulating exclusively the timing of the intervention. Our results indicate that the children who participated in the voluntary interaction setting showed a better performance in the problem solving activity during the evaluation session despite their large variability in the frequency of self-initiated interactions with the robot. Additionally, we present a detailed description of the problem-solving trajectory for a representative single case-study, which reveals specific developmental patterns in the context of the specific task. Implications and future work are discussed regarding the development of intelligent robotic systems that allow child-initiated interaction as well as targeted and not constant robot interventions.