Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing the Emotional and Cognitive Components of Initial Trust Formation in Air Traffic Controller-Autonomy Teams

The use of intelligent decision aids in Air Traffic Management is recommended to manage the exponential rise in global air traffic. Consequently, trust, which is one of the main drivers of how Air Traffic Controllers use such decision aids, has become an important area of research. It has been suggested that there is a strong emotional influence in the formation of Human-Human Trust, and it is unclear if this paradigm is valid for Human-Autonomy Trust. The extent of the cognitive and emotional components in the initial trust relationship between Air Traffic Controllers and a simulated conflict detection autonomous decision aid was examined with the use of functional Magnetic Resonance Imaging. The results confirmed that the emotional component showed higher activation than the cognitive component for the initial formation of trust between Air Traffic Controllers and autonomous decision aids.
Learn, Experience, Reflect Framework for Training Design

The Learn, Experience, Reflect framework for training design provides a structure for communication and collaboration among researchers, trainers, training designers, and technology developers. The framework was articulated in the context of efforts to develop effective recognition skills training for combat medics using augmented reality technology. The Learn component presents didactic information to extend and refine learners’ existing mental models. The Experience component leverages augmented reality to provide opportunities to practice applying learned concepts in context. The Reflect component is designed to help learners reflect on their own knowledge to highlight and address knowledge gaps.
Individual Differences in the Acceptance and Adoption of AI-enabled Autonomous Systems

With the deployment of AI-enabled autonomous systems in various fields of application, it is critical to understand the factors affecting the acceptance and in turn the adoption of such technology. While previous research has established that individual differences have an impact on the acceptance and adoption of technology, little research has examined the extent and specificity of those individual differences. The current research attempts to address this gap in the literature by examining individual differences concerning the willingness to accept and adopt general technology versus specific AI-enabled autonomous systems. Our findings reveal several significant results between an individual’s personality traits of Openness, Emotionality, and Honesty-Humility, as well as age, gender, and career field with an individual’s level of acceptance and adoption of general versus specific AI-enabled AS technology. Our findings call for future research to further explore these individual differences in detail and to validate current technology models.
Adult listeners can extract age-related cues from child-directed speech

This study investigated adult listeners’ ability to detect age-related cues in child-directed speech (CDS). Participants (N = 186) listened to two speech recordings directed at children between the ages of 6 and 44 months and guessed which had addressed a younger or an older child. The recordings came from North American English-speaking mothers and listeners were native speakers of Turkish with varying degrees of English knowledge. Participants were randomly assigned to listen either to the original recordings or to the low-pass filtered versions. Accuracy was above chance level across all groups. Participants’ English level, age, and the age difference between the addressees significantly predicted accuracy. After controlling for these variables, we found a significant effect of condition. Participants’ accuracy tended to be better in the unfiltered condition with the exception of male participants without children. These results suggest that age-related variations in CDS are perceptually available to adult listeners. Furthermore, even though sensitivity to the age-related cues is facilitated by the availability of content-related cues in speech, it does not seem to be solely dependent on these cues, providing further support for the form–function relations in CDS.
Design Considerations of Task-Driven Icons for Point-of-Care (POC) Documentation In Long-Term Care (LTC) Settings

Graphical icons have been introduced as a design solution, i.e., task-driven icons, to improve certificate nurse assistants (CNAs) charting efficiency in long-term care settings. It aims to motivate CNAs to complete POC documentation at work, thus reduce the after-hour charting workload. Currently, few studies have examined the effectiveness of task-driven icons in POC systems and their performance on affecting users’ charting behaviors. This study intends to investigate existing types of task-driven icons in POC systems, and whether those icons have effectively influenced CNAs’ charting behaviors. By analyzing ways of interpreting icons and associating charting tasks, we aim to establish design considerations of the task-driven icons used for POC documentation on future implementations.
A Survey on Robotic Vacuum Cleaners: Evaluation of Expressive Robotic Motions based on the Framework of Laban Effort Features for Robot Personality Design

The adoption of robotic vacuum cleaners (RVCs) has drastically increased. During interaction with these embodied autonomous agents, humans tend to ascribe certain personality traits to them even when the robot has a mechanoid appearance and low degree of freedom. As the social capabilities and the persuasiveness of robots increase, the design of robot personality will become important. This paper investigates the impact of expressive motions on people’s perception of robot personality. The framework of Laban Effort Features was implemented for a simple cleaning task. Movement features were programmed in iRobot Create2, and participants were asked to rate the robot’s personality in an online survey. The results indicated that Flow factor was closely associated with neuroticism ratings, Weight factor impacted both agreeableness and conscientiousness ratings, while Time factor impacted only the agreeableness ratings. Movement characteristics should be considered when designing personality into domestic service robots like RVCs, which are expected to operate in highly social settings.
Capturing Driver Status Using Naturalistic Driving Study Data: Implications for Assessing Health and Safety

The design of advanced driver-assistance systems (ADASs) and driving monitoring systems can be improved with a better understanding of on-road driving behavior. Information on traffic environment, health, engagement in secondary tasks, and corresponding eye glance locations can provide important insights into driver’s in-vehicle movements and status. This study examines the in-vehicle head movement of the driver and the factors affecting it using data from a naturalistic driving study. Linear mixed models were used to examine head position at a given point in time, and hierarchical clustering with dynamic time warping (DTW) was used to explore the trajectories of the head position. The findings show that some health conditions (e.g., limited flexibility, cancer) were correlated to restrictive head position during driving, and vehicle acceleration and traffic environment factors contributed to the variation in head positions.
Operators over-rely even more when automated decision support is the exception and not the norm

Previous findings indicate that operator’s reliance towards a static automated aid increases with the degree of automation (DOA) especially when decision-making is affected. In this data reexamination of a previously conducted study, operators’ automation verification was investigated comparing a static automation supporting decision selection with an automation which in most trials only narrowed down possible diagnoses. Thus, in the majority of trials information sampling was essential for task completion in the latter condition. However, in a few trials the automation provided a diagnosis, too – giving participants the rare opportunity to fully rely on the automation. The question was investigated how participants behave in the exceptional occasions in which reliance is possible compared to participants who always have the opportunity to rely. Results show that when reliance was possible as an exception, participants verified their aid significantly less compared to the group who could rely throughout all trials. Implications for approaches of flexible automation are discussed.
Coevolution of metallicity and star formation in galaxies to z=3.7: I. A fundamental plane

With the aim of understanding the coevolution of star formation rate (SFR), stellar mass (M*), and oxygen abundance (O/H) in galaxies up to redshift z ≃ 3.7, we have compiled the largest available data set for studying Metallicity Evolution and Galaxy Assembly (MEGA); it comprises 1000 galaxies with a common O/H calibration and spans almost two orders of magnitude in metallicity, a factor of 106 in SFR, and a factor of 105 in stellar mass. From a principal component analysis, we find that the three-dimensional parameter space reduces to a Fundamental Plane in metallicity (FPZ) given by 12 + log (O/H) = -0.14 log (SFR) + 0.37 log (M*) + 4.82. The mean O/H FPZ residuals are small (0.16 dex) and consistent with trends found in smaller galaxy samples with more limited ranges in M*, SFR, and O/H. Importantly, the FPZ is found to be approximately redshift invariant within the uncertainties. In a companion paper, these results are interpreted with an updated version of the model presented by Dayal, Ferrara & Dunlop.
Evidence for spin alignment of spiral and elliptical/S0 galaxies in filaments

ABSTRACT Galaxies are not distributed randomly in the cosmic web but are instead arranged inﬁlaments and sheets surrounding cosmic voids. Observationally there is still no con-vincing evidence of a link between the properties of galaxies and their host structures.However, by the tidal torque theory (our understanding of the origin of galaxy angularmomentum), such a link should exist. Using the presently largest spectroscopic galaxyredshift survey (SDSS) we study the connection between the spin axes of galaxies andthe orientation of their host ﬁlaments. We use a three dimensional ﬁeld of orientations to describe cosmic ﬁlaments. Torestore the inclination angles of galaxies, we use a 3D photometric model of galaxiesthat gives these angles more accurately than traditional 2D models.We found evidence thatthe spin axesofbrightspiralgalaxieshavea weaktendencyto be aligned parallel to ﬁlaments. For elliptical/S0 galaxies, we have a statisticallysigniﬁcant result that their spin axes are aligned preferentially perpendicular to thehost ﬁlaments; we show that this signal practically does not depend on the accuracyof the estimated inclination angles for elliptical/S0 galaxies.Key words: methods: statistical – galaxies: general – galaxies: statistics – galaxies:evolution – large-scale structure of Universe.
Broadband X-Ray Spectral Analysis of the Double-nucleus Luminous Infrared Galaxy Mrk 463

We present a broadband (0.4–70 keV) X-ray spectral analysis of the luminous infrared galaxy (LIRG) system Mrk 463 observed with Nuclear Spectroscopic Telescope Array (NuSTAR), Chandra, and XMM-Newton, which contains double active galactic nuclei (AGNs; Mrk 463E and Mrk 463W) with a separation of ∼3.8 kpc. Detecting their transmitted hard X-ray >10 keV continua with NuSTAR, we confirm that Mrk 463E and Mrk 463W have AGNs with intrinsic luminosities of (1.6–2.2) × 1043 and (0.5–0.6) × 1043 erg s−1 (2–10 keV) obscured by hydrogen column densities of 8 × 1023 and 3 × 1023 cm−2, respectively. Both nuclei show strong reflection components from cold matter. The luminosity ratio between X-ray (2–10 keV) and [O iv] 25.89 μm of Mrk 463E is ∼5 times smaller than those of normal Seyfert galaxies, suggesting that the intrinsic SED is X-ray weak relative to the UV luminosity. In fact, the bolometric AGN luminosity of Mrk 463E estimated from L′-band (3.8 μm), [O iv] 25.89 μm, and [Ne v] 14.32 μm lines indicate a large bolometric-to-X-ray luminosity ratio, κ2–10 keV ≈ 110–410, and a high Eddington ratio, λEdd ∼ 0.4–0.8. We suggest that the merger triggered a rapid growth of the black hole in Mrk 463E, which is not yet deeply “buried” by circumnuclear dust. By contrast, the L′-band luminosity of Mrk 463W is unusually small relative to the X-ray luminosity, suggesting that the Eddington ratio is low (<10−3) and it might be still in an early phase of merger-driven AGN activity.
Factors Affecting Interior Acceleration Sound Preference for Electric Vehicles: A Path Analysis

Vehicle sound design is gaining attention in the automotive industry, especially for Electric Vehicles (EV). For EVs, acceleration sound is critical for both user experience (UX) and safety. Despite the abundance of UX-related studies investigating the external presentation of acceleration sound for EVs, internal presentation of acceleration sound seems to be overlooked. Thus, further understanding on what influences the user preferences for internal EV sound is essential for better EV sound design. This study aims to explore and develop a simple theoretical path model to help understand the relationship between pragmatic quality, hedonic quality, novelty, and user preferences for EV internal acceleration sounds. Thirty-two participants evaluated twenty-seven EV acceleration sound samples using a 12-item semantic differential scale with bipolar adjective pairs that describe the measured variables in a controlled experimental setting. The relationship between the modeled variables was analyzed using bias-corrected factor score path analysis (BCFSPA). Results showed that the modified model yielded good model fit indices and partially confirmed the initial hypotheses. It was found that pragmatic and hedonic quality had a positive relationship with user preference, whereas, novelty had a negative relationship with hedonic quality and user preference for EV sounds. This study contributes to the understanding of factors that affects user preference for EV sound and provides initial accounts to different approaches and methods for model testing.
A Friendly Indoor Navigation App for People with Disabilities (FIND)

Persons with disabilities in our communities often find it difficult to achieve and maintain an independent and high quality of life. A significant cause of this issue is the challenge in independently navigating locations. Some prior studies investigated indoor navigation apps for one group of disabled users but few have addressed wayfinding needs of people with various disabilities simultaneously. The objective of this research was to design a friendly indoor navigation app for people with disabilities (FIND). The interface was evaluated and enhanced using a heuristic evaluation and focus group meeting with usability experts. The results were analyzed based on Molich and Nielsen’s usability principles and using a content analysis approach. The provided recommendations can be beneficial to improve the design of navigation apps for people with disabilities.
Examining the effects of interruption timing and frequency on performance: An update

The present study re-examined how the timing and frequency of interruptions impact performance on a planning and decision-making task. Undergraduates performed a trip planning task and were interrupted at coarse breakpoints, fine breakpoints, or not at all. Additionally, interruptions occurred at either a low or high frequency. Based on the memory for goals and event segmentation theories, it was predicted that a higher number of interruptions would be more disruptive than fewer interruptions, and that this effect would be more pronounced at the fine breakpoints. The results supported these predictions. Participants took longer to resume the primary task and experienced higher mental workload and frustration when interruptions occurred at fine breakpoints and at a higher frequency. Overall, these results demonstrate that the disruptiveness of interruptions is tied to their frequency and the point within the task hierarchy at which they occur.
“Run to the hills”: Specific contributions of anticipated energy expenditure during active spatial learning

Grounded views of cognition consider that space perception is shaped by the body and its potential for action. These views are substantiated by observations such as the distance-on-hill effect, described as the overestimation of visually perceived uphill distances. An interpretation of this phenomenon is that slanted distances are overestimated because of the integration of energy expenditure cues. The visual perceptual processes involved are, however, usually tackled through explicit estimation tasks in passive situations. The goal of this study was to consider instead more ecological active spatial processing. Using immersive virtual reality and an omnidirectional treadmill, we investigated the effect of anticipated implicit physical locomotion cost by comparing spatial learning for uphill and downhill routes, while maintaining actual physical cost and walking speed constant. In the first experiment, participants learnt city layouts by exploring uphill or downhill routes. They were then tested using a landmark positioning task on a map. In the second experiment, the same protocol was used with participants who wore loaded ankle weights. The results from the first experiment showed that walking uphill routes led to a global underestimation of distances compared with downhill routes. This inverted distance-of-hill effect was not observed in the second experiment, where an additional effort was applied. These results suggest that the underestimation of distances observed in Experiment 1 emerged from recalibration processes whose function was to solve the transgression of proprioceptive predictions linked with uphill energy expenditure. The results are discussed in relation to constructivist approaches on spatial representations and predictive coding theories.
The Impact of Automation Conditions on Reliance Dynamics and Decision-Making

The decision process of engaging or disengaging automation has been termed reliance on automation, and it has been widely analyzed as a summary measure of automation usage rather than a dynamic measure. We provide a framework for defining temporal reliance dynamics and apply it to a data-set from a previous study. Our findings show that (1) the higher the reliability of an automated system, the larger the reliance over time; and (2) more workload created by the automation type does not significantly affect the operators’ reliance dynamics in high-reliability systems, but it does produce greater reliance in low-reliability systems. Furthermore, on average, operators with low performance make fewer decision changes and prefer to stick to their decision of using automation even if it is not performing well. Operators with high performance, on average, have a higher frequency of decision change, and therefore, their automation usage periods are shorter.
Strategy Selection in Teams: Exploring How Teams Coordinate Responses to Time Pressure

Effective teamwork in dynamic environments relies on the ability to adapt individual as well as collective behavior to respond to varying and uncertain demands. This paper describes an experiment conducted to analyze a two-person team’s strategy selection during a simulated search and retrieve task using Blocks World for Teams (BW4T). The experiment imposes different levels of temporal demands on teams to characterize how individual strategy selection affects team strategy and performance. Hollnagel’s Contextual Control Models are used as the basis for analyzing the experiment data and identifying the control mode of the team and its individual members during the task. Results from the experiment show that control modes are adapted at both the individual and team level to maintain performance under varying temporal demands. The results from the experiment point to the need to have system design support a range of individual and team control strategies to facilitate effective coordination and adaptation in teams.
The Effectiveness of Gaze Guidance Lines in supporting JTAC’s Attention Allocation

We examined the utility of gaze guidance lines to facilitate the direction of attention between features on a minimap and their counterparts in a virtually rendered visual scene (Experiment 1) and between described features in the visual scene and their location on the minimap (Experiment 2); the experiment was designed to simulate a critical element of scene understanding for joint tactical attack controller (JTAC) communications with an attack pilot. In each experiment participants encountered 40 scenarios, half supported by a gaze guidance line and half without. The results of both experiments yielded a large and significant benefit of the gaze guidance line over the control condition, expressed in both speed and accuracy. The results of Experiment 2 however revealed some evidence that the gaze guidance lines led to an automation bias when the automation algorithm, creating the lines, misidentified a landmark in the visual scene.
The Role of Trait Mindfulness in Aggressive Driving Behavior

Aggressive driving behavior is regarded as a social dysfunction that poses a major risk to traffic safety. Previous research has indicated trait mindfulness as a protective factor for maladaptive thoughts and driver anger. The current study was designed to examine the mediating role of trait driver aggressiveness on the relationship between trait mindfulness and propensity for aggressive driving behavior. A sample of 122 drivers responded to a series of online questionnaires that assessed trait mindfulness, trait driver aggressiveness, and propensity for aggressive driving behavior. Results indicated that trait mindfulness was a significant predictor of trait driver aggressiveness. Similarly, trait mindfulness had also a moderating effect on the relationship between propensity for aggressive driving and trait driver aggressiveness. This indicated that those with higher trait mindfulness scores and lower trait driver aggressiveness scores were less likely to engage in aggressive driving behavior. Both theoretical and practical implications are discussed, and directions for future research are presented.
Trait Loneliness and Social Presence in Human-Human and Human-Robot Interaction

Social robots are a proposed solution to feelings of loneliness and social isolation. Given the psychological complexity of experienced trait loneliness and its potential to reduce perceived social presence, an experiment using a social robot was conducted to examine how trait loneliness impacted perceived social co-presence, psychobehavioral interdependence, and subjective mutual presence in social robot interactions. Furthermore, we explored whether these effects differed from human-to-human interactions. Although trait loneliness only affected third order subjective copresence among the three social presence dimensions, individuals with higher trait loneliness were more likely to accept the robot as a social companion.