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In this work, the phenomenon of strain induced by a mismatch in thermal expansion coefficients between a thin film and its substrate is harnessed in a new context, replacing the canonical planar support with a three-dimensional (3-D), nanoconfining scaffold in which we embed a material of interest. In this manner, we demonstrate a general approach to exert a continuously tunable, triaxial, tensile strain, defying the Poisson ratio of the embedded material and achieving the exotic condition of “negative pressure.” This approach is hypothetically generalizable to materials of low modulus and high thermal expansion coefficient, and we use it here to achieve negative pressure in perovskite-phase CsPbI₃embedded within the cylindrical pores of anodic aluminum oxide membranes. Through controlled thermal hysteresis, the perovskite crystal structure can be continuously tuned toward higher symmetry when confined in a scaffold with pore size <40 nm, in contrast with the symmetry-reducing action of any other mechanical perturbation. We use this effect to control the octahedral rotation angle that is critical to the remarkable photovoltaic attributes of halide perovskites. Under hundreds of megapascals of apparent negative pressure, the bandgap tunability is observed to follow the same quantitative trend observed for hydrostatic positive pressure, exploring the negative pressure region and demonstrating the relative dominance of bond stretching effects over average octahedral rotation angle on electronic structure. This study reveals and quantifies the structural and electronic consequences of 3D tensile strain present by design and provides a framework for understanding adventitious strain present in all nanocomposite materials. 

Team workload is a team-level construct considered similar to, but not reducible to, individual workload and mediated by team coordination. Despite this, the conceptualization and measurement of team workload in action teams lags behind that of individual workload. In most empirical studies, team workload is often simply considered as the sum or average of individual team members’ workload. However, unique characteristics of action teams, such as interdependence and heterogeneity, suggest that traditional approaches to conceptualizing and measuring team workload may be inadequate or even misleading. As such, innovative approaches are required to accurately capture this complex construct. This paper presents the development of a simulation designed to investigate the influence of interdependence and demand levels on team workload measures within a 3-person action-team command and control scenario. Preliminary results, which suggest that our manipulations are effective, are provided and discussed. 

Objective We review the current state-of-the-art in team cognition research, but more importantly describe the limitations of existing theories, laboratory paradigms, and measures considering the increasing complexities of modern teams and the study of team cognition. Background Research on, and applications of, team cognition has led to theories, data, and measures over the last several decades. Method This article is based on research questions generated in a spring 2022 seminar on team cognition at Arizona State University led by the first author. Results Future research directions are proposed for extending the conceptualization of teams and team cognition by examining dimensions of teamness; extending laboratory paradigms to attain more realistic teaming, including nonhuman teammates; and advancing measures of team cognition in a direction such that data can be collected unobtrusively, in real time, and automatically. Conclusion The future of team cognition is one of the new discoveries, new research paradigms, and new measures. Application Extending the concepts of teams and team cognition can also extend the potential applications of these concepts. 

Cyber attackers commonly operate in teams, which may process information collectively and thus, may be best understood when the team is treated as the unit of analysis. Future research in Oppositional Human Factors (OHF) should consider the impact of team-influencing and team-level biases and the impact that defensive interventions have on team cognition in general. Existing measurement approaches using team interactions may be well suited for studying red teams, and how OHF interventions impact cyber attackers. 

The goal of the Space Challenge project is to identify the challenges faced by teams in space operations and then represent those challenges in a distributed human-machine teaming scenario that resembles typical space operations and to measure the coordination dynamics across the entire system. Currently, several challenges have been identified through semi-structured interviews with nine subject matter experts (SMEs) who were astronauts or those who have experienced or have been involved with interplanetary space exploration. We conducted a thematic analysis on the interviews through an iterative process. Challenges were categorized into four categories, including, communication, training, distributed teaming, and complexity. Based on the findings, challenges and key teamwork characteristics of space operations were integrated into the initial scenario development. In addition to the scenario, we plan to use dynamical system methods to analyze team activity in real time. 

This research examines the relationship between anticipatory pushing of information and trust in human– autonomy teaming in a remotely piloted aircraft system - synthetic task environment. Two participants and one AI teammate emulated by a confederate executed a series of missions under routine and degraded conditions. We addressed the following questions: (1) How do anticipatory pushing of information and trust change from human to human and human to autonomous team members across the two sessions? and (2) How is anticipatory pushing of information associated with the trust placed in a teammate across the two sessions? This study demonstrated two main findings: (1) anticipatory pushing of information and trust differed between human-human and human-AI dyads, and (2) anticipatory pushing of information and trust scores increased among human-human dyads under degraded conditions but decreased in human-AI dyads. 

Objective This work examines two human–autonomy team (HAT) training approaches that target communication and trust calibration to improve team effectiveness under degraded conditions. Background Human–autonomy teaming presents challenges to teamwork, some of which may be addressed through training. Factors vital to HAT performance include communication and calibrated trust. Method Thirty teams of three, including one confederate acting as an autonomous agent, received either entrainment-based coordination training, trust calibration training, or control training before executing a series of missions operating a simulated remotely piloted aircraft. Automation and autonomy failures simulating degraded conditions were injected during missions, and measures of team communication, trust, and task efficiency were collected. Results Teams receiving coordination training had higher communication anticipation ratios, took photos of targets faster, and overcame more autonomy failures. Although autonomy failures were introduced in all conditions, teams receiving the calibration training reported that their overall trust in the agent was more robust over time. However, they did not perform better than the control condition. Conclusions Training based on entrainment of communications, wherein introduction of timely information exchange through one team member has lasting effects throughout the team, was positively associated with improvements in HAT communications and performance under degraded conditions. Training that emphasized the shortcomings of the autonomous agent appeared to calibrate expectations and maintain trust. Applications Team training that includes an autonomous agent that models effective information exchange may positively impact team communication and coordination. Training that emphasizes the limitations of an autonomous agent may help calibrate trust.