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A decade ago, veganism was a fringe radical movement. It was also largely absent from the geographical discipline, despite a rich history of vegan scholarship being present in disciplines such as Sociology and Psychology. However, veganism has recently seen a surge in popularity, with more people than ever before becoming vegan for a mixture of animal welfare, environmental, and health-based reasons. With this mainstreaming, veganism has become contentious and fiercely defended. As veganism has become a growing social and political force, geographers have started to take notice of this previously fringe movement, which is gaining economic, ecological, and cultural power as investment flows into ‘plant-based’ products and new markets are emerging. In this commentary, we look at how veganism has recently been taken up in Geography via several distinct trends that all stake a claim in defining an emerging geographical sub-discipline, vegan geographies. We note the importance of scholarly pluralism and attention to establishing geographical sub-disciplines more broadly.

OBJECTIVES: To evaluate outcomes and cost-effectiveness of targeted therapy sequencing for metastatic and recurrent cervical cancer. METHOD: Models were simulated based on phase II and III trials on bevacizumab (bev) from GOG-240, cemiplimab (cemi) from GOG 3016, pembrolizumab (pembro) from KEYNOTE-826, and tisotumab vedotin (tiso) from GOG 3023. Costs were based on IBM Micromedex RED BOOK™ and company listed costs. RESULTS: For [chemo + bev → chemo], total cost was $125,918.04, with median overall survival (mOS) of 21.8 months, and cost-effectiveness ratio (CER) of $119,835.79. For [chemo + bev → cemi], total cost was $187,562.99 with mOS of 28.5 months and CER of $162,039.16. For [chemo + bev + pembro → chemo], total cost was $319,963.78 with mOS 32.9 months and CER of $249,930.10. For [chemo + bev + pembro → tiso], total cost was $455,204.45, with mOS 36.5 months and CER of $320,072.99. CONCLUSION: The combination of immunotherapies and biologics have significantly increased overall survival, but with associated higher costs, primarily related to drug costs.

This study uses the biographical method to explore the postbellum Indian Wars that resulted in the consolidation of federal authority over the territory and peoples of the trans-Mississippi West. Frontier army officers Richard Pratt, Gustavus Doane, and Charles Gatewood commanded Indian scouts during campaigns to subjugate tribes that resisted federal authority. Military records and other archival sources, including personal memoirs, allow us to understand this process of consolidation through their experiences. What these officers accomplished by, with, or through Indian scouts provide windows on the army’s essential role in consolidating federal authority. They also demonstrate the effect of their individual agency on the broader outcomes of consolidation.The army was sent west to nation build following the Civil War, facilitating settlement and development throughout the region. To limit friction between settler and Indian communities along the frontier the federal government sought to concentrate Indians on reservations. The army’s role was to subjugate Indian tribes that violently resisted concentration. Pratt enabled General Philipp Sheridan’s plan to subdue the Comanche by employing scouts from a variety of tribes to lead army columns during the 1874-75 Red River War campaign. Doane acted through the Crow tribe to support army commands during the Great Sioux War of 1876-77. In the final phase of consolidation, Gatewood acted with two Apache scouts to open negotiations with Geronimo, resulting in his surrender to General Nelson Miles. The role of commanding scouts also allowed officers to transcend the rigid regimental structure and stagnation of the army’s promotion system. These officers had outsized effects on how consolidation was implemented and, importantly, how we understand that historical process today. Pratt changed the national discourse on Indian assimilation, eliminating overt extermination from the debate. Doane’s official reports motivated natio

Ciliated cell markers expressed in epithelial ovarian cancers (EOC) are associated with improved survival. We examined the distribution of cells expressing ciliated cell markers in various EOC histologies and stages. Immunohistochemistry and/or multiplex immunofluorescence were used to determine the expression of FOXJ1 and/or CAPS (ciliated cell markers) in tissue microarrays including 4 normal fallopian tubes, 6 normal endometria, 16 cystadenomas, 25 borderline tumors, 21 low-grade carcinomas, and 118 high-grade carcinomas (HGSOC) (46 serous, 29 endometrioid, 30 clear cell, 13 mucinous). CAPS+ cells were observed in normal fallopian tubes and endometria and in ~85% of serous benign and borderline tumors and low-grade carcinomas but only in <40% of HGSOC. mRNA data from an independent cohort showed higher FOXJ1 and CAPS expression in serous borderline tumors and low-grade carcinomas compared to HGSOC. In HGSOC, ciliated cell-positive markers were observed in 52% primary tumors compared to 26% of patient-matched synchronous metastases, and 24% metachronous metastases (p = 0.009). mRNA data from an independent HGSOC cohort showed lower levels of CAPS in metastases than in primary tumors (p = 0.03). Overall, the study revealed that ciliated cells were less common in mucinous EOC, the percentage of ciliated cell marker-positive cases decreased with increasing grade, and the percentage of ciliated cells decreased in HGSOC metastases compared to patient-matched primary tumors.

The ongoing Russo-Ukrainian conflict provides a complex environment for the study of modern warfare. Surprisingly, one of the most intriguing facets of this conflict involves the melding of military operations and the commercial space industry. The Ukrainian military has made use of donated commercial satellite communications terminals with great success and devastating consequences for its Russian adversaries. The mobility, quantity, and range of these systems have aided the Ukrainians in their fight against the Russian Army in each stage of the conflict. Operating within the weapons ranges of Russian forces, the Ukrainian military has leveraged emerging commercial space technology to counter Russian aggression on the battlefield and in the information environment. Coincidentally, the fight being carried out by the Ukrainian Army at times has been similar to the proposed concept for the Marine Corps Stand-In Forces. Given the Ukrainian success in leveraging commercially owned proliferated low Earth orbit (pLEO) satellite communications, the Marine Corps should look to identify applications of their success to its own emerging warfighting concepts. The similarities in the defense of Ukraine and the future of Marine operations make it apparent that the Marine Corps should view commercial satellite communication as a viable solution for Stand-In Forces., Captain, United States Marine Corps, Approved for public release. Distribution is unlimited.

Interpersonal coordination is a key determinant of successful social interaction but is disrupted for people who experience social anxiety. Effective coordination rests on individuals directing their attention toward others, an effect well-documented in previous literature. Yet, little research has considered the concurrent behaviour of interaction partners. Using a novel virtual reality task, we investigated how partner gaze (i.e., direct vs. averted) influenced the emergence of interpersonal coordination. The results revealed two novel effects: (i) spontaneous coordination was diminished in the averted (cf. direct) gaze condition; (ii) spontaneous coordination was positively related to symptoms of social anxiety, but only when partner gaze was averted. This latter finding contrasts the extant literature and points to interaction intensity as a factor governing the social anxiety-coordination association. More broadly, this work provides further evidence that emergent patterns of interpersonal coordination fluctuate as a function of changes in social context and the behaviour of others.

Modeling human navigation and route selection in complex environments has used path planning in the past and more recently, dynamical models. The current study modeled the navigational movement trajectories of human herder agents tasked with corralling an autonomous target agent into a specified containment zone. Analyses of trajectories of participants completing a first-person herding game revealed that their movement entailed sequential (i) approach and then (ii) corral phases that were invariant to the initial location of the herder and target agents. More importantly, the trajectories of human herders could be captured using a low-dimensional environmentally coupled dynamical model. The novelty of this work is in extending the previous research in modeling navigational behaviors of humans to include moving targets that need to be manipulated into a desired position. Implications of the findings for the development of artificial agents for human-machine herding, as well as more general human-machine teaming are discussed.

Social cognition is shaped by cultural and social-psychological contexts. Depending on the social cues displayed, the cognitive processes that emerge during embodied social interactions can vary. This study explored the influence of gender diverse social cues on interpersonal coordination and decision-making during dyadic interaction in virtual reality. Participants embodied either a transgender or cisgender avatar and interacted with a transgender confederate (human-controlled virtual agent). Results suggest that transgender embodied women and men displayed more interpersonal affiliation, via their coordination dynamics with the confederate, after an explicit gender identity disclosure. Additionally, cognitive flexibility for ambiguous decisions was influenced by attributions of responsibility made toward the confederate. However, cisgender embodied men did not substantially change their decision-making behaviours or increase their coordination with the confederate. Viscerally taking on the perspective and appearance of a transgender person, achieved through virtual embodiment and interaction, may support positive interactions between cisgender and transgender communities.

Social motor coordination (SMC), defined as the intentional or unintentional coordination of movement between individuals in a social setting, has been linked to greater feelings of rapport and social connectedness. Here, we investigated this relationship using a silent disco paradigm where groups of 3 or 4 individuals danced to either the same music or different music. Visual information was manipulated by initially separating the participants with curtains (2 minutes), after which the curtains were opened (10 minutes). Head movements were recorded with a wireless motion tracking system attached to the silent disco headphones. Rapport and social connectedness measures were obtained using questionnaires completed after participation in the silent disco. Results showed that groups who listened to the same music exhibited a greater degree of SMC than groups that listened to different music. Greater degrees of SMC were also observed when group members were able to see one another. Finally, greater SMC was associated with perceptions of increased self-other overlap and interaction quality.

Agents trained using deep reinforcement learning (DRL) are capable of meeting or exceeding human-levels of performance in multi-agent tasks. However, the behaviors exhibited by these agents are not guaranteed to be human-like or human-compatible. This poses a problem if the goal is to design agents capable of collaborating with humans in cooperative or team-based tasks. Previous approaches to encourage the development of human-compatible agents have relied on pre-recorded human data during training. However, such data is not available for the majority of everyday tasks. Importantly, research on human perceptual-motor behavior has found that task-directed behavior is often low-dimensional and can be decomposed into a defined set of dynamical perceptual-motor primitives (DPMPs). Accordingly, we propose a hierarchical approach to simplify DRL training by defining the action dynamics of agents using DPMPs at the lower level, while using DRL to train the decision-making dynamics of agents at the higher level. We evaluate our approach using a multi-agent shepherding task used to study human and multi-agent coordination. Our hierarchical, DRL-DPMP approach resulted in agents which trained faster than vanilla, black-box DRL agents. Further, the hierarchical agents reached higher levels of performance not only when interacting with each other during self-play, but also when completing the task alongside agents embodying models of novice and expert human behavior. Finally, the hierarchical DRL-DPMP agents developed decision-making policies that outperformed heuristic-based agents used in previous research in human-agent coordination.

Deep reinforcement learning (DRL) is capable of training agents that exceed human-levels of performance in multi-agent tasks. However, the behaviors exhibited by these agents are not guaranteed to be human-like or human-compatible. This poses a problem if the goal is to design agents capable of collaborating with humans or augmenting human actions in cooperative or team-based tasks. Indeed, recommender systems designed to augment human decision-making need to not only recommend actions that align with the task goal, but which also maintain coordinative behaviors between agents. The current study simultaneously explored skill learning performance of human learners when working alongside different artificial agents (AAs) during a collaborative problem-solving task, as well as evaluated the effectiveness of the same AAs as action decision recommender systems to aid learning. The action decisions of the AAs were either modelled by a heuristic model based on human performance or by a deep neural network trained by reinforcement learning using self-play. In addition to evaluating skill learning performance, the current study also tested the congruence between the decisions of the AAs with actual decisions made by humans. Results demonstrate that the performance of humans was significantly worse when working alongside the DRL AA compared to the heuristic AA. Additionally, the action decisions participants made also showed less allignment with the recommendations made by the DRL AA.

Humans are social animals. Human cognition evolved in a social context. Human cognition develops in a social context. Thus, both the internal mechanisms of cognition and the information we use are social. In this workshop, we aim to extend the boundaries of cognitive sciences beyond individual minds. Following the lead of Dingemanse et al. (2023), we put interaction in focus as a complementary starting point for the study of human cognition.

While communication is an essential part of life, it is not always easy and effortless. This is especially true when talking with someone in a noisy environment. Although communicating in noise is often the rule rather than the exception, very little research has investigated the behavioral processes individuals might use to minimize miscommunication when listening becomes challenged. Here we explored synergistic speech and movement processes that 22 pairs of adults used to hear and be heard when (mis)communicating in noise. The results revealed intricate dynamics both with respect to acoustic optimization of the speech produced and heard, as well as how individuals modulate interpersonal distance and behavioral coordination patterns.

As society embraces technology to support collaboration anywhere and at anytime, there is a growing opportunity for artificial agents to support such collaboration. However, little seems known about how such agents impact the behavioural performance of human teams. To answer this, we devised a Wizard of Oz study where teams of 3 participants located and corralled targets into a containment area in a virtual desert environment. The Wizard played the role of an artificial intelligent operator who had a map view showing the location of participants, targets and the containment area, and could verbally communicate this information. The Wizard operated under two conditions: they could solely use the map view to decide what responses to utter (non-responsive interaction) or could also listen to participant queries (responsive interaction). The results revealed that participant performance was unaffected by responsive interaction condition, despite having a significantly more favourable perception of a responsive agent.

Intention prediction often plays a crucial role in successful social interaction. Previous studies have attempted to understand this skill by focusing on the role of movement kinematics in isolation. However, this approach is limited as the same kinematics typically map to multiple action possibilities (affordances) and as a result, individual's also employ contextual information to predict others' intentions. In this study we present preliminary findings from a qualitative study aimed at investigating intention prediction in naturalistic contexts. Participants viewed an individual reaching for a cup with one of two object-directed intentions: to drink OR to clear the table. A third non-object-directed intention was also included where the observed individual placed their hand on the table next to the cup. For each intention the contextual information was varied by changing the environmental scene between (1) cups full of juice, (2) almost empty cups, and (3) half-empty cups. The findings reveal that participants perceived the cup's functional (most salient) affordance - drink - for the intention so far as the movement kinematics specified an object-directed intention (drink or clear) with a context that clearly afforded it (full and half-full cups). However, participants were also sensitive to the kinematic differences between the object-directed intentions when the context made the functional affordance seem improbable (almost empty cups).

Perceptual-motor tasks offer redundant solutions to achieve a goal. However, not all solutions are equally robust to error-producing variability and thus, skill learning requires the search for behaviors that are error-tolerant. Throwing a ball to hit a target is a skill that has been studied via the “skittles” task, a simplified 2-dimensional throwing environment. The study investigated whether participants learning the skittles task benefit from task scaffolding via the placements of targets provided by either a human confederate posing as a teacher, or by the participant. These groups were compared to a third sample who received an unstructured curriculum consisting of randomly placed targets. The results demonstrate that participants in the unstructured training condition were better able to perceive the task’s underlying solution geometry, compared to scaffolding provided by a human. Future work will explore methods to design training curricula that are more efficient in facilitating perceptual-motor skill development.

Solving problems with others not only reduces the time required to complete a challenge but may also enable the discovery of novel strategies that qualitatively change how a problem is approached. At the dyadic level, the laboratory-based ‘shepherding task’ demonstrated that, when tasked to contain evasive agents to a centralized location, some participants discover a non-obvious but optimal strategy to solve the task. This paper quantified the interactions between participants engaged in the task using Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA), applied to each participant’s gaze and hand movements. The results demonstrated that strategy discoverers exhibited greater amounts of incidental coupling than non-discoverers prior to discovery. Once discovered, the strategy reduced the strength of coupling between participants, indicating that the strategy also reduced coordination demands. Future work will investigate whether differences in problem-solving can be attributable to differences in the perceptual features participants use which scaffold the discovery of task-optimal solutions.

Collaboration and teaming are critical for solving complex problems. However, little is known about how group dynamics affect teaming behaviours and, ultimately, problem-solving effectiveness. The present study aimed to validate a novel measure of the dynamics of team communication – here termed turn-taking entropy – and to investigate what aspects of those dynamics affect collaborative-problem-solving performance. Thirty-two teams of 4 were asked to complete a simulated crisis-response task in which they had to rank 15 items in order of their importance to their team’s survival (first individually and then as a team). Group responses were better than the aggregated individual responses of team members (suggesting teaming benefits), and were better when team members had task-relevant skills and knowledge. However, response quality was not significantly related to task completion time. Additionally, the proposed entropy measure appeared to capture group communication dynamics, and appeared to differentiate stable an unstable patterns of communication. Implications and directions for future research are discussed.

Nanomaterials are widespread in the human environment as pollutants, and are being actively developed for use in human medicine. We have investigated how the size and dose of polystyrene nanoparticles affects malformations in chicken embryos, and have characterized the mechanisms by which they interfere with normal development. We find that nanoplastics can cross the embryonic gut wall. When injected into the vitelline vein, nanoplastics become distributed in the circulation to multiple organs. We find that the exposure of embryos to polystyrene nanoparticles produces malformations that are far more serious and extensive than has been previously reported. These malformations include major congenital heart defects that impair cardiac function. We show that the mechanism of toxicity is the selective binding of polystyrene nanoplastics nanoparticles to neural crest cells, leading to the death and impaired migration of those cells. Consistent with our new model, most of the malformations seen in this study are in organs that depend for their normal development on neural crest cells. These results are a matter of concern given the large and growing burden of nanoplastics in the environment. Our findings suggest that nanoplastics may pose a health risk to the developing embryo.

With artificial intelligence technologies becoming commonplace today, enhancing the efficiency of human-artificial agent (AA) interactions has become increasingly important. A growing body of research has revealed how dynamic motor primitives (DMPs) of human perceptual-motor behavior can be used to create ‘human-like’ AAs, primarily focusing on cooperative tasks. Using air hockey as a representative task, the current experiment is the first part of a large study aimed at determining the utility of DMP-based models for developing ‘human-like’ competitive AAs. Participants played against a preliminary DMP model and the differences in their behaviors were analyzed. Based on these observed differences, a revised model is proposed, with preliminary results revealing that the new model exhibits behaviors more consistent with those of humans. A major implication of this work is that it presents a framework for creating ‘human-like’ AAs that capture the essential human decision and movement dynamics without requiring large human gameplay datasets.

Perceptual-motor tasks offer redundant solutions to achieve a goal. However, not all solutions are equally robust to error-producing noise or variability and thus, skill learning can be viewed as a search process to identify behaviors that are error-tolerant. Throwing a ball to hit a target is one such example of a complex perceptual-motor skill that has been studied in the laboratory via the virtual “skittles” task, a simplified 2D task involving throwing a tetherball around a pole to hit a target. We implemented the task as a Unity3D environment (code here: https://github.com/ShortFox/SkittlesTaskEnvironment/) which enables participants to complete the task with a computer mouse and replicated key findings from previous research. Our implementation allows for remote data collection and can serve as a pedagogical tool to teach concepts in skill acquisition. Future work will use this task to explore human versus machine skill acquisition by leveraging Unity’s MLAgents reinforcement learning package.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad’s efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed.

With artificial intelligence technologies becoming commonplace today, enhancing the efficiency of human-artificial agent (AA) interactions has become increasingly important. A growing body of research has revealed how dynamic motor primitives (DMPs) of human perceptual-motor behavior can be used to create ‘human-like’ AAs, primarily focusing on cooperative tasks. Using air hockey as a representative task, the current experiment is the first part of a large study aimed at determining the utility of DMP-based models for developing ‘human-like’ competitive AAs. Participants played against a preliminary DMP model and the differences in their behaviors were analyzed. Based on these observed differences, a revised model is proposed, with preliminary results revealing that the new model exhibits behaviors more consistent with those of humans. A major implication of this work is that it presents a framework for creating ‘human-like’ AAs that capture the essential human decision and movement dynamics without requiring large human gameplay datasets.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad’s efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed.

Perceptual-motor tasks offer redundant solutions to achieve a goal. However, not all solutions are equally robust to error-producing noise or variability and thus, skill learning can be viewed as a search process to identify behaviors that are error-tolerant. Throwing a ball to hit a target is one such example of a complex perceptual-motor skill that has been studied in the laboratory via the virtual “skittles” task, a simplified 2D task involving throwing a tetherball around a pole to hit a target. We implemented the task as a Unity3D environment (code here: https://github.com/ShortFox/SkittlesTaskEnvironment/) which enables participants to complete the task with a computer mouse and replicated key findings from previous research. Our implementation allows for remote data collection and can serve as a pedagogical tool to teach concepts in skill acquisition. Future work will use this task to explore human versus machine skill acquisition by leveraging Unity’s MLAgents reinforcement learning package.

Older patients and those who require interpreters are least likely to use telehealth for gynecologic oncology care, showing disparities which continued after statewide vaccinations.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad's efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed., CC BY 4.0Creative Commons Attribution 4.0 International License (CC BY)© 2022 The Author(s)MJR was supported by the Australian Research Council Future Fellowship (FT180100447). The authors would like to thank Dr. Patrick Nalepka for his helpful comments and suggestions throughout this work.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad's efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed., CC BY 4.0Creative Commons Attribution 4.0 International License (CC BY)© 2022 The Author(s)MJR was supported by the Australian Research Council Future Fellowship (FT180100447). The authors would like to thank Dr. Patrick Nalepka for his helpful comments and suggestions throughout this work.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad's efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed., CC BY 4.0Creative Commons Attribution 4.0 International License (CC BY)© 2022 The Author(s)MJR was supported by the Australian Research Council Future Fellowship (FT180100447). The authors would like to thank Dr. Patrick Nalepka for his helpful comments and suggestions throughout this work.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad's efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed., CC BY 4.0Creative Commons Attribution 4.0 International License (CC BY)© 2022 The Author(s)MJR was supported by the Australian Research Council Future Fellowship (FT180100447). The authors would like to thank Dr. Patrick Nalepka for his helpful comments and suggestions throughout this work.

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad's efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed., CC BY 4.0Creative Commons Attribution 4.0 International License (CC BY)© 2022 The Author(s)MJR was supported by the Australian Research Council Future Fellowship (FT180100447). The authors would like to thank Dr. Patrick Nalepka for his helpful comments and suggestions throughout this work.

Deep reinforcement learning (Deep RL) methods can train artificial agents (AAs) to reach or exceed human-level performance. However, in multiagent contexts requiring competitive behavior or where the aim is to use AAs for human training, the qualitative behaviors AAs adopt may be just as important as their performance to ensure representative training. This paper compares human behaviors and performance when competing against either a human expert or an AA opponent trained using Deep RL on a 2-dimensional version of Pong. Results show that participants were not sensitive to the movement differences between the human expert and AA. Further, the participants did not alter their behaviors, except to compensate for differences in the environmental states caused by the opponents. The paper concludes with discussion on the potential impacts of AA training on human behavior with regard to representative design in the areas of skill development and team training.

In many team-based activities, members search for information to gain situational awareness and thereby structure their own behavior. The extent to which members are coupled and in control of their surrounding environment can be accessed via the fluctuations of their searching behaviors. To facilitate prospective control, assistive technologies such as a head-up display (HUD) can alleviate the demands of search and facilitate team performance. This study investigated how three-person teams divided their labor and structured their search behavior when playing a multiplayer search-and-retrieval task where first-person visibility and access to a HUD were manipulated. Results showed that access to task relevant information facilitated performance and division of labor, and increased prospective control of searching behaviors, as indexed by detrended fluctuation analysis (DFA). Over multiple sessions, teams learned to use the HUD to structure their behavior to achieve the task goal. Results indicate the potential in using DFA for monitoring prospective control in team contexts.

The current study explores the dynamics of interpersonal collision avoidance during an everyday coordination task. The task was a full body adaptation of the collision avoidance arm-movement task employed by Richardson et al. (2015) and required pairs of co-actors to avoid colliding into one another as they moved back and forth within a collaborative workspace. Specifically, participants were required to serve drinks to humanoid customers in a virtual bar where they needed to move back and forth between drink service and refill stations. As expected, stable patterns of movement coordination emerged between co-actors, with one participant in a pair exhibiting a more circular movement trajectory between the service and refill locations, while the second participant in a pair exhibited a more straight-line trajectory between the two locations. Consistent with the results of Richardson et al., (2015), this pattern was observed across nearly all pairs, indicating that the same dynamical processes governing simple hand-arm coordination tasks also regulate more complex, full-body and naturalistic goal-directed interpersonal coordination tasks.

Altering an individual’s identity during virtual tasks, such that it is incongruent with their own identity, can reduce unconscious biases and increase empathy and prosocial behavior. While such virtual embodiment has been investigated for race, age, and socioeconomic status, the question remains whether immersive perspective taking reduces implicit gender bias. Accordingly, we investigated the effect of gendered embodiment on gender bias related to the underrepresentation of women in science, technology, engineering, and math fields. Undergraduate students (N=65) undertook a simulated virtual interview task, which included the rating and selection of male and female candidates. Females were significantly more empathetic than males. Greater empathy predicted higher candidate ratings, except for competence of the female candidate. Preliminary findings establish foundations for future comparative studies and contribute to elucidating the nature of empathy during and after virtual perspective taking, such that it may have a greater impact on males for modulating gender bias.

Team interaction involves the division of labor and coordination of actions between members to achieve a shared goal. Although the dynamics of interactions that afford effective coordination and performance have been a focus in the cognitive science community, less is known about how to generate these flexible and adaptable coordination patterns. This is important when the goal is to design artificial agents that can augment and enhance team coordination as synthetic teammates. Although previous research has demonstrated the negative impact of model-based agents on the pattern of interactions between members using recurrence quantification methods, more recent work utilizing deep reinforcement learning has demonstrated a promising approach to bootstrap the design of agents to team with humans effectively. This paper explores the impact of artificial agent design on the interaction patterns that are exhibited in human-autonomous agent teams and discusses future directions that can facilitate the design of human-compatible artificial agents.

More than 400,000 people each year suffer adverse effects following bites from venomous snakes. However, snake venom is also a rich source of bioactive molecules with known or potential therapeutic applications. Manually 'milking' snakes is the most common method to obtain venom. Safer alternative methods to produce venom would facilitate the production of both antivenom and novel therapeutics. This protocol describes the generation, maintenance and selected applications of snake venom gland organoids. Snake venom gland organoids are 3D culture models that can be derived within days from embryonic or adult venom gland tissues from several snake species and can be maintained long-term (we have cultured some organoids for more than 2 years). We have successfully used the protocol with glands from late-stage embryos and recently deceased adult snakes. The cellular heterogeneity of the venom gland is maintained in the organoids, and cell type composition can be controlled through changes in media composition. We describe in detail how to derive and grow the organoids, how to dissociate them into single cells, and how to cryopreserve and differentiate them into toxin-producing organoids. We also provide guidance on useful downstream assays, specifically quantitative real-time PCR, bulk and single-cell RNA sequencing, immunofluorescence, immunohistochemistry, fluorescence in situ hybridization, scanning and transmission electron microscopy and genetic engineering. This stepwise protocol can be performed in any laboratory with tissue culture equipment and enables studies of venom production, differentiation and cellular heterogeneity.

The current study explores the dynamics of interpersonal collision avoidance during an everyday coordination task. The task was a full body adaptation of the collision avoidance arm-movement task employed by Richardson et al. (2015) and required pairs of co-actors to avoid colliding into one another as they moved back and forth within a collaborative workspace. Specifically, participants were required to serve drinks to humanoid customers in a virtual bar where they needed to move back and forth between drink service and refill stations. As expected, stable patterns of movement coordination emerged between co-actors, with one participant in a pair exhibiting a more circular movement trajectory between the service and refill locations, while the second participant in a pair exhibited a more straight-line trajectory between the two locations. Consistent with the results of Richardson et al., (2015), this pattern was observed across nearly all pairs, indicating that the same dynamical processes governing simple hand-arm coordination tasks also regulate more complex, full-body and naturalistic goal-directed interpersonal coordination tasks.

Deep reinforcement learning (Deep RL) methods can train artificial agents (AAs) to reach or exceed human-level performance. However, in multiagent contexts requiring competitive behavior or where the aim is to use AAs for human training, the qualitative behaviors AAs adopt may be just as important as their performance to ensure representative training. This paper compares human behaviors and performance when competing against either a human expert or an AA opponent trained using Deep RL on a 2-dimensional version of Pong. Results show that participants were not sensitive to the movement differences between the human expert and AA. Further, the participants did not alter their behaviors, except to compensate for differences in the environmental states caused by the opponents. The paper concludes with discussion on the potential impacts of AA training on human behavior with regard to representative design in the areas of skill development and team training.

Team interaction involves the division of labor and coordination of actions between members to achieve a shared goal. Although the dynamics of interactions that afford effective coordination and performance have been a focus in the cognitive science community, less is known about how to generate these flexible and adaptable coordination patterns. This is important when the goal is to design artificial agents that can augment and enhance team coordination as synthetic teammates. Although previous research has demonstrated the negative impact of model-based agents on the pattern of interactions between members using recurrence quantification methods, more recent work utilizing deep reinforcement learning has demonstrated a promising approach to bootstrap the design of agents to team with humans effectively. This paper explores the impact of artificial agent design on the interaction patterns that are exhibited in human-autonomous agent teams and discusses future directions that can facilitate the design of human-compatible artificial agents.

Altering an individual’s identity during virtual tasks, such that it is incongruent with their own identity, can reduce unconscious biases and increase empathy and prosocial behavior. While such virtual embodiment has been investigated for race, age, and socioeconomic status, the question remains whether immersive perspective taking reduces implicit gender bias. Accordingly, we investigated the effect of gendered embodiment on gender bias related to the underrepresentation of women in science, technology, engineering, and math fields. Undergraduate students (N=65) undertook a simulated virtual interview task, which included the rating and selection of male and female candidates. Females were significantly more empathetic than males. Greater empathy predicted higher candidate ratings, except for competence of the female candidate. Preliminary findings establish foundations for future comparative studies and contribute to elucidating the nature of empathy during and after virtual perspective taking, such that it may have a greater impact on males for modulating gender bias.

In many team-based activities, members search for information to gain situational awareness and thereby structure their own behavior. The extent to which members are coupled and in control of their surrounding environment can be accessed via the fluctuations of their searching behaviors. To facilitate prospective control, assistive technologies such as a head-up display (HUD) can alleviate the demands of search and facilitate team performance. This study investigated how three-person teams divided their labor and structured their search behavior when playing a multiplayer search-and-retrieval task where first-person visibility and access to a HUD were manipulated. Results showed that access to task relevant information facilitated performance and division of labor, and increased prospective control of searching behaviors, as indexed by detrended fluctuation analysis (DFA). Over multiple sessions, teams learned to use the HUD to structure their behavior to achieve the task goal. Results indicate the potential in using DFA for monitoring prospective control in team contexts.

More than 400,000 people each year suffer adverse effects following bites from venomous snakes. However, snake venom is also a rich source of bioactive molecules with known or potential therapeutic applications. Manually ‘milking’ snakes is the most common method to obtain venom. Safer alternative methods to produce venom would facilitate the production of both antivenom and novel therapeutics. This protocol describes the generation, maintenance and selected applications of snake venom gland organoids. Snake venom gland organoids are 3D culture models that can be derived within days from embryonic or adult venom gland tissues from several snake species and can be maintained long-term (we have cultured some organoids for more than 2 years). We have successfully used the protocol with glands from late-stage embryos and recently deceased adult snakes. The cellular heterogeneity of the venom gland is maintained in the organoids, and cell type composition can be controlled through changes in media composition. We describe in detail how to derive and grow the organoids, how to dissociate them into single cells, and how to cryopreserve and differentiate them into toxin-producing organoids. We also provide guidance on useful downstream assays, specifically quantitative real-time PCR, bulk and single-cell RNA sequencing, immunofluorescence, immunohistochemistry, fluorescence in situ hybridization, scanning and transmission electron microscopy and genetic engineering. This stepwise protocol can be performed in any laboratory with tissue culture equipment and enables studies of venom production, differentiation and cellular heterogeneity.

More than 400,000 people each year suffer adverse effects following bites from venomous snakes. However, snake venom is also a rich source of bioactive molecules with known or potential therapeutic applications. Manually 'milking' snakes is the most common method to obtain venom. Safer alternative methods to produce venom would facilitate the production of both antivenom and novel therapeutics. This protocol describes the generation, maintenance and selected applications of snake venom gland organoids. Snake venom gland organoids are 3D culture models that can be derived within days from embryonic or adult venom gland tissues from several snake species and can be maintained long-term (we have cultured some organoids for more than 2 years). We have successfully used the protocol with glands from late-stage embryos and recently deceased adult snakes. The cellular heterogeneity of the venom gland is maintained in the organoids, and cell type composition can be controlled through changes in media composition. We describe in detail how to derive and grow the organoids, how to dissociate them into single cells, and how to cryopreserve and differentiate them into toxin-producing organoids. We also provide guidance on useful downstream assays, specifically quantitative real-time PCR, bulk and single-cell RNA sequencing, immunofluorescence, immunohistochemistry, fluorescence in situ hybridization, scanning and transmission electron microscopy and genetic engineering. This stepwise protocol can be performed in any laboratory with tissue culture equipment and enables studies of venom production, differentiation and cellular heterogeneity.

The inclusion of sport climbing at the Tokyo 2020 Olympics marks a decade of transformation for this once niche, countercultural sport. Alongside rapid growth in popularity, improved indoor facilities and increased mainstream media presence, climbing’s participation demographics have diversified. This thesis offers a timely examination of the experiences of sponsored female climbers, who receive more media coverage and social media attention than ever before. Through a multi-methods approach that combines media discourse analysis, ethnography, digital ethnography and interviews, the thesis shows that gendered experiences are complex, yet those athletes who comply with gendered expectations by displaying heteronormative gender characteristics benefit the most, especially on social media. All the change underway in climbing puts its countercultural roots at odds with the increasing need for sponsors’ portrayal on social media. Gendered, feminine bodies are central to the tension that the need for authenticity creates. Deploying the theoretical framework of ‘athletic labour of femininity’ (Toffoletti, Thorpe, Giulianotti, & Numerato, 2018), the thesis additionally analyses female athletes’ construction of femininity on social media. My analysis contributes to this valuable framework by including sociotechnical aspects that take into account algorithms, and the need for not creating controversy that can deter followers. Situated at a time when scholarly investigations into gendered representations on social media and in sports are responding to the changing social and commercial imperatives of sport, this thesis provides key insights into expectations and experiences of gender for women seeking to forge identities and livelihoods in sport. Located at the intersection of feminist cultural studies, media studies and sociology of sport, this study advances our understanding of the cultural undercurrents in a lifestyle sport such as climbing. Previous research in different

Wnt dependency and Lgr5 expression define multiple mammalian epithelial stem cell types. Under defined growth factor conditions, such adult stem cells (ASCs) grow as 3D organoids that recapitulate essential features of the pertinent epithelium. Here, we establish long-term expanding venom gland organoids from several snake species. The newly assembled transcriptome of the Cape coral snake reveals that organoids express high levels of toxin transcripts. Single-cell RNA sequencing of both organoids and primary tissue identifies distinct venom-expressing cell types as well as proliferative cells expressing homologs of known mammalian stem cell markers. A hard-wired regional heterogeneity in the expression of individual venom components is maintained in organoid cultures. Harvested venom peptides reflect crude venom composition and display biological activity. This study extends organoid technology to reptilian tissues and describes an experimentally tractable model system representing the snake venom gland.

Wnt dependency and Lgr5 expression define multiple mammalian epithelial stem cell types. Under defined growth factor conditions, such adult stem cells (ASCs) grow as 3D organoids that recapitulate essential features of the pertinent epithelium. Here, we establish long-term expanding venom gland organoids from several snake species. The newly assembled transcriptome of the Cape coral snake reveals that organoids express high levels of toxin transcripts. Single-cell RNA sequencing of both organoids and primary tissue identifies distinct venom-expressing cell types as well as proliferative cells expressing homologs of known mammalian stem cell markers. A hard-wired regional heterogeneity in the expression of individual venom components is maintained in organoid cultures. Harvested venom peptides reflect crude venom composition and display biological activity. This study extends organoid technology to reptilian tissues and describes an experimentally tractable model system representing the snake venom gland.