Visualizations often encode multivariate data by mapping attributes to distinct visual channels such as color, size, or shape. The effectiveness of these encodings depends on separability--the extent to which channels can be perceived independently. Yet systematic evidence for separability, especially in map-based contexts, is lacking. We present a crowdsourced experiment that evaluates the separability of four channel pairs--color (ordered) x shape, color (ordered) x size, size x shape, and size x orientation--in the context of bivariate symbol maps. Both accuracy and speed analyses show that color x shape is the most separable and size x orientation the least separable, while size x color and size x shape do not differ. Separability also proved asymmetric--performance depended on which channel encoded the task-relevant variable, with color and shape outperforming size, and square shape especially difficult to discriminate. Our findings advance the empirical understanding of visual separability, with implications for multivariate map design.

Homophily refers to the tendency of individuals to associate with others who are similar to them in characteristics, such as, race, ethnicity, age, gender, or interests. In this paper, we investigate if individuals exhibit racial homophily when viewing visualizations, using mass shooting data in the United States as the example topic. We conducted a crowdsourced experiment (N=450) where each participant was shown a visualization displaying the counts of mass shooting victims, highlighting the counts for one of three racial groups (White, Black, or Hispanic). Participants were assigned to view visualizations highlighting their own race or a different race to assess the influence of racial concordance on changes in affect (emotion) and attitude towards gun control. While we did not find evidence of homophily, the results showed a significant negative shift in affect across all visualization conditions. Notably, political ideology significantly impacted changes in affect, with more liberal views correlating with a more negative affect change. Our findings underscore the complexity of reactions to mass shooting visualizations and suggest that future research should consider various methodological improvements to better assess homophily effects.

Freshwater ecosystems are among the most biodiverse ecosystems on the planet and constitute key natural resources for human economies. These ecosystems, however, are endangered due to persistent human activities, whose effects range from temperature changes to water pollution. Here, we develop an online serious game to educate youth regarding human impact on freshwater ecosystems. In particular, we focus on how environmental variables can affect the behavior and well-being of freshwater fish, which are critical to the food web and the function of the whole ecosystem. In the game, players aim to maximize fish fitness by foraging and reproducing, despite adversarial environmental conditions. We leverage dynamical systems and control theory to create mathematical models for all game characters and components, including animal locomotion and hydrodynamic interactions with the flow physics of a virtual river. We test the educational value and usability of the game on a group of middle-school students from New York City. Our results suggest that games like the proposed serious game could be a viable tool to engage youth in environmental education about freshwater ecosystems.

[This corrects the article DOI: 10.1371/journal.pcbi.1008644.].

Understanding how animals navigate complex environments is a fundamental challenge in biology and a source of inspiration for the design of autonomous systems in engineering. Animal orientation and navigation is a complex process that integrates multiple senses, whose function and contribution are yet to be fully clarified. Here, we propose a data-driven mathematical model of adult zebrafish engaging in counter-flow swimming, an innate behavior known as rheotaxis. Zebrafish locomotion in a two-dimensional fluid flow is described within the finite-dipole model, which consists of a pair of vortices separated by a constant distance. The strength of these vortices is adjusted in real time by the fish to afford orientation and navigation control, in response to of the multi-sensory input from vision, lateral line, and touch. Model parameters for the resulting stochastic differential equations are calibrated through a series of experiments, in which zebrafish swam in a water channel under different illumination conditions. The accuracy of the model is validated through the study of a series of measures of rheotactic behavior, contrasting results of real and in-silico experiments. Our results point at a critical role of hydromechanical feedback during rheotaxis, in the form of a gradient-following strategy.

Engagement is a key element in game design, and competition is frequently used to enhance players' engagement. However, it is presently unclear how winning or losing might influence players' engagement. We hypothesized that users in a competitive game will increase their level of engagement when they are losing. To test this hypothesis, we created a game in virtual reality in which each user competed against a virtual opponent that was programmed to either underperform, tie with, or overperform the user. We conducted a series of experiments on 72 volunteers who played four rounds of the game, with three rounds against each of the potential virtual opponents and one round alone. We found that user engagement increased when the virtual opponent outperformed the user, compared to when they played alone. A similar increase in user engagement was not registered when the user played against an underperforming or equally performing virtual opponent. To further elucidate the effect of the virtual opponent on user engagement, we applied the information-theoretic notion of transfer entropy, which offers a model-free approach for the inference of causal relationships between dynamical systems. Our findings provide insight into technology-mediated competition and its impact on engagement, thereby opening the door for targeted system interventions to modulate human response.

The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.

Advancements in computer‐mediated exercise put forward the feasibility of telerehabilitation, but it remains a challenge to retain patients' engagement in exercises. Building on our previous study demonstrating enhanced engagement in citizen science through social information about others' contributions, we propose a novel framework for effective telerehabilitation that integrates citizen science and social information into physical exercise. We hypothesized that social information about others' contributions would augment engagement in physical activity by encouraging people to invest more effort toward discovery of novel information in a citizen science context. We recruited healthy participants to monitor the environment of a polluted canal by tagging images using a haptic device toward gathering environmental information. Along with the images, we displayed the locations of the tags created by the previous participants. We found that participants increased both the amount and duration of physical activity when presented with a larger number of the previous tags. Further, they increased the diversity of tagged objects by avoiding the locations tagged by the previous participants, thereby generating richer information about the environment. Our results suggest that social information is a viable means to augment engagement in rehabilitation exercise by incentivizing the contribution to scientific activities.

In this work, we leverage the information-theoretic notion of transfer entropy theory to study causal information flow in epidemic spreading over temporal networks. An improved understanding of causal information flow may lead to the early detection of population segments that should be monitored or immunized to enhance epidemic containment. We focus on activity driven networks, which constitute a powerful and elegant paradigm to capture the inherent time-varying nature of contacts and population heterogeneity. Our preliminary results confirm the intuition that individuals who have a higher propensity in contacting others are responsible for the largest information transfer. Moreover, we find that epidemic parameters such as the probability of infection and recovery may dominate the spreading phenomenon over heterogeneities in the contact formation.

Online participation is becoming an increasingly common means for individuals to contribute to citizen science projects, yet such projects often rely on only a small fraction of participants to make the majority of contributions. Here, we investigate a means for influencing the performance of citizen scientists toward enhancing overall participation. Building on past social comparison research, we pair citizen scientists with a software‐based virtual peer in an environmental monitoring project. Through a series of experiments in which virtual peers outperform, underperform, or perform similarly to human participants, we investigate the influence of their presence on citizen science participation. To offer insight into the psychological determinants to the response to this intervention, we propose a new dynamic model describing the bidirectional interaction between humans and virtual peers. Our results demonstrate that participant contribution can be enhanced through the presence of a virtual peer, creating a feedback loop where participants tend to increase or decrease their contribution in response to their peers' performance. By including virtual peers that systematically outperform the participants, we demonstrate a fourfold increase in their contribution to the citizen science project.

Crowdsourcing has seen a substantial increase in interest from researchers and practitioners in recent years. Being a new form of work facilitated by information technology, the rise of crowdsourcing calls for the development of new theoretical insights. Our focus in this article is on extra‐role behavior—employees' voluntary activities, which are not part of their prescribed duties. Specifically, we explored how user interface design can help increase extra‐role behavior among crowdsourcing workers. In a randomized experiment, we examined the joint effects of the presentation of a performance display to crowdsourcing workers and the personal attributes of these workers on the workers' likelihood to engage in extra‐role behavior. The experimental setting included an image analysis task performed on an environmental monitoring website. We compared workers' behavior across the different experimental conditions and found that the interaction between the presence of a performance display and the workers' personality trait of curiosity has a significant impact on the likelihood of engaging in extra‐role behavior. In particular, the presence of a performance display was associated with increased likelihood of extra‐role behavior among low‐curiosity workers, and no change in extra‐role behavior was observed among high‐curiosity users. Implications for design are discussed.

Informal science education is a key contributing factor to scientific literacy, which determines our capacity as a society to technologically progress and make cognizant decisions on pressing issues of global scale. Both the fields of robotics and natural user interfaces have been separately proposed as effective means to aid informal science education, by increasing users' engagement through multiple interactive features. Here, we demonstrate the integration of these two fields of investigation toward a novel educational platform, revolving around the control of a robotic fish via a natural user interface. Users control the robotic fish through upper limb gestures that are captured by the Kinect. The robotic fish incorporates a temperature sensor, which collects data in a tank instrumented with heating and cooling sources. Participants observe the measurements they are recording in real-time to map the environment. Self-reported post-activity surveys and behavioral coding data on young users were collected to assess their level of engagement in the activity and their perception of the system. Our results indicate that the robotic fish is intuitive to drive with the natural user interface, the activity of collecting water temperature is interesting, and robotics may be a viable and accessible career option.

Environmental tracking and formation control for a platoon of autonomous vehicles is studied. Vehicles travel through an environment that possesses a measurable scalar field, with the goal of moving in a desired spatial pattern about a desired constant value contour in the field. Each vehicle measures the local value of the field along its trajectory and shares information about its measurements and trajectory with other vehicles in the platoon. Platoon control involves estimation of a virtual leader trajectory coinciding with the target contour and about which vehicles form. Two approaches to leader estimation are considered. The first involves the synthesis of a common leader trajectory, whereas the second involves decentralized estimation of the leader trajectory by individual vehicles. Under the second approach, platoon control is posed as a two-level consensus problem, where vehicles reach agreement on the leader trajectory at one level and reach formation about the leader at the other level. The decentralized approach is effective even when communication among vehicles is limited. A target application involving an underwater vehicle platoon is considered