Objective: We present a new photoacoustic tomography system that provides visualization of angiographic features in a human breast with mammogram-like images. Methods: The system images a mildly compressed breast, from both top and bottom, using two 128-element, 2.25 MHz linear transducer arrays and line optical fiber bundles. The mild compression is achieved using plastic films, which is a more comfortable experience for the patient compared to rigid metal plates used in a traditional mammogram. Results: We could image a D cup-sized breast of 7 cm thickness within 1 minute and achieved a spatial resolution of around 1 mm in all directions. Conclusion: Our system possesses the benefits of portability, speedy scanning, and patient comfort. The craniocaudal-view images can be easily correlated with existing imaging modalities for data interpretation. Significance: Early cancer detection plays a critical role in overall cancer survival rate. Our system may address the limitations of mammogram and offer a radiation-free screening technique for patients with dense breasts.

As educational tools continue to evolve technologically, game-based learning (GBL) has emerged for its ability to improve specific learning outcomes such as motivation, engagement, and knowledge acquisition and retention. Despite recent advances with educators incorporating games and gaming strategies into higher-learning curricula, there is a current void in the literature that clarifies the critical relationship between GBL implementations and learning outcomes. In this effort, we build upon previous research by detailing the specification, design, and deployment of a series of GBL experiential learning interventions intended to improve conceptual understanding of vehicle dynamics. This implementation should result in positive downstream impacts on safety, both for the vehicle (i.e., design/interface)—and its driver. In our intervention, we deploy three separate pilot studies in a graduate engineering vehicle dynamics course, all of which leverage advanced GBL environments deployed on a high-fidelity motion-based driving simulator. The primary goals of the pilot studies are to interactively achieve an enhanced understanding of: (i) oversteer/understeer vehicles at ever-increasing speed; (ii) an optimal cornering strategy subject to the tire conditions of the vehicle; and (iii) lateral handling and yaw stabilization of a vehicle within an extreme evasive maneuver at varying entry speeds. The outcomes of the current effort serve to promote a future Theory of Change for planned best practices to improve human factors and human–vehicle machine interfaces through authentication of GBL in engineering education on a broader scale.

Despite numerous recent advances in the classroom and in-vehicle driver training and education over the last quarter-century, traffic accidents remain a leading cause of mortality for young adults—particularly, those between the ages of 16 and 19. Obviously, despite recent advances in conventional driver training (e.g., classroom, in-vehicle, Graduated Driver Licensing programs), this remains a critical public safety and public health concern. As advanced vehicle technologies continue to evolve, so too does the unintended potential for mechanical, visual, and/or cognitive driver distraction and adverse safety events on national highways. For these reasons, a physics-based modeling and high-fidelity simulation have great potential to serve as a critical supplementary component of a near-future teen-driver training framework. Here, a case study is presented that examines the specification, development, and deployment of a “blueprint” for a simulation framework intended to increase driver training safety in North America. A multi-measure assessment of simulated driver performance was developed and instituted, including quantitative (e.g., simulator-measured), qualitative (e.g., evaluator-observed), and self-report metrics. Preliminary findings are presented, along with a summary of novel contributions through the deployment of the training framework, as well as planned improvements and suggestions for future directions.