A roadmap for improving data quality through standards for collaborative intelligence in human-robot applications.

Collaborative intelligence (CI) involves human-machine interactions and is deemed safety-critical because their reliable interactions are crucial in preventing severe injuries and environmental damage. As these applications become increasingly data-driven, the reliability of CI applications depends on the quality of data, shaping the system's ability to interpret and respond in diverse and often unpredictable environments. In this regard, it is important to adhere to data quality standards and guidelines, thus facilitating the advancement of these collaborative systems in industry.

Brominated flame retardants in Caretta caretta sea turtles from the Adriatic Sea.

This study evaluated the levels of 10 polybrominated diphenyl ethers (PBDEs) and 3 hexabromocyclododecanes (HBCDDs) in liver and fat tissue of 45 Caretta caretta stranded along the Adriatic Sea. The analytical methodology was based on gas or liquid chromatography coupled with high-resolution mass spectrometry. The mean values of PBDEs and α-HBCDD were 0.

Neuroergonomic Attention Assessment in Safety-Critical Tasks: EEG Indices and Subjective Metrics Validation in a Novel Task-Embedded Reaction Time Paradigm.

This study addresses the gap in methodological guidelines for neuroergonomic attention assessment in safety-critical tasks, focusing on validating EEG indices, including the engagement index (EI) and beta/alpha ratio, alongside subjective ratings. A novel task-embedded reaction time paradigm was developed to evaluate the sensitivity of these metrics to dynamic attentional demands in a more naturalistic multitasking context. By manipulating attention levels through varying secondary tasks in the NASA MATB-II task while maintaining a consistent primary reaction-time task, this study successfully demonstrated the effectiveness of the paradigm.

Experiment data: Human-in-the-loop decision support in process control rooms.

These datasets contain measures from multi-modal data sources. They include objective and subjective measures commonly used to determine cognitive states of workload, situational awareness, stress, and fatigue using data collection tools such as NASA-TLX, SART, eye tracking, EEG, Health Monitoring Watch, a survey to assess training, and a think-aloud situational awareness assessment following the SPAM methodology. Also, data from a simulation formaldehyde production plant based on the interaction of the participants in a controlled control room experimental setting is included.