Noise is a pervasive feature of everyday environments that can influence cognitive performance in both detrimental and beneficial ways. These apparently contrasting effects may depend on the interplay between acoustic structure and task-specific cognitive demands. This study compared how various types of noise may influence specific cognitive functions. Participants completed cognitive tasks under six different acoustic conditions: silence, white, pink, sharp, fluctuating and rough noise. Cognitive tasks measured selective attention (Attention Matrices), visuospatial memory maintenance and manipulation (forward and backward Corsi), executive functions and attentional resources (backward counting). The results showed that selective attention improved with continuous white and sharpness-filtered noise compared to silence, whereas fluctuating noise reduced performance on selective attention and visuospatial short-term maintenance. Rough noise impaired visuospatial short-term manipulation, while backward counting was not affected by noise types. Therefore, the different types of noise exerted a selective influence on cognitive performance.
As a promising solution for manned Urban Air Mobility (UAM), electric vertical takeoff and landing (eVTOL) aircraft are expected to be available to the general public in the near future. However, the existing control system in aviation might be too complex for the general public. Thus, eVTOL manufacturers have been revolutionizing eVTOL control systems in recent years, and the single-hand joystick control interface is one example. In a mixed-reality (MR), 6-degrees-of-freedom (6-DOF) flight simulator, we evaluated a novel single-hand joystick control interface for eVTOL aircraft, a solution that simulates drone operation and has already been adopted by a commercial eVTOL, and examined the effects of short-term operational training on potential users’ operating performance. Given that the operating skills in similar domains might be transferable, participants with (drone pilots, n = 12) and without (non-pilots, n = 12) drone operating experience were recruited. All participants underwent a 30-minute MR-based eVTOL operation training. Comparing pilots’ performance metrics before and after training showed improved eVTOL aircraft operational performance, supported by changes in electrocardiogram, electrodermal activity, respiration, and electromyography metrics. We also found that pilots performed better than non-pilots overall, and that non-pilots benefited more from the short-term training program. These findings highlight the feasibility of short-term training for basic eVTOL operational performance using a drone-like simplified control system and reveal, from a cognitive perspective, the transferability of operational skills between drone operation and eVTOL control. Short-term training significantly enhanced non-pilots’ eVTOL control performance. Drone pilots generally outperformed non-pilots, showing experience transfer effects. Physiological stress and muscle effort decreased after training in both groups. Findings highlight the value of simplified controls for future eVTOL users.
This study examines farmers' views of data privacy, data ownership, cybersecurity, and governance in Canadian agriculture. Evidence on data protection and security in this context remains limited. To address this gap, we interviewed 45 stakeholders between 2020 and 2025, primarily in Ontario and Nova Scotia. Participants included 31 farmers (three of whom combine farming with another occupation), 13 other agricultural stakeholders, and one government representative. Following Lochmiller's (2021) three phases of thematic analysis, we coded participants' reasons inductively into nine first-order categories. These categories were consolidated into six themes and overarching three classifiers: Socio-Technical Risk and Assurance, Technological and Systemic Vulnerabilities, and Economic and Strategic Impact. Across all three classifiers, trust emerged as the central mechanism connecting cybersecurity, governance, privacy, AI, and technology adoption. Farmers generally trusted that the technologies worked while distrusting the organisations behind them. They treated AI as a tool to be verified rather than an authority. Farmers did not reject innovation outright. Resistance arose mainly where technologies seemed opaque, poorly governed, externally controlled, insufficiently regulated, or economically burdensome. The findings reframe cybersecurity adoption in agriculture as a socio-technical process rather than a purely technical issue. This process is shaped by governance, legitimacy, transparency, awareness, and economic realities. They also highlight farmers' potential to act as agents of change. Informal mechanisms, such as peer learning and community-driven adaptations, should complement formal policies. Transparent, participatory governance is needed to align society with technological progress.
Motion sickness (MS) presents an important challenge to the widespread adoption of autonomous vehicles (AVs), as it impairs passenger comfort and may compromise overall safety. To support adaptive comfort management and timely intervention, reliable real-time assessment of MS is needed. However, objective assessment remains challenging because no single measurable biomarker has been established for continuous monitoring. This study investigated real-time salivary sodium ion (Na⁺) monitoring via a wearable sensor as a candidate biomarker of MS severity under controlled automated-driving simulator conditions. Thirty participants completed a simulated Level 4 automated-driving exposure while salivary Na⁺, subjective symptom ratings, and multimodal physiological signals were recorded. Minute-level salivary Na⁺ changes were positively associated with MISC severity (ρ = 0.581–0.700 across groups). Ordinal generalized additive mixed modelling further indicated a stage-dependent association, with an approximately linear pattern in the low-symptom group and a significant nonlinear pattern in the high-symptom group. A Random Forest model achieved moderate predictive performance (R2 = 0.692), and salivary Na⁺ showed the highest model-specific feature importance among the measured predictors. Taken together, these findings support salivary Na⁺ as a candidate biomarker for further investigation under simulator conditions; validation in real vehicles and broader passenger populations is required before practical in-vehicle performance can be established.
Resilience Engineering provides organisations with a theoretical lens through which performance is understood not merely as the avoidance of failure but as the active, ongoing maintenance of adaptive capacity across changing conditions. Despite the richness of this theoretical corpus, practitioner-facing tools that operationalise resilience thinking at the system level remain scarce. This paper introduces the Resilience Canvas, a single-page conceptual artefact inspired by the methodological lineage of the Business Model Canvas but grounded in Resilience Engineering theory. Drawing on Hollnagel’s four resilience potentials (Anticipate, Monitor, Respond, Learn), Woods’ notion of graceful extensibility, Leveson’s systems-theoretic perspective, and the constructs of Simplexity, Complixity, and Complexity Compression developed by Falegnami et al. (2024) for the analysis of complexity in sociotechnical systems, we develop a nine-block ontological structure that maps the resilience potential of a sociotechnical system in a single visual representation. The canvas integrates functional, informational, artefactual, and resource dimensions into a coherent framework, designed to be usable without the modelling expertise that existing methods require. A walkthrough application in an urban hospital emergency department and a second application in a grocery distribution centre illustrate what the artefact makes visible in contrasting conditions. Its usefulness in practice has not been measured and remains a matter for empirical work. The Resilience Canvas is proposed as a boundary object enabling cross-domain, cross-disciplinary dialogue on system resilience.
