To address rising comfort expectations in turbofan aircraft cabins, this study developed a predictive model for multimodal discomfort from combined noise and vibration. The noise/vibration stimuli were generated based on recordings in front and middle cabins during taxiing and cruising and amplitude-modulated to four intensity levels. Using a 6-DOF vibration simulator replicating cabin dynamics, we exposed 26 participants to isolated and combined stimuli. Results revealed vibration attenuated noise discomfort in middle cabin during taxiing, while noise bidirectionally modulated vibration discomfort in middle cabin during taxiing or cruising and front cabin during cruising. Mutual inhibition neutralised cross-modal effects during peak taxiing conditions in middle section. Equivalence discomfort contours quantified the relative impact of each modality, identifying optimisation priorities. A multivariate regression model predicting combined discomfort from modality-specific inputs achieved high accuracy (adjusted = 0.819), providing an engineering tool for cabin environment design.

Ride-hailing and delivery work are major components of the gig economy but often involve long and unpredictable hours, making fatigue an inherent safety risk. This study aimed to identify solutions to mitigate fatigue and minimise its risk, using Indonesia as a case study. A two-stage methodology was applied: first, a scoping review identified proposed measures, then a two-day workshop with gig workers, platform companies, government representatives, and academics ( = 24) discussed their feasibility. Most identified measures were administrative in nature. Stakeholders diverged on employment status reclassification: workers supported it as a structural safeguard, whereas platform companies and government representatives resisted it due to economic and regulatory implications. Training was perceived as a feasible option by both parties. The results represent perceived feasibility rather than measured outcomes, highlighting the need for future research to evaluate real-world effectiveness, and reflect participants perspectives, with platform companies underrepresented and government voices more prominent.

The study aimed to develop a comprehensive flight performance evaluation model based on flight parameters, covering the entire flight and applicable to normal and abnormal conditions. Thirty-seven pilots performed one normal traffic pattern flight and one single-engine failure emergency flight using a Cessna-172 simulator. The complete flight was divided into distinct phases - takeoff, climb, cruise, descent, approach/landing, and emergency, with evaluation metrics defined for each phase. The analytic hierarchy process was employed to determine the weights of flight phases and evaluation metrics. Two flight instructors provided ratings of performance after reviewing video recordings of the flights. ChatGPT generated five sets of performance scores based on the flight data. Intraclass correlation coefficient and correlation analyses indicated good consistency across multiple evaluation sources. Significant correlations were found among model-derived scores, instructor ratings, and ChatGPT-generated scores. These findings demonstrate that the model is reliable, and potentially applicable to real-world flight training and operations.

To investigate the optimisation scheme for a floor evacuation map, library, and mall scenarios were considered as examples, and drive designs, including non-drive design, salient stimulus-drive design, and working memory-drive design, were introduced in the experiment. Participants' wayfinding behaviour and responses were studied by analysing the average duration of fixation (ADF), average fixation counts (AFC), accuracy rate (AR), response time (RT), and other relevant indices. The experimental data revealed that both the salient stimulus-drive and working memory-drive designs significantly reduced the ADF and AFC compared to the non-drive design while improving the AR. The RT of the salient stimulus-driven group was significantly longer than that of the other two groups. The experimental results indicated that incorporating floor plans and relevant salient stimuli into the design of floor evacuation maps can enhance their readability, thereby facilitating better retention of evacuation routes by participants.

Implementing real-time driving anger detection and appropriate intervention are crucial for road safety. A naturalistic driving study (NDS) was conducted to further validate the anger detection method tested in simulated experiments. Thirty-four drivers participated in the tests, each lasting one to two weeks. A smartphone with a self-developed application was used to record the encountered anger-provoking events, drivers' facial expressions, and vehicle kinematic data. Drivers' anger-related traits were collected through questionnaires. A total of 570 events were collected. Abnormal lane-changing, being blocked, and slow driving were the most common anger triggers, mainly occurring during morning rush hours on ring roads and inbound/outbound highways/main roads. The driving anger detection model with the collected data achieved 93.6% accuracy and 93.4% F1 score. Anger-sensitive features and their variations during anger were presented. These findings may enhance drivers' emotional experience in intelligent vehicles and facilitate the development of emotion detection and intervention systems.

Augmented Reality revolutionises education by enhancing learning with interactive, immersive experiences. However, the impact of long-term AR use, particularly in terms of physical demand, within educational environments remains poorly understood. This study investigates the relationship between AR engagement and physical demand, utilising motion capture technology, NASA Task Load Index, and HoloLens eye-tracking to quantify user posture, engagement, and perceived workload. We hypothesise that prolonged AR interaction results in a change in slouching scores, indicating increased fatigue. The results show a strong correlation between the slouching score and the NASA-TLX physical demand score. Our study lays the groundwork for incorporating predictive modelling to develop proactive physical demand measures.

This study examines dynamic personality for in-vehicle voice assistants (IVVAs), addressing a gap in research dominated by fixed assistant personality. Through field investigation of 14 vehicle brands in the Chinese market and a literature review to developed a dynamic personality framework for eight representative in-vehicle tasks. A 2 (personality: dynamic vs. fixed) × 2 (scenario: commuting vs. travel) mixed-design experiment was conducted with 32 participants. The Self-Assessment Manikin (SAM) and the User Experience Questionnaire (UEQ) assessed the effects of assistant personality on driver affect and user experience in autonomous driving. Results showed that compared to fixed personality, dynamic personality significantly improved drivers' pleasure, arousal and dominance across both scenarios. In terms of user experience, dynamic personality enhanced perceived attractiveness, stimulation and novelty but led to lower ratings in perspicuity, efficiency and dependability. These findings highlight the importance of dynamical personality in improving driver affect and optimising the in-vehicle user experience.

This article revisits the Equivalent Contact Temperature (ECT) model by incorporating winter scenarios with seat heating, which were unaddressed in previous studies. The research focuses on enhancing the model's accuracy in evaluating thermal comfort for seated individuals under non-uniform conditions, particularly for the buttocks and back. These contact areas are crucial for both local and overall comfort, especially with Personalised Environmental Control Systems (PECS), like seat heating and ventilation, which operate close to the body. PECS are more energy efficient than traditional HVAC systems, offering customisation to individual comfort preferences while enhancing individual thermal comfort and energy efficiency in buildings and vehicles. A participant study at air temperatures of 17 °C and 18 °C validated the ECT approach, confirming the effectiveness of seat heating and revealing key correlations between ECT values and thermal comfort ratings. Additionally, an equivalent skin temperature and a comfort evaluation scheme for winter conditions were introduced.

Touchscreens have transformed digital interactions, but the absence of physical feedback may disadvantage users with reduced tactile sensitivity. This study investigates vibrotactile feedback for touchscreen home appliances to enhance comfort and certainty across young adults (18-55) and late middle-aged and older users (55+), highlighting inclusive design for multigenerational smart-home environments. Using a washing machine touchscreen , 32 participants experienced 28 vibration conditions varying in duration, intensity, and frequency. Mixed ANOVAs indicated significant main effects of all three parameters on certainty (all < .05). Comfort ratings in the 18-55 group were influenced by intensity and frequency (both < .05), while the 55+ group showed reduced parameter sensitivity. Settings around 100-200 ms, 0.55-0.70 g, and ∼230 Hz jointly maximised certainty and comfort across groups. This study demonstrates how parameters adjustments can optimise usability for late middle-aged and older users, fostering inclusivity in touchscreen interaction.

In the current context of increasing levels of driving automation for passenger vehicles, addressing the issue of motion sickness has become a major challenge in the perspective of optimising motion comfort and the ride experience. 30 motion sickness-sensitive participants experienced a 20-minute passenger ride consisting of a series of cornering manoeuvres, with a focus on a visuomotor gaming activity. In a within-subjects design involving two experimental conditions, acceleration-coded seat belt tensions were generated as intervention. It was hypothesised that administering the intervention would result in lower levels of motion sickness severity and reduce postural sway. The tensions significantly reduced postural sway during cornering and met good user acceptance. In addition, significant gender differences were observed. Postural sway was more reduced in female participants, but only male participants exhibited lower motion sickness when experiencing the seat belt tensions as intervention.

Additional contact points in sitting workstations (e.g., backrests, armrests) are advantageous by providing variable posture support, but no research has focused on increased contact points for standing workstations. This study investigated standing postural strategies and muscle recruitment characteristics for both pain developers (PDs) and non-pain developers (NPDs) when additional support was provided for the trunk and pelvis during prolonged standing at workstations. Sixteen participants each visited twice to test standing workstations (with and without the contact intervention) while subjective low back pain (LBP), movement patterns, movement variability, and muscle activation were monitored for 60 minutes. Results revealed that additional contact points reduced subjective LBP in PDs (47%) and triggered additional body movements (lumbar fidgeting: 38%; centre of pressure (CoP) shifting: 46%; and CoP fidgeting: 44%). In conclusion, improved postural stability throughout additional contact intervention encouraged alternate postures and thus decreased subjective LBP.

To explore the effects of sleep inertia (SI) on physiological responses and cognitive performance, this study involved 1-h night-time sleep arousal experiments with twelve healthy participants. The KSS Scale, EEG, pulse rate (PR), blood pressure (BP), N-back test, and LRT Task were tested. The experimental design included a control condition (no intervention) and two behavioural countermeasure conditions (verbal communication and video watching). Results showed that during the first 10 min affected by SI, the EEG relative power decreased significantly by 72.1%, PR and BP increased significantly by 8.1 and 2.5%, respectively. After countermeasures, KSS scores decreased by 14.12 and 28.25%, EEG increased by 50.00 and 19.23%, the working memory increased by 24.32 and 43.24% for two countermeasures, respectively. Besides, cognitive and physiological responses affected by SI and the effects of countermeasures showed significant sex differences. Future research should explore SI effects across ages and develop more effective countermeasures to address SI.

This study aimed to assess the risk of biomechanical overload among physiotherapists of an orthopaedic institute using the REBA method integrated with organisational analysis. A preliminary checklist facilitated a detailed reconstruction of work organisation, enabling the quantification of time spent in awkward postures for the entire body and specific body regions. The findings indicate that physiotherapists were exposed to medium and high risk at least two-thirds of their working time. The back and shoulders emerged as the most affected body regions, with peaks at high risk and extensive medium risk. The integration of organisational analysis and REBA proves to be effective for accurate risk assessment. However, a major limitation is the considerable time required. This study underscores the importance of detailed work organisation analysis to support risk assessment in work settings with high postural variability and to develop targeted strategies for reducing biomechanical overload risk.

As cycling grows in popularity as a sustainable transport mode in Europe, cyclist safety has become a priority. Advanced Cyclist Assistance Systems (ACAS), inspired by Advanced Driver Assistance Systems (ADAS), offer potential safety improvements but remain underexplored. This study examines ACAS acceptance among 5,991 cyclists from 19 European countries, focusing on public perceptions and adoption drivers. Participants evaluated various ACAS types-crash prevention, visibility enhancement, environmental monitoring, and post-crash assistance-based on safety, usability, and reliability. Acceptance varied across countries, with higher rates in areas with strong cycling infrastructure. Safety and reliability were universally valued, though gender differences emerged: women prioritised safety and visibility, while men favoured usability and added features. The findings highlight the importance of infrastructure, reliable technology, and awareness efforts to promote adoption. Policymakers and developers can use these insights to tailor ACAS innovations, ultimately enhancing cycling safety and supporting the broader development of smart, cyclist-focused technologies.

While occupational footwear (OF) are designed to protect workers from acute injury, it is unclear whether OF affects worker function in otherwise innocuous tasks (i.e., standing and walking). Twenty individuals attended two sessions, wearing athletic footwear (AF) in one and OF in the other. Perceived discomfort, standing balance and gait parameters were measured before and after a 2-h prolonged standing protocol. Compared to AF, foot discomfort was 46 ± 4% greater ( = 0.020) after prolonged standing in OF. Standing balance was also differentially affected between footwear, with medio-lateral sway frequency increasing by 2 ± 3% when wearing OF ( = 0.020) but not in AF. Prolonged standing altered some gait parameters (e.g. increased stance duration, reduced propulsive force, etc.), but all changes were independent of footwear. Therefore, wearing OF is unlikely to cause any substantial changes in standing balance or gait that increases the risk of overuse workplace injury.

This study aims to analyse the actual conditions for tenant participation in social housing energy renovation projects, which are considered necessary for achieving sustainability goals, not only be considered in relation to environmental and technological solutions but also concern tenants' activities, construction teams, and social landlords' work and their cooperation. Based on a case study-the renovation of 153 mining houses in the North of France-we assess tenant participation by analysing the concrete interactions between a construction team and tenants. Our analyses detail the gaps between the construction team and tenants in terms of the perspectives and problems addressed. These results open avenues for improving the participation of tenants, cooperation and mutual learning in energy renovation projects, by giving a real value to their knowledge, setting up co-design workshops well in amount of renovation projects proposing them and construction teams actual projection methodologies, such as activity simulation.

In coal mining environments, underground transport vehicles are essential for transportation operations, yet high accident rates persist due to environmental and human factors. This study investigated the effects of auditory, tactile, and combined auditory-tactile warnings on driver driving and cognitive performance in a simulated underground transport vehicle cabin. 24 participants (12 novice, 12 experienced) completed baseline driving, stimulus-response tasks and interference tasks while their driving behaviour, physiological indicators and subjective evaluations were recorded. Results showed that tactile and combined warnings improved response performance over auditory warnings, with combined warnings enhancing attentional focus and reducing reaction times, particularly for novice drivers. Tactile and combined warnings also demonstrated superior resistance to distraction. For experienced drivers, tactile alerts most effectively reduced cognitive load under high demand. These findings highlight the potential of tactile and combined warnings to improve operational safety and reduce accident risks in underground coal mine transport operations.

Despite the growing interest in multimodal communication in human-robot interaction (HRI), research about how to design robots' multimodal feedback in educational contexts remains limited. This study employed a 2 × 3 (voice gender: male vs female × body movements: head vs hand vs combined movements) within-subject experimental design to investigate the effects of multimodal feedback (voice and body movements) on learning outcomes from three perspectives: affective outcomes, visual attention, and cerebral activity. The results revealed that voice gender and body movements significantly influenced users' affective outcomes and cerebral activity. Voice gender impacted visual attention, and an interaction effect between voice gender and body movements was observed in cerebral activity. Moreover, this research suggested that robots with female voices and combined movements promoted learning outcomes and revealed that robot voice gender and body movements may independently shape users' learning outcomes in low-demand cognitive feedback.

This study investigated the vibration-induced discomfort experienced at the second-row seat in multi-purpose vehicles (MPVs) and proposed a deep learning-based prediction model for discomfort. Experiments were conducted on a four-poster test rig to collect time-domain accelerations in three directions at the backrest, seat pan and armrests, with different seat absorber designs and vehicle operating conditions. A Long Short-Term Memory (LSTM) neural network was developed to model the nonlinear relationship between the objective vibration features and subjective discomfort ratings. To increase the sample size and enhance generalisation, a data augmentation strategy was implemented by filtering white noise signals to match the spectral characteristics of the measured accelerations. Results demonstrated that using the three-directional backrest acceleration as input yielded high prediction accuracy; however, expanding input features to include vibrations from other seat components led to degraded performance. This study established a framework for modelling the relationship between seat vibration and occupant discomfort.

Feedback plays a crucial role in enhancing the efficiency of a personal computer aviation training device (PCATD) which makes it a key application of optimising resource use and improving training outcomes. This paper makes a new attempt to explore the training feedback as a novel approach for the performance effect in PCATDs. A prototype was designed and evaluated in a lab-based experimental study with 29 student pilots, during which we compared the impact on design of feedback time, granularity, type and content on flight training outcomes. The results indicate that feedback interventions significantly enhance performance. Specifically, shorter feedback intervals and finer feedback granularity were found to improve training outcomes by reducing cognitive overload caused by excessive information. Furthermore, adaptive feedback had potential applications in PCATDs. These findings contribute valuable insights to the design of advanced instructional strategies for PCATDs, paving the way for more effective and efficient pilot training methodologies.