Search Results (2,026)

Distance learning has become essential to higher education, yet its application in military officer training presents unique academic, operational, and security challenges. For Lithuania’s future officers, remote education must foster not only knowledge acquisition but also decision-making, leadership, and operational readiness—competencies traditionally developed in immersive, in-person environments. This study addresses these challenges by integrating System Dynamics Modelling, Contemporary Risk Management Standards (ISO 31000:2022; Dynamic Risk Management Framework), and Learning Analytics to evaluate the interdependencies among twelve critical factors influencing the system resilience and effectiveness of distance military education. Data were collected from fifteen domain experts through structured pairwise influence assessments, applying the fuzzy DEMATEL method to map causal relationships between criteria. Results identified key causal drivers such as Feedback Loop Effectiveness, Scenario Simulation Capability, and Predictive Intervention Effectiveness, which most strongly influence downstream outcomes like learner engagement, risk identification, and instructional adaptability. These findings emphasize the strategic importance of upstream feedback, proactive risk planning, and advanced analytics in enhancing operational readiness. By bridging theoretical modelling, contemporary risk governance, and advanced learning analytics, this study offers a scalable framework for decision-making in complex, high-stakes education systems. The causal relationships revealed here provide a blueprint not only for optimizing military distance education but also for enhancing overall system resilience and adaptability in other critical domains. Full article

This study presents the development and evaluation of an Augmented Reality (AR)-based training system aimed at improving patient setup accuracy in radiation therapy. Leveraging Microsoft HoloLens 2, the system provides an immersive environment for medical staff to enhance their understanding of patient setup procedures. High-resolution 3D anatomical models were reconstructed from CT scans using 3D Slicer, while Luma AI was employed to rapidly capture complete body surface models. Due to limitations in each method—such as missing extremities or back surfaces—Blender was used to merge the models, improving completeness and anatomical fidelity. The AR application was developed in Unity, employing spatial anchors and 125 × 125 mm² QR code markers to stabilize and align virtual models in real space. System accuracy testing demonstrated that QR code tracking achieved millimeter-level variation, with an expanded uncertainty of ±2.74 mm. Training trials for setup showed larger deviations in the X (left–right), Y (up-down), and Z (front-back) axes at the centimeter scale. This meant that we were able to quantify the user’s patient setup skills. While QR code positioning was relatively stable, manual placement of markers and the absence of real-time verification contributed to these errors. The system offers a radiation-free and interactive platform for training, enhancing spatial awareness and procedural skills. Future work will focus on improving tracking stability, optimizing the workflow, and integrating real-time feedback to move toward clinical applicability. Full article

Parkinson’s disease (PD) presents an association of motor and non-motor impairments that impact the independence and quality of life of individuals. Rehabilitation programs must address multiple domains, simultaneously maintaining patients’ adherence and the implications of the disease. Immersive virtual-reality-based rehabilitation (IVRBR) is a promising alternative tool, or can be used in conjunction with traditional or passive programs, using interactive tasks in valid environments with specific training programs adapted to each individual’s needs. This narrative review synthesizes the medical literature published in the last decade from PubMed, Scopus, and Web of Science, on the effectiveness, limitations, and implementations of IVRBR in PD patients. Evidence from RTCs and non-RTCs suggests that IVRBR can improve balance, motor learning, and dual task performance. At the same time, the evidence suggests that it can improve cognitive and emotional status. The integration of objective assessment tools (motion and posture analyses, wearable sensors, center of pressures and machine learning models capable of predicting freezing gait-FoG) enhances clinical and individualized rehabilitation programs. However, the evidence base remains limited, with a small sample size, heterogeneity in measured outcomes, and short follow-up duration. In general, reported adverse reactions were minor, but required standardized reporting patterns. Implementation is challenging due to the equipment cost and varying technological demands, but also due to patient selection and training of the medical personnel. IVRBR is a feasible and engaging alternative or can form part of an individualized rehabilitation program in PD patients; however, future large RTCs, long-term follow-up with standardized protocols, cost-effectiveness analyses, and integration of predictive modeling are essential for its broader clinical usage. Full article

Shotcrete used in underground structures like tunnels is susceptible to sulfate and chloride erosion. In order to systematically study the deterioration law and mechanism of the durability of high-performance shotcrete under a salt erosion environment, the durability test of high-performance shotcrete was carried out by an indoor long-term immersion test using a clear water solution, Na₂SO₄ solution, and Na₂SO₄ and NaCl mixed solution as erosion mediums. A comparative study was conducted on the effects of different curing time, erosion time, erosion medium, and erosion direction on the physical and mechanical properties and SO₄²⁻ content. The microstructure was analyzed to reveal the time evolution process and mechanism of the durability of high-performance shotcrete under coupled erosion. The results show the following: (1) The mass change rate of high-performance shotcrete under the action of coupling erosion increases first, then decreases, and then increases. The compressive strength of the surface perpendicular to the jet direction is better than that of the surface along the vertical jet direction. (2) The diffusion depth of SO₄²⁻ along the injection direction is larger, and the content of SO₄²⁻ is larger at the same depth. The existence of Cl⁻ delays the diffusion of SO₄²⁻ to a certain extent. (3) In the early stage of erosion, the corrosion expansion products generated by the external SO₄²⁻ entering the concrete will fill the original pores and cracks, which improves the durability of the concrete. In the late stages of erosion, the accumulation of corrosion products increases, which accelerates the deterioration of its durability. Full article

As sustainable tourism practices gain traction globally, immersive technologies such as augmented reality (AR) and virtual reality (VR) have emerged as effective tools to enrich visitor experiences while supporting heritage site preservation. Particularly within built cultural environments, these technologies facilitate non-invasive interpretation of architectural spaces, enabling sustainable interaction with fragile historical structures. Despite growing scholarly attention, existing research has primarily focused on the pre-adoption phase or the technical affordances of AR/VR, with limited understanding of user behavior in the post-adoption phase. To address this gap, this study integrates the Expectation Confirmation Model (ECM) with the experiential attributes of AR/VR-enabled heritage applications, proposing an integrated theoretical model to identify key determinants of tourists’ continuance intention. Based on 434 valid survey responses collected at the Terracotta Warriors Museum, a UNESCO World Heritage Site, and analyzed using structural equation modeling (SEM), the results reveal that perceived usefulness, perceived ease of use, satisfaction, and confirmation directly influence continuance intention, while visual appeal, entertainment, enjoyment, interactivity and confirmation exert indirect effects through mediating mechanisms. The findings contribute theoretically by extending ECM to the heritage tourism domain and empirically by providing robust evidence from a high-profile non-Western site. Practically, this study offers actionable implications for designing immersive experiences that enhance post-visit continuance intention and align with broader sustainability objectives. Full article

Virtual communication, involving the transmission of all human senses, is the next step in the development of telecommunications. Achieving this vision requires real-time data exchange with low latency, which in turn necessitates the implementation of the Tactile Internet (TI). TI will ensure the transmission of high-quality tactile data, especially when combined with audio and video signals, thus enabling more realistic interactions in virtual environments. In this context, advances in realism increasingly depend on the accurate simulation of the grasping process and hand–object interactions. To address this, in this paper, we methodically present the challenges of human–object interaction in virtual environments, together with a detailed review of the datasets used in grasping modeling and the integration of physics-based and machine learning approaches. Based on this review, we propose a multi-step framework that simulates grasping as a series of biomechanical, perceptual, and control processes. The proposed model aims to support realistic human interaction with virtual objects in immersive settings and to enable integration into applications such as remote manipulation, rehabilitation, and virtual learning. Full article

Background/Objectives: Novice nurses often struggle to assertively voice patient safety concerns due to limited clinical experience and hierarchical healthcare environments. Immersive virtual reality simulation (IVRS) may provide opportunities to practice assertive communication skills essential for interprofessional collaboration in a psychologically safe environment. This study aimed to evaluate the short- and long-term effectiveness of an IVRS speak-up training program in enhancing communication clarity and collaborative attitudes, as well as reducing experiences of nursing malpractice among novice nurses. Methods: A quasi-experimental study was conducted with 36 novice nurses (18 participants each in control and experimental groups). The experimental group received a 200 min IVRS speak-up training program incorporating TeamSTEPPS communication strategies through four virtual reality scenarios. The control group received a 110 min conventional group lectures and discussions on communication training covering the same TeamSTEPPS strategies. Communication clarity and collaborative attitudes were measured at baseline, immediately post-intervention, and 6 weeks post-intervention. Nursing malpractice experiences were assessed at 6 weeks post-intervention. Results: Communication clarity showed no significant interaction effect between groups and time points (F = 0.84, p = 0.437), though both groups demonstrated immediate post-intervention improvements. Collaborative attitudes showed a significant interaction effect (F = 4.23, p = 0.020), with the experimental group exhibiting significantly greater and sustained improvements at immediate and 6-week follow-up compared with the control group. No significant difference in nursing malpractice experiences was observed between groups (Z = 0.16, p = 0.872). Conclusions: The IVRS speak-up training program effectively enhanced novice nurses’ assertive communication skills in immersive, interactive environments tailored for realistic practice compared to conventional group discussion-based training. This program improved communication clarity in the short term and enhanced collaborative attitudes up to 6 weeks. Integrating or boosting IVRS training into novice nurses’ communication education may foster interprofessional collaboration and advance patient safety in clinical practice. Full article

Hybrid computer-aided design and computer-aided manufacturing (CAD/CAM) materials have gained prominence in restorative dentistry due to their advantageous mechanical and esthetic properties; however, their long-term performance may be adversely affected by acidic oral environments, such as those associated with gastroesophageal reflux disease (GERD). This in vitro study aimed to investigate the effects of simulated gastric acid exposure on the surface roughness, gloss, color stability, and microhardness of two hybrid CAD/CAM materials: Vita Enamic and Cerasmart. Standardized rectangular specimens (2 mm thickness) were prepared and polished using a clinically relevant intraoral protocol. Baseline measurements were obtained for surface roughness, gloss, color change (ΔE), and Vickers microhardness. All specimens were then immersed in hydrochloric acid (pH 1.2) for 24 h to simulate prolonged gastric acid exposure, after which the same properties were re-evaluated. Post-immersion analysis revealed significant increases in surface roughness and reductions in gloss and microhardness for both materials (p < 0.05), with Vita Enamic demonstrating greater susceptibility to degradation. Color changes remained below the clinically perceptible threshold, with no significant differences between materials. These findings highlight the potential vulnerability of hybrid CAD/CAM materials to acidic environments and underscore the importance of careful material selection in patients predisposed to acid-related challenges. Full article

The evolution of Human–Computer Interaction (HCI) has laid the foundation for more immersive and dynamic forms of communication between humans and machines. Building on this trajectory, this work introduces a significant advancement in the domain of Human–Robot Manipulation (HRM), particularly in the remote operation of humanoid robots in complex scenarios. We propose the Advanced Manipulation Assistant System (AMAS), a novel manipulation method designed to be low cost, low latency, and highly efficient, enabling real-time, precise control of humanoid robots from a distance. This method addresses critical challenges in current teleoperation systems, such as delayed response, expensive hardware requirements, and inefficient data transmission. By leveraging lightweight communication protocols, optimized sensor integration, and intelligent motion mapping, our system ensures minimal lag and accurate reproduction of human movements in the robot counterpart. In addition to these advantages, AMAS integrates multimodal feedback combining visual and haptic cues to enhance situational awareness, close the control loop, and further stabilize teleoperation. This transition from traditional HCI paradigms to advanced HRM reflects a broader shift toward more embodied forms of interaction, where human intent is seamlessly translated into robotic action. The implications are far-reaching, spanning applications in remote caregiving, hazardous environment exploration, and collaborative robotics. AMAS represents a step forward in making humanoid robot manipulation more accessible, scalable, and practical for real-world deployment. Full article

Pharmacy and nursing professions collaborate closely in healthcare settings. Effective interprofessional practice is now widely recognised as essential for achieving optimal patient care outcomes. Little has been published on nursing-pharmacy Interprofessional learning (IPL) in a simulated environment in Australian contexts. This study aimed to evaluate whether an IPL activity improved participants’ communication confidence, role understanding, clinical knowledge, and preparedness for hospital placement, while also assessing student satisfaction and identifying areas for improvement. A pedagogically structured teaching and learning model was developed, involving a high-fidelity on-campus simulated hospital ward, supplemented with a virtual online environment to immerse nursing and pharmacy students in a realistic clinical environment to achieve deep learning in preparation for safe practice. An online anonymous survey was conducted to evaluate participants’ experience and preparedness following the simulation. 280 students participated and 52 completed the evaluation. Most students reported that the experience boosted their confidence in communicating with other healthcare professionals (82%), increased clinical/therapeutic knowledge (86%), gave them a better understanding of the roles of nurses/pharmacists within the hospital setting (88%) and left them feeling better prepared for hospital placement (85%). Student free-text responses from the evaluation survey further supported the expansion of the IPL sessions in the future. IPL involving nursing and pharmacy students in a simulated hospital builds confidence in communicating and increases self-reported preparedness for placement. Full article

As HEIs face increasing hybrid environment and communication demands, digital tools and AI can offer timely solutions (for more inclusive and more effective mediation. By applying Media Richness and Social Presence theories, we study how platforms like Zoom and AI-powered chatbots can replicate attributes similar to trust and empathy in virtual contexts. Case studies from pioneering institutions show that hybrid mediation models that blend traditional and digital approaches can enhance engagement as well as fairness. Despite possible disadvantages such as fatigue and ethics, emotionally intelligent AI and immersive technology are pointing toward a more adaptable, empathetic leadership paradigm. Full article

This study introduces a machine learning–driven extended reality (XR) interaction framework that leverages electroencephalography (EEG) for decoding consumer intentions in immersive decision-making tasks, demonstrated through functional food purchasing within a simulated autonomous vehicle setting. Recognizing inherent limitations in traditional “Preference vs. Non-Preference” EEG paradigms for immersive product evaluation, we propose a novel and robust “Rest vs. Intention” classification approach that significantly enhances cognitive signal contrast and improves interpretability. Eight healthy adults participated in immersive XR product evaluations within a simulated autonomous driving environment using the Microsoft HoloLens 2 headset (Microsoft Corp., Redmond, WA, USA). Participants assessed 3D-rendered multivitamin supplements systematically varied in intrinsic (ingredient, origin) and extrinsic (color, formulation) attributes. Event-related potentials (ERPs) were extracted from 64-channel EEG recordings, specifically targeting five neurocognitive components: N1 (perceptual attention), P2 (stimulus salience), N2 (conflict monitoring), P3 (decision evaluation), and LPP (motivational relevance). Four ensemble classifiers (Extra Trees, LightGBM, Random Forest, XGBoost) were trained to discriminate cognitive states under both paradigms. The ‘Rest vs. Intention’ approach achieved high cross-validated classification accuracy (up to 97.3% in this sample), and area under the curve (AUC > 0.97) SHAP-based interpretability identified dominant contributions from the N1, P2, and N2 components, aligning with neurophysiological processes of attentional allocation and cognitive control. These findings provide preliminary evidence of the viability of ERP-based intention decoding within a simulated autonomous-vehicle setting. Our framework serves as an exploratory proof-of-concept foundation for future development of real-time, BCI-enabled in-transit commerce systems, while underscoring the need for larger-scale validation in authentic AV environments and raising important considerations for ethics and privacy in neuromarketing applications. Full article

In this study, polysaccharide xanthan gum (XG), used in the oil and gas industry as a thickening agent, was evaluated as an active anti-corrosion component against sweet corrosion at high temperatures and pressures in a saline environment for N80 carbon steel in the oil and gas industry. The evaluation involved measuring weight loss and conducting electrochemical assessments at 5 bar CO₂ partial pressure, different temperatures (e.g., 30 °C and 90 °C), and immersion times (up to 72 h). The electrochemical results indicated that XG effectively mitigated CO₂ corrosion at both low and high temperatures, demonstrating inhibition efficiencies of 70.10% at 30 °C and 61.41% at 90 °C using 1.0 g L⁻¹ of XG, after 24 h. The good inhibition efficiency observed even at high temperatures is likely due to the denaturation process that XG undergoes at high temperatures, where a rigid double-stranded helical structure transitions into two single-stranded, more flexible, worm-like macromolecular conformations. This increases the number and mobility of XG macromolecules available for adsorption on the metal surface. EIS measurements have shown that XG was capable of protecting the metal surface even after prolonged exposure. Potentiodynamic measurements indicated that the inhibitive action of XG is of a mixed type. The Temkin adsorption isotherm model provided a good fit for the observed data, and the calculated parameters suggested that the adsorption of XG primarily occurred through physical adsorption processes, with a contribution from chemical processes. The associated activation energy and the heat of adsorption further supported the physical nature of XG’s adsorption. FTIR analysis was employed to elucidate the interaction between the XG and the N80 carbon steel surface, while SEM-EDS analysis provided visual confirmation of the XG’s impact on the metal surface. Full article

In response to the challenges of metal corrosion detection and anti-corrosion coating performance evaluation in the marine environment of Zhoushan, this study proposes an improved object detection model, YOLO v5-EfficientViT-NWD-CCA, to enhance the recognition accuracy and detection efficiency of corrosion images on marine structures. Based on YOLO v5, the model incorporates the EfficientViT backbone network, NWD (Normalized Wasserstein Distance) loss function, and CCA (Criss-Cross Attention) attention mechanism, outperforming comparative models across multiple key metrics. Experimental results show that the proposed model increases precision from 0.73 to 0.76 (approximately 4% improvement) and raises the True Positive rate from 0.66 to 0.70 (approximately 6% improvement) according to the confusion matrix, demonstrating more stable overall detection performance. Building on this, the study combines the model’s detection results to conduct a quantitative analysis of the corrosion area of eight types of anti-corrosion coatings in two typical marine environments—tidal zones and fully immersed zones—across different exposure periods (24, 60, and 96 months). The results indicate that the tidal zone presents a harsher corrosion environment, with corrosion severity significantly increasing over time. Fusion-bonded epoxy coatings, powder epoxy coatings, and fluorocarbon coatings exhibit good corrosion resistance, whereas chlorinated rubber coatings and conventional epoxy coatings perform poorly. This study not only achieves intelligent identification and precise quantification of corrosion areas but also provides a scientific basis for the selection and evaluation of anti-corrosion coatings in different marine environments. Full article

The increasing use of immersive 3-D technologies in education raises critical questions about their cognitive impact on learners. This systematic review evaluates how electroencephalography (EEG) and eye-tracking have been used to objectively measure cognitive load in 3-D learning environments. We conducted a comprehensive literature search (2009–2025) across PubMed, Scopus, Web of Science, PsycInfo, and ERIC, identifying 51 studies that used EEG or eye-tracking in experimental contexts involving stereoscopic or head-mounted 3-D technologies. Our findings suggest that 3-D environments may enhance learning and engagement, particularly in spatial tasks, while affecting cognitive load in complex, task-dependent ways. Studies reported mixed patterns across psychophysiological measures, including spectral features (e.g., frontal theta, parietal alpha), workload indices (e.g., theta/alpha ratio), and gaze-based metrics (e.g., fixation duration, pupil dilation): some studies observed increased load, while others reported reductions or no difference. These discrepancies reflect methodological heterogeneity and underscore the value of time-sensitive assessments. While a moderate cognitive load supports learning, an excessive load may impair performance, and overload thresholds can vary across individuals. EEG and eye-tracking offer scalable methods for monitoring cognitive effort dynamically. Overall, 3-D and XR technologies hold promise but must be aligned with task demands and learner profiles and guided by real-time indicators of cognitive load in immersive environments. Full article