PurposeThis study examined whether phonological complexity enhances auditory word learning within a statistical learning framework. Specifically, we tested if exposure to phonologically complex speech patterns (i.e., marked consonant clusters) facilitates the segmentation and generalization of both complex and simple artificial words.MethodSeventy-eight adults were randomly assigned to either a complex or simple pattern induction group and exposed to bisyllabic artificial words varying in onset complexity. Participants then heard an auditory stream containing both complex and simple words, followed by a wordlikeness rating task assessing both previously heard and novel items.ResultsExposure to complex speech patterns did not enhance wordlikeness ratings for either previously heard (stream) or novel (generalization) artificial words. Wordlikeness ratings were significantly higher for stream items than for generalization items, indicating sensitivity to exposure, but no reliable effects of induction condition or stimulus complexity were observed.ConclusionsFindings suggest that passive exposure to complex patterns does not enhance generalization within a statistical learning paradigm.

Decision-making in military occupations is vital for operational success and personnel safety and relies on situational awareness, executive control, and strategic alignment of operational goals. This study examined the effects of acute operational and passive heat stress on cognitive performance in a randomized controlled trial with 68 service members. Participants were assigned to either a low- or high-stress group and completed two military scenarios using a desktop simulator. Passive heat stress was applied only to the high-stress group in a portable environmental facility. Decision-making and situational awareness were scored from scenario recordings, while executive functioning was assessed through a cognitive test battery. In addition to the group comparison, a heat index capturing individual variability in thermal strain was calculated. Contrary to expectations, heat stress did not impair cognitive performance across most domains. Decision-making performance actually improved over time in the high-stress group, with significantly better performance during the second assessment compared to the low-stress group. Cognitive flexibility also improved significantly within both groups. These changes are attributed primarily to learning effects rather than stress-induced performance. Situational awareness showed no significant differences between groups. Exploratory heat index analyses revealed that participants in the high heat index group exhibited increased situational awareness over time, suggesting a possible inverted U-shaped relationship between thermal strain and performance. In contrast, inhibition improved only in the low heat index group. Together, these findings emphasize that the heat stress protocol may not have been potent enough to generate the cortisol response needed to detrimentally affect higher-order cognition. Nevertheless, the findings highlight that thermal strain can interact with cognitive performance in complex, nonlinear ways. While passive heat stress remains a promising stressor for research, its effect may only become fully apparent under more intense or physiologically demanding conditions, warranting further investigation into its potential impact on higher-order cognitive functions in military contexts.

Virtual reality simulation is a fundamental adjunct to robotic surgery training. It is not clear if individual performance at the simulator can be affected by predisposing factors such as gender, video gaming, and instrument playing. Sixty-three volunteering medical students performed five times the same exercise at the DaVinci Simulator, and performance scores were collected for each participant (Overall Score, Time to Complete, Economy of Motion, Penalty Score) along with their demographics. Data were collected and analyzed within an electronic database. The difference (delta) between the highest score obtained in tests 2 to 5 and the score obtained in test 1 was calculated for each of the 4 scores and for each participant. All participants showed a significant improvement in their scores with practice (deltas were always positive). Median PS was significantly lower in women, but PSdelta was significantly higher in women than in men. Median TC and median PS were significantly lower in non-video game users. No significant difference of performance scores was found between music players and non-music players. Multivariable analysis confirmed that female gender was an independent prognostic variable towards PSdelta, that is, women showed a steeper improvement in their performance. Repeated simulation improves the performance of surgically naïve medical students. Women and non-video gamers had higher penalty scores, but women tend to improve their skills quickly. As videogaming is much more frequent within the group of men, it is possible that videogaming itself, and not gender, can have a positive effect by enhancing eye-hand coordination.

Virtual clinical simulation as a pedagogical strategy in healthcare learning: Evidence and gap map.

Virtual interactions trigger caregiving attributions: Using a simulation to examine perceived control.

Patient-specific prediction of 3D ablation zones via oncological feature-conditioned deep generative modeling: An in silico feasibility study.

The Effects of Education Program on Nursing Care for Child with Gastroenteritis Using Virtual Simulation

Artificial intelligence (AI) is rapidly reshaping adult cardiac surgery, enabling more accurate diagnostics, personalized risk assessment, advanced surgical planning, and proactive postoperative care. Preoperatively, deep-learning interpretation of ECGs, automated CT/MRI segmentation, and video-based echocardiography improve early disease detection and refine risk stratification beyond conventional tools such as EuroSCORE II and the STS calculator. AI-driven 3D reconstruction, virtual simulation, and augmented-reality platforms enhance planning for structural heart and aortic procedures by optimizing device selection and anticipating complications. Intraoperatively, AI augments robotic precision, stabilizes instrument motion, identifies anatomy through computer vision, and predicts hemodynamic instability via real-time waveform analytics. Integration of the Hypotension Prediction Index into perioperative pathways has already demonstrated reductions in ventilation duration and improved hemodynamic control. Postoperatively, machine-learning early-warning systems and physiologic waveform models predict acute kidney injury, low-cardiac-output syndrome, respiratory failure, and sepsis hours before clinical deterioration, while emerging closed-loop control and remote monitoring tools extend individualized management into the recovery phase. Despite these advances, current evidence is limited by retrospective study designs, heterogeneous datasets, variable transparency, and regulatory and workflow barriers. Nonetheless, rapid progress in multimodal foundation models, digital twins, hybrid OR ecosystems, and semi-autonomous robotics signals a transition toward increasingly precise, predictive, and personalized cardiac surgical care. With rigorous validation and thoughtful implementation, AI has the potential to substantially improve safety, decision-making, and outcomes across the entire cardiac surgical continuum.

Assessing Student Socio-Cognitive Outcomes from Virtual Experiment Simulators in Polymer Science Education

This article explores how technology has historically been an extension of human biological and intellectual development. It analyzes the transformative role of digital twins in Industry 4.0 and their projection into Industry 5.0, highlighting their capacity to optimize processes through precise virtual simulations, their applications, strategic advantages, and implementation challenges. These digital representations connected to physical objects allow for anticipating failures and improving design, production, and maintenance. Although they offer advantages in cost, time, and customization, they face challenges in connectivity, security, infrastructure, and training. The review demonstrates that the convergence of these technologies represents a paradigm shift in the way modern production systems are designed, operated, and optimized. It also addresses ethical, technical, and organizational considerations for their effective adoption.

Advancements in technology and intelligence, as well as deliberate targeting of medical personnel and vehicles, have made casualty extraction increasingly hazardous. The Russo-Ukrainian War has further demonstrated that the rapid development of unmanned technologies may also enable novel approaches. Although some of these systems have been deployed, reporting on their performance is scarce and understandably incomplete, which limits their evidence-based and effective integration with fighting forces. This paper addresses this gap by presenting preliminary findings on potential ranges of evacuation unmanned ground vehicles (UGVs) utilisation. A virtual simulation experiment was conducted, where a platoon defended against a mechanised infantry company. The experiment was a repeated military exercise with different groups of participants. The defending force had evacuation UGVs, which were placed close behind the defensive line. The aim was to determine whether UGVs could survive long enough to support evacuation and whether evacuation could be carried out before the conflict ended. Furthermore, the availability of UGVs and the likelihood that an evacuation attempt could avoid enemy interference were assessed. The experiment involved 470 participants divided into 11 groups. Each participant completed four combat scenarios. Players of each group switched sides and environments. In total, 44 instances of skirmishes were fought in a virtual simulation environment. The simulation results indicated UGV loss rate of 53%. Evacuations were attempted in 45% of skirmishes. Furthermore, 81% of initiated evacuation attempts were successful. The experiment provided estimates of evacuation UGV loss rates near the defence line amid active conflict. It also offered evidence on the feasibility of initiating evacuation before the active conflict had fully ceased, and the likelihood of the moving evacuation vehicle encountering enemy fire. These findings can guide decisions on whether the risk of losing small evacuation vehicles and their equipment is acceptable when deployed near front lines.

Facing the urgent demand of the "three-child" policy, this paper puts forward a framework for the development and application of AI-empowered digital teaching resources for higher vocational nursery education in the perspective of "great ideological and political education (IPE)". The research focuses on morality cultivation, follows the five principles of "IPE guidance, combination of education and training, man-machine cooperation, dynamic optimization, and ecological integration", constructs four types of resource systems covering knowledge transfer, skill training, IPE integration, evaluation and diagnosis, and designs a four stage iterative development process of "demand analysis - design generation - Audit optimization - Application iteration". Through technologies such as KG (Knowledge Graph), virtual simulation, adaptive learning and multi-modal learning portrait, we can realize the pre-positioning of value guidance, the scene of skill training and the personalization of learning support, and form a closed loop of "teaching-evaluation-feedback". This framework has significantly improved students' professional values, ethical decision-making ability and practical norms, and provided a replicable and generalizable paradigm for digital education in higher vocational education.

Medicine is highly practical, and requires strong clinical skills. Evolving medical models and greater patient awareness have intensified doctor-patient tensions, while increasing the number of students has strained clinical training resources. Innovative approaches, such as virtual patient simulations, are essential for enhancing medical education. A quasi-experimental study was conducted on 114 clinical medical students from Zhejiang University. The participants were divided into a reform group (n = 50), taught using the DxR-Clinician platform and mind mapping, and a conventional group (n = 64), taught traditionally. Assessments and questionnaires were used to compare engagement and clinical reasoning. The reform group showed significantly improved student engagement (89.87% vs 39.06%, P < .001) and overall clinical competence (87.67% vs 50.28%, P < .001). However, 81.4% reported increased workload, and 73% perceived insufficient class time. The subjective learning outcomes also improved significantly (P < .05). Virtual patient simulations combined with mind mapping improve clinical reasoning and engagement. Optimizing the workload and time allocation is necessary for wider implementation. Further studies should explore these applications in other educational contexts.

Biotechnology education in secondary schools and universities still faces challenges in the form of high levels of student misconceptions, mainly due to the abstract nature of the material and the rapid development of technology. This study aims to identify common misconceptions in conventional and modern biotechnology material and analyse effective remediation strategies based on previous research findings. The research method used is a systematic literature review, through searching and analysing nationally and internationally accredited journal articles published between 2015 and 2025. The articles analysed were selected based on topic relevance, methodological quality, and relevance of findings. The results of the study show that the most dominant misconceptions arise in the understanding of the concept of anaerobic fermentation, the difference between cloning and IVF, and the impact of genetically modified organisms (GMOs). Remediation strategies that have proven effective include the use of Conceptual Change Text, the application of the Socio-Scientific Issues (SSI) approach, and the use of virtual laboratory simulations to help students reconstruct their understanding of concepts more accurately.

With the continuous development of global intelligent shipping technology, in fields such as virtual testing of intelligent ships and crew training and assessment, there is an urgent need for a highly realistic model to reproduce the driver’s bumpy feeling of ship drivers. Due to the limited travel of the six-degree-of-freedom platform, the platform is unable to provide continuous acceleration during the simulation of the driver’s body sensation in the three degrees of freedom of the ship, namely, sway, surge, and yaw. To overcome the above problems, a six-degree-of-freedom motion model of ships is constructed under low sea conditions based on the MMG-separated ship motion model and the FFT wave simulation method. Secondly, the otolith model and the semicircular canal model are introduced to establish a human body perception deception mechanism. The gravity is transferred by using the deflection angles of roll and pitch to extend the acceleration sensation in the three degrees of freedom of sway, surge, and yaw. Finally, through the real ship rotation and Z-shaped test experiments, the simulation trajectory, real ship attitude, and platform motion data are compared to verify the effectiveness of the established method. To simplify the research, under the low sea conditions where the three degrees of freedom of heave, roll, and pitch are ignored, the virtual ship simulation trajectory based on the above method is basically consistent with the real ship, and the correlation between the platform and the real ship body-sensing data is at least 81.2%. Through scoring the simulation driving body-sensing reproduction experience, it is proven that the above method can achieve a better body-sensing reproduction effect on the six-degree-of-freedom platform.

Background Multiplayer Virtual Reality-Based Simulations (MPVR-based simulations) with immersive 3D environments have become an important tool in interprofessional education (IPE). However, instruments to measure interprofessional socialization in MPVR-based education are limited. The Interprofessional Socialization and Valuing Scale (ISVS) is a useful tool for evaluating interprofessional socialization. This pilot study aimed to adapt and validate the ISVS-24 for use in interprofessional MPVR-based simulations settings. Methods Seventy-two participants, including anesthesiology residents (at novice, junior, and senior levels), general physicians, and professional nurses, were recruited voluntarily. The ISVS-24 was cross-culturally adapted and reviewed by experts for content validity in the MPVR simulation context. Participants completed the adapted ISVS after undergoing an interprofessional MPVR-based simulation. Structural validity was assessed using factorial analysis through principal component analysis. Content validity was measured using the mean content validity index (CVI). Consistency validity was evaluated with Pearson correlation coefficients (PCC), and reliability was assessed using Cronbach’s alpha. Results The Kaiser-Meyer-Olkin test indicated sampling adequacy (0.885), and Bartlett’s sphericity test was significant (χ 2 (42) = 472.725, p &lt; 0.05). A three-section structure was confirmed. The mean CVI was 0.815, with 21 valid items (Aiken’s V ≥ 0.5). Among the 72 respondents, 40 were female (55.6%) and 32 were male (44.4%); 26 were anesthesiology residents (36.1%), 23 were general physicians (31.9%), and 23 were professional nurses (31.9%). The overall Cronbach’s alpha was 0.959. PCC for all items exceeded the r table value (&gt; 0.232) with p &lt; 0.05, showing significant item relationships. Conclusions The adapted version of ISVS for MPVR simulation-based education has good validity and reliability to assess interprofessional socialization in an MPVR-based simulation setting.

GPU-Accelerated Virtual Screening and Molecular Dynamics Simulations for Identification of Novel DPP-4 Inhibitors

GPER1 belongs to the large GPCR family, known for its diverse biological functions and therapeutic value in multiple diseases. It has gained attention for its role in mediating estrogenic signaling pathways, which exert protective and beneficial effects in disease. The current study aims to identify potential compounds for effective therapies targeting GPER1 employing in silico approaches. This study integrates a suite of computational techniques, including molecular modeling, pharmacophore-based virtual screening, docking studies, and molecular dynamics simulations, to analyze structural dynamics, functional relevance, and potential therapeutic applications. Ligand Scout was used to construct the pharmacophore models of reported inhibitors and drugs retrieved before the virtual screening. RMSD, RMSF, and B-factor graphs are generated through simulations for 50 nanoseconds to reveal the structural features of the GPER1 model. The comparative modeling approach was applied to build the GPER1 3D model, yielding an overall quality factor of 89%. Energy minimization and simulations for structure optimization were followed until a 92% quality factor was attained. Two novel leads, ZINC39470612 and ZINC72326045, appeared to have maximum binding affinities, i.e., 63.4983 and 58.87, respectively, with the GPER1 receptor. Post-docking analyses identified Phe-98, Met-260, Tyr-324, and Leu-327 as crucial residues for the effective drug therapies targeting GPER1. Extensive analyses have demonstrated that ZINC39470612 and ZINC72326045 are identified as potential compounds for targeting GPER1. These compounds also exhibited better binding affinities and ADME features than reported drugs and inhibitors. These in silico findings provide critical structural and functional insights with promising therapeutic relevance.

Identification of Diosmetin, Arbutin, and Phenyl Glucoside as Novel Inhibitors from Origanum majorana Targeting Human Cyclooxygenase-2 Enzyme: Insight from Virtual Screening, MD Simulation and Density Functional Theory

Enhancing medical student learning through virtual pharmacology simulations: a pre-post evaluation study.