Search Results (554)

The rapid integration of artificial intelligence (AI), particularly generative AI (Gen-AI), into higher education presents a critical challenge: preparing students for the complex ethical dilemmas inherent in AI-driven research and practice. Current AI ethics education, however, often remains fragmented, overly theoretical, and disconnected from practical application, leaving a significant gap between knowing ethical principles and acting upon them. To address this pressing issue, this study proposes and validates a full-cycle AI ethics education system designed to bridge this gap. The system integrates three core components: (1) an updated four-dimensional ethics framework focused on Gen-AI challenges (research review, data privacy, algorithmic fairness, intellectual property); (2) a “cognition-behavior” dual-loop training mechanism that combines theoretical learning with hands-on, simulated practice; and (3) a full life-cycle education platform featuring tools like virtual laboratories to support experiential learning. A mixed-methods study with 360 students and 20 instructors demonstrated the system’s effectiveness, showing significant improvement in students’ ethical knowledge, a large effect size in enhancing ethical decision-making capabilities, and high user satisfaction. These findings validate a scalable model for AI ethics education that moves beyond passive instruction toward active, situated learning, offering a robust solution for higher education institutions to cultivate ethical responsibility in the age of Gen-AI. Full article

Urbanization exacerbates mental health challenges, prompting the exploration of biophilic design solutions. This study examined the therapeutic potential of raw earth through its thermal interactions in architecture. First, energy consumption simulations established distinct indoor temperature ranges for raw earth, concrete, and steel under identical energy constraints: low (22.8 ± 0.32 °C), medium (26.5 ± 0.39 °C), and high (30.1 ± 0.84 °C). The study then quantified the differences in physical and psychological perceptions across material-dominated spaces under controlled temperatures above. Nine scenes were constructed for emotional healing evaluation, incorporating the olfactory dimension into the Electroencephalogram (EEG) + Virtual reality (VR) + Laboratory environmental control (LEC) approach. The results indicated that raw earth materials were most effective in promoting emotional recovery under thermal stress conditions (low/high temperatures), as evidenced by a significant enhancement of α EEG rhythms. However, under moderate conditions, concrete environments produced the greatest relaxation effects, while steel environments were most conducive to enhancing focus. The core conclusion of this study is that the therapeutic effects of building materials are not static but are intricately linked to the surrounding thermal environment. This provides a new perspective for evidence-based healthy building design and underscores the importance of optimizing material selection based on specific environmental conditions and needs. Full article

The purpose of this narrative review is to critically appraise recent advances in sports injury rehabilitation—primarily focusing on biopsychosocial (BPS) approaches alongside emerging technological innovations—and identify current gaps and future directions. A literature search was conducted in PubMed, Scopus, and Web of Science for the years 2018–2024. Eligible records were English-language, human studies comprising systematic reviews, clinical trials, and translational investigations on wearable sensors, artificial intelligence (AI), virtual reality (VR), regenerative therapies (platelet-rich plasma [PRP], bone marrow aspirate concentrate [BMAC], stem cells, and prolotherapy), and BPS rehabilitation models; single-patient case reports, editorials, and non-scholarly sources were excluded. The synthesis yielded four themes: (1) BPS implementation remains underutilised owing to a lack of validated tools, variable provider readiness, and system-level barriers; (2) wearables and AI can enhance real-time monitoring and risk stratification but are limited by data heterogeneity, non-standardised pipelines, and sparse external validation; (3) VR/gamification improves engagement and task-specific practice, but evidence is dominated by pilot or laboratory studies with scarce longitudinal follow-up data; and (4) regenerative interventions show mechanistic promise, but conclusions are constrained by methodological variability and regulatory hurdles. Conclusions: BPS perspectives and emerging technologies have genuine potential to improve outcomes, but translation to practice hinges on (1) pragmatic or hybrid effectiveness–implementation trials, (2) standardisation of data and intervention protocols (including core outcome sets and effect-size reporting), and (3) integration of psychological and social assessment into routine pathways supported by provider training and interoperable digital capture. Full article

The Maxillary Skeletal Expander (MSE) is used for maxillary expansion in adolescents and young adults. Virtual planning using 3D models, CBCT and 3D printers help in case selection, appliance design and fabrication. Using the proposed digital workflow, the accuracy of the patient selection phase and appliance delivery are increased, and the required number of visits to the clinic is decreased. The MSE serves as a guide for the insertion of mini-implants, reducing the number of appointments needed for installation. (1) Introduction: Mini-Implant-Assisted Rapid Palatal Expansion (MARPE) appliances, like the MSE, decrease the side effects that regular tooth-anchored appliances have on dental and periodontal structures, especially for skeletally mature patients, combining palatal anchorage with dental support for guidance. The digital planning of the insertion sites, length and angulation of the mini screws, and the fabrication of the 3D-printed appliance that stands as a mini-implant insertion guide give an undeniable precision. (2) Materials and methods: The laboratory steps used in the digital design and fabrication, and clinical steps needed for the insertion protocol are described. (3) Discussions: The individual assessment of the anatomical structures and the use of virtual integrated dental impressions and CBCT increase the accuracy of diagnosis, appliance fabrication and treatment progress. Implementing a digital workflow for mini-implant-supported expansion is a real advantage for both dental teams and patients. (4) Conclusions: The wide range of advantages and the ease of the process support the introduction of this digital workflow in every orthodontic practice. Full article

Technological advancements, shifting consumer preferences, and societal changes drive the cosmetics industry to evolve continuously. The cosmetics industry is experiencing a renaissance, with new ingredients that are more environmentally friendly, natural, and transparent in terms of sourcing and manufacturing and, last but not least, which are also multifunctional. The use of technology in cosmetics has been rising, including AI (artificial intelligence) and AR (augmented reality) for virtual try-ons, skin analysis tools, and smart beauty devices that provide at-home skincare treatments. Meanwhile, fermented cosmetic ingredients are becoming increasingly popular in the beauty industry due to their improved efficacy and skin benefits. The benefits include enhanced absorption, improved stability (due to the self-produced preservatives), microbiome-friendliness (supporting the skin’s microbiome), and anti-inflammatory and soothing effects. The most common cosmetic ingredients produced by microorganisms are fermented rice, soy, green tea, fruits, and vegetables. Our laboratory investigates a mineral rock called alginite, which has shown many benefits in other fields, such as agriculture and cosmetics (e.g., as a facemask). It has been proven that alginite combined with LAB (lactic acid-producing bacteria) probiotics is beneficial for health and can increase biomass production. However, cell lysates with alginite have never been investigated for cosmetic purposes. This study aimed to investigate the potential of alginite, a mineral rock, in enhancing the cosmetic properties of LAB lysates, specifically focusing on antioxidant effects, skin-whitening properties, and, in preliminary tests, skin-moisturising effects. LAB strains were cultured with and without alginite, and the resulting cell lysates were analysed for these cosmetic applications. The preliminary results suggested that alginite may boost the hydrating effect of LAB lysate, increasing it tenfold compared to LAB lysate alone. The antioxidant effect was enhanced fivefold in the case of Lactobacillus acidophilus when cultured with alginite. However, no significant effect was observed on mushroom tyrosinase inhibition, suggesting no impact on pigment formation. Further research is needed to fully understand the mechanisms underlying these effects and to explore potential applications in cosmetic formulations. Limitations of this study include the focus on specific LAB strains and the need for in vivo studies to confirm the observed effects on human skin. Full article

This study evaluated the effects of different doses of the herbicide fluroxypyr on soil microbial communities under controlled laboratory conditions. Specific enzymatic activities ((dehydrogenase (DA), urease (UA), catalase (CA), phosphatase (PA)) and quantitative variations in bacterial and fungal populations were measured regarding key physico-chemical soil parameters (temperature, pH, electrical conductivity, moisture, organic matter, ammonium, nitrate nitrogen, and available phosphate content). The effects of the herbicide on the targeted parameters were dose- and time-dependent. Fluroxypyr induced a clear decrease in DA, CA, and PA during the first 14 days after administration, while UA showed a decrease in the first 7 days, followed by a slight increase starting on day 14, closely related to the applied dose. Microbial populations decreased in direct relation to the fluroxypyr dose. Organic matter content exhibited a positive correlation with DA, UA, CA, as well as with microbial populations. In addition, three natural compounds structurally similar to fluroxypyr were identified via 3D virtual screening, demonstrating potential herbicidal activity. Fluroxypyr can alter soil metabolic activity and disrupt microbial communities, thereby affecting soil fertility. Used as a reference in 3D screening, fluroxypyr helped identify three natural compounds with potential herbicidal activity as safer alternatives to synthetic herbicides. Full article

The aim of this study is to explore the role of virtual reality in engineering education. Specifically, it analyzed 342 studies that were published during 2010–2025 following a systematic approach. It examined how virtual reality is used in engineering education, explored the document main characteristics, and identified emerging topics. The study also revealed existing limitations and suggested future research directions. According to the outcomes, the following six topics emerged: (i) Immersive technologies in engineering education, (ii) Virtual laboratories, (iii) Immersive and realistic simulations, (iv) Hands-on activities and practical skills development, (v) Engineering drawing, design, and visualization, and (vi) Social and collaborative learning. Virtual reality was proven to be an effective educational tool which supports engineering education and complements existing learning practices. Using virtual reality, students can apply their theoretical knowledge and practice their skills within low-risk, safe, and secure learning environments characterized by high immersion and interactivity. Virtual reality through the creation of virtual laboratories can also effectively support social, collaborative, and experiential learning and improve students’ academic performance, engagement, interaction, and motivation. Learning using virtual reality can also enhance students’ knowledge acquisition, retention, and understanding. Improvements on students’ design, planning, and implementation skills and decision making, problem-solving skills, and visual analytic skills were also observed. Finally, when compared to physical laboratories, virtual reality learning environments offered lower costs, reduced infrastructure requirements, less maintenance, and greater flexibility and scalability. Full article

The rapid development of digital technologies is opening up new avenues for transforming education, particularly in fields that require practical training, such as electronic circuit design. In this context, this paper presents the development of a multiplayer virtual learning platform that makes use of digital twins technology to offer a realistic, collaborative experience in a simulated environment. Users can interact in real time through synchronized avatars, voice communication, and multiple viewing angles, simulating a physical classroom. Evaluation of the platform with undergraduate students showed positive results in terms of usability, collaboration, and learning effectiveness. Despite the limitations of the sample, the findings reinforce the prospect of virtual laboratories as a modern tool in technical education. Full article

Atmospheric corrosion significantly impacts infrastructure worldwide, with traditional assessment methods being time-intensive and costly. This study developed a comprehensive machine learning framework for predicting atmospheric corrosion rates using environmental and material parameters. Three regression models (Linear Regression, Random Forest, and Gradient Boosting) were trained on a scientifically informed synthetic dataset incorporating established corrosion principles from ISO 9223 standards and peer-reviewed literature. The Gradient Boosting model achieved superior performance with cross-validated R² = 0.835 ± 0.024 and RMSE = 98.99 ± 16.62 μm/year, significantly outperforming the Random Forest (p < 0.001) and Linear Regression approaches. Feature importance analysis revealed the copper content (30%), exposure time (20%), and chloride deposition (15%) as primary predictors, consistent with the established principles of corrosion science. Model diagnostics demonstrated excellent predictive accuracy (R² = 0.863) with normally distributed residuals and homoscedastic variance patterns. This methodology provides a systematic framework for ML-based corrosion prediction, with significant implications for protective coating design, material selection, and infrastructure risk assessment, pending comprehensive experimental validation. Full article

The increasing complexity of cybersecurity risks highlights the critical need for novel teaching techniques that provide students with the necessary skills and information. Traditional on-premises laboratory setups frequently lack the scalability, flexibility, and accessibility necessary for efficient training in today’s dynamic world. This study compares the efficacy of cloud-based solutions—specifically, Amazon Web Services (AWS) Elastic Compute Cloud (EC2)—against traditional settings like VirtualBox, with the goal of determining their potential to improve cybersecurity education. The study conducts systematic experimentation to compare lab environments based on parameters such as lab completion time, CPU and RAM use, and ease of access. The results show that AWS EC2 outperforms VirtualBox by shortening lab completion times, optimizing resource usage, and providing more remote accessibility. Additionally, the cloud-based strategy provides scalable, cost-effective implementation via a pay-per-use model, serving a wide range of pedagogical needs. These findings show that incorporating cloud technology into cybersecurity curricula can lead to more efficient, adaptable, and inclusive learning experiences, thereby boosting pedagogical methods in the field. Full article

Background/Objectives: The introduction of composite attachments has greatly improved orthodontic aligner therapy, through better force delivery, more predictable movements, and enhanced retention. This in vitro study aims to present and investigate an innovative digital protocol for aligner attachment fabrication incorporating the latest 3D technology used in dentistry. Methods: A virtual attachment measuring 2.5 × 2 × 2 mm was designed using computer-aided design (CAD) software (Meshmixer, Autodesk Inc., San Francisco, CA, USA) and exported as an individual STL file. The attachments were fabricated using a digital light processing (DLP) 3D printer (model: Elegoo 4 DLP, Shenzhen, China) and a dental-grade biocompatible resin. A custom 3D-printed placement guide was used to ensure precise positioning of the attachments on the printed maxillary dental models. A flowable resin was applied to secure the attachments in place. Following attachment placement, the models were scanned using a laboratory desktop scanner (Optical 3D Smart Big, Open Technologies, Milano, Italy) and three intraoral scanners: iTero Element (Align Technology, Tempe, AZ, USA), Aoral 2, and Aoral 3 (Shining 3D, Hangzhou, China). Results: Upon comparison, the scans revealed that the iTero Element exhibited the highest precision, particularly in the attachment, with an RMSE of 0.022 mm and 95.04% of measurements falling within a ±100 µm tolerance. The Aoral 2 scanner showed greater variability, with the highest RMSE (0.041 mm) in the incisor area and wider deviation margins. Despite this, all scanners produced results within clinically acceptable limits. Conclusions: In the future, custom attachments made by 3D printing could be a valid alternative to the traditional composite attachments when it comes to improving aligner attachment production. While these preliminary findings support the potential applicability of such workflows, further in vivo research is necessary to confirm clinical usability. Full article

Digital transformation has profoundly impacted engineering education, demanding new pedagogical approaches that ensure effective and sustainable learning. Educational psychology plays a fundamental role in strategically integrating educational technologies, fostering more inclusive, interactive, and efficient learning environments. This article explores the intersection of technological innovation, engineering education, and educational psychology, analyzing how digital tools such as Artificial Intelligence, virtual reality, gamification, and remote laboratories can optimize the teaching–learning process. It also examines the psychopedagogical impact of these technologies, addressing challenges like cognitive load, student motivation, digital accessibility, and emotional well-being. Finally, the article presents guidelines for sustainable implementation aligned with the Sustainable Development Goals (SDGs), promoting efficient, equitable, and student-centered education. As a theoretical and exploratory study, it also points to directions for future empirical investigations and practical applications. The insights provided offer strategic guidance for academic managers and educational policymakers seeking to implement sustainable, inclusive, and pedagogically effective digital innovation in engineering education. Full article

This study develops a comprehensive artificial neural network (ANN) model for predicting the mechanical properties of carbon–manganese cast steel, specifically, the yield strength (YS), tensile strength (TS), elongation (El), and reduction of area (RA), based on the chemical composition (16 alloying elements) and heat treatment parameters. The neural network model, employing a 20-44-44-4 architecture and trained on 400 samples from an industrial dataset of 500 samples, achieved 90% of test predictions within a 5% deviation from actual values, with mean prediction errors of 3.45% for YS and 4.9% for %EL. A user-friendly graphical interface was developed to make these predictive capabilities accessible, without requiring programming expertise. Sensitivity analyses revealed that increasing the copper content from 0.05% to 0.2% enhanced the yield strength from 320 to 360 MPa while reducing the ductility, whereas niobium functioned as an effective grain refiner, improving both the strength and ductility. The combined effects of carbon and manganese demonstrated complex synergistic behavior, with the yield strength varying between 280 and 460 MPa and the tensile strength ranging from 460 to 740 MPa across the composition space. Optimal strength–ductility balance was achieved at moderate compositions of 1.0–1.2 wt% Mn and 0.20–0.24 wt% C. The model provides an efficient alternative to costly experimental trials for optimizing C-Mn steels, with prediction errors consistently below 6% compared with 8–20% for traditional empirical methods. This approach establishes quantitative guidelines for designing complex multi-element alloys with targeted mechanical properties, representing a significant advancement in computational material engineering for industrial applications. Full article

Mixed reality (MR) laboratories combine physical elements with virtual components, providing convenient experiential environments for testing engineering concepts. This article reports the design, validation, and implementation of an MR laboratory for engineering students to practice the implementation of control algorithms in microcontrollers. First, the design of the MR lab is described in detail. In this, a seesaw electromechanical system is emulated, being synchronized with electrical signals that represent sensors’ measurements and actuators’ commands. Thus, a control algorithm implemented by the students in a microcontroller can affect the simulated system in real time. The real seesaw system was used to validate the simulated plant in the MR lab, finding that the same control algorithm effectively controls both the simulated and physical seesaw systems. A practice, designed based on Kolb’s experiential learning cycle, where the students must implement P, PI, and PID controllers in the MR lab, was implemented. A survey was conducted to assess the students’ motivation, and a post-test was administered to evaluate their learning outcomes. Full article

In this paper, we propose the use of virtual labs (VLs) as a solution to bridge the gap between theory and practice in physics education. Through an experiment conducted in two towns in the Democratic Republic of the Congo (DRC), we demonstrate that our proposed lab (BRVL) is more effective than global alternatives in correcting misconceptions and ensuring compliance with the current curriculum in the DRC. We combine Conjoint Analysis (from SPSS) to weigh selected criteria—curriculum compliance, knowledge construction, misconception correction, and usability—alongside eight MCDA methods: AHP, CAHP, TOPSIS, ELECTRE I, ELECTRE II, ELECTRE TRI, PROMETHEE I, and PROMETHEE II. Our findings show that, among six VLs, BRVL consistently outperforms global alternatives like Algodoo and Physion in terms of pedagogical alignment, curriculum compliance, and correction of misconceptions for Congolese schools. Methodologically, the respondents are consistent and in agreement, despite individual differences. The sensitivity analysis of the ELECTRE and PROMETHEE methods has shown that changes in parameter values do not alter the conclusion that BRVL is the best among the compared VLs. Full article