Search Results (1,671)

Sunflower (Helianthus annuus L.) is an important oilseed crop in Northwest China, exhibiting resistance to salt and drought. Mining its excellent tolerance genes can be used for breeding. However, the current platforms for identifying gene function in sunflower is inadequate. The transient transformation system, which can rapidly validate gene function, shows promising prospects in research. In this study, we established an efficient transient expression transformation system for sunflower using three methods: Agrobacterium-mediated infiltration, injection, and ultrasonic-vacuum. The detailed procedures were as follows: Agrobacterium GV3101 carrying a GUS reporter gene on the pBI121 vector with an OD₆₀₀ of 0.8 as the bacterial suspension and 0.02% Silwet L-77 as the surfactant were utilized in all three approaches. For the infiltration method, seedlings grown hydroponically for 3 days were immersed in a bacterial suspension containing 0.02% Silwet L-77 for 2 h; for the injection method, the same solution was injected into the cotyledons of seedlings grown in soil for 4 to 6 days. Subsequently, the seedlings were cultured in the dark at room temperature for three days; for the ultrasonic-vacuum method, seedlings cultured in Petri dishes for 3 days were first subjected to ultrasonication at 40 kHz for 1 min, followed by vacuum infiltration at 0.05 kPa for 5–10 min. Agrobacterium-mediated transient transformation efficiency achieved by the three methods exceeded 90%, with gene expression being sustained for at least 6 days. Next, we employed the infiltration-based sunflower transient transformation technology with the Arabidopsis stable transformation platform to confirm salt and drought stress tolerance of candidate gene HaNAC76 from sunflower responding to various abiotic stresses. Altogether, this study successfully established an Agrobacterium-mediated transient transformation system for sunflower using these three methods, which can rapidly identify gene function and explore the molecular mechanisms underlying sunflower’s resistance traits. Full article

Cement–Soil Mixing (CSM) Pile is an important technology for soft ground reinforcement, and its as-formed compressive strength directly affects engineering design and construction quality. To address the significant discrepancy between laboratory-tested strength and field as-formed strength arising from differing environmental conditions, this study conducted modified laboratory experiments simulating key field formation characteristics. A cement–soil preparation system considering actual immersion conditions was established, based on controlling the initial water content state of the foundation soil before pile formation and applying submerged conditions post-formation. Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. Engineering validation demonstrated that the model achieved an RMSE of 0.138, an MAE of 0.112, and an R² of 0.961. It effectively addresses the issue of large prediction deviations caused by insufficient environmental simulation in traditional mix proportion tests. The research findings establish a quantitative relationship between as-formed strength and preparation parameters, providing an effective experimental improvement and strength prediction method for the engineering design of CSM Pile. Full article

The present study investigates dye-sensitized solar cells (DSSCs) incorporating natural extracts from the microalgae Spirulina and Chlorella as photosensitizers. TiO₂-based electrodes were prepared and immersed in methanolic algae extracts for 24 and 48 h. UV–Vis spectroscopy revealed absorption peaks near 400 nm and 650 nm, characteristic of chlorophyll. Electrochemical analyses, including photochronoamperometry and open-circuit potential, confirmed the photosensitivity and charge transfer capabilities of all systems. The cell sensitized with Chlorella after 48 h of immersion exhibited the highest energy conversion efficiency (0.0184% ± 0.0015), while Spirulina achieved 0.0105% ± 0.0349 after 24 h. Chlorella’s superior performance is attributed to its higher chlorophyll content and enhanced light absorption, facilitating more efficient electron injection and interaction with the TiO₂ surface. Although the efficiency remains lower than that of conventional silicon-based solar cells, the results highlight the potential of natural colorants as sustainable and low-cost alternatives for photovoltaic applications. Nonetheless, further, improvements are required, particularly in dye stability and anchorage, to improve device performance. This research reinforces the viability of natural photosensitizers in DSSC technology and supports continued efforts to optimize their application. Full article

Subsurface mass concrete infrastructure—including immersed tunnels, dams, and nuclear waste containment systems—frequently faces calcium-leaching risks from prolonged groundwater exposure. An anisotropic stress-leaching damage model incorporating microcrack propagation is developed for underground concrete’s chemo–mechanical coupling. This model investigates stress-induced anisotropy in concrete through the evolution of oriented microcrack networks. The model incorporates nonlinear anisotropic plastic strain from coupled chemical–mechanical damage. Unlike conventional concrete rheology, this model characterizes chemical creep through stress-chemical coupled damage mechanics. The numerical model is incorporated within COMSOL Multiphysics to perform coupled multiphysics simulations. A close match is observed between the numerical predictions and experimental findings. Under high stress loads, calcium leaching and mechanical stress exhibit significant coupling effects. Regarding concrete durability, chemical degradation has a more pronounced effect on concrete’s stiffness and strength reduction compared with stress-generated microcracking. Full article

In response to the stress commonly experienced by young people in high-pressure daily environments, a music-based stress-relief interactive system was developed by integrating music-assisted care with emotion-sensing technology. The design principles of the system were established through a literature review on stress, music listening, emotion detection, and interactive devices. A prototype was created accordingly and refined through interviews with four experts and eleven users participating in a preliminary experiment. The system is grounded in a four-stage guided imagery and music framework, along with a static activity model focused on relaxation-based stress management. Emotion detection was achieved using a wearable EEG device (NeuroSky’s MindWave Mobile device) and a two-dimensional emotion model, and the emotional states were translated into visual representations using seasonal and weather metaphors. A formal experiment involving 52 users was conducted. The system was evaluated, and its effectiveness confirmed, through user interviews and questionnaire surveys, with statistical analysis conducted using SPSS 26 and AMOS 23. The findings reveal that: (1) integrating emotion sensing with music listening creates a novel and engaging interactive experience; (2) emotional states can be effectively visualized using nature-inspired metaphors, enhancing user immersion and understanding; and (3) the combination of music listening, guided imagery, and real-time emotional feedback successfully promotes emotional relaxation and increases self-awareness. Full article

The formation mechanism of Virtual Reality (VR) Immersive Experience (VRIE) is notably complex; this study aimed to dynamically decode its underlying drivers by innovatively integrating Flow Theory and Privacy Calculus Theory, focusing on Perceptual-Interactive Fidelity (PIF), Consumer Willingness to Immerse in Technology (CWTI), and the applicability of Loss Aversion Theory. To achieve this, we analyzed approximately 30,000 user reviews from Amazon using Latent Semantic Analysis (LSA) and regression analysis. The findings reveal that user attention’s impact on VRIE is non-linear, suggesting an optimal threshold, and confirm PIF as a central influencing mechanism; furthermore, CWTI significantly moderates users’ privacy calculus, thereby affecting VRIE, while Loss Aversion Theory showed limited explanatory power in the VR context. These results provide a deeper understanding of VR user behavior, offering significant theoretical guidance and practical implications for future VR system design, particularly in strategically balancing user cognition, PIF, privacy concerns, and individual willingness. Full article

This study aims to analyze the bending behavior of polylactic acid (PLA) structures made by fusion deposition modeling (FDM) technology. The investigation analyzed chiral structures such as lozenge and clepsydra, as well as geometries with wavy patterns such as roller and Es, in addition to a honeycomb structure. All geometries have a relative density of 50%. After being subjected to three-point bending tests, the capacity to spring back with respect to the bending angle and the shape recovery of the structures were measured. The roller and lozenge structures demonstrated the best performance, with shape recovery assessed through three consecutive hot water immersion cycles. The lozenge structure exhibits 25% higher energy absorption than the roller, but the latter ensures better replicability and shape stability. Additionally, the roller absorbs 15% less energy than the lozenge, which experiences a 27% decrease in absorption between the first and second cycle. This work provides new insights into the bending-based energy absorption and recovery behavior of PLA metamaterials, relevant for applications in adaptive and energy-dissipating systems. Full article

This study explores the potential of Intelligent Geographic Information Systems (GISs) in advancing educational practices through the integration of real-time data models. The objective is to investigate how GIS technology can enhance teaching and learning by providing interactive and dynamic learning environments. The research employs a bibliometric analysis based on the Scopus database, covering the period from 2000 to 2024, to identify key trends, the evolution of GIS applications in education, and their pedagogical impact. Findings reveal that GISs, particularly when incorporating real-time data, enable a more immersive learning experience, facilitate data-driven decision-making, and promote student engagement through project-based learning. However, challenges such as the lack of specialized training for educators and limitations in technological infrastructure remain significant barriers to widespread adoption. The study concludes that Intelligent GISs have the potential to transform education by fostering personalized, interdisciplinary learning and enhancing educational management. It emphasizes the need for further research aimed at developing user-friendly systems and addressing ethical concerns to ensure the benefits of GIS technology are accessible to all students. Future studies should examine the long-term effects of GISs on student outcomes and explore their integration into diverse educational contexts. Full article

Background/Objectives: Fear detection through EEG signals has gained increasing attention due to its applications in affective computing, mental health monitoring, and intelligent safety systems. This systematic review aimed to identify the most effective methods, algorithms, and configurations reported in the literature for detecting fear from EEG signals using artificial intelligence (AI). Methods: Following the PRISMA 2020 methodology, a structured search was conducted using the string (“fear detection” AND “artificial intelligence” OR “machine learning” AND NOT “fnirs OR mri OR ct OR pet OR image”). After applying inclusion and exclusion criteria, 11 relevant studies were selected. Results: The review examined key methodological aspects such as algorithms (e.g., SVM, CNN, Decision Trees), EEG devices (Emotiv, Biosemi), experimental paradigms (videos, interactive games), dominant brainwave bands (beta, gamma, alpha), and electrode placement. Non-linear models, particularly when combined with immersive stimulation, achieved the highest classification accuracy (up to 92%). Beta and gamma frequencies were consistently associated with fear states, while frontotemporal electrode positioning and proprietary datasets further enhanced model performance. Conclusions: EEG-based fear detection using AI demonstrates high potential and rapid growth, offering significant interdisciplinary applications in healthcare, safety systems, and affective computing. Full article

This review examines the design of thermal control systems for state-of-the-art deep ultraviolet (DUV) and extreme ultraviolet (EUV) projection lithography tools. The lithographic system under investigation integrates several critical subsystems along the optical transmission chain, including the light source, reticle stage, projection optics (featuring DUV refractive lenses and EUV multilayer mirrors), immersion liquid, wafer stage, and metrology systems. Under high-power irradiation conditions with concurrent thermal perturbations, the degradation of thermal stability and gradient uniformity within these subsystems significantly compromises exposure precision. Through a systematic analysis of the thermal challenges specific to each subsystem, this review synthesizes established thermal control systems across two technical dimensions: thermal control structures and thermal control algorithms. Prospects for future advancements in lithographic thermal control are also discussed. Full article

This paper presents a qualitative case study on the design, implementation, and validation of the Art Nouveau Path, a mobile augmented reality game developed to foster sustainability competences through engagement with Aveiro’s Art Nouveau built heritage. Grounded in the GreenComp framework and developed through a Design-Based Research approach, the game integrates location-based interaction, narrative storytelling, and multimodal augmented reality and multimedia content to activate key competences such as systems thinking, futures literacy, and sustainability-oriented action. The game was validated with 33 in-service schoolteachers, both through a simulation-based training workshop and a curricular review of the game. A mixed-methods strategy was used, combining structured questionnaires, open-ended reflections, and curricular review. The findings revealed strong emotional and motivational engagement, interdisciplinary relevance, and alignment with formal education goals. Teachers emphasized the game’s capacity to connect local identity with global sustainability challenges through immersive and reflective experiences. Limitations pointed to the need for enhanced pedagogical scaffolding, clearer integration into STEAM subjects, and broader accessibility across technological contexts. This study demonstrates that these games, when grounded in competence-based frameworks and inclusive design, can meaningfully support multimodal, situated learning for sustainability and offer valuable contributions to pedagogical innovation in Education for Sustainable Development. Full article

As autonomous driving technologies advance, the need for human-in-the-loop systems becomes increasingly critical to ensure safety, adaptability, and public confidence. This paper presents the design and evaluation of a context-aware immersive teleoperation interface that integrates real-time simulation, virtual reality, and multimodal feedback to support remote interventions in emergency scenarios. Built on a modular ROS2 architecture, the system allows seamless transition between simulated and physical platforms, enabling safe and reproducible testing. The experimental results show a high task success rate and user satisfaction, highlighting the importance of intuitive controls, gesture recognition accuracy, and low-latency feedback. Our findings contribute to the understanding of human-robot interaction (HRI) in immersive teleoperation contexts and provide insights into the role of multisensory feedback and control modalities in building trust and situational awareness for remote operators. Ultimately, this approach is intended to support the broader acceptability of autonomous driving technologies by enhancing human supervision, control, and confidence. Full article

We propose a single-phase chiral elastic metamaterial capable of simultaneously exhibiting negative effective mass density and negative bulk modulus in the ultrasonic frequency range. The unit cell consists of a regular hexagonal frame connected to a central circular mass through six obliquely oriented, slender aluminum beams. The design avoids the manufacturing complexity of multi-phase systems by relying solely on geometric topology and chirality to induce dipolar and rotational resonances. Dispersion analysis and effective parameter retrieval confirm a double-negative frequency region from 30.9 kHz to 34 kHz. Finite element simulations further demonstrate negative refraction behavior when the metamaterial is immersed in water and subjected to 32 kHz and 32.7 kHz incident plane wave. Equifrequency curves (EFCs) analysis shows excellent agreement with simulated refraction angles, validating the material’s double-negative performance. This study provides a robust, manufacturable platform for elastic wave manipulation using a single-phase metallic metamaterial design. Full article

This research addresses the long-standing dependence on printed maps for navigation and highlights the limitations of existing digital services like Google Street View and Google Street View Player in providing comprehensive solutions for route analysis and understanding. The absence of a systematic approach to route analysis, issues related to insufficient street view images, and the lack of proper image mapping for desired roads remain unaddressed by current applications, which are predominantly client-based. In response, we propose an innovative automatic system designed to generate videos depicting road routes between two geographic locations. The system calculates and presents the route conventionally, emphasizing the path on a two-dimensional representation, and in a multimedia format. A prototype is developed based on a cloud-based client–server architecture, featuring three core modules: frames acquisition, frames analysis and elaboration, and the persistence of metadata information and computed videos. The tests, encompassing both real-world and synthetic scenarios, have produced promising results, showcasing the efficiency of our system. By providing users with a real and immersive understanding of requested routes, our approach fills a crucial gap in existing navigation solutions. This research contributes to the advancement of route planning technologies, offering a comprehensive and user-friendly system that leverages cloud computing and multimedia visualization for an enhanced navigation experience. Full article

The evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0. Full article