Science Exploration Press

Bone defects represent a significant orthopedic challenge, with associated disorders continue to pose clinical difficulties. In the biomedical field, advancements in three-dimensional (3D) printing technology have established bone tissue engineering (BTE) scaffolds as a promising approach for effective treatment. These scaffolds not only provide structural support for cells but also serve as templates to guide bone tissue regeneration. In recent years, owing to their exceptional physicochemical properties, two-dimensional nanomaterials (2D NMs) have garnered increasing attention and have been widely explored as additives in the fabrication of BTE scaffolds. This review centers on the most recent developments in the combination of 2D NMs and 3D printing for BTE applications. It begins with a concise summary of the common synthesis and surface modification methods of 2D NMs. Then, it offers a comprehensive overview of recent advancements in their use within BTE. Finally, it discusses current challenges and future perspectives regarding the application of 2D NMs-based 3D-printed scaffolds in bone tissue regeneration.

The development of high-performance narrowband red organic light-emitting diodes (OLEDs) has garnered significant attention, offering both exciting opportunities and formidable challenges. In this study, we report the synthesis of a novel red thermally activated delayed fluorescence (TADF) molecule, 10,10',10''-([1,2,4]triazolo[1,5-a][1,3,5]triazine-2,5,7-triyltris(benzene-4,1-diyl))tris(10H-phenoxazine) (TPXZ-TAZTRZ), which integrates a highly electron-deficient triazolotriazine unit as the acceptor and three strongly electron-donating phenoxazine (PXZ) moieties as donors. TPXZ-TAZTRZ exhibits a small singlet-triplet energy gap, enabling a rapid reverse intersystem crossing rate. Additionally, it shows a broad emission spectrum peaking at 634 nm, spanning the yellow-to-red region. These features render TPXZ-TAZTRZ as an ideal TADF sensitizer for narrowband red fluorescent OLEDs. Accordingly, TPXZ-TAZTRZ was employed to sensitize the conventional fluorescent emitter DBP. The resulting TADF-sensitized fluorescence OLEDs (TSF-OLEDs) demonstrated efficient energy transfer from the TADF sensitizer to the emitter, effectively addressing the limitations previous encountered with TADF systems. The devices achieved high-performance pure red emission, with Commission International de l'Éclairage (CIE) coordinates of [0.67, 0.33], an emission peak at 612 nm, a narrow full width at half maximum (FWHM) of 27 nm, and a maximum external quantum efficiency of 16.2%.

Aims: This study aims to enhance the design of augmented reality (AR) technologies for remote collaboration by examining the complex relationships among individual factors (user characteristics), psychological and physiological states during AR-mediated remote collaboration, and outcomes within an Input-Mediator-Output (IMO) model. The goal is to evaluate how individual characteristics influence psychological and physiological experiences, as well as task performance, in AR-mediated collaboration.

Methods: We hypothesize and evaluate an IMO model and use correlation analyses to examine the relationships among person-related input variables (e.g., predispositions, traits, attitudes, states, and contextual factors), psychological and physiological emergent states, and performance-related output variables.

Results: Our results demonstrate that individual characteristics significantly influence subjective experiences, physiological responses, and task performance, emphasizing the critical role of individual differences, alongside task- and technology-related factors, in shaping collaboration experiences and performance. These findings highlight the importance of considering individual characteristics in the design of AR tools to optimize user well-being and performance outcomes.

Conclusion: Our study provides a foundational framework for understanding the interplay between individuals, tasks, and technology, underscoring the need for AR tools that align with user characteristics. It also lays the groundwork for future IMO research in AR-mediated remote collaboration, contributing to the development of more effective and health-promoting AR technologies.

Neuropeptides are crucial signaling molecules that regulate diverse physiological processes spanning growth, social behavior, learning, memory, metabolism, homeostasis, reproduction, and neural differentiation across both nervous and peripheral systems. Dysregulation of neuropeptides signaling is closely linked to various pathological conditions, such as neurological disorders, metabolic diseases, cardiovascular conditions, and even cancer, positioning them as potential therapeutic agents or targets for intervention. In recent years, research into neuropeptides has accelerated, with vast amounts of data continuously accumulating in multiple databases. However, the study of neuropeptides is often impeded by the need for extensive and time-consuming experimental investigations. As a result, computational tools have become essential for the rapid, large-scale identification of neuropeptides. This review systematically discusses neuropeptide-related databases and computational tools. These databases organize extensive data on neuropeptide sequences, structures, and functions. Among these, NeuroPep2.0, with 11,417 neuropeptide entries, is currently the most widely used dataset for neuropeptide prediction. Additionally, this review explores the application of computational approaches in neuropeptide prediction. While early methods predominantly relied on homologous sequence alignment and biochemical feature statistics, recent advances in machine learning have significantly enhanced prediction accuracy and efficiency. Tools such as NeuroPred-PLM and DeepNeuropePred, developed by our research group using protein language models, have substantially improved prediction performance. In conclusion, this review provides a comprehensive overview of current neuropeptide databases and computational tools, offering researchers a thorough survey of available resources and analytical methods, and emphasizing the necessity of continuous optimization to advance neuropeptide research and its therapeutic applications.

High-performance and long-lifetime blue organic light-emitting diodes (OLEDs) are crucial for meeting the demands of advanced display and lighting technologies. Despite high device efficiency has been achieved in blue OLEDs, development of high-performance and long-lifetime blue OLEDs still lag far behind their red/green counterparts due to the presence of long-lived high-energy triplet excitons and polarons. Given the critical role of charge and exciton management in both the emission and degradation processes of OLEDs, this review systematically summarizes strategies for suppressing charge leakage and exciton quenching, as well as for enhancing exciton utilization in blue fluorescent, phosphorescent, and thermally activated delayed fluorescent (TADF) OLEDs. In this context, we further discuss the roles of conventional fluorescent hosts, triplet-triplet annihilation/hot exciton hosts, TADF assistant hosts, phosphorescent assistant hosts, and exciplex/electroplex hosts in regulating charge and exciton dynamics in blue OLEDs. Additionally, the modification of emitting layer materials is highlighted as a key strategy for managing charge and exciton processes in efficient and stable solution-processed blue OLEDs. Based on current insights into the efficiency and operational stability of blue OLEDs, this review proposes feasible charge and exciton management strategies to address the current challenges.

The architecture, engineering and construction (AEC) industry is currently encountering numerous challenges and actively pursuing industrial upgrades through digital transformation. Digital twin (DT) technology aligns well with the industry's evolving needs due to its capabilities in data integration, intelligent decision-making, and effective management of project progress, efficiency, and quality. This study conducts a comprehensive literature review to analyze the strengths, weaknesses, opportunities, and threats (SWOT) associated with DT applications in the AEC sector. Additionally, field visits and semi-structured interviews were conducted on a selected construction project where DT was implemented, allowing for an in-depth examination of both its significant benefits and potential limitations. To further evaluate and prioritize the identified SWOT factors, a SWOT-AHP analysis was performed. The results indicate that the AEC industry has a strong interest in DT's advantages, particularly its potential to enhance resource allocation and process efficiency. Furthermore, the analysis reveals that the strategic quadrilateral occupies the largest area in the fourth quadrant (0.8554), with the strategic center of gravity located at (0.2321, -0.04135), suggesting that Strengths-Threats (ST) strategies should be implemented to support the future development and adoption of DT. Based on this strategic framework, the study formulates actionable development strategies to facilitate the effective integration and widespread adoption of DT in the AEC industry.