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.

In pursuit of proactive safety management in construction, accurate and real-time recognition of workers' cognitive states is essential for crafting targeted interventions to minimize safety risks. Unlike conventional manual and qualitative methods, electroencephalogram (EEG) offers a reliable and objective solution for cognitive state recognition. Notably, efforts that integrate EEG with deep learning have exhibited significant advancements. Nevertheless, certain constraints, such as experimental costs and limited participants, have caused a scarcity of high-quality data, which has impeded performance in recognition tasks. Although transfer learning demonstrates its capability in addressing this challenge, the lack of relevant explorations into EEG-based cognitive state recognition remains a significant research gap. Therefore, customizing pre-trained deep learning models for these tasks would be beneficial. This study aims to develop pre-trained models to advance future studies in this domain through transfer learning, encompassing: 1) extracting extensive and accurately labeled EEG data from the DEAP dataset, 2) selecting appropriate network architectures and implementing pre-trained model development, and 3) collecting EEG data for mental fatigue recognition and evaluating model effectiveness. Rigorous evaluation suggests a substantial improvement in model performance, with test accuracy increasing from 63.19% to 92.29% by leveraging the pre-trained convolutional neural networks (CNN)—long short-term memory (LSTM) model. In conclusion, this study significantly contributes to enhancing safety management for construction workers through EEG by providing validated pre-trained models to address challenges of data scarcity. Future research may advance by exploring additional network architectures, increasing sample size, and considering more specific recognition tasks for model evaluation.

This study investigates the integration of Building Information Modeling (BIM) and the Internet of Things (IoT) in construction projects to enhance efficiency, safety, and lifecycle monitoring. Despite the significant potential of BIM and IoT to facilitate the transformation of the construction industry, existing research lacks a comprehensive framework that addresses its interoperability challenges, data security concerns, and real-world implementation barriers. To address this gap, a multiple case study approach was employed, incorporating semi-structured interviews, document analysis, and real-world project evaluations. The results find that standardized protocols, data encryption, and modular IoT devices are essential for effective BIM-IoT adoption across different construction phases. The proposed framework offers a structured approach for construction teams to effectively utilize BIM and IoT, facilitating smarter and more sustainable project management. The contribution of this paper resides in the detailed analysis of the BIM-IoT applications, clearly demonstrating its advantages, such as improving building productivity and safety, and its potential to align with China's sustainable urban development goals. The study also provides a forward-looking prediction of the future development trend of BIM-IoT in China, offering valuable insights for construction project teams and decision makers. By demonstrating the structured framework and its practical application, this study provides guidance for the industry's transition to smarter and safer construction practices.

This paper explores two virtual child simulators, BabyX and the VR Baby Training Tool, which provide immersive, interactive platforms for child-focused research and training. These technologies address key ethical and practical constraints, enabling the systematic study of caregiver-infant interactions and the development of professional relational skills with young children. We examine their design, features, and applications, as well as their future trajectories, highlighting their potential to advance research and improve training methodologies.

The predominance of a linear economic model and the limited integration of circular strategies in the design and execution of building projects—particularly in the construction sectors of developing countries—have resulted in ongoing pressure on natural resources, high levels of waste generation, reduced productivity, and frequent time and cost overruns. Collectively, these issues contribute to unsustainable development, adversely impacting the social, economic, and environmental dimensions of sustainability. This study explores the perceptions of design professionals regarding the benefits, awareness, and implementation of Design for Deconstruction (DfD) within the Nigerian construction industry (NCI). Data were collected through a structured questionnaire distributed electronically to design experts in Nigeria's South-South geopolitical zone using a snowball sampling technique. With a 40.10% response rate and a reliability index above 0.800, the data were analysed using Exploratory Factor Analysis (EFA) and Partial Least Squares Structural Equation Modelling (PLS-SEM). Findings reveal that awareness of DfD is moderate, but its adoption remains low. EFA identified five key categories of DfD benefits: (1) business benefits, (2) economic benefits, (3) environmental benefits, (4) green certification and technology integration, and (5) social benefits. PLS-SEM results show that all five categories have a positive and significant influence on the decision to adopt DfD within the NCI. This study contributes to the theoretical advancement and practical understanding of circular construction practices, particularly DfD, with implications for reducing construction waste, improving resource efficiency, and supporting the achievement of Sustainable Development Goals (SDGs) 3, 9, 11, 12, and 13.

Digital twin (DT) technology is revolutionizing the architecture, engineering, construction, and operation (AECO) industry, driven by the advancements of Construction 4.0 (C4.0). Despite this, adopting DT in the AECO sector remains limited due to various barriers. This study, driven by four research questions (RQ), aims to advance DT adoption in the AECO industry under C4.0 using an integrated approach. The degrees of influence and importance ranking of barriers are assessed through the decision-making trial and evaluation laboratory (DEMATEL). The hierarchy and causal relationships among barriers are revealed through interpretative structural modeling (ISM). Then, barriers are divided into four clusters employing the cross-impact matrix multiplication applied to classification (MICMAC) method. The paper reveals that "lack of government financial and policy support" is the most critical barrier, "lack of trust and long-term perspective in DT" is the most significant direct-influence barrier, and "immature 3D engine technology" is the most fundamental barrier. By exploring interrelationships and prioritizing barriers, the study provides insights to enhance adopting DT in the AECO industry in the context of C4.0.

Energy performance contracting (EPC) has been implemented as a turnkey solution to enhance the energy efficiency of building systems and fixtures. The two most common types of EPC-guaranteed savings contracts and shared savings contracts-are widely applied in the industry, with their selection primarily depending on stakeholders' risk tolerance and the availability of external financing. EPC involves multiple key participants, including the government, third-party financiers, building owners, and energy service companies (ESCOs). The relationships among these stakeholders vary based on the contract type: in a guaranteed savings contract, the owner has a direct financial relationship with the third-party financier, whereas in a shared savings contract, the ESCO assumes this role. This paper provides a critical review of previous studies on EPC, categorizing them into four key areas: (1) challenges in EPC adoption, (2) critical success factors, (3) diffusion strategies from different stakeholder perspectives, and (4) a stakeholder relationship framework linking key success factors and strategies. By analyzing these aspects, this review aims to inform potential investors and contractors about essential considerations for EPC implementation while examining the stakeholder dynamics within EPC projects.

Supercapacitors, renowned for their high-power density, rapid charge/discharge capabilities, and exceptional cycling stability, have emerged as promising solutions for sustainable and efficient energy storage. Among various electrode materials, carbon materials stands out due to its abundance, excellent electrical conductivity, chemical stability and structural versatility. This review explores the design strategies, performance optimization, and the expanding applications of carbon-based electrodes for supercapacitors. We first analyze the key factors that impact the performance of carbon electrodes for supercapacitors, including pore structure, surface chemistry, electrical conductivity and nanoscale architecture. Subsequently, we provide an in-depth analysis of recent advancements in the rational design of carbon materials, focusing on strategies for optimizing pore architecture, functionalizing surfaces, enhancing conductivity and designing nanostructures. By addressing performance limitations, the review highlights strategies that have significantly improved the efficiency of carbon electrodes. Furthermore, we explore the practical applications of carbon-based supercapacitors in wearable electronics, self-powered devices, and implantable systems. Lastly, we discuss the challenges and opportunities associated by carbon-based electrodes from the perspective of electrode design and practical application.

Circularly polarized light (CPL) features electromagnetic vectors that rotate regularly in a plane perpendicular to the direction of propagation, transmitting optical chirality information that is imperceptible to human beings. CPL can be classified into the left-handed and right-handed circularly polarization light (L-/R-CPL), depending on whether the rotation direction is clockwise or anticlockwise, respectively. The ability to manipulate and characterize CPL is crucial for advancing various optical technologies, making the effective and direct detection of CPL extremely important. Breeding in the hotbed provided by the explosively increased chiral materials with CPL luminescence and strong circular dichroism (CD), CPL detectors are currently experiencing savage growth. Mainstream strategies can be divided into the leverage of photoactive materials with inherent chirality and the integration of chiral metamaterials with nonchiral photoactive materials. In this review, we not only highlight significant material innovations and detector architectures for CPL detection but also address the broader implications of these advancements. We discuss the challenges and future directions in this field, particularly focusing on how these developments could impact existing commodities, such as polarimetric imaging and security communications, and contribute to sustainability in technology through improved detection efficiency. Our goal is to inspire further promising developments in CPL photodetectors and encourage a broader application spectrum.

Magnetorheological fluid (MRF) has broad application prospects in the field of engineering vibration damping due to its magnet-sensitive characteristics. However, owing to its dependence on external electric or magnetic fields, devices based on MRF can't work once the power is turned off. Here we developed a magnetorheological shear thickening fluid (MRSTF) with both the magnet-sensitive and rate-sensitive characteristics. The shear thickening effect of MRSTF was examined, revealing that the critical shear rate ${\dot{\gamma }}_c$ of the suspension gradually decreases from 79.4 s^-1 to 30.2 s^-1 and the shear thickening power β of the suspension gradually decreases from 0.27 to 0.19 as the carbonyl iron powder (CIP) content increases from 0 to 30 vol.% when the mass fraction of SiO₂ is 54 wt.%. Besides, the MRSTF-based dampers were tested under different frequencies and amplitudes. The results show that the MRSTF-based dampers still exhibit the energy dissipation characteristics in the absence of magnetic field because of the rate-sensitive property of MRSTF. Under the condition of an applied magnetic field, the dampers exhibit stronger energy dissipation characteristics due to the magnetic-sensitive characteristics of MRSTF. Concurrently, the dissipation capacity of the dampers increases with the increase of frequency and amplitude. This work provides an approach to enhance the mechanical properties of dampers and widen the application field.

Aims: To give a comprehensive understanding of current research on immersive empathic computing, this paper aims to present a systematic review of the use of Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR) technologies in empathic computing, to identify key research trends, gaps, and future directions.

Methods: The PRISMA methodology was applied using keyword-based searches, publishing venue selection, and citation thresholds to identify 77 papers for detailed review. We analyze these papers to categorize the key areas of empathic computing research, including emotion elicitation, emotion recognition, fostering empathy, and cross-disciplinary applications such as healthcare, learning, entertainment and collaboration.

Results: Our findings reveal that VR has been the dominant platform for empathic computing research over the past two decades, while AR and MR remain underexplored. Dimensional emotional models have influenced this domain more than discrete emotional models for eliciting, recognizing emotions and fostering empathy. Additionally, we identify perception and cognition as pivotal factors influencing user engagement and emotional regulation.

Conclusion: Future research should expand the exploration of AR and MR for empathic computing, refine emotion models by integrating hybrid frameworks, and examine the relationship between lower body postures and emotions in immersive environments as an emerging research opportunity.

Incorporation of two dimensional (2D) materials into a polymer matrix is an efficient way to prepare high performance coatings. Here we report the in-situ mechanical exfoliation of graphite in a mixture of hydroxyethylacrylate terminated polybutadiene urethane (HTPU) prepolymer and reactive diluent. The mixture containing exfoliated graphite nanoplatelets (GN) is directly used to prepare UV cured composite resins (G/HTPU) with various GN concentrations. Various techniques, such as scanning electron microscopy (SEM), Raman, atomic force microscopy (AFM), have been used to characterize the GN, confirming that few-layered GN are obtained after the in-situ mechanical exfoliation. The incorporation of GN exerts little effect on the curing of the coatings with a gelation around 95%, but greatly enhances the elastic modulus. Tafel polarization curves, electrochemical impedance spectroscopy (EIS) and salt-spray testing were conducted to comparatively evaluate the G/HTPU coatings with different GN loadings. The results indicate that the incorporation of GN greatly improves the corrosion resistance of the HTPU UV coatings. The self-corrosion current density (I _corr) and the charge transfer resistance (R _c) of G/HTPU-2 (0.2% GN loading) are greatly reduced to 1.03 × 10^-8 A·cm^-2 and increased by two magnitudes, respectively, compared to those of the parent HTPU coating. Additionally, the G/HTPU-2 coating with thickness of 100 μm can protect galvanized sheet against 0.5 mol/l sulfuric acid for at least 24 h. The practical application in protection of electronics was illustrated by coating the G/HTPU-2 on a standard printed circuit board (PCB, IPC-B-24A). No corrosion was observed after it was immersed in an artificial sweat solution even under open-circuit voltage of 12 V for 72 h and then 24 V for 48 h.

White-color organic light-emitting diodes (WOLEDs) have aroused wide interests for future lighting because of low energy consumption in principle, while still suffer from the degradation by Joule heating and polaron-induced quenching under high luminance caused by high current in practical. To obtain high current efficiency, which means high luminance at low current density, tandem WOLEDs with multiple electroluminescence (EL) units connected in series with charge generation layers (CGLs) have been developed. Here we report the improved hybrid tandem WOLED with two EL units, EL1 and EL2, where EL1 and EL2 generate fluorescent blue and phosphorescent yellow emissions from a metal-free material BCzVBi and a Ir-complex (fbi)₂Ir(acac), respectively, with CGL composed of a HATCN/NPB bilayer. The white-light emitting device shows the maximum current efficiency and power efficiency of 60.2 cd/A and 29.6 lm/W, respectively, without out-coupling structure. A low driving voltage of 6.5 V at 1,000 cd/m² is realized, which is an important value because such a luminance is required for actually employed lighting device. The blue emission appears from 5.4 V, and the light color changes from yellowish to bluish white during 5.4 V to 13.4 V, which could be explained by the energy level structures of the device and proved by the J-V characteristics. Additionally, this tandem WOLED also shows photovoltaic effect. This work provides a design of room light source whose color temperature could be tuned through applied voltage when needed, and a display system for low-current operated amorphous Si-TFT due to its high current efficiency.

Blue emitters are highly desired in organic light-emitting diodes (OLEDs), but their electroluminescence efficiencies and roll-offs are always less than satisfactory. In this work, a triazine-based deep-blue emitter (2PhCzTRZ-Cz) is designed and synthesized. It prefers high thermal stability with a decomposition temperature of up to 543 °C, and possesses strong deep-blue photoluminescence. The doped OLEDs using 2PhCzTRZ-Cz as an emitter attain deep-blue lights at 418-424 nm, with high maximum external quantum efficiencies (η_extS) of 4.46-5.68%, maximum luminances of 2,820-7,400 cd m^-2, CIE_y values < 0.1 and small efficiency roll-offs. In addition, multiple-resonance thermally activated delayed fluorescence OLED by using 2PhCzTRZ-Cz as host realizes a high maximum η_ext of 21.5%, significantly higher than those of the device based on traditional mCBP host (12.9%). These outstanding performances demonstrate the great potential of 2PhCzTRZ-Cz as an emitter and host for OLEDs.

With the development of 3D printing technologies, cellulose has been explored to realize its sophisticated geometry fabrication in this field for a variety of applications. This review focuses specifically on the latest research progress of 3D printing cellulose by discussing the characteristics of cellulose materials, different 3D printing technologies, and their optimal performance for applications in various fields like biomedicine, food packaging, and tissue engineering. The challenges of preparing 3D printing "ink" of cellulose using dissolved cellulose or nanocellulose are introduced. Finally, the corresponding applications of cellulose using 3D printing are classified and the strategies to optimize production performance are provided.

Aims: Recent world events have resulted in companies using remote meeting tools more often in design processes. The shift to remote meeting tools has had a notable impact on collaborative design activities, such as design reviews (DRs). When DRs depend on computer-aided design (CAD) software, the lack of direct support for CAD functionalities in videoconferencing applications introduces novel communication challenges, i.e. friction. This study investigates friction encountered in real world remote DRs when using a combination of standard CAD and videoconferencing applications. The objective was to understand the main sources of friction when carrying out DRs using a combination of CAD and videoconferencing applications.

Methods: At a single Swedish automobile manufacturer, 15 DRs of a fixture component were passively observed. These observations were subjected to a qualitative thematic analysis to identify categories and sources of friction during these DRs. The DRs were carried out using a combination of CATIA CAD software and Microsoft Teams for videoconferencing.

Results: The analysis of the 15 remote DRs identified four recurring friction categories: requesting specific viewpoints, indicating specific elements, expressing design change ideas, and evaluating ergonomics. Each category highlights specific challenges that were observed during the DRs and emerged due to constraints imposed by existing methods and technologies for remote meetings.

Conclusion: This study provides a framework for understanding the current sources of friction in remote DRs using videoconferencing tools. These insights can support the future development of DR software tools, guiding the integration of features that address these friction points. Additionally, the results serve as a guideline for organizations to implement methods that reduce friction in remote DRs and improve DR quality and efficacy.

This mini-review explores advancements in the synthesis of nano-carrier-based drug delivery systems using microfluidic chip technology and their evaluation using tumor organ-on-a-chip models. We discuss the principles and advantages of hydrodynamic fluid focusing (HFF) and micromixer for synthesizing polymeric nano-carriers, highlighting their ability to precisely control particle size, shape, and surface properties. The functionalization of nano-carriers for targeted drug delivery is also explored, emphasizing the potential for personalized medicine. The review emphasizes the use of tumor organ-on-a-chip models for evaluating nano-carrier-based drug delivery systems, highlighting their ability to simulate physiological environments and provide dynamic and controllable evaluation platforms. This approach holds great promise for enhancing our understanding of drug behaviors and accelerating the translation of nanomedicines from bench to bedside.

Brain diseases, including psychosis, neurological disorders, strokes, etc., account for more than 15% of all global health damage, which is higher than that caused by cancer and cardiovascular diseases. Brain health and the treatment of brain diseases have become major challenges of the 21st century. The past few decades have witnessed a series of significant advances in human brain science research. The pathogenesis of brain diseases at the molecular and genetic level is being revealed, indicating promising outcomes. However, the existence of the blood-brain barrier (BBB) significantly impedes the delivery of drugs and genes to the brain, which seriously hinders the treatment of brain diseases. This review article provides a brief overview of the concept and history of the BBB. We focus on the critical obstacles and solutions of different kinds of therapeutics, including small molecule drugs, peptides, proteins, and genes, to break through the BBB. Delivery mechanisms, strategies, and vehicles are summarized. Recent advances and efforts in drug delivery studies that aim to overcome the BBB will greatly facilitate the development of brain disease treatment.

Prefabricated housing (PH) is widely supported and applied in China due to its high efficiency and low carbon emissions. However, the adoption of this sustainable construction method has been slow in rural areas, hindered by economic, policy and location factors. To promote the development of low-carbon construction in rural areas and address the obstacles, this study focuses on Jiangsu province as a case study, proposing effective strategies to modernize and advance sustainable rural housing. The primary barrier to the prefabricated concrete (PC) adoption in rural Jiangsu were identified through a literature review and expert interviews. A survey was then conducted to assess the impact of these barriers, yielding 228 valid responses from industry professionals. Factor analysis was conducted using SPSS 19.0 to calculate the multi-level weights for influencing factors across dimensions. Based on these findings, key obstacles were further analyzed through strengths, weaknesses, opportunities and threats (SWOT) analysis to develop targeted countermeasures and recommendations. The research results show that: (1) Among secondary indicators, Policy factors (weight = 0.219) and Location factors (weight = 0.215) have the most significant impact PC promotion in rural Jiangsu; (2) Among the tertiary indicators, the critical factors are "The standard system is incomplete" (weight = 0.059), "The technical system is not mature" (weight = 0.048), "Lack of specific departments for promoting and supervising at the grassroots level" (weight = 0.046); (3) Strategies such as enhancing policy alignment and market penetration, tailoring solutions to local demands, establishing a robust regulatory framework, and fostering community engagement and acceptance can effectively address the challenges of promoting PC in rural areas. This research provides actionable pathways for the advancing prefabricated housing in Jiangsu and offers valuable references for other regions seeking to promote prefabricated housing in China.

Every household uses an average of around 360 litres of water each day. About 21% of a typical gas consumption is attributed to heating the water for showers, baths, and hot water from the tap. An environmentally friendly, low-cost device called the CombiSave valve can be used to manage gas and water consumption and should be fitted to most combination boilers to automatically control the flow of water every time a hot tap is turned on. This allows the boiler to heat the water faster and only return the flow to normal once a usable temperature is reached. An experimental test was conducted in the exemplar modern house of Liverpool John Moores University in order to assess the amount of water, energy, and CO₂ reduction for varying temperatures and flow rates. The test was carried out for a duration of 9 hours during the daytime between June and October. Although the test was conducted over relatively warm months when ambient water temperatures were higher compared to winter months, results showed that good savings could be achieved through this product. The best savings for gas consumption and hence CO₂ reduction were achieved at high water pressure and low temperature setting (40 ℃) of 36% compared with the case without combiSave. While water consumption was reduced by 56% at full flow rate and 45 ℃. Further research is needed encompassing multiple occupied dwellings with different family sizes and testing these in extreme weather conditions to see if similar results would be reflected.

Nitrogen/boron-based multi-resonance thermally activated delayed fluorescence (MR-TADF) materials offer advantages in terms of high photoluminescence quantum yield (PLQY) and narrowband emission, making them highly promising for display applications. Represented by ν-DABNA, diboron MR-TADF materials demonstrate the potential for high-efficiency narrowband emission. However, their large planar structures are susceptible to intermolecular interactions, thus increasing the complexity of device fabrication. In this research, our objective was to enhance the anti-aggregation capabilities of the diboron-based ν-DABNA by incorporating sterically hindered terphenyl groups. We synthesized two luminescent materials, DTPF-ν-DABNA and DTP-ν-DABNA, with intermolecular distances exceeding 4 Å in single-crystal stacking, significantly inhibiting intermolecular interactions. Both materials achieved an external quantum efficiency (EQE) exceeding 30% and full width at half maximum (FWHM) of no more than 22 nm, demonstrating characteristics of high-efficiency narrowband emission. Our research provides a straightforward and practical method to obtain MR-TADF materials with high device efficiency and low sensitivity to doping concentration.