Search Results (7,671)

Unmanned aerial vehicles (UAVs) and deep learning (DL) have introduced a new framework for intelligent building façade defect detection, yet existing studies often focus on isolated technical components and lack a systematic evaluation of the entire pipeline. To address this gap, this paper conducts a systematic literature review of 135 peer-reviewed journal articles retrieved from the Web of Science database over the period 2021–2026. This review investigates four key domains: (1) UAV inspection path planning and data acquisition; (2) multi-modal data fusion; (3) DL-driven defect detection algorithms; and (4) 3D reconstruction and digital twin integration. Our analysis reveals the following main findings. Real-time perception-aware planning is central to UAV path planning, yet most studies lack robustness evaluations under real-world deployment conditions. Multi-modal data fusion improves detection across multiple defect types, yet edge deployment requires balancing lightweight design with recognition stability. Defect recognition algorithms increasingly adopt task-driven architectures, but limited edge-device resources demand joint optimization of efficiency and accuracy. In digital twins, systematic research is still lacking on semantically integrating recognition results into BIM for O&M decision-making, leaving the closed loop from defect detection to maintenance unresolved. This review aims to help researchers and practitioners advance UAV-based inspection from an auxiliary tool to a fully autonomous, reliable intelligent agent for refined management of the urban built environment. Full article

Ceramics, as a handicraft, is the crystallization of art and science. In order to study the firing process of ceramics, improve their density, mechanical properties, viscosity, and surface tension, and enhance the surface quality of the shaft, this article uses first-principles methods to study the electronic properties of ceramic colorants Al₂O₃, Fe₂O₃, TiO₂, CaO, MgO, Na₂O, KO₂, and ceramic body SiO₂. Research has shown that these seven color-developing agents exhibit anisotropy and have stable crystal structures. The bandgap values of Al₂O₃, CaO, Fe₂O₃, KO₂, MgO, Na₂O, TiO₂, and ceramic SiO₂ are 6.325 eV, 3.654 eV, 0 eV, 0 eV, 4.731 eV, 1.972 eV, 2.18 eV and 6.002 eV, respectively. In Al₂O₃/SiO₂, Fe₂O₃/SiO₂, TiO₂/SiO₂, CaO/SiO₂, MgO/SiO₂, Na₂O/SiO₂, and KO₂/SiO₂ systems, due to the influence of the potential field in the SiO₂ system, the charge characteristics exhibit obvious interfacial and non-periodic characteristics. The research results revealed the charge transfer and distribution patterns at the interface between ceramic colorants and ceramic ligands, elucidating the influence mechanism of different colorants/embryo components on firing temperature, shrinkage rate, and finished product defects. This mechanism can be used to predict the advantages and disadvantages of alkali metals, iron, titanium, and aluminum components in raw materials, optimize low-temperature rapid firing formulas, suppress firing deformation, control pore defects, and improve the mechanical properties of finished products. It provides micro theoretical support for the industrialization, stabilization, and high-quality production of local ceramics in southwestern China. Full article

Microbial resistance to conventional antimicrobials is a growing public health challenge, driving the search for effective and sustainable alternatives. Among emerging strategies, the combination of silver nanoparticles (AgNPs), recognized for their potent antimicrobial action, with biosurfactants, natural, biodegradable compounds capable of interacting with microbial cell membranes and promoting their stabilization stands out. In this context, the aim of this study was to produce a biosurfactant by Candida glabrata UCP 1002 from agroindustrial residues, reducing costs and environmental impacts. The compound exhibited a surface tension of 29 mN/m, a critical micellar concentration of 0.3%, and a yield of 9 g/L; furthermore, it demonstrated stability across wide ranges of temperature, pH, and salinity. The AgNPs were synthesized using the biosurfactant as a stabilizing agent and ascorbic acid as a reducing agent, resulting in stable particles. In antimicrobial assays, the formulation inhibited Gram-positive microorganisms, Gram-negative microorganisms, and fungi. The best results were obtained against Pseudomonas aeruginosa (26.63%) and Candida albicans (28.11%), followed by Staphylococcus aureus (17.58%), Enterobacter sp. (14.42%), and Escherichia coli (13.68%). Although less effective than commercial antibiotics such as streptomycin and moxifloxacin, it showed potential as a complementary alternative in combating multidrug-resistant pathogens. Cytotoxicity assays revealed low toxicity toward normal cells (28.42% inhibition in Vero CCL-81) and minimal activity against tumor cells. The results demonstrate that the BS-AgNPs association combines relevant antimicrobial activity with environmental safety and biocompatibility, establishing itself as a promising and sustainable approach for application in health, industry, and the environment, with potential for scale-up production from low-cost raw materials. Full article

The filamentous fungus Trichoderma reesei is one of the most important workhorses for industrial enzyme production, but the cellular mechanisms that balance protein folding stress with secretion, such as the unfolded protein response (UPR) and repression under secretion stress (RESS), are still not fully understood. In this study, we set out to clarify how these pathways contribute to secretion in both laboratory settings and industrial-scale fermentations. Exposure to the reductive agent dithiothreitol for 5 h increased transcript levels of UPR-related genes at least 6-fold, and, simultaneously, transcript levels of target genes cbh1 and egl2 were reduced at least 5- or 6-fold, respectively. Interestingly, RESS was detected even when UPR was suppressed by the prevention of protein de novo synthesis, pointing to a non-hierarchical relation of the two mechanisms. With the aim to understand on which levels RESS is acting, in particular, whether it is transcription initiation or transcript stability, an experiment involving blocking the transcription was performed. Further, a recombinant strain with an exchanged promoter had an at least 45-fold-increased cbh1 transcript level, while a terminator exchange did not increase chb1 transcript levels, indicating that RESS operates mainly at the level of transcription initiation. Importantly, whole transcriptome data from industrial cellulase production did not reveal the signatures of UPR or RESS despite the heavy secretory load. Instead, expression profiles highlighted the induction of diverse hydrolytic enzymes and pathway adjustments that support efficient production. Full article

TiO₂-based heterostructures have attracted considerable attention in photocatalytic pollutant degradation owing to their enhanced photoresponse and improved charge separation. The phase structure of TiO₂ strongly affects its band structure and interfacial charge-transfer behavior, making phase structure control critical for optimizing photocatalytic performance. However, due to the small difference in free energy among TiO₂ phase structure and the strong dependence of TiO₂ nucleation and growth on the local reaction environment, it remains challenging to precisely control the phase structure of TiO₂ in the TiO₂-based heterostructure nanomaterials. Herein, we achieved the phase engineering of TiO₂/MXene heterostructure nanomaterials through a solvent-regulation strategy. Specifically, by regulating the acetonitrile/water ratio in the hydrothermal solvent, TiO₂ with distinct phase structures was in situ grown on hydrothermally treated MXene nanosheets, resulting in two representative TiO₂/MXene heterostructure nanosheets: anatase TiO₂/MXene and rutile TiO₂/MXene. Acetonitrile likely acted as a surface-adsorbing agent during TiO₂ formation, stabilizing the anatase phase and promoting the preferential formation of anatase TiO₂. Benefiting from the optimized heterostructure, TiO₂/MXene heterostructure nanosheets promoted the generation of singlet oxygen (¹O₂), leading to enhanced photocatalytic degradation. Full article

Natural microbial pigments offer important advantages and are widely studied for food applications. We investigated the biosynthetic pathways, characteristics, and bioactivities of the orange–red pigment produced by Bacillus velezensis YM–3, a strain isolated from the traditional Pixian Douban condiment. Whole-genome sequencing revealed complete pathways for melanin, phytoene, and heme biosynthesis. The purified extracellular pigment was characterized using ultraviolet–visible spectroscopy, Fourier-transform infrared spectroscopy, nuclear magnetic resonance spectroscopy, and ultra-performance liquid chromatography–high-resolution mass spectrometry; it was preliminarily characterized as melanin-like pigment. The pigment was highly soluble in alkaline solutions, moderately soluble in water, and insoluble in common organic solvents. It exhibited strong photostability and remained stable at low temperature, precipitated under acidic conditions, and showed high stability under alkaline environments. Furthermore, the pigment demonstrated in vitro free radical scavenging activity. Hence, this study provides a scientific foundation for exploring the potential utility of B. velezensis YM–3 and its pigment metabolites as functional agents. Full article

The rapid emergence of antimicrobial resistance has intensified the need for advanced therapeutic platforms capable of improving the efficacy, stability, and targeted delivery of antimicrobial agents. Electrospun nanofibers have emerged as highly promising materials for biomedical applications due to their large surface area, high porosity, tunable morphology, and ability to incorporate a broad range of bioactive compounds. This review provides a comprehensive overview of the design, fabrication, and biomedical applications of electrospun bioactive nanofibers functionalized with antimicrobial drugs. It presents the main nanofiber fabrication techniques, with particular emphasis on electrospinning and the influence of solution, process, and environmental parameters on fiber morphology and drug-loading efficiency. Natural, synthetic, and hybrid polymer systems commonly employed in electrospun antimicrobial nanofibers are analyzed in relation to their physicochemical properties, biocompatibility, and therapeutic performance. In addition, the review highlights different drug incorporation strategies, including encapsulation, immobilization, and surface coating, as well as the mechanisms of action of antimicrobial agents. Recent advances in nanotechnology-based antimicrobial systems and their role in overcoming analytical, biopharmaceutical, and drug-delivery limitations are also examined. Furthermore, the review addresses current challenges related to scalability, reproducibility, stability, and clinical translation of electrospun nanofibers. Finally, future perspectives focusing on multifunctional, stimuli-responsive, and personalized antimicrobial nanofiber systems are discussed as promising directions for combating bacterial infections and reducing the global burden of antimicrobial resistance. Full article

Agri-food by-products (BP) and BP-derived fractions are increasingly recognized as sources of functional and nutritional compounds (e.g., dietary fibers, proteins, waxes, phytosterols, phenolics, carotenoids) that can be upcycled into high-value food ingredients, to improve the sustainability of agri-food chains. This review provides a wide-ranging vision of the potential use of BP and BP-derived fractions in OG formulations, emphasizing the roles they can play (e.g., structuring agents, stabilizers, surfactants, physical scaffolds, fillers, sources of antioxidants), while offering mechanistic insights and science-based perspectives to support the rational design of tailor-made OGs for specific food applications. Particular attention is given to emerging areas including plant-based and hybrid products, and the valorization of insect BP and co-products. Finally, key gaps limiting BP-based OG design and application (e.g., effects on crystallization, interfacial phenomena, dispersion, scaffold/filler behavior, etc.) are identified and translated into a research roadmap and design guidelines for the formulation of tailor-made, scalable BP-based OGs. Full article

Microbial biocontrol agents often exhibit limited shelf life, which restricts their commercialization, storage, and large-scale agricultural application. In this study, freeze-drying (FD) microencapsulation was evaluated as a strategy to improve the stability of a wettable powder (WP) formulation based on Bacillus subtilis fermented broth using maltodextrin (MD) as a carrier. The physicochemical, structural, morphological, and antifungal properties of the resulting formulation were characterized. Physical characterization revealed complete solubility (100% at 0.1 g mL⁻¹), rapid wettability (2 s), and low hygroscopicity (3.86%), indicating favorable properties for handling and application. Scanning electron microscopy revealed irregular glass-like particles of different sizes, while Fourier transform infrared spectroscopy indicated the distribution of components within the maltodextrin matrix. The antifungal activity of the WP and the effects of its volatile organic compounds (VOCs) were evaluated against the phytopathogenic fungi Fusarium oxysporum, Fusarium solani, Fusarium graminearum, Rhizoctonia solani, and Sclerotinia sclerotiorum. The formulation inhibited fungal growth within the tested concentration range (0.1–0.2 g mL⁻¹), although no clear inhibition zone was observed for S. sclerotiorum. Furthermore, the WP maintained 65% viability after 24 months of storage at 4 °C. These results demonstrate the potential of FD microencapsulation to enhance the storage stability of Bacillus subtilis formulations while preserving their antifungal activity. Full article

Flavonoids are a structurally diverse class of plant-derived polyphenolic compounds widely recognized for their pleiotropic biological activities, including antioxidant, anti-inflammatory, and anticancer effects. In oncology, these compounds have demonstrated the ability to modulate key signaling pathways involved in cell proliferation, apoptosis, angiogenesis, and metastasis, highlighting their potential as multitarget therapeutic agents. However, their clinical translation remains significantly limited by unfavorable pharmacokinetic properties, such as poor aqueous solubility, extensive first-pass metabolism, rapid systemic clearance, and consequently low oral bioavailability. In this context, nanotechnology has emerged as a promising strategy to overcome these limitations. This review provides a comprehensive and critical analysis of current nanocarrier-based delivery systems for flavonoids, including polymeric nanoparticles, lipid-based nanocarriers (liposomes, solid lipid nanoparticles, and nanoemulsions), micelles, and cyclodextrin complexes, emphasizing their role in improving drug stability, enhancing cellular uptake, and enabling targeted delivery to tumor tissues through both passive mechanisms, such as the enhanced permeability and retention effect, and active targeting approaches. In addition, recent in vitro and in vivo studies demonstrating the superior antitumor efficacy of nanoencapsulated flavonoids compared to free compounds are discussed. Finally, the major translational challenges, safety considerations, and future perspectives for the clinical application of flavonoid-based nanomedicines in cancer therapy are highlighted. Full article

Excessive application of chemical preservatives has raised increasing concerns regarding food safety and human health, prompting the search for safer natural alternatives. Lavender essential oil (LEO), a plant-derived antimicrobial agent, has been considered a promising substitute for synthetic preservatives, but its high volatility and poor water solubility limit its practical application. In this study, LEO nanoemulsions were fabricated via high-pressure homogenization using sodium caseinate (SC) and tea polyphenols (TPs) as composite emulsifiers. The preparation process was optimized using a three-factor, three-level orthogonal design, and the physicochemical properties, storage stability, and antibacterial activity were systematically investigated. The optimal preparation conditions were determined as an SC/TP mass ratio of 2:1, homogenization pressure of 70 MPa, and 7 homogenization cycles. The optimized nanoemulsion exhibited a droplet size of 130–210 nm, zeta potential of −30.89 mV, and encapsulation efficiency of 98.61%, with typical shear-thinning behavior and excellent storage stability. The percentage of free LEO remained below 7.5% within 15 days, indicating high stability, and the release behavior followed a zero-order kinetic model. The prepared nanoemulsion showed significant antibacterial activity against Staphylococcus aureus and Escherichia coli, with a minimum inhibitory concentration (MIC) of 62.5 μg/mL for both strains. This study confirms that the SC/TP composite interface can effectively stabilize LEO nanoemulsions, providing a theoretical basis for the development of natural and efficient food preservatives. Full article

Modern power grids with high renewable energy penetration are vulnerable to fast voltage disturbances caused by grid faults. Among these, voltage sags are critical because they develop within milliseconds and require rapid reactive current support to maintain grid stability and power reliability. Reinforcement learning has previously shown potential for reactive current injection control during voltage sag events due to its fast response and adaptability to changing system conditions. However, existing approaches rely on separate policies for specific subsets of the operating space, which limits their ability to provide optimal actions when the system operates across broader or combined state regions. To address this limitation, this paper proposes a unified Soft Actor–Critic (SAC) target policy trained over the full state and action space by integrating multi-source transfer learning with potential-based reward shaping approach. Results show that the proposed multi-source transfer approach enables the target agent to converge faster and reach a higher reward solution than the baseline SAC and single-source transfer approach. The trained policy also improved prediction accuracy, achieving reactive-current errors below 0.2 A with respect to the ground-truth reference generated through extensive simulations over the full observation and action space. The reference follows the grid-code requirement for minimum reactive current injection during faults and provides a benchmark for evaluating prediction accuracy. This can help distributed generation sources respond more effectively during severe perturbations such as voltage sags, support voltage recovery, and reduce the risk of cascaded disconnections that could lead to unwanted blackouts. Additionally, the inference execution time is also sufficiently fast to satisfy the response-time requirement of voltage sag events, confirming the real-time feasibility of the proposed controller. Full article

Green synthesis of metal nanoparticles has attracted significant attention due to its sustainability, yet achieving precise control over their physicochemical properties via continuous-flow systems remains a challenge. This study evaluates the sustainable synthesis of copper nanoparticles using 3D-printed microfluidic reactors fabricated via the fused filament technique with glycol-modified polyethylene terephthalate. A systematic experimental design was performed to investigate the effects of the reducing agent concentration, the channel architecture, and the medium pH on particle size and morphology. Fluid dynamics theoretical modeling revealed a laminar flow regime, dominated by advection, where the serpentine geometry successfully induced stable homogeneous mixing. Statistical analysis identified pH as the most critical factor, demonstrating that an alkaline medium of pH 8 combined with a 5:1 reductant-to-precursor ratio optimizes the production of uniformly spherical copper nanoparticles with significantly smaller diameters. Advanced experiments also assessed the influence of flow rates and stabilizer agents on particle size, morphology and purity. These findings validate the integration of additive manufacturing and continuous microfluidics as a robust, low-cost, and eco-friendly platform for the reproducible and scalable production of metallic nanoparticles. Full article

Autonomous navigation of unmanned surface vehicles (USVs) in complex obstacle scenarios remains challenging due to redundant perception inputs, unstable value estimation, and inefficient policy convergence. To address these problems, this paper proposes LDA-D3QN, an improved deep reinforcement learning method for USV autonomous navigation. The proposed method constructs a compact navigation state representation by combining target-related information with local obstacle features, allowing the agent to retain key decision-making information while reducing unnecessary environmental redundancy. Based on this representation, an enhanced value-learning framework is developed to improve the stability of navigation decisions in cluttered environments. Moreover, a reward-guided and staged training strategy is introduced to help the agent gradually adapt to increasingly complex navigation tasks. The proposed method was evaluated on a Unity–ROS–MATLAB integrated simulation platform. Experimental results show that LDA-D3QN achieves superior overall navigation performance compared with several representative reinforcement learning algorithms. Specifically, the proposed method achieves a final training success rate of 91.4%, outperforming PPO (82.3%), Dueling DQN (78.5%), Double DQN (79.8%), and Rainbow DQN (86.5%). Additional tests in complex multi-obstacle and multi-target scenarios further demonstrate that the learned policy can generate safe, stable, and effective navigation behaviors. Preliminary validation using real-USV sensor data also confirms the feasibility of the LiDAR and GPS data processing procedures, providing a basis for future closed-loop autonomous navigation experiments and multi-sensor fusion deployment. Full article

This contribution examines the role of artificial intelligence technologies in the co-construction of social reality, with specific attention to AI-generated data as emergent agents of knowledge production. Building on perspectives from science and technology studies and recent debates on algomorphic sociology, the contribution conceptualizes generative AI systems not as research instruments, but as active participants in epistemic processes. The analysis argues that AI-generated data exhibit a performative character: they do not simply represent social phenomena but actively contribute to their stabilization, classification, and circulation. This performativity fosters a shift from researcher-centered interpretation toward hybrid configurations in which meaning emerges through human–machine assemblages. Through a theoretical synthesis of recent methodological and epistemological reflections, the contribution highlights a transition from anthropocentric models of knowledge production to post-anthropocentric, relational frameworks in which agency, cognition, and sense-making are distributed across sociotechnical networks. The contribution concludes by outlining the implications of this shift for the future of digital social research and also for reflexivity, methodological design, and the ethics of social research, advocating a critical and adaptive stance toward AI as a co-producer of knowledge rather than a subordinate analytical tool. Full article