Search Results (3,512)

The obligate mutualism between Ficus and its pollinating wasps provides a suitable system to investigate these dynamics because it encompasses two contrasting pollination modes: active and passive. Here we compared pollen traits in an actively pollinated fig tree, Ficus citrifolia, and a passively pollinated species, F. obtusiuscula, examining pollen both at anther presentation and after deposition on the bodies of their pollinating wasps. Pollen morphology, hydration-related behavior, cytology, and reserve composition were characterized using scanning electron microscopy (conventional and modified), light and transmission electron microscopy, histochemical assays, and viability tests. Across species, pollen traits at anthesis showed broad overlap in morphology, viability and major reserve classes, indicating that these characteristics are not consistently predicted by pollination mode alone. In both species, pollen was bicellular, harmomegathic and highly viable at presentation, consistent with resilience during transport. The main divergence emerged after pollen transfer to the pollinator. In the actively pollinated species, pollen recovered from wasp thoracic pockets exhibited pronounced intracellular remodeling, including vacuolization, starch depletion, lipid redistribution and localized cytoplasmic degradation. By contrast, pollen of the passively pollinated species retained a comparatively stable cytological organization after transport despite changes in reserve distribution. These results suggest that the more pronounced cytoplasmic reorganization observed in the pollen of the actively pollinated species after deposition on the wasp body may represent a preparatory phase for rapid germination following pollination, reflecting the stronger dependence of larval development on successful flower fertilization in actively pollinated figs. More broadly, our study provides the first comparative account of pollen structural and cytophysiological dynamics on fig-wasp bodies, linking pollen cell biology to pollinator-mediated dispersal and highlighting how different pollination strategies may impose distinct selective pressures on male gametophytes. Full article

Prefabricated steel structures have been increasingly adopted in modern construction due to their high efficiency, sustainability, and industrialized production. However, their construction quality and efficiency are often compromised by accumulated geometric deviations during fabrication, transportation, assembly, and welding, while traditional construction control and welding processes remain highly dependent on manual measurements and empirical operations. To address these challenges, this study proposes a digital construction framework for prefabricated steel structures, integrating high-precision three-dimensional (3D) laser scanning, Building Information Modeling (BIM), and intelligent welding technologies. First, high-precision 3D laser scanning is employed to capture the as-built geometric information of prefabricated steel components, generating dense point cloud data for construction-stage deviation detection and quantitative comparison with BIM-based design models. Based on deviation analysis, a digital construction control strategy is established to support real-time feedback, error compensation, and assembly adjustment. An engineering case study involving a complex prefabricated steel structure is conducted to validate the proposed framework. The results demonstrate that the integrated digital construction and intelligent welding approach significantly improves assembly accuracy, weld positioning precision, and construction efficiency, while reducing manual intervention and error accumulation. Overall, this study contributes to the body of knowledge by proposing a unified closed-loop digital construction paradigm that integrates geometric perception, deviation-driven decision-making, and intelligent welding execution, thereby bridging the gap between construction control and robotic fabrication in prefabricated steel structures. Full article

Cobalt–copper bimetallic oxides (CoCuO_x) show great potential for constructing high-performance micro-supercapacitors (MSCs) for micro-electronic applications. However, their poor conductivity and complex preparation procedures significantly hinder their broad applications. To address these challenges, oxygen-vacancy-modified CoCuO_x-based binder-free electrodes were fabricated using a one-step computer numerical control wire electrical discharge machining (CNCWEDM) strategy. This approach enabled the fabrication of CoCuO_x-based maze-like MSCs (CoCuMMSCs) with designable electrochemical performance, which could be simply controlled by their geometric shape and machining voltage. Subsequently, theoretical simulations were conducted for studying the effect of MSCs geometric shape on their capacitive behavior. Remarkably, the CoCuMMSCs fabricated by a machining voltage of 100 V achieved the maximum capacitance of 32.8 mF cm⁻² at 0.15 mA cm⁻². Furthermore, the CoCuMMSCs demonstrated outstanding performance at ultrahigh scan rates of up to 50,000 mV s⁻¹, exceeding by more than two orders of magnitude the values previously reported in the literature. The obtained results proved that the development of the CNCWEDM technique facilitated manufacturing CoCuMMSCs devices with excellent performance by the comprehensive utilization of oxygen-vacancy incorporation, synergistic effect of cobalt and copper oxides, binder-free electrode design, proper device construction and controllable machining voltage. The advanced CNCWEDM strategy creates a new pathway for the high-efficiency fabrication of high-performance bimetallic-oxide-based micro-electronic devices, such as MSCs, intelligent micro-sensors and micro-batteries. Full article

Bone resorption secondary to stress shielding is a leading cause of hip implant failure, primarily due to the stiffness mismatch between the femur and the prosthesis. Although anatomical stem designs generally provide improved load transfer, Dorr type C femurs often require straight stems to ensure adequate primary stability. This work presents a systematic approach to designing a straight, additively manufactured porous titanium hip stem aimed at minimizing stress shielding. The lattice architecture is customized to replicate the mechanical properties of bone based on patient-specific femoral CT scans. The performance of the resulting porous implant is numerically assessed under simplified physiological gait loading conditions. The implant behavior is evaluated through a homogenization strategy to model the lattice structure, significantly reducing the computational effort and making the methodology easily replicable. Compared to its full counterpart, the porous design achieves a significant reduction in predicted bone loss, suggesting that the proposed framework is a promising proof of concept for patient-specific implants. While further experimental validation and larger cohort studies are required, these findings highlight the potential of mechanically tunable porous structures to mitigate the stress shielding phenomenon in anatomical conditions such as Dorr type C femurs, which require straight stems. Full article

Warm-mix asphalt (WMA) technology and basalt fiber modification have been increasingly applied in road engineering. However, conventional basalt fibers often disperse unevenly and tend to agglomerate. In this study, basalt fiber powder (BFP) was incorporated into a Sasobit-based WMA system and systematically compared with matrix asphalt, Sasobit-modified WMA, conventional basalt fiber-modified WMA, and styrene butadiene styrene (SBS)-modified asphalt. Multiscale characterization—including dynamic shear rheometry (DSR), bending beam rheometry (BBR), scanning electron microscopy (SEM), and nanoindentation—was conducted to elucidate rheological behavior and interfacial micromechanical responses. The corresponding Asphalt Concrete-13 (AC-13) mixtures were further evaluated through rutting tests, low-temperature bending tests, and moisture susceptibility tests. Results demonstrate that micronized BFP achieves more homogeneous dispersion within the asphalt matrix and may promote a more effective reinforcing morphology, significantly enhancing high-temperature deformation resistance while partially mitigating the low-temperature stiffness increase induced by Sasobit. Compared with conventional basalt fiber systems, BFP shows better stress relaxation capacity and interfacial mechanical response under the tested conditions. At the mixture level, the BFP–Sasobit system showed the best overall performance, with the dynamic stability increasing by 242.2% relative to the base asphalt mixture and the residual Marshall stability reaching 92.3%, while the low-temperature flexural strain increased by 33.3%. Overall, the findings suggest that morphology-controlled micronization provides a morphology-guided enhancement strategy for Sasobit-based warm-mix asphalt by promoting coordinated improvements across the rheological, micromechanical, and mixture scales. Full article

Marine biofouling is a major global concern affecting the marine industry, the environment, and public health. The accumulation of organisms on submerged surfaces causes significant economic losses, including increased fuel consumption, higher pollutant emissions, and accelerated corrosion. Antifouling (AF) coatings with biocides are widely used to prevent this problem. However, many conventional biocides have been banned due to toxicity, creating an urgent need for environmentally friendly alternatives. In previous studies, we synthesized a gallic acid derivative and three flavonoids that showed AF activity against the settlement of mussel larvae (Mytilus galloprovincialis) together with low ecotoxicity. In the present work, to further assess their potential in marine coatings and exploit the advantages of nanocarriers in protecting and prolonging bioactive effects, these compounds were loaded into halloysite nanotubes (HNTs) and incorporated into epoxy coatings. Coatings containing the same AF compounds in free form were also prepared for comparison. HNTs were characterized by scanning electron microscopy (SEM), and compound loading was quantified by thermogravimetric (TG) analysis. The resulting composites were analyzed by SEM and dynamic water contact angle measurements. Laboratory bioassays with M. galloprovincialis larvae showed that coatings containing HNT-loaded synthetic compounds generally reduced larval settlement more effectively than the corresponding coatings containing the same compounds directly dispersed in the epoxy matrix, with values below 20% after both 15 and 40 h of exposure for the best-performing formulation. These findings highlight the novelty of the proposed HNT-based delivery strategy for nature-inspired synthetic antifoulants and support its potential for the development of effective and environmentally safer AF coatings. Full article

Electrically conductive photopolymers enable the fabrication of functional 3D-printed components with customized electrical properties, expanding additive manufacturing applications beyond traditional structural uses. This study reports the formulation and characterization of electrically conductive, water-washable photopolymer resins for masked stereolithography (MSLA) through the incorporation of nano-graphite, PEDOT:PSS, and dimethyl sulfoxide (DMSO) as a secondary dopant. Single filler and hybrid resin systems were prepared and processed via MSLA printing, then subjected to sequential thermal treatments, 25 °C curing for 48 h followed by annealing at 80 °C and 120 °C, to investigate conductivity enhancement and microstructural evolution. Electrical characterization via current–voltage (I–V) measurements, referenced to the transversal conductivity (${\sigma }_{TRA}$), showed that the hybrid formulation containing PEDOT:PSS, graphite, and DMSO achieved the highest conductivity (9.40 × 10⁻² S·cm⁻¹), outperforming PEDOT:PSS/graphite systems (2.6 × 10⁻³ S·cm⁻¹) and graphite-only samples (9.76 × 10⁻⁴ S·cm⁻¹). Conductivity increased consistently after each thermal step, indicating enhanced charge transport. Scanning electron microscopy further revealed improved filler dispersion and interconnectivity within the polymer matrix. The synergistic combination of PEDOT:PSS, graphite nanofillers, and DMSO enables MSLA printed components with tunable and reproducible electrical performance. This work demonstrates a scalable strategy for producing functional, water-washable photopolymer resins suitable for applications in sensors, soft electronics, and lightweight conductive structures. Full article

The Xi’an Beilin Museum preserves a large collection of archeological photographic negatives and films dating from the 1950s to the early 1980s. These images document significant archeological discoveries, including Tang dynasty imperial tomb murals, the excavation of the terracotta warriors, and various historical grottoes and stone carvings. As unique visual records of cultural heritage, these materials provide valuable references for studying environmental deterioration processes and for guiding conservation and restoration practices. However, long-term storage under uncontrolled environmental conditions has resulted in severe degradation of the negatives, including mold contamination, emulsion layer powdering, deformation, and partial detachment. Among these deterioration phenomena, microbial growth is particularly destructive because fungal hyphae cause light scattering and image obscuration, preventing scanning and digital archiving. In this study, mold species present on the negatives were isolated and identified using morphological observation and ITS rDNA sequence analysis. Based on the characteristics of the microbial contamination, targeted removal and restoration treatments were applied to recover the original image information. Furthermore, preventive protection strategies were implemented through the development of antifungal storage materials and protective containers. The results establish an integrated conservation approach combining microbial identification, restoration treatment, risk elimination, and preventive protection, providing a scientific basis for the long-term preservation of historical photographic archives. Full article

The incorporation of plastic waste into cement-based materials offers a promising strategy for improving sustainability; however, it is often associated with reduced mechanical performance due to weak interfacial bonding. This study investigates the effect of metakaolin on the interfacial transition zone (ITZ) and mechanical properties of cement mortars modified with polyethylene terephthalate (PET) flakes used for the partial replacement of natural sand. Mortars containing 10 and 50 wt% metakaolin (as cement replacement) and 5 vol.% PET flakes (as sand replacement) were prepared and tested after 28 days of curing. Compressive and flexural strength were evaluated, and microstructural analysis was conducted using scanning electron microscopy (SEM) with a focus on the ITZ. The results indicate that the incorporation of PET flakes leads to a reduction in mechanical properties due to the formation of a porous and weak ITZ. However, the addition of 10 wt% metakaolin significantly improved mechanical properties, enabling PET-modified mortars to achieve strength comparable to the reference mix. SEM observations revealed that metakaolin contributed to the refinement of the microstructure and reduction in ITZ porosity, which enhanced interfacial bonding and improved stress transfer between PET particles and the cement matrix. These findings demonstrate that metakaolin can effectively mitigate the negative effects associated with PET incorporation by improving the microstructural characteristics of the ITZ, thereby enhancing the performance of sustainable cement-based composites. Full article

Elastic fibers are key components of the skin extracellular matrix and are essential for maintaining skin integrity and elasticity. During skin aging, particularly photoaging, elastic fiber integrity is progressively compromised by increased elastase activity and the downregulation of elastin and scaffold-related gene expression. Therefore, effective strategies to preserve elastic fiber function should address not only elastin synthesis but also enzymatic degradation and scaffold integrity. In this study, we investigated a multitarget approach to restoring the elastic fiber network by modulating elastin production, elastase activity, and scaffold protein expression. We found that Copper Tripeptide-1 enhanced elastin expression and secretion, ethyl ferulate inhibited elastase activity, and cedrol promoted scaffold-related gene expression and microfibrillar protein restoration in dermal fibroblasts. To assess the biological relevance of this approach, the combined treatment was evaluated using UV-damaged human skin biopsy samples. This combination effectively mitigated UV-induced elastic fiber disruption and significantly improved fiber architecture, as confirmed by immunofluorescence staining and scanning electron microscopy. These findings indicate that coordinated modulation of elastin production, proteolytic protection, and scaffold reinforcement is essential for maintaining elastic fiber integrity and represents a promising approach for preserving skin elasticity during aging. Full article

Deep learning has revolutionized medical image segmentation; however, the clinical deployment of state-of-the-art models is severely impeded by their quadratic computational complexity and substantial resource demands, particularly in multisensor and multimodal imaging scenarios. In response, the field is undergoing a paradigm shift towards efficiency, characterized by the rise of linear-complexity architectures and the optimization of foundation models. This paper presents a comprehensive survey of efficient medical image segmentation methodologies, systematically reviewing the evolution from heavy, accuracy-driven models to lightweight, deployment-ready paradigms. In particular, we highlight the growing importance of efficient segmentation in multisensor medical imaging, where heterogeneous data sources such as CT, MRI, ultrasound, and infrared imaging introduce additional challenges in scalability and computational cost. We propose a novel taxonomy that categorizes these advancements into four distinct streams: (1) Mamba and State Space Models, which leverage selective scanning mechanisms to achieve global receptive fields with linear complexity; (2) Efficient Adaptation of Foundation Models, focusing on parameter-efficient fine-tuning and knowledge distillation to tailor the Segment Anything Model (SAM) for medical domains; (3) Advanced Lightweight Architectures, covering the resurgence of large-kernel CNNs and the emergence of Kolmogorov–Arnold Networks (KANs); and (4) Data-Efficient Strategies, including semi-supervised and federated learning to address annotation scarcity. Furthermore, we conduct a rigorous comparative analysis of representative algorithms on mainstream benchmarks, providing a granular evaluation of the trade-offs between segmentation accuracy and computational overhead. The survey also discusses key challenges in multisensor and multimodal settings, including modality heterogeneity, data fusion complexity, and resource constraints. Finally, we identify critical challenges and outline future research directions, serving as a roadmap for the development of next-generation efficient and scalable medical image analysis systems. Full article

Multi-Robot Systems (MRS) demand optimal spatial resource configuration to ensure systemic efficiency in mission-critical applications. Conventional paradigms rely on rigid coverage-first principles, prioritizing exhaustive spatial scanning over rapid target discovery, thereby compromising systemic responsiveness. To bridge this gap, this study proposes the Attraction of Unknown area Centroid for Exploration (AUCE) architecture, a centralized framework designed to simultaneously optimize global exploration efficiency and early-stage target discovery rates. The control framework incorporates a dynamic region planning strategy that adaptively modulates the systemic search focus based on the specific field of view of autonomous agents, alongside an optimized S-shaped trajectory pattern to establish a rigorous balance between localized path simplicity and global coverage. A versatile profit function synthesizing constant and time-varying coefficient strategies explicitly regulates the systemic trade-off between accelerated early-stage target discovery and global path cost minimization. Quantitative simulations demonstrate that AUCE significantly outperforms established methods by mitigating redundant path costs and generating a distinct front-loading effect to accelerate target localization. Subsequent evaluations confirm the framework’s computational scalability in expanded swarms and its systemic adaptability when navigating static obstacles. Full article

This paper documents the preliminary observations and applications of a Ka-band cloud radar newly installed at the Hong Kong International Airport. A special scanning strategy of the cloud radar was developed and is described in detail. The radar provides reasonable cloud base height data as compared with a co-located laser ceilometer, by identifying the lowest vertical layer with reflectivity > −30 dBZ and at least 150 m thick, filtering measurements influenced by rainfall, and removing noise with differential reflectivity thresholds. As demonstrated in a heavy rain case study, the radar provides good estimates of the cloud top height as well, consistent with the cloud liquid water content profiles from a microwave radiometer. The various applications of the cloud radar are then explored, including (1) observations of supercooled liquid water in clouds associated with a late-season tropical cyclone in the South China Sea, (2) monitoring of low visibility in light rain or mist at the airport region using reflectivity as well as Doppler velocity data, and (3) monitoring severe weather such as windshear and turbulence to be encountered by departing aircraft due to low-level jets and initiation of heavy rain, using the Doppler velocity and spectrum data. These observations demonstrated the robustness in the cloud radar in the observation of high clouds and the applicability of the radar’s Doppler velocity in plan position indicator scans under light rain situations. Potential research with the radar, such as visibility maps, turbulence intensity maps, and automatic cloud observations, is also discussed. Full article

Accurate and real-time localization is a fundamental prerequisite for the autonomous navigation of mobile robots. LiDAR–Inertial Odometry (LIO) achieves high-precision state estimation and scene reconstruction in unknown environments by effectively fusing data from LiDAR and Inertial Measurement Units (IMU). However, conventional LIO methods typically rely solely on geometric features during point cloud registration. In complex scenarios, such as outdoor unstructured or dynamic environments, these methods are often susceptible to reduced localization accuracy due to geometric degeneration or mismatches. To address these challenges, we propose SV-LIO, A Probabilistic Adaptive Semantic Voxel Map for LiDAR–Inertial Odometry, which leverages point-wise semantic information from semantic segmentation to enhance registration accuracy and system robustness. Specifically, we construct a probabilistic adaptive semantic voxel map that extracts multi-scale spatial planes attached with semantic information. Building on this representation, we employ a semantic-guided strategy for nearest-neighbor plane association between LiDAR scans and the local map, and construct semantic-weighted point-to-plane residuals to constrain pose estimation. By jointly optimizing the IMU-propagated pose prior and semantic-guided LiDAR observation constraints, SV-LIO realizes high-precision real-time state estimation and semantic scene reconstruction. Extensive experiments on the KITTI dataset demonstrate that SV-LIO achieves significant improvements in both localization accuracy compared to state-of-the-art (SOTA) LIO methods, while also constructing semantic maps capable of providing rich environmental information. Full article

Background: Wolfram syndrome (WFS) is a rare neurodegenerative disease that is genetically determined and inherited in an autosomal recessive manner. Although the first clinical symptom appearing in early childhood is diabetes mellitus, subsequent symptoms are associated with optic nerve atrophy, followed by central nervous system atrophy. Methods: The aim of the study was to analyse magnetic resonance images (MRI) of the brain in combination with single-voxel magnetic resonance spectroscopy (MRS) and to assess the copy number of mitochondrial DNA (mtDNA-CN) in 10 patients with WFS compared with a control group of 17 healthy individuals. Results: A significant decrease in the amount of selected metabolites was observed in WFS patients compared to controls in all assessed brain regions (pons, cerebellum, white matter, thalamus, and hippocampus). For three metabolites, Glutamate (Glu), Glutamate + Glutamine (Glx) and total N-acetylaspartate (TNAA), significant differences in concentrations were found between the study groups in almost all matrices evaluating specific areas of the brain (p < 0.011), with the exception of a trend toward reduced TNAA in the hippocampus (p = 0.065). In addition, patients with WFS had a significant decrease in the mitochondrial-to-nuclear DNA ratio compared to controls (p < 0.0003). Some metabolites, such as N-acetylaspartate and total N-acetylaspartate, showed strong correlations with specific regions of the visual pathway on MRI scans in patients with WFS. Conclusions: Selected brain metabolites and mtDNA-CN may become potential markers of WFS, and the results of this study may be used to define indicators for future therapeutic strategies. Full article