Search Results (10,829)

The reconstruction of complex orbitomaxillary defects requires biomaterials that can simultaneously provide structural stability, biocompatibility, and accurate restoration of facial volume and contour. While rigid polymers such as polyetheretherketone (PEEK) offer reliable mechanical support, they do not adequately replicate the viscoelastic behavior of soft tissues. This report presents a translational revision case employing a personalized hybrid biomaterial approach that combines a 3D-printed PEEK implant for structural orbital floor support with a patient-specific polydimethylsiloxane (PDMS) implant for malar volumetric augmentation. Reconstruction was planned using CT segmentation and contralateral mirroring. Patient-specific implants were subsequently designed using CAD/CAM techniques, combining a rigid PEEK implant for structural orbital support with a flexible PDMS implant for malar volumetric augmentation with complementary mechanical properties. Revision surgery included the removal of inadequately positioned titanium hardware, the release of incarcerated extraocular muscles, and the restoration of orbital anatomy and facial symmetry. Postoperative imaging demonstrated stable implant positioning and sustained orbitomaxillary stability. Despite successful anatomical reconstruction, residual functional sequelae, including strabismus related to the severity of the initial orbital trauma, persisted and were addressed separately in a staged manner, resulting in satisfactory ocular alignment and resolution of diplopia in primary gaze. This case underscores the complementary functional roles of rigid and elastic polymers and highlights the translational potential of PDMS as a permanent, patient-specific implant material for volumetric and contour restoration in craniofacial reconstruction. Full article

Multi-line-scan camera systems provide high-frequency sampling and wide field-of-view coverage, making them valuable for three-dimensional measurement and dynamic reconstruction. However, their one-dimensional projection property introduces scale ambiguity and strong parameter coupling during calibration, which limits the consistency and stability of local optimization in multi-camera systems. To address this issue, this paper proposes a global calibration method based on physical constraints and hierarchical optimization. A unified imaging and motion model is constructed by incorporating physical scale constraints and structural priors, and geometric scale information is introduced into the joint optimization to reduce scale ambiguity and parameter coupling. Parameter normalization and staged optimization are further adopted to improve numerical stability for variables of different magnitudes and enable consistent estimation of multi-camera parameters within a unified framework. Simulation and experimental results show that the method achieves stable convergence under focal-length initialization perturbation, baseline deviation, and noise interference, with a three-dimensional reconstruction error below 0.67 mm and a convergence probability of at least 99.7%. These results indicate that the proposed method effectively reduces calibration uncertainty in multi-line-scan camera systems and supports high-precision online measurement and dynamic three-dimensional perception. Full article

In ultra-wideband (UWB) synthetic aperture radar (SAR) imaging, in-band antenna standing waves (SW) can generate range ghosts, degrading image quality. To address this issue, an image-domain suppression method is proposed, leveraging the phase symmetry property (PSP) between the SW signal and its mirror SW (MSW) signal. Based on PSP, the MSW signal is rapidly constructed from the SW signal, ensuring that both share the same target region but exhibit different ghost regions. PSP is further extended to the image domain. Specifically, the SW-induced phase is extracted in the wavenumber domain. Based on the PSP, this phase is then used to construct the MSW signal, which exhibits a phase spectrum that is symmetric to that of the SW signal with respect to the origin. The MSW image is subsequently fused with the original SAR image, thereby effectively suppressing SW-induced ghosts. The experimental results demonstrate that the proposed method significantly mitigates ghosting while preserving the amplitude and structural integrity of the main signal, thereby enhancing overall imaging quality. Full article

Background/Objectives: Magnetic nanoparticles have emerged as powerful tools for biomedical imaging, targeted drug delivery, and hyperthermia therapy. Magnetic particle imaging (MPI) is among the most promising technologies built around its properties: a radiation-free, quantitative tomographic modality that detects superparamagnetic iron oxide nanoparticles (SPIONs) directly against a biologically silent background. This review synthesizes MPI’s physical principles, nanoparticle design strategies, and preclinical applications within the broader landscape of magnetic material engineering for biomedical use. Methods: A systematic review was conducted covering MPI signal generation and image reconstruction, nanoparticle core synthesis and surface coating approaches, and preclinical applications, spanning cell tracking, oncological imaging, vascular perfusion, neuroimaging, and MPI-guided theranostics. Studies were selected to provide quantitative benchmarks and direct comparisons with competing modalities where available. Results: MPI delivers signal-to-background ratios above 1000:1, iron-mass linearity at R² ≥ 0.99, regardless of tissue depth, and acquisition rates up to 46 volumes per second. Tracer architecture—encompassing single-core particles, multicore nanoflowers, and stimuli-responsive cluster designs—is the primary determinant of sensitivity, environmental robustness, and theranostic capability. Preclinical results include detection of cell populations in the low thousands, earlier ischaemia identification than diffusion-weighted MRI, real-time drug release quantification, and spatially confined tumour hyperthermia. Three translational bottlenecks are identified: the absence of a clinically approved tracer with optimal relaxation dynamics, hardware performance losses when scaling to human-bore systems, and overestimation of passive tumour accumulation in murine models. Conclusions: MPI illustrates how progress in magnetic material design directly expands clinical imaging and theranostic possibilities. Successful translation will require indication-driven, interdisciplinary development that integrates materials science, scanner engineering, and regulatory strategy in parallel. Full article

In the deep mining of metal mines, the stability of pillar–backfill composite materials (PBCMs) under cyclic loading is crucial for preventing dynamic disasters in goafs. Although previous studies have extensively investigated backfill materials under static loading, the damage evolution mechanism of PBCM under cyclic disturbance—particularly the coupled effects of pillar width and disturbance amplitude—remains insufficiently understood. To address this gap, this study explored the mechanical properties and damage evolution of PBCM under cyclic loading using an indoor testing system. Tests were conducted on composite specimens with varying pillar widths (6, 9, 12, 15 mm) and disturbance amplitudes (3, 4, 5 MPa), combined with acoustic emission (AE), digital image correlation (DIC), and scanning electron microscopy (SEM). Results show that wide-pillar specimens (≥12 mm) exhibit significantly improved bearing strength and deformation modulus, with increases of nearly 90% and over 40%, respectively, compared to narrow-pillar specimens. Notably, wide pillars maintain over 95% strength stability even under 5 MPa cyclic disturbances. Narrow pillars are prone to localized damage concentration with high-frequency AE signals and shear failure, while wide pillars exhibit uniform damage development. Failure morphology confirms that pillar size dictates failure mode: narrow pillars undergo sudden through failure, whereas wide pillars display progressive composite failure, with fewer damage-induced cavities and directional crack propagation along maximum shear stress. These findings provide a theoretical basis for stope structure optimization and dynamic disaster prevention in deep mines. Full article

To address the accumulation of construction and demolition waste (W&D), this study recycled it into regenerated fine aggregate and prepared 3D-printed mortars with replacement ratios ranging from 0% to 100%. The mechanical properties of hardened specimens were tested, and the degradation mechanisms of mechanical performance were investigated through SEM, MIP, and microhardness analysis. The carbon emissions of the materials were evaluated. The results indicated that while the 3D-printed mortar exhibited excellent buildability, its compressive strength, flexural strength, and interlayer bond strength gradually decreased with increasing replacement ratio. MIP results showed that as the replacement ratio of the W&D increased from 0% to 100%, the total porosity of the 3D-printed specimens significantly increased from 14.7433% to 27.5903%. SEM and microhardness images confirmed severe ITZ deterioration, and the average ITZ width increased from 31 to 79 μm. As the W&D replacement ratio increased from 0% to 100%, the total GWP decreased from 0.4043 to 0.3800 kg CO₂-eq/kg mortar. Maximizing the utilization of W&D is key to achieving efficient utilization of solid waste. Considering printability, mechanical performance, interlayer behavior, microstructural characteristics, and environmental impact in a comprehensive manner, the 80% W&D replacement ratio can be regarded as a relatively balanced and promising selection. This work not only suggests the technical feasibility of recycling W&D in 3D printing mortar, but also proposes a sustainable pathway to reduce carbon emissions in construction. Full article

Recently, lead-free metal halide perovskite variant nanocrystals (NCs) have emerged as promising alternatives to their lead-based counterparts, with tunable optoelectronic properties achievable through structural and compositional engineering. Their tunable bandgaps, near-unity quantum yields, solution-processable synthesis routes, and intrinsic environmental benignity render them attractive candidates for a broad range of optoelectronic applications. This review comprehensively summarizes recent advances in perovskite-derived NCs, including diverse synthetic strategies, as well as structural and compositional engineering approaches for optimizing their photophysical properties. Additionally, this review critically discusses the emerging applications of lead-free metal halide perovskite variants, such as solid-state lighting, high-sensitivity photodetection, and advanced radiation imaging. This review aims to provide in-depth insight into the structure–composition–performance relationship of lead-free perovskite variant NCs and pave the way for next-generation eco-friendly optoelectronic materials and devices. Full article

Conventional spatial frequency domain imaging (SFDI) based optical property inversion is inefficient, while deep learning methods suffer from heavy reliance on large-scale real datasets. To address this contradiction, a simulation-driven approach for subsurface fruit bruise discrimination was proposed. An SFDI simulation environment was built with Blender to generate 800 paired datasets of diffuse reflectance images and optical transport coefficients, overcoming the high cost and long cycle of real dataset acquisition. We designed the CBAM-GAN-U-Net model and adopted surface profile correction in the prediction method to eliminate curved surface-induced non-planar distortion, with the whole method validated on liquid phantoms, green apples and crown pears. This prediction method achieved high accuracy in predicting the reduced scattering coefficient μ_s′, with NMAE of 0.021 ± 0.007 (phantoms), 0.039 ± 0.012 (severely bruised green apples) and 0.044 ± 0.015 (severely bruised crown pears), outperforming U-Net and GANPOP. Based on the predicted μ_s′, a discrimination strategy combining coefficient of variation, mean ratio and receiver operating characteristic (ROC) curve analysis was adopted, attaining 100% accuracy for non-bruised/bruised fruit discrimination, with misclassification rates of 6% (green apples) and 8% (crown pears) for mild/severe bruise differentiation. This method enables accurate subsurface fruit bruise detection, providing a reliable technical solution for the fruit and vegetable industry and helping reduce postharvest supply chain losses. Full article

Feijoa fruits are known for their pronounced post-harvest ripening. Phytopathogen-infected specimens pose a significant risk to storage stability and overall fruit quality. Early detection and removal of defective fruits during the initial storage stages are critical for maintaining market value and preventing the spread of disease. In this study, we analyze how the multispectral reflectance properties of the feijoa surface change in response to various defects. ‘Superba’ cultivar fruits were selected, including healthy controls and samples exhibiting bruises, anthracnose, stink bug damage, tissue suberization, and gray mold. Biochemical analyses were conducted to measure the levels of organic acids, sugars, ascorbic acid, and total polyphenols. Multispectral imaging was performed with a 12-channel camera operating in the 400–1000 nm wavelength range. Results showed that the fruits affected by gray mold had the lowest concentrations of malic and citric acids but the highest levels of succinic acid. Fruits with anthracnose or insect damage exhibited the highest sugar content. Distinct differences in spectral reflectance were observed between healthy and affected areas of fruit. Based on these findings, an image processing algorithm for defective fruit detection was developed. Full article

Geological hazards are characterized by their sudden occurrence, high destructiveness, and wide spatial impact. In particular, landslides and debris flows triggered by earthquakes and intense rainfall often lead to severe casualties and substantial property losses. Therefore, the rapid delineation of affected areas is crucial for disaster assessment and post-disaster reconstruction. To this end, several geohazard datasets have been developed from remote sensing imagery, focusing on specific regions, disaster types, and data sources, providing valuable support for geohazard detection and risk assessment. Our study addresses the diversity of real-world geological disasters in terms of their types, causes, and spatial distribution and constructs the Composite Geological Hazards Dataset (CGHD), a dual-temporal geohazard dataset that enhances generalisation and practical applicability. CGHD incorporates pre- and post-disaster remote sensing images of 14 landslide and debris flow events that occurred worldwide between 2017 and 2024, collected using four remote sensing platforms and encompassing multiple spatial scales and land-cover categories. The affected areas varied significantly in size and shape, with land-cover types including roads, buildings, vegetation, farmland, and water bodies. This resulted in 3963 pairs of pre- and post-disaster images, each with a size of 1024 × 1024 pixels. We validated the reliability of the CGHD through experiments with nine change-detection models and further evaluated its generalisation capability using an unseen dataset. The experimental results demonstrate that CGHD achieves high recognition accuracy and strong generalisation across diverse geographic environments, providing comprehensive data support for intelligent geohazard recognition and disaster assessment. Full article

Currently, silicone is a common material used in medical research and biomedical applications. This research aims to characterize extra-soft platinum silicone (shore A 00 50) and compare its mechanical behavior with that of the human thoracic aorta. By developing molds to get samples, for tensile testing according to ISO 37 and ASTM D412, and for compression testing according to ISO 7743 and ASTM D575, using a universal testing machine for tensile and compression tests, and applying digital image correlation (DIC) algorithms, the mechanical properties were characterized in a total of 10 tensile samples and 6 compression samples. The results show an ultimate tensile strength up to 1.77 ± 0.12 MPa in the ASTM samples and 2.10 ± 0.14 MPa in the ISO samples; alongside an incremental elastic module of 80.08 ± 7.94 kPa and 117.98 ± 11.39 kPa; finally, an elongation at break of 1114.49 ± 76.77% and 936.08 ± 63.56%, corresponding to the values of a healthy thoracic aorta. The replica of the thoracic aorta in this material was developed by a brush method, with a thickness of 1.82 mm, a length from the aortic arch to the descending aorta of 200.49 mm, and diameters of 20.45 and 16.05 mm for the ascending and descending aorta, respectively. Full article

Acoustic emission (AE) and digital image correlation (DIC) techniques enable real-time capture of damage signals and full-field deformation at anchored rock–concrete interfaces under shear loading, which is critical for quantitatively characterizing freeze–thaw (F-T) degradation and preventing geological disasters in cold regions. This study synchronously monitored full-shear-process AE signals using a broadband AE system (150 kHz resonant frequency, 5 MS/s sampling) and captured high-precision full-field deformation via a 5-megapixel monocular DIC system (25 fps). F-T cycle and direct shear tests were conducted on sandstone–concrete anchored specimens with varying F-T cycles and anchor depths to investigate their effects on shear mechanical properties, AE characteristics and failure modes. Results show that AE peak ring count first decreases by 44.9% then increases by 56.5%, while cumulative ring count exhibits a three-stage evolution. Shear crack proportion first decreases then increases, with tensile failure remaining dominant throughout. DIC reveals that F-T cycles shift failure from crack propagation to surface delamination and interface slip, while different anchor depths induce distinct failure patterns. This study confirms that AE and DIC can accurately characterize F-T degradation, providing a reliable non-destructive monitoring method for cold-region anchorage engineering. Full article

Agriculture, as a basis of sustainable development, faces increasing pressure to meet rising global food demands while confronting the increasing impacts of climate change. Precision agriculture offers a data-driven approach to address these challenges by optimizing input use, improving productivity, and reducing environmental impacts. Sensor technologies play a critical role in smart and precision agriculture, offering high-resolution spatial and temporal insights into soil conditions, plant development and environmental conditions. This review highlights the current state and future potential of various sensor and imaging systems, particularly their role in monitoring soil properties, crop nutrition, plant health and detecting biotic and abiotic stressors. Special attention is given to accessible paper-based and printed electrochemical devices for on-site soil and plant analysis, as well as active handheld multispectral sensors designed for real-time canopy assessment. The integration of sensor-derived data with predictive models, IoT networks and decision-support tools enables more precise, site-specific management, improves input efficiency and supports climate-resilient agricultural practices. By examining the capabilities, limitations and future potential of these sensing platforms, this review highlights their growing importance in advancing sustainable intensification and strengthening crop production. Full article

Biochemical detection is fundamental to various scientific disciplines, yet conventional methods still face inherent bottlenecks in achieving rapid, ultrasensitive, and simultaneous multi-target analysis. Terahertz (THz) waves, characterized by their unique spectral fingerprinting capabilities and non-destructive properties, have emerged as a compelling platform for advanced biochemical sensing. This review outlines the evolution of THz biochemical sensing over the past two decades, tracing its progression from passive identification toward intelligent perception. We structure this technological trajectory around four core themes: sensitivity enhancement, specific recognition, multi-target visualization, and system intelligence. We first evaluate the fundamental limitations of direct detection techniques, such as THz time-domain spectroscopy (THz-TDS). Building on this, we examine how metamaterial-assisted architectures utilize high-quality-factor resonances to achieve trace-level detection, pushing the limits of detection (LOD) down to the ng/mL or even pg/mL scale, and how surface chemical functionalization provides a molecular lock mechanism for selective targeting in complex samples. Furthermore, we highlight the paradigm shift from single-point spectral measurements to spatially resolved multi-target imaging using pixelated metasurfaces. Finally, the review addresses emerging directions, including dynamically tunable intelligent metasurfaces, multimodal on-chip integration platforms, and the growing integration of artificial intelligence (AI) in inverse design and data interpretation, which achieves classification accuracies exceeding 95% even in complex matrices. By synthesizing these developments, this review provides a comprehensive perspective on the future trajectory of THz sensing technologies. Full article

Ensuring the durability and safety of modern infrastructure critically depends on the quality and strength of concrete. The Ultrasonic Pulse Velocity (UPV) method is a widely used non-destructive testing technique for evaluating concrete properties; however, factors such as aggregate size distribution, compaction methods, and surface quality can significantly influence UPV results and their correlation with compressive strength. This study investigates the effects of different aggregate sizes and an innovative vibration-assisted compaction method—developed using piezoelectric (PZT) transducers—on the mechanical, ultrasonic, and surface properties of concrete. Four distinct aggregate size distributions were employed to produce sixteen concrete specimens with constant mix proportions. Unlike conventional low-frequency, high-power vibration practices, a high-frequency (40 kHz), low-power (120 W) vibration protocol was applied through PZT elements placed within the molds to enhance compaction and reduce entrapped air. Experimental results indicated that the heaviest specimen (7.13 kg) was the medium-aggregate sample compacted using tamping and rodding methods. The highest UPV value (4143 m/s) was obtained from the coarse-aggregate specimen subjected to three minutes of vibration. In contrast, the best compressive strength performance (22.73 MPa) was observed in the medium-aggregate specimen without any vibration treatment. The findings revealed that both aggregate size and advanced vibration techniques have significant effects on the mechanical properties, ultrasonic response, and surface quality of concrete. In addition, a proof-of-concept portable surface-finishing prototype consisting of a steel plate instrumented with multiple PZT transducers was developed, and preliminary trials qualitatively suggested improved surface leveling when applied in contact with the concrete surface. Surface roughness was quantified via image processing (Light Map 150 and Specular Map 150). The rough-area fraction decreased from ~29.8% in the untreated specimen to ~4.3% after ultrasonic application, indicating a marked improvement in surface leveling and overall surface quality. The results indicate that the applied PZT vibration protocol did not improve compressive strength; in several cases, particularly under prolonged excitation, a reduction in strength was observed. In contrast, a significant improvement in surface quality was achieved, with the rough-area fraction decreasing from approximately 29.8% to 4.3%. However, due to the limited number of specimens, the findings should be interpreted as preliminary. Overall, the method appears more promising as a surface enhancement technique rather than a direct alternative to conventional compaction methods. Full article