Search Results (12,050)

The rapid deployment of 5G networks and the proliferation of Internet of Things (IoT) devices have significantly increased the complexity of urban electromagnetic radiation (EMR) environments. Conventional ground-based monitoring systems are spatially limited and unable to provide three-dimensional field characterization. This paper proposes an integrated IoT–UAV framework for high-resolution EMR monitoring, spatial reconstruction, and intelligent source classification. A four-layer architecture combining distributed sensing, edge computing, cloud analytics, and visualization is developed. A formal electromagnetic propagation model is introduced to ensure consistency between broadband exposure measurements and frequency-selective spectral analysis. A CNN–LSTM architecture is implemented for spectral–temporal source classification, achieving 95% validation accuracy across five EMR categories. Simulation-based validation demonstrates up to an eightfold improvement in spatial coverage compared to fixed ground networks while maintaining a practical anomaly detection threshold of −55 dBm in the spectrum-analysis RF chain. The proposed framework establishes a mathematically consistent and practically deployable solution for next-generation EMR monitoring systems. Full article

Anti-corrosive coatings are among the most widely used methods for corrosion protection. Zero-dimensional (0D) carbon nanomaterials have attracted increasing attention due to their advantages, such as small size, high specific surface area, ease of surface functionalization, and strong interfacial regulation capability, which enable enhanced barrier properties, densification, and multifunctional protection of coatings. However, existing reviews have largely focused on the application of 2D carbon nanomaterials in anti-corrosive coatings, with a lack of systematic summaries on 0D carbon nanomaterials, particularly comprehensive reviews that combine quantitative bibliometric analysis with qualitative content analysis. To address this gap, this review employs a combined approach of bibliometric analysis and content analysis to systematically summarize the research progress of three typical types of 0D carbon nanomaterials, including nanodiamonds, fullerenes, and carbon dots, in the field of corrosion protective coatings. The quantitative analysis is conducted using CiteSpace 6.4 R.2 to reveal publication trends, research hotspots, and frontier evolution in this field, while the qualitative analysis selects representative studies to summarize application systems, performance characteristics, and underlying mechanisms. On this basis, the key challenges currently faced are identified, and future research directions are proposed. This review provides a systematic reference for the material design, mechanistic understanding, and engineering application of 0D carbon nanomaterial-based anti-corrosive coatings. Full article

Three-dimensional (3D) printing is increasingly used for the fabrication of definitive crowns; however, whether specific post-curing hardware is mandatory for clinical success remains a practical concern. This study provided a practical comparison evaluating the effect of two post-curing units on the biaxial flexural strength (BFS), Weibull modulus (m), Martens hardness (HM), indentation modulus (EIT), water sorption (WSP), and water solubility (WSL) of 3D-printed resins for permanent crowns, compared with a conventional resin composite. A total of 200 specimens were fabricated from two 3D-printed resins (Permanent Crown™ and CrownTec™) and a conventional resin composite (Filtek Universal Restorative™) used as a control. The 3D-printed specimens were post-cured using either a Formcure or an Otoflash G171 unit. WSP and WSL were measured after 90 days of water ageing, while BFS, HM, and EIT were evaluated after 24 h of storage using standardised methods. All materials exhibited WSP and WSL values within ISO limits, with the control group showing significantly higher values and superior mechanical properties. Among the 3D-printed resins, post-curing significantly affected only HM and EIT for Permanent Crown™ resin, with no significant differences in BFS. Overall, the tested 3D-printed resins demonstrated high processing stability across different curing protocols, suggesting that clinical performance remains consistent regardless of the post-curing unit used. Full article

Background: Endoscopic sacrocolpopexy (ESC) is a widely performed procedure for pelvic organ prolapse, with laparoscopic sacrocolpopexy (LSC) and robotic-assisted sacrocolpopexy (RSC) approaches. However, suturing to the anterior longitudinal ligament at the sacral promontory carries a risk of massive hemorrhage due to presacral vascular injury. This study aimed to determine the frequency of presacral venous variations considered clinically relevant during suturing at the promontory and to explore their association with perioperative outcomes using contrast-enhanced three-dimensional computed tomography (3D-CT). Methods: Among 319 consecutive ESC cases performed between 2014 and 2025, 265 patients who underwent preoperative contrast-enhanced CT were retrospectively analyzed in this single-center cohort study. Two vascular findings were defined as clinically significant: (1) anomalous drainage of the internal iliac vein into the contralateral common iliac vein and (2) a clearly visualized median sacral vein on 3D reconstruction. The clinical impact of vascular abnormalities was evaluated using surgical time, blood loss, and perioperative complication rates as indicators. Student’s t-test was used for comparing continuous variables, and the chi-squared test was used for comparing categorical variables. The data for this study were retrospectively collected from electronic medical records, anonymized, and then analyzed. Results: Anomalous internal iliac vein drainage was observed in 11.3% (30/265), and a visible median sacral vein was observed in 10.2% (27/265). Overall, 17.7% (47/265, CI: 13.2–22.2%) of patients had at least one clinically significant variation. There were no significant differences between the groups in terms of age, parity, BMI, operative time, blood loss, or perioperative complication rates. No cases required transfusion. Conclusions: Clinically significant presacral vein mutations were present in approximately 1 in 6 patients. The main findings of this study are that clinically significant presacral vascular mutations are relatively frequent (17.7%) in ESC and that there was no significant difference in perioperative outcomes between patients with and without vascular mutations. Clinically relevant presacral vascular variations are relatively common in ESC. Preoperative contrast-enhanced 3D-CT may support risk assessment and surgical planning. Full article

Skid resistance is a critical functional property of asphalt pavements and is strongly influenced by surface topography. However, existing studies often rely on limited texture indicators, making it difficult to comprehensively characterize pavement surface morphology and directly relate it to braking performance. In this study, the surface topography of eight asphalt mixtures, including six porous asphalt concrete (PAC-13) mixtures with different air-void contents, one stone mastic asphalt (SMA-13) mixture, and one asphalt concrete (AC-13) mixture, was characterized using a high-precision three-dimensional laser scanner. The acquired point-cloud data were analyzed using one-dimensional, two-dimensional, three-dimensional, and ISO 25178 surface parameters. Correlation analysis was first used to remove redundant indicators, and principal component analysis was then performed to reduce dimensionality. Three principal components explaining 67.45%, 9.94%, and 6.42% of the total variance, respectively, were extracted and combined into a comprehensive surface topography index (F). The results showed that F effectively distinguished different mixture types and PAC surfaces with different air-void levels. Field validation was further conducted on PAC, SMA, and AC pavements in Xi’an, China, and a regression model relating F to the braking distance from 60 km/h to 0 km/h (D60) was established, with an R² of 0.8864. The proposed index provides a multidimensional and practical approach for asphalt pavement surface characterization and offers a useful basis for skid-resistance evaluation and braking distance prediction. Full article

The Yellow Sea is an important offshore area in China, and the accurate prediction of its seawater temperature is of great significance for marine environmental monitoring and climate adaptation management. However, existing research on predicting the three-dimensional (3D) temperature field in the Yellow Sea is scarce and insufficiently accurate. This study proposes a TCN-U-Net++ fusion model to reconstruct the Yellow Sea temperature field using remote sensing satellite data and SODA reanalysis data, while considering the influence of a series of factors, including wind (USSW and VSSW), absolute bathymetric data (BAT), sea surface height anomaly (SSHA), latitude (LAT), longitude (LON), solar radiation (SR), surface runoff (SRO), and precipitation (P). The results show that the model can accurately capture the temporal and spatial distribution characteristics of the temperature field in the Yellow Sea. The results indicate that the deviations from SODA are generally within 2 °C, with errors being approximately 45% lower than those of other models, while the prediction errors relative to Argo and voyage observations are mostly within 1 °C, further demonstrating the accuracy and robustness of the proposed model. In addition, the predictions of the Yellow Sea Cold Water Mass (CWM) are highly consistent with SODA in terms of their evolution and key characteristic parameters. Specifically, the maximum deviation in core temperature is only 0.3 °C, and the difference in its spatial extent is less than 1%. The results demonstrate that TCN-U-Net++ effectively enhances the accuracy of 3D sea temperature prediction in the Yellow Sea, providing technical support for temperature monitoring, ecological early warning, and climate change research. Full article

Background/Objectives: This study analyzed intraoperative parameters, structural safety, and morphofunctional outcomes of vitreoretinal procedures performed using a conventional operating microscope versus a three-dimensional (3D) heads-up digital visualization system. Methods: A retrospective single-surgeon case series included 248 eyes undergoing pars plana vitrectomy for epiretinal membrane (ERM), macular hole (MH), or rhegmatogenous retinal detachment (RRD). Patients were divided into conventional microscope (n = 122) and 3D heads-up (n = 126) groups. Primary outcomes included surgical duration, endoillumination intensity, best-corrected visual acuity (BCVA), anatomical success, and complications over a 6-month follow-up. Results: The 3D cohort showed a significantly shorter global median surgical duration (50.0 vs. 60.0 min, p = 0.001). Multivariate regression confirmed the 3D system as an independent predictor of shorter operative time globally (p = 0.011). After adjusting for baseline disease severity imbalances in the ERM subgroup, the 3D system maintained an independent reduction in surgical duration of 5.5 min (p = 0.044). The 3D system also required significantly lower endoillumination across all procedures (p ≤ 0.002). Anatomical success rates were high and comparable across indications. Both groups achieved similar and significant visual improvement at 6 months (p = 0.120). Structural safety biomarkers (SANFL, DONFL) and complication rates remained comparable. Conclusions: The 3D heads-up visualization system demonstrated comparable functional and anatomical outcomes to conventional microscopy across standard vitreoretinal procedures. It allows for surgery under significantly lower light conditions and demonstrates the potential to optimize operative time, particularly in ERM peeling. Furthermore, it maintains an equivalent structural safety profile to conventional surgery. Full article

Humidity sensors are widely employed in diverse fields such as healthcare, agriculture, construction, and the storage of food and pharmaceuticals. In these areas, accurate and reliable humidity monitoring is essential to ensure appropriate environmental conditions and prevent material degradation or device malfunction. Recently, organic–inorganic hybrid materials have emerged as promising platforms for humidity sensing, as they integrate the complementary properties of both organic and inorganic components. Notably, hybrid materials with three-dimensional architectures have received growing attention owing to their large specific surface area, which affords enhanced reactivity and improved sensing performance. In this review, recent progress in humidity sensors based on organic–inorganic hybrid materials is summarized, with particular emphasis on three-dimensional hybrid architectures. The analysis suggests that 3D hybrid architectures can enhance sensing performance by improving water adsorption and charge transport pathways. Overall, the potential and significance of organic–inorganic hybrid architectures for the development of high-performance humidity sensors are critically discussed. Full article

The COVID-19 pandemic highlighted the need for effective disinfection strategies in order to minimize human exposure and reduce the risk of contagion in indoor environments. Ultraviolet-C (UV-C) irradiation has proven to be an effective solution for inactivating a wide range of pathogens. However, traditional fixed UV-C systems suffer from limited coverage and lack operational flexibility. To address these limitations, this paper proposes an augmented reality (AR)-based teleoperation framework for an omnidirectional mobile robot equipped with a UV-C disinfection light. Unlike traditional toolchain integrations, our framework synergizes immersive spatial visualization of a reconstructed environment, operator-guided waypoint-based remote navigation, and real-time interaction with the disinfection payload in a single operational workflow. The system is implemented using a ROSMASTER X3 Plus robotic platform, which generates a three-dimensional representation of the environment through visual simultaneous localization and mapping using RTAB-Map. The result is a 3D map that is imported into the Unity game engine and deployed to a Meta Quest 3 head-mounted display, enabling immersive visualization and interaction. Communication between the AR interface and the robotic system is achieved via the ROS-TCP-Connection, allowing real-time data exchange and remote robot control. Through the AR interface, the operator can navigate the robot within the scanned environment and activate the UV-C light. Experimental validation conducted in a classroom demonstrates the feasibility of the proposed approach and shows measurable reductions in surface microbial load. These results indicate that our system-level integration of AR-assisted teleoperation with mobile UV-C robotics represents a feasible proof-of-concept for flexible, operator-guided disinfection of indoor spaces. Full article

Recent advances in edge computing and Tiny Machine Learning (TinyML) have enabled the deployment of artificial intelligence models directly on microcontrollers with extremely limited computational and memory resources. In this context, this work presents the design, implementation, and validation of a real-time cardiac arrhythmia classification system based on a quantized one-dimensional convolutional neural network (1D-CNN), deployed on an 8-bit Arduino UNO microcontroller. The proposed system integrates end-to-end processing, including ECG signal acquisition using a low-cost AD8232 analog front-end, signal preprocessing, heartbeat segmentation, classification, and real-time visualization on an OLED display. The model was trained and evaluated using the MIT-BIH Arrhythmia Database, considering a reduced three-class problem (Normal, Ventricular, and Supraventricular) to meet the constraints of ultra-low-cost hardware deployment. Under benchmark conditions, the quantized model achieved an accuracy of 97.6%, with a memory footprint below 24 KB and an average inference time of 200 ms per heartbeat, enabling real-time operation on a resource-constrained microcontroller. Real-time experiments were conducted using signals acquired from healthy volunteers to validate system functionality, although no annotated ground truth was available for these recordings, and therefore no diagnostic performance was derived from them. The results demonstrate the feasibility of deploying lightweight deep learning models on ultra-constrained embedded systems using the TinyML paradigm, implemented using TensorFlow 2.15 and TensorFlow Lite. This work should be interpreted as a proof-of-concept platform that highlights the trade-off between classification performance and hardware limitations, providing a foundation for future development of low-cost cardiac monitoring technologies in resource-limited environments. Full article

Near-infrared hyperspectral imaging (NIR-HSI) is widely used as a non-destructive technique for evaluating internal fruit quality; however, reliable pixel-wise visualization remains challenging due to geometry-induced spectral distortions and the lack of statistically interpretable validation criteria. This study proposes an integrated framework for three-dimensional visualization of soluble solids content (SSC) across the entire surface of strawberries using NIR-HSI combined with shape-aware spectral correction and pixel-level reliability assessment. Two complementary imaging systems—a line-scan system and a rotation-scan system—were used to acquire hyperspectral and 3D shape data. Fruit height and surface orientation were incorporated into spectral preprocessing to reduce illumination and curvature effects. Partial least squares regression (PLSR) models were developed using region-of-interest-averaged spectra and applied to pixel-wise SSC mapping. To assess the statistical validity of pixel-level predictions, an imaging reliability index based on the Mahalanobis distance in the PLS score space was introduced. The results show that models with high sample-level accuracy do not necessarily produce reliable SSC maps, whereas reliability-based model selection improves image interpretability. This framework enables consistent three-dimensional SSC visualization and is applicable to hyperspectral imaging of internal fruit attributes. Full article

Additive manufacturing (AM) enables the fabrication of complex three-dimensional components with embedded internal flow channels, but the as-built inner surfaces often exhibit high roughness and poor surface-quality uniformity, particularly at non-coplanar corner regions such as sharp bends and junctions. Conventional abrasive flow machining (AFM) can improve the overall surface finish of such channels; however, corner regions commonly remain weak-removal zones because of local flow stagnation and insufficient abrasive action. To address this limitation, this study proposes a six-degree-of-freedom (6-DOF) robotic-arm-assisted liquid metal-driven abrasive flow (LM-AF) polishing strategy in which robotic pose regulation is used to guide the liquid metal droplet to designated corner regions while preserving its responsiveness to the electric field. Numerical simulations and conventional AFM experiments on S-shaped and M-shaped spatial channels were first conducted to identify the corner regions as the primary sources of polishing non-uniformity. A robotic posture-control framework was then established through manipulator kinematics, point-cloud-based flow-direction identification, and Rodrigues-matrix-based pose transformation. On this basis, localized secondary polishing was experimentally performed on an S-shaped channel using an AC electric-field-driven liquid-metal abrasive system. The results show that corner-region roughness was significantly reduced and approached the straight-channel benchmark after secondary polishing, demonstrating a marked improvement in inner-surface uniformity. This study provides a practical route for targeted compensation polishing in complex three-dimensional internal channels and offers a new framework for robotic-assisted post-processing of AM-fabricated flow paths. Full article

The impact of short-distance lateral shield tunneling threatens the safety of operational high-speed railways (HSRs). To address the engineering challenge of “how to select isolation pile density under fixed cost constraints,” this study focuses on the Xi’an Metro shield tunnel section passing laterally adjacent to the Daxi and Zhengxi Passenger Dedicated Lines. Under the constraint of identical total economic costs, two isolation pile schemes—low-density and high-density—were established to investigate the control patterns of different densities on HSR bridge piles and surrounding ground surface deformation. A three-dimensional (3D) numerical model was developed for the lateral shield tunneling process. Combined with field-measured data, numerical simulations were conducted for corresponding construction stages to analyze the disturbance effects of shield tunneling on HSR piers and the surrounding ground, as well as the deformation restraint performance of isolation piles. The results indicate that the high-density isolation pile scheme (pile spacing: 2.0 m; pile length: 22 m) provides superior control compared to the low-density scheme (pile spacing: 4 m; pile length: 28 m). Following single- and double-track excavation, the vertical displacement of HSR piers was reduced by 0.6 mm and 1.1 mm, respectively—a reduction of 40–74%. Furthermore, the pier displacement along the depth direction shifted from non-uniform to relatively uniform. The difference in surface settlement between the two schemes was only 0.2 mm, suggesting that isolation pile density has a marginal impact on ground deformation. The horizontal displacement of high-density isolation piles stabilized at 1.7–1.9 mm, with vertical heave ranging from 1.2 to 1.4 mm. The lateral displacement profile exhibited a regular “double-C outward expansion” shape, which is better suited to the characteristics of water-rich sand layers. Initial excavation causes significant disturbance to the original strata, necessitating enhanced stress field protection measures. The high-density scheme is recommended for engineering applications, as it achieves optimal control of bridge pile deformation under cost constraints and meets regulatory specifications. Full article

Fueled by the push for “More than Moore”, three-dimensional integrated circuits (3D ICs) have become a backbone of next-generation electronics. Their complex architectures place unprecedented demands on etching technologies, which must now deliver atomic precision, stringent high-aspect-ratio (HAR) control, and virtually damage-free profiles. Meeting these challenges requires metrology capable of true 3D, quantitative analysis at the nanoscale. Atomic force microscopy (AFM) has proven essential in this regard, offering non-destructive, sub-nanometer characterization that other techniques cannot provide. This review systematically examines AFM’s pivotal role in advancing key etching processes for 3D ICs, including deep reactive ion etching of through-silicon vias (TSVs), atomic layer etching (ALE), and cryogenic plasma etching. We detail AFM’s unique contributions to quantifying sidewall roughness, verifying etch-per-cycle rates, and assessing surface damage. We also discuss how recent innovations, such as tilting-AFM, HAR probes, and automated inline systems, are overcoming traditional barriers in throughput and access to sidewalls and deep trenches. Looking forward, the integration of AFM with optical metrology, machine learning, and multi-scale modeling opens a path toward truly autonomous process control and optimization. As such, AFM stands as an indispensable tool for developing and refining the etching processes that underpin next-generation 3D semiconductor manufacturing. Full article

Gelatin–alginate composite hydrogels are some of the most prevalent bioinks used for extrusion-based three-dimensional (3D) bioprinting because of their combined bioactivity and ability to ionically crosslink. Ionically crosslinked gelatin–alginate constructs containing human bone marrow–derived mesenchymal stem cells (hBM-MSCs) were characterised over time under standardised in vitro conditions to assess physicochemical properties and resultant cell behaviour. Water uptake and degradation were quantified over time in phosphate-buffered saline (PBS) and collagenase type II media for up to 21 days. Cell viability and metabolic activity were quantified, and osteogenic gene expression (RUNX2, COL1A1, OCN) was assessed. Raman spectroscopy and compressive mechanical characterisation were performed. Collagen and glycosaminoglycan-related peaks were observed from extracellular matrix (ECM)-associated components, with an increased presence of protein-associated signatures later in culture. Hydrogels displayed nonlinear elastic behaviour with increased stress after longer incubation times, suggesting no degradation of mechanical integrity over the duration of the study. Hydrogels experienced rapid hydration followed by decreased swelling over time, with a maximum swelling ratio at 24 h. Degradation rates significantly increased over longer incubation times (p < 0.001) and in collagenase media compared to PBS (p < 0.001). Observed differences were likely due to both ion-exchange-mediated network disassembly and the dissolution of gelatin components. Cell metabolic activity decreased under osteogenic culture conditions, while changes in osteogenic marker expression were sequential, suggesting a transition from proliferation to early osteogenic commitment in this 3D system. This work provides both physicochemical and biological characterisation of a commonly utilised gelatin–alginate bioink system, to provide future optimisations within the field of extrusion-based bone tissue engineering, a reproducible baseline for future optimisation of bioink systems in extrusion-based bone tissue engineering. Full article