Search Results (1,048)

The development of high-performance MEMS-based eye trackers, crucial for next-generation medical diagnostics and human–computer interfaces, is often hampered by the mechanical instability and time-consuming recalibration of physical prototypes. To address this bottleneck, we present the development and rigorous validation of a high-fidelity digital twin (DT) designed to accelerate the design–test–refine cycle. We conducted a comparative study of a physical MEMS scanning system and its corresponding digital twin using a USAF 1951 test target under both static and dynamic conditions. Our analysis reveals that the DT accurately replicates the physical system’s behavior, showing a geometric discrepancy of <30 µm and a matching feature shift (1 µm error) caused by tracking dynamics. Crucially, the DT effectively removes mechanical vibration artifacts, enabling the precise analysis of system parameters in a controlled virtual environment. The validated model was then used to develop a pupil detection algorithm that achieved an accuracy of 1.80 arc minutes, a result that surpasses the performance of a widely used commercial system in our comparative tests. This work establishes a validated methodology for using digital twins in the rapid prototyping and optimization of complex optical systems, paving the way for faster development of critical healthcare technologies. Full article

Urban heritage documentation often separates 3D data acquisition from immersive interaction, limiting both accuracy and user impact. This study develops and validates an end-to-end workflow that integrates UAV photogrammetry with terrestrial LiDAR and deploys the fused model in a VR environment. Applied to Piazza Vittorio Emanuele II in Rovigo, Italy, the approach achieves centimetre-level registration, completes roofs and upper façades that ground scanning alone cannot capture, and produces stable, high-fidelity assets suitable for real-time interaction. Effectiveness is assessed through a three-layer evaluation framework encompassing vision, behavior, and cognition. Eye-tracking heatmaps and scanpaths show that attention shifts from dispersed viewing to concentrated focus on landmarks and panels. Locomotion traces reveal a transition from diffuse roaming to edge-anchored strategies, with stronger reliance on low-visibility zones for spatial judgment. Post-VR interviews confirm improved spatial comprehension, stronger recognition of cultural values, and enhanced conservation intentions. The results demonstrate that UAV-enabled completeness directly influences how users perceive, navigate, and interpret heritage spaces in VR. The workflow is cost-effective, replicable, and transferable, offering a practical model for under-resourced heritage sites. More broadly, it provides a methodological template for linking drone-based data acquisition to measurable cognitive and cultural outcomes in immersive heritage applications. Full article

Selective laser melting (SLM) builds metal parts layer by layer by locally melting powder with a fine laser beam, generating complex, geometry-dependent temperature gradients that govern density, microstructure, defects, and residual stresses. Resolving these gradients with high-fidelity finite-element (FE) models is prohibitively slow because the temperature field must be evaluated at dense points along every scan track across multiple layers, while the laser spot is orders of magnitude smaller than typical layer dimensions. This study replaces FE analysis with a deep neural network that predicts the end-of-build temperature field orders of magnitude faster. A benchmark part containing characteristic shape features is introduced to supply diverse training cases, and a novel control-volume-based geometry-abstraction scheme encodes arbitrary workpiece shapes into compact, learnable descriptors. Thermal simulation data from the benchmark train the network, which then predicts the residual temperature field of an unseen, geometrically dissimilar part with a mean absolute error of ~10 K and a mean relative error of ~1% across 500–1300 K. The approach thus offers a rapid, accurate surrogate for FE simulations, enabling efficient temperature-driven optimization of SLM process parameters and part designs. Full article

During deep coalbed methane (CBM) drilling, wellbore stability is significantly influenced by the interaction between drilling fluid and coal rock. However, quantitative data on mechanical degradation under long-term high-temperature and high-pressure conditions are lacking. This study subjected coal cores to immersion in field-formula drilling fluid at 60 °C and 10.5 MPa for 0–30 days, followed by uniaxial and triaxial compression tests under confining pressures of 0/5/10/20 MPa. The fracture evolution was tracked using micro-indentation (µ-indentation), nuclear magnetic resonance (NMR), and scanning electron microscopy (SEM), establishing a relationship between water absorption and strength. The results indicate a sharp decline in mechanical parameters within the first 5 days, after which they stabilized. Uniaxial compressive strength decreased from 36.85 MPa to 22.0 MPa (−40%), elastic modulus from 1.93 GPa to 1.07 GPa (−44%), cohesion from 14.5 MPa to 5.9 MPa (−59%), and internal friction angle from 24.9° to 19.8° (−20%). Even under 20 MPa confining pressure after 30 days, the strength loss reached 43%. Water absorption increased from 6.1% to 7.9%, showing a linear negative correlation with strength, with the slope increasing from −171 MPa/% (no confining pressure) to −808 MPa/% (20 MPa confining pressure). The matrix elastic modulus remained stable at 3.5–3.9 GPa, and mineral composition remained unchanged, confirming that the degradation was due to hydraulic wedging and lubrication of fractures rather than matrix damage. These quantitative thresholds provide direct evidence for predicting wellbore stability in deep CBM drilling. Full article

To address the issue of insufficient contrast in conventional X-ray absorption imaging for biological soft tissues and weakly absorbing materials, this paper proposes a beam tracking X-ray phase-contrast imaging system using a conventional X-ray source. A periodic pinhole array mask is placed between the X-ray source and the sample to spatially modulate the X-ray beam, dividing it into multiple independent sub-beams. Each sub-beam is deflected due to the modulation effect of the sample, resulting in slight positional shifts in the intensity patterns formed on the detector. The experiments employ an X-ray source with a 400 μm focal spot and use a two-dimensional step-scanning approach to acquire image sequences of various samples. The experimental results show that this method can extract the edge profile and structural changes in the samples to some extent, and it demonstrates good contrast and detail recovery under weak absorption conditions. These results suggest that this method has certain application potential in material inspection, non-destructive testing, and related fields. Full article

Spinocerebellar ataxia type 2 (SCA2) is a neurodegenerative disorder marked by progressive brainstem and cerebellar atrophy, leading to gait ataxia. Quantifying this atrophy in magnetic resonance imaging (MRI) is critical for tracking disease progression in both symptomatic patients and preclinical subjects. However, manual segmentation of brainstem subregions (mesencephalon, pons, and medulla) is time-consuming and prone to human error. This work presents an automated deep learning framework to assess brainstem atrophy in SCA2. Using T1-weighted MRI scans from patients, preclinical carriers, and healthy controls, a U-shaped convolutional neural network (CNN) was trained to segment brainstem subregions and quantify volume loss. The model achieved strong agreement with manual segmentations, significantly outperforming four U-Net-based benchmarks (mean Dice scores: whole brainstem 0.96 vs. 0.93–0.95, pons 0.96 vs. 0.91–0.94, mesencephalon 0.96 vs. 0.89–0.93, and medulla 0.95 vs. 0.91–0.93). Results revealed severe atrophy in preclinical and symptomatic cohorts, with pons volumes reduced by nearly 50% compared to controls (p < 0.001). The mesencephalon and medulla showed milder degeneration, underscoring regional vulnerability differences. This automated approach enables rapid, precise assessment of brainstem atrophy, advancing early diagnosis and monitoring in SCA2. Full article

Hastelloy X exhibits outstanding thermal fatigue resistance, making it a promising material for repairing 50CrVA landing gear via directed energy deposition (DED). However, the substantial differences in composition and thermophysical properties between 50CrVA and Hastelloy X pose challenges by affecting interfacial microstructure and surface quality. This study investigates the effect of DED process parameters (laser power p, powder feed rate f, scanning speed v, and overlap rate) on the dilution ratio (η), microscopic morphology, surface flatness (ζ), and porosity of Hastelloy X claddings on a 50CrVA substrate. An optimization methodology integrating thermal–flow coupled simulation models and orthogonal experiments is developed to fabricate high-quality claddings. Furthermore, the corrosion–wear performance of the claddings is evaluated. The results indicate that the η of a single track increases with higher p or lower f, while it first increases and then decreases with the increase in v. Ablation marks tend to occur at excessive p or insufficient f, while low v causes surface ripples. The ζ of a single layer initially improves and subsequently deteriorates with increasing overlap rate. Porosity is significantly influenced by p and f. The optimal p, f, v, and overlap rate are 1600 W, 2.4 g/min, 240 mm/min, and 55%, respectively. The wear resistance of the cladding is nearly identical to that of the substrate, while corrosion resistance is significantly improved. This work provides a theoretical foundation for high-performance repair of 50CrVA landing gear in aircraft. Full article

Controlled demolition is a critical engineering practice that enables the safe and efficient dismantling of structures while minimizing risks to the surrounding environment. This study presents, for the first time, a detailed, structured framework for understanding the fundamental principles of controlled demolition by outlining key procedures, methodologies, and directions for future research. Through original, carefully designed charts and full-scale numerical simulations, including two 23-story building scenarios with different delay and blasting sequences, this paper provides real-life insights into the effects of floor-to-floor versus axis-by-axis delays on structural collapse behavior, debris spread, and toppling control. Beyond traditional techniques, this study explores how emerging technologies, such as real-time structural monitoring via object tracking, LiDAR scanning, and Unmanned Aerial Vehicle (UAV)-based inspections, can be further advanced through the integration of artificial intelligence (AI). The potential Deep learning (DL) and Machine learning (ML)-based applications of tools like Convolutional Neural Network (CNN)-based digital twins, YOLO object detection, and XGBoost classifiers are highlighted as promising avenues for future research. These technologies could support real-time decision-making, automation, and risk assessment in demolition scenarios. Furthermore, vision-language models such as SAM and Grounding DINO are discussed as enabling technologies for real-time risk assessment, anomaly detection, and adaptive control. By sharing insights from full-scale observations and proposing a forward-looking analytical framework, this work lays a foundation for intelligent and resilient demolition practices. Full article

This study presents the development and evaluation of an Augmented Reality (AR)-based training system aimed at improving patient setup accuracy in radiation therapy. Leveraging Microsoft HoloLens 2, the system provides an immersive environment for medical staff to enhance their understanding of patient setup procedures. High-resolution 3D anatomical models were reconstructed from CT scans using 3D Slicer, while Luma AI was employed to rapidly capture complete body surface models. Due to limitations in each method—such as missing extremities or back surfaces—Blender was used to merge the models, improving completeness and anatomical fidelity. The AR application was developed in Unity, employing spatial anchors and 125 × 125 mm² QR code markers to stabilize and align virtual models in real space. System accuracy testing demonstrated that QR code tracking achieved millimeter-level variation, with an expanded uncertainty of ±2.74 mm. Training trials for setup showed larger deviations in the X (left–right), Y (up-down), and Z (front-back) axes at the centimeter scale. This meant that we were able to quantify the user’s patient setup skills. While QR code positioning was relatively stable, manual placement of markers and the absence of real-time verification contributed to these errors. The system offers a radiation-free and interactive platform for training, enhancing spatial awareness and procedural skills. Future work will focus on improving tracking stability, optimizing the workflow, and integrating real-time feedback to move toward clinical applicability. Full article

Laser direct energy deposition (LDED) has been widely employed in surface modification and remanufacturing. Achieving high-precision geometries and superior mechanical properties in cladding layers remains a persistent research focus. In this study, an Fe-based alloy was deposited on an AISI 1045 substrate via a wide-beam laser cladding system. Single-track multi-layer samples were prepared with varying z-increment (Z_d), interlayer dwell time (T_I) and laser scanning speed (V) values. The geometry, microstructure, microhardness and wear resistance of the samples were analyzed. Experimental results showed that an estimated Z_d can ensure a constant standoff distance of the laser head and resulting geometric accuracy improvement. Planar grains form at the layer–substrate bonding interface and transition to columnar grains adjacently, while dendrites and equiaxed grains are distributed in the middle and top regions of the layer. The coating layer exhibits much better wear resistance and friction properties than the substrate. The cooling rate can be substantially increased by either raising V or prolonging T_I, resulting in refined grain structures and enhanced microhardness. Real-time monitoring and controlling the mean cooling rate have been demonstrated to be effective strategies for enhancing cladding layer performance. Full article

This work provides the first demonstration of FFTCCV as a dual-purpose method, serving both as a real-time diagnostic tool and as a phase- and morphology-engineering strategy. By adjusting the scan rate, FFTCCV directs the crystallographic evolution of Ni (OH)₂ on Ni foam—stabilizing α-nanoflakes at 0.7 V·s⁻¹ and β-platelets at 0.007 V·s⁻¹—while simultaneously enabling electrode-resolved ΔQ tracking and predictive state-of-health (SoH) monitoring. This approach enabled the precise regulation of electrode morphology and phase composition, yielding high areal capacitance (546.5 mF·cm⁻² at 5 mA·cm⁻²) with ~75% retention after 3000 cycles. These improvements advance the development of high-performance micro-supercapacitors, facilitating their integration into wearable and miniaturized devices where compact and durable energy storage is required. Beyond performance enhancement, FFTCCV also enabled continuous monitoring of capacitance during extended operation (up to 40,000 s). By recording both anodic and cathodic responses, the method provided time-resolved insights into device stability and revealed characteristic signatures of electrode degradation, phase transitions, and morphological changes. Such detection allows recognition of early failure pathways that are not accessible through conventional testing. This monitoring capability functions as an embedded health sensor, offering a pathway for predictive diagnosis of supercapacitor failure. Such functionality is particularly important for energy-driven actuators and smart materials, where uninterrupted operation and preventive maintenance are critical. FFTCCV therefore provides a scalable strategy for developing energy-autonomous microsystems with improved performance and real-time state-of-health monitoring. Full article

This study examines how architectural expertise shapes visual perception, extending the “Seeing for Speaking” hypothesis into a non-linguistic domain. Specifically, it investigates whether architectural training influences unconscious visual processing of architectural content. Using eye-tracking, 48 architects and 48 laypeople freely viewed 15 still images of built, mixed, and natural environments. Visual behavior was analyzed using Shannon’s entropy scores based on dwell times within 16 × 16 grids during the first six seconds of viewing. Results revealed distinct visual attention patterns between groups. Architects showed lower entropy, indicating more focused and systematic gaze behavior, and their attention was consistently drawn to built structures. In contrast, laypeople exhibited more variable and less organized scanning patterns, with greater individual differences. Moreover, architects demonstrated higher intra-group similarity in their gaze behavior, suggesting a shared attentional schema shaped by professional training. These findings highlight that domain-specific expertise deeply influences perceptual processing, resulting in systematic and efficient attention allocation. Entropy-based metrics proved effective in capturing these differences, offering a robust tool for quantifying expert vs. non-expert visual strategies in architectural cognition. The visual patterns exhibited by architects are interpreted to reflect a “Grammar of Space”, i.e., a structured way of visually parsing spatial elements. Full article

Carbon fibre reinforced polymer (CFRP) is a composite material known for its light weight and exceptional durability, composed of carbon fibres within a polymer matrix. Despite its high cost, CFRP is favoured for its outstanding strength-to-weight ratio and rigidity. It is widely used in the aerospace industry and ship superstructures, among others. These components often rub against different materials in various structural and mechanical assemblies. These interactions typically occur where metallic fasteners, bearings, hinges, and sliding components interface with CFRP parts causing, for example, fretting wear. The main novelty of the present study consists of a systematic comparison of titanium (Ti6Al4V) and aluminium (AA2024-T6) alloy spheres under identical test conditions, evaluating how each material interacts with different CFRP configurations. CFRP was tested against titanium and aluminium alloy spheres as counterbodies under reciprocating sliding conditions. Different contact conditions (applied loads) were used for tribotests. The wear volume and coefficient of friction were determined, as well as the wear mechanisms. Different analytical techniques were employed, such as profilometry, optical microscopy (OM), and scanning electron microscopy (SEM/EDS), to characterise the wear tracks. It was possible to determine the coefficient of friction as well as the wear rate on both CFRP specimens and their respective counterbodies. It was found that the coefficient of friction (CoF) depends on load, fibre orientation, and counterbody material, ranging from 0.14 to 0.29. The lowest wear rate coefficient was observed for CFRP sliding against titanium alloy in the layer configuration, at 1.48 × 10⁻¹³ mm³/N·m. In contrast, aluminium alloy counterbodies experienced significantly higher wear, with a maximum wear rate of 6.88 × 10⁻⁵ mm³/N·m. Wear volume increased with load across all conditions and was highest for the CFRP cross-section against aluminium alloy. Full article

Background: Chronic Recurrent Multifocal Osteomyelitis (CRMO) is a rare auto-inflammatory condition affecting the growing skeleton. The standard first-line treatment of high-dose NSAIDs (non-steroidal anti-inflammatory drugs) is adequate only in a subset of patients. The American College of Rheumatology Consensus Guidelines suggest considering bisphosphonates in a certain category of patients based on evidence from a handful of case series reporting the outcome of pamidronate use. Aims: The aim of this study was to report the efficacy and safety of bisphosphonate, predominantly zoledronate, use in CRMO. Methods: A retrospective cohort study of children with CRMO receiving bisphosphonates was conducted between January 2008 and September 2023 at a single tertiary referral centre. We described the baseline characteristics; clinical indication, regimen and response to bisphosphonate treatment; changes in bone mineral density (BMD) and spine remodelling on dual-energy X-ray absorptiometry (DXA) scans; and safety data. Results: During the study period, 64 (72%, n = 46 females) patients with CRMO with a median age at diagnosis of 10 years (range: 3 to 16 years) were identified. Approximately 31% (n = 20) received either pamidronate (n = 2) or zoledronate (n = 14) or both (n = 4) due to changes in local protocols. The most frequent indications for bisphosphonate use were refractory pain [55%, n = 11/20], pain + spine involvement [35% (n = 7/20)] and spine involvement only [10% (n = 2)]. Prior to bisphosphonate therapy, 100% took regular NSAIDs (n = 19/19), 21% (n = 4/19) used opioids, 47% (n = 9/19) received oral steroid courses, and 10% (n = 2/19) received methotrexate. The median age at bisphosphonate treatment initiation was 12 years (range 6–18 years), and the duration of treatment was 2 years (range: 6 months to 5 years). Improvement in pain was reported by 88% of patients (n= 15/17, 1 was excluded as they had not started treatment yet). All non-responders (n = 2/17;) to bisphosphonate therapy were later recognised clinically to have pain amplification syndrome and were referred to the chronic pain multi-disciplinary team. This correlated to the complete treatment de-escalation of opioids (n = 3/3; 1 was excluded as they had not yet started treatment), steroids (n = 8/8) and methotrexate (n = 2/2). NSAIDs were discontinued in 44% of patients (n = 7 of 16; 1 was excluded due to missing data, and 3 were excluded due to NSAID intolerance). The median first-year increase in the LS BMAD (lumbar spine bone mineral apparent density) Z-score was +1.35, and that in the TBLH BMD (total body less head bone mineral density) Z-score was +0.7 (n = 11). Subsequently, median average annual increases in the LS BMAD Z-score of +0.65 and in the TBLH BMD Z-score of +0.45 (n = 5) were recorded. Around 30% of patients (n = 6) required treatment modification (dose reduction, frequency reduction or cessation) due to a rapid escalation in BMD. There were no fractures documented due to raised BMD. Evidence of spine remodelling on DXA vertebral fracture assessment was seen in 38% of patients with spinal lesions (n = 3 of 8). There was no radiological evidence of improvement in any vertebra plana lesion. First-phase reactions (pyrexia) were reported universally in patients who received bisphosphonates, but none were significant requiring hospitalisation. Conclusions: Similar to pamidronate, zoledronate with an advantageous dosing regimen is well tolerated and effective in improving pain and enabling the de-escalation of adjunctive therapy in CRMO. This is the first report tracking changes in BMD and spinal remodelling in response to zoledronate in CRMO patients. Spinal remodelling is minimal in vertebra plana lesions. Bone density monitoring and personalisation of the bisphosphonate dose and regimen are strongly recommended to avoid overtreatment. Full article

Background/Objectives: Over the past twenty years, there has been a rapid increase in studies aimed at comprehending how cells communicate with each other via Extracellular Vesicles (EVs), accompanied by a heightened interest in plant-derived extracellular vesicles due to their potential relevance in dietary supplementation and therapeutic applications. However, there is a limited amount of research on extracellular vesicles derived from mushrooms (MDEVs). Among edible mushrooms, Pleurotus eryngii is peculiar due to its flavor and interesting nutritional profiling. It also produces a wide array of secondary metabolites including biologically active compounds with many health-promoting benefits such as anticancer, antioxidant, antitumor, antiviral, antibacterial, antidiabetic, and anti-hypercholesteremic activities. The aim of this work has been to isolate EVs from the fruiting body and mycelium of P. eryngii in order to investigate their potential applications as nutraceuticals. Methods: MDEVs were isolated by differential and density gradient centrifugation, characterized by Nanoparticle Tracking Analysis (NTA), Scanning Electron Microscopy (SEM) and immunoblotting, and subjected to metabolomic and phenolic profiling. Their antioxidant potential was assessed through in vitro radical scavenging (DPPH, ABTS) and metal-reducing (CUPRAC, FRAP) assays. Results: The findings suggest that mycelium-derived EVs may represent a valuable source of high-quality MDEVs, which exhibited promising antioxidant properties in all assays conducted, particularly in radical scavenging assays. Conclusions: These results highlight the potential of P. eryngii mycelium-derived EVs as a novel natural source of bioactive compounds, paving the way for future applications in nutraceutical and therapeutic fields. Full article