Debris flows represent significant landslide hazards and assessing their destructive potential requires understanding and predicting key parameters such as volume and peak discharge. However, a lack of detailed field data limits our understanding of the spatio-temporal evolution of these quantities. This study addresses these unknowns by utilizing a new suite of high-resolution measurements from 3D LiDAR scanners, which measure instantaneous velocity and flow depth fields. We analyze four debris flows at three monitoring stations along the Illgraben fan. Discharge and volume estimates derived from traditional methods are compared against a novel column-wise (CW) method, which calculates discharge by integrating area and velocity for discrete vertical columns, allowing the exclusion of deposited material (where v = 0 ). We classify the analyzed events into three types: a) fast front, b) depositional and c) wavy. For type a and b events, traditional methods overestimate event volume by >2× compared to the CW approach. This overestimation is attributed to assuming a constant or depth-dependent velocity that does not account for the decrease in velocity after the passage of the front or waves. The overestimation further results from the inclusion of deposited material (e.g. levees) in the cross-sectional area. For type c events, traditional methods underestimate peak discharge associated with wave arrivals, which reached up to 5× the front discharge. Our results align well with empirical relations between volume and peak discharge and are an important step towards obtaining more accurate values of these quantities, which are crucial for the design of check dams and retention basins. • Four debris flows were recorded at three monitoring stations along the Illgraben fan. • High-resolution 3D LiDARs enable a column-wise method to get discharge and volume. • Traditional methods overestimate volume >2× for fast front and depositional flows. • For events with surge waves, traditional approaches underestimate peak discharge. • The peak discharge of these waves can be up to 5× the front discharge. • Traditional methods fail to exclude deposited material and overestimate velocities.

Metal ions-enhanced classification of the origin and prediction of antioxidant activity of Chrysanthemum morifolium Ramat. cv. "Hangbaiju" by 3D fluorescence spectroscopy combined with chemometrics.

A navigation-guided 3D breast ultrasound scanning and reconstruction system for automated multi-lesion spatial localization and diagnosis.

Reconstructing the complex human behaviours that manifest in the Palaeolithic archaeological record remains an elusive but important challenge for capturing traces of how the human mind evolved. The roughly 1.5 million years of handaxe-making throughout the Acheulean provides a consistently preserved manifestation of hominin technological skills. Here, we analyse 1108 3D scans of handaxes from 12 sites in the Great Rift Valley of eastern Africa and the southern Levant spanning much of the Acheulean. We set out to chart the evolution of Acheulean toolmaking skill using a suite of computational 3D methods to quantify how well these handaxes have been thinned, shaped, and sharpened; traits which demand manual dexterity, planning, and hierarchical cognition. We find evidence that cognitive evolution likely played a role in improvements in handaxe-making skill, but only in the first half of the Acheulean. The most skilfully made handaxes among our sample begin to be made by about one million years ago. Any increases in cranial capacity, cognitive complexity, or manual dexterity after this point do not make a noticeable impact on how skilfully handaxes were made, and nor does raw material quality. Instead, the techno-morphology of handaxes appears to be relatively untethered from evolutionary constraints after about a million years ago, at which point we need to seek alternative explanations for handaxe variability. Above all, we show that the difficult pursuit of lowering bifacial asymmetry was more often achieved than any other skilful attribute, suggesting it was a fundamental goal of handaxe-making. Attempting to maintain 3D symmetry appears to be a common goal throughout the entire Acheulean and was routinely achieved by its second half. This capacity to consistently maintain bifacial balance while knapping was in place by at least 1.0 Ma, revealing the evolved technological abilities and hierarchical cognition of Acheulean hominins. • We analyse 1108 3D scans of Acheulean handaxes from 12 sites from the Great Rift Valley. • Computational 3D methods were used to estimate how skilfully each handaxe was made. • Hominins enacted handaxe reduction sequences with equivalent fidelity on raw materials of different qualities. • Early improvements in handaxe-making skill were likely governed by cognitive evolution, but not later improvements. • Acheulean knappers appear to be aiming to minimise bifacial asymmetry and routinely achieved this by one million years ago.

To address the issue of missing discrete element simulation parameters for sweet sorghum seeds, this study systematically calibrated their contact parameters using a method combining physical experiments and numerical simulations. First, a discrete element model of sweet sorghum seeds was constructed via 3D scanning and the multi-sphere filling method, and their basic physical parameters were measured (mean triaxial dimensions: 4.51 mm × 3.20 mm × 2.40 mm, density: 1.156 g/cm³, moisture content: 9.8%). The static friction coefficient (0.303), rolling friction coefficient (0.038), and coefficient of restitution (0.534) between the seeds and polylactic acid (PLA) material were calibrated using inclined plane sliding/rolling tests and free-fall collision tests. Based on the physical test results of the dynamic angle of repose (measured value: 34.61°), the inter-seed static friction coefficient and rolling friction coefficient were screened out as significantly influential parameters via a single factor test. A quadratic regression model was then used to establish a mapping relationship between parameters and the angle of repose, optimizing to obtain the optimal parameter combination (static friction coefficient: 0.124, rolling friction coefficient: 0.020). Simulation verification showed that under this parameter combination, the simulated dynamic angle of repose was 34.59°, with a relative error of only 0.03% compared to the actual value. The parameter calibration method established in this study features high precision and good repeatability, providing reliable parameter support for the discrete element simulation of sweet sorghum sowing equipment, and holding significant engineering application value for optimizing seed metering device design and reducing seed damage rates.

Modern forensic odontology is undergoing a digital transformation associated with the introduction of 3D technologies and the creation of specialized digital databases. These innovations radically change traditional approaches to personal identification, providing increased accuracy, speed and objectivity of analysis. The use of 3D scanning, CAD/CAM systems, computed tomography, and 3D printing makes it possible to create highly detailed digital models of the maxillofacial region that can be used to identify individuals in cases of mass disasters, criminal investigations, and when working with severely damaged remains. Despite the obvious advantages, the integration of these technologies faces challenges of standardization, implementation costs, and cybersecurity. A systematic search and analytical review of scientific literature published over the past 10 years (2014—2024) was conducted. Relevant publications were searched in international electronic databases (PubMed, Cochrane Library, Scopus, Web of Science) and in Russian scientific electronic libraries (eLibrary, CyberLeninka). The inclusion criteria were: focus on the application of 3D technologies (3D scanning, CAD/CAM, 3D printing) and/or digital databases in the context of forensic dentistry; description of specific clinical cases or research techniques; the presence of an analysis of advantages, limitations and prospects. Articles that did not contain original data were excluded, as well as publications that were not available in full text. As part of the study, 20 publications were selected from the proposed 254 that meet the specified inclusion criteria.

Natural history collections contain millions of microscope slides documenting global microscopic biodiversity, yet these materials remain largely undigitized and are vulnerable to deterioration and loss. Recent advances in slide scanner technology, originally developed for medical pathology, offer new opportunities for comprehensive digitization of slide-based collections. Here we present an optimized protocol for digitizing diverse microscope slide specimens, using the Hamamatsu NanoZoomer S20 slide scanner, developed while imaging slides at the Smithsonian National Museum of Natural History. We provide specimen-specific recommendations for scanning parameters, including scan area, focal points, Z-stack configuration, and file management workflows. Scanning times range from 41 seconds for small invertebrates to 18 minutes for palynological samples, with final compressed file sizes of 0.15-28 GB. High-resolution images (0.23 μm/pixel) captured diagnostic morphological features across all specimen types, including pollen, diatoms, radiolarians, plant and fungi tissues, and invertebrates. Using this method, we estimated that just the NMNH's paleo-palynology slide collection contains approximately 4.3 billion individual specimens, 30 times more than the current estimated size of the entire NMNH collection. Slide scanning enables 3D data capture, facilitates remote collaboration, improves reproducibility of taxonomic identifications, and creates permanent digital records that mitigate risks of physical deterioration. This protocol provides practical guidance for institutions looking to digitize slide-based collections to preserve and unlock their full research potential.

Patient-specific 3D-printed jigs improve surgical outcomes, yet their use in high tibial osteotomy (HTO) lacks widespread acceptance due to cost-related scepticism and workflow adaptation challenges. This work aims to facilitate the adoption of 3D printed patient-specific instrumentation by demonstrating the precision of jigs produced using affordable resin 3D printing. Full-length tibial CT scans were used for 3D modelling, virtual HTO planning and designing of patient-specific jigs. The jigs were 3D printed using a ∼$550 resin printer, whereas the bones were printed in a ∼$600 filament printer. Achieved vs. planned corrections were compared using the 3D scanning superimposition method. Accuracy was assessed with paired t-tests, Bland-Altman plots, linear regression, and two one-sided t-tests (TOST). For Medial Proximal Tibial Angle (MPTA), the mean error was-0.05°±1.32° with no systematic bias (p=0.912), whereas for Posterior Proximal Tibial Angle (PPTA), it was 0.57°±0.38°, having a significant over-correction (p=0.004). Strong to excellent correlations were observed (R2: 0.77 for MPTA, 0.99 for PPTA). Corrections were equivalent within ±1° (TOST: p=0.042 and p=0.007). Affordable 3D-printed jigs could achieve acceptable corrections in a preclinical simulation setting, offering cost-effective preoperative planning and surgical training.

Three-dimensional (3D) printing holds great promise for creating patient-specific rehabilitative devices. While previous studies have demonstrated that behavioral interventions can induce cortical reorganization in stroke, direct evidence that a device alone—specifically, a patient-specific 3D-printed orthotic—can modulate brain function remains lacking. This proof-of-concept case series bridges this gap by integrating a complete digital workflow—from upper limb 3D scanning to stereolithography (SLA) fabrication of a custom hand orthotic—with longitudinal multimodal functional magnetic resonance imaging (fMRI) to assess cortical reorganization in chronic stroke. Four patients participated, with two index cases wearing the 3D-printed orthosis daily for four months alongside conventional rehabilitation, while two reference patients underwent conventional therapy only. Pre- and post-intervention neuroimaging revealed consistent, orthosis-associated neural changes: enhanced activity in the primary somatosensory cortex and greater functional integration within sensorimotor networks. Structural adaptations in motor regions were also observed in both index cases. Quantitatively, the index cases exhibited functional changes in nine brain regions and structural changes in six regions, substantially exceeding the minimal changes observed in the reference cases. This work provides the first direct evidence that a 3D-printed, patient-specific orthotic can drive targeted neuroplasticity independent of intensive behavioral coaching, validating its role not merely as a passive assistive device but as an active neuromodulatory tool. It establishes a translational framework for using objective neuroimaging biomarkers to guide the development and personalization of 3D-printed interventions in neurorehabilitation.

Abstract Digital 3D city models support urban planning, simulation, and immersive applications, but common production methods such as manual CAD modelling, photogrammetry/LiDAR, and GIS-based extrusion are often slow, costly, difficult to scale, and hard to update. Procedural modelling offers a scalable alternative, yet practitioners still need clear guidance on when to use it and how to evaluate its outputs. This paper presents and evaluates a CityEngine workflow that combines open geospatial inputs with rule-based generation of road networks, blocks and parcels, and buildings. Using a commodity laptop (Intel Core i5‑3210 M, 6 GB RAM) and CityEngine, we generated three canonical morphologies (organic, raster/grid, and radial) over an area of approximately 2 km 2 under both default and dense scenarios. We report computational performance metrics, including generation time, peak RAM, CPU seconds, exported file size, and polygon count, and we complement these with output checks aimed at plausibility and visual realism for each morphology. Compared with a traditional modelling workflow, procedural generation reduces production time by one to two orders of magnitude while keeping resource use within desktop limits. Based on the case study results, we derive a decision matrix (Table 3) that compares procedural modelling with photogrammetry/LiDAR, GIS extrusion, and manual/CAD approaches across criteria such as time, scalability, update cadence, and required visual detail. This synthesis positions procedural modelling as a practical middle ground and motivates hybrid workflows that combine procedural background fabric with data-driven and manual elements when projects must balance fidelity, cost, and the frequency of updates.

BackgroundThe choroid plexus (ChP) is increasingly recognized as an essential component in the pathogenesis of cognitive impairment associated with Alzheimer's disease. DL-3-n-butylphthalide (NBP) has been confirmed to exert neuroprotective effects through multiple pathways and thereby enhance cognitive function. However, the role of NBP in the ChP volume remains unclear at present.ObjectiveThis trial aimed to explore the clinical efficacy of NBP in patients with mild cognitive impairment (MCI) and its corresponding ChP imaging characteristics.MethodsThis randomized, double-masked, placebo-controlled study included 270 MCI patients, randomly assigned in a 1:1 ratio to receive either NBP or placebo. Concurrently, all participants received clinical cognitive evaluations and 3D T1-weighted magnetic resonance imaging scans at both baseline and post-treatment phases. The objective was to evaluate the efficacy of 12-month NBP treatment on cognitive impairment and investigate the neuroimaging correlates of NBP therapy, focusing specifically on longitudinal alterations in ChP.ResultsThe NBP treatment significantly improved the cognitive symptoms of MCI patients, which was strongly correlated with the decrease in ChP volume in the drug group. Moreover, subgroup analysis indicated that cognitive enhancement was closely related to changes in ChP volume in the effective group. Mediation effect analysis revealed that ChP volume partially mediated the enhancement of cognitive symptoms in MCI patients undergoing NBP treatment.ConclusionsThis research provided evidence that NBP may improve cognitive symptoms in MCI patients by regulating changes in ChP volume, as well as offered insight into identifying early neuroimaging markers of MCI and drug targets for NBP.Clinical trial registry nameEfficacy and safety of butylphthalide on patients with mild cognitive impairment; Registration number: ChiCTR1800018362.

The potential of soft actuators for tasks in complex environments remains constrained by their lack of real-time proprioceptive capabilities. Here, this challenge is addressed through a multimaterial digital light processing (DLP) 3D printing strategy for constructing bilayer actuators integrating thermoresponsive actuation with strain-sensing functions. Two photocurable functional inks were developed and integrated into a single heterogeneous bilayer system via multimaterial DLP 3D printing. The passive layer consists of a dual-network ionoelastomer based on a polymerizable deep eutectic solvent (PDES) and carboxymethyl cellulose (CMC), with favorable mechanical properties (tensile strength ∼0.5 MPa) and sensitive strain-sensing performance (gauge factor = 2.11). The active layer is composed of a functionalized poly(N-isopropylacrylamide) hydrogel; the incorporation of a DES synergistically enhanced its mechanical performance (compressive strength ∼1.05 MPa) while enabling effective regulation of the lower critical solution temperature (LCST: 32-46 °C). Seamless integration and robust interfacial bonding between these heterogeneous materials were achieved by systematically optimizing the printing process. The resulting bilayer actuators demonstrated efficient and tunable thermoresponsive actuation, with programmable complex deformations realized through the structural design of the active layer. Furthermore, the integrated sensing capabilities enabled self-perception, allowing the actuator to monitor its own deformation states during actuation. This multimaterial DLP 3D printing strategy established a material and processing foundation for the construction of intelligent soft systems with proprioceptive capabilities.

To address the issues of insufficient seismic source energy and low prediction accuracy caused by the superposition of effective reflected signals in traditional geological advance forecasting, a high-resolution data processing method for vibroseis data has been proposed. By integrating high-resolution vibroseis technology with three-dimensional laser scanning, a high-fidelity geological advance prediction combining multimodal and long-short distance approaches has been achieved and applied to the Dangshun Tunnel. The research results demonstrate that the proposed synchrosqueezed wavelet transform correlation operation effectively resolves wavefield superposition issues and enhances the resolution of seismic records. Additionally, the joint multimodal inversion interpretation eliminates the limitations of single-method approaches, reliably restores the properties of anomalous geological bodies, and enables accurate prediction of target structures. The joint prediction results are basically consistent with excavation verification. Multi domain and multi-level detection methods are feasible in tunnel geological advance prediction. Conducting dynamic joint advance prediction is very important for improving the accuracy of prediction.

Metachromatic leukodystrophy (MLD) is arare lysosomal storage disorder characterized by progressive white matter demyelination. Quantification of demyelinated white matter on MRI-typically expressed as the demyelination load-serves as akey imaging biomarker of disease burden, enabling objective monitoring beyond visual rating scales. However, current semi-automated pipelines are limited by manual interaction, pediatric brain variability, and differences in MRI acquisition. This study aimed to develop and validate aself-configuring convolutional neural network (CNN) for automated segmentation of demyelinated white matter in MLD and to compare its performance with aconventional semi-automated method across heterogeneous MRI datasets. An nnU-Net was trained on 189 3D T1- and axial T2-weighted scans from 35MLD patients using visually controlled conventional masks as ground truth. Independent testing was performed on 130 scans (73high-resolution 3D, 57lower-resolution 2D T1-weighted) from 49patients. Performance was assessed by Dice coefficient, Bland-Altman bias, correlation with Gross Motor Function Classification (GMFC-MLD), MLD MRI severity score, longitudinal consistency, and qualitative review of outliers. CNN-based segmentation showed strong spatial agreement with the reference method, with amedian Dice coefficient of 0.82 for 3D T1-weighted scans and 0.75 for 2D scans. Volumetric bias was minimal on Bland-Altman analysis. CNN-derived demyelination load correlated significantly with motor impairment (rS = 0.38 for 3D and r = 0.56 for 2D; both p < 0.001) and showed astronger association with the MLD MRI severity score than conventional segmentation (3D: rS = 0.48 vs. 0.28; 2D: rS = 0.83 vs. 0.29). Correlations with clinical status were slightly lower (CNN: rS = 0.38, p < 0.001; conventional: (rS = 0.26, p < 0.025)) Longitudinal analyses demonstrated stable, monotonic changes over time, and qualitative review revealed fewer boundary misclassifications. The nnU-Net enables fast, reproducible, and clinically meaningful segmentation of demyelinated white matter in MLD. It generalizes across MRI protocols, correlates with motor function, and offers ascalable tool for standardized biomarker extraction in clinical trials and other leukodystrophies.

During shield tunneling, inaccurate measurements and delayed corrections can lead to deviations of the propulsion axis from the design alignment. Therefore, timely monitoring and measurement of tunnel sections after the assembly of shield construction tube segments are essential. While 3D laser scanning technology provides significant potential for tunnel section monitoring, extracting tunnel profiles in curved tunnels remains challenging, and software dedicated to post-processing point cloud data for shield tunnel profiles is limited. This paper presents an integrated method and software system for monitoring shield tunnel cross sections, including curved alignments, using 3D laser scanning data. The approach employs a vector-based extraction method that uses design data to calculate section normal vectors, avoiding reliance on central axis fitting from point clouds in curved segments. The workflow, from data acquisition to deformation visualization, is implemented within a dedicated software tool, providing a practical solution for shield tunnel profile post-processing.

Remanufacturing by casting of end-of-life (EoL) components can be challenging as it requires specific molds/cores, machinery and tooling. The use of 3D scanning technology and rapid casting processes can produce high-quality, efficient components. However, error propagation during the manufacturing process can significantly affect the dimensional accuracy of the final product. In this study, the dimensions of a case study part were evaluated at the main stages of the rapid hybrid low-pressure sand casting (LPSC) process, from the initial CAD model to the final casting, to identify the main causes of final 3D surface deviation. The casting design was optimized using coupled thermal and fluid-flow FE computations for two suitable casting orientations: horizontal (H) and vertical (V). After the 3D sand-mold printing process, an optical 3D scanner was used to extract surface data from each printed mold part. 3D surface deviations caused by the printing process were evaluated by comparing the individual mold components to their original CAD models using GOM Inspect Pro ® software. The final castings were also compared to the initial CAD models for both orientations to quantify the overall 3D surface deviations resulting from the rapid LPSC process chain, including 3D printing, liquid metal shrinkage and contraction during solidification and cooling. The results provide a foundation for improving dimensional accuracy of one-off replacement components produced by the hybrid LPSC process.

Wear resistance of composite repairs: Direct vs. semi-direct techniques in simulated oral aging.

Prototype of 3D scanner dedicated to forensic practice.

In comparison to conventional medical computed tomography (CT), cone-beam CT (CBCT) has become widely used in dental and maxillofacial applications due to its accurate 3D information, high resolution, minimal radiation dose, and affordable machine cost. In this study, we investigated the image quality and radiation doses of dental CBCT and X-ray machines developed in Thailand. Our in-house reconstruction algorithm including artifact reduction was based on GPU calculations of filtered backprojection and was significantly faster than a CPU-based algorithm. The image quality aspects for CBCT were evaluated in terms of high contrast resolution, gray value uniformity, noise, and geometric accuracy, while image quality assessment for 2D images included high contrast resolution, low contrast levels, and distortion rate. Radiation doses were measured and calculated for the dose-area product (DAP). The technical image quality and radiation dose assessment was compared with those of other commercial extraoral imaging machines. The findings demonstrate that, when compared to other units, the proposed 2D and 3D extraoral imaging systems yielded comparable technical image quality and radiation doses. Based on these results, the Thai-made 2D and 3D extraoral imaging machines appear suitable for further clinical evaluation.

This work presents a case study detailing an end-to-end workflow for reconstructing a damaged plastic component when no original design data are available. The approach integrates microscopic inspection of fracture surfaces, selective enhancement of 3D scan data, CAD-based modification of geometrically and functionally critical features, and continuous fibre-reinforced additive manufacturing. The component examined functions as a structural mounting element in an automotive lighting module, where it maintains correct alignment and provides mechanical support in service. The study concentrates on the cost-effective replacement of unique parts produced in very small batches. The results indicate that this fracture-analysis-informed reverse engineering strategy offers a practical solution for reproducing low-volume, custom, or replacement components in situations where standard manufacturing methods are not economically viable. The reconstructed part matched the geometry necessary for installation in the original assembly and successfully passed initial functional checks; however, this study did not include quantitative measurements of mechanical performance.