Local 3D Research Articles

Highly Precise Prediction of Micro- and Supra-pKa Based on 3D Descriptors Integrating Non-Covalent Interactions.

Accurate pKa prediction is crucial for understanding proton dissociation in complex molecular systems. However, existing models often face challenges in addressing subtle stereoelectronic effects and conformational flexibility. This study presents H-SPOC, a localized 3D descriptor that captures covalent and non-covalent interactions and incorporates solvent effects to predict site-specific pKavalues accurately. H-SPOC was validated on multiple benchmark datasets, including SAMPL6, SAMPL7, and SAMPL8, where it outperformed state-of-the-art methods. H-SPOC also proved versatile across various applications, including aspirin's non-equilibrium conformations, glycine's microstate distributions, and the stereoelectronic anomalies of Janus Sponge and Meldrum's Acid. It addressed challenging supra-pKapredictions in crystalline environments and accurately correlated pKa with reaction rates, selectivity, tautomerism, and pharmacokinetic properties. With its chemically intuitive design and computational efficiency, H-SPOC provides an efficient framework for rapid and precise micro- and supra-pKapredictions, offering significant potential in drug discovery, catalysis, and materials science.

Highly Precise Prediction of Micro‐ and Supra‐pKa Based on 3D Descriptors Integrating Non‐Covalent Interactions

Accurate pKa prediction is crucial for understanding proton dissociation in complex molecular systems. However, existing models often face challenges in addressing subtle stereoelectronic effects and conformational flexibility. This study presents H‐SPOC, a localized 3D descriptor that captures covalent and non‐covalent interactions and incorporates solvent effects to predict site‐specific pKa values accurately. H‐SPOC was validated on multiple benchmark datasets, including SAMPL6, SAMPL7, and SAMPL8, where it outperformed state‐of‐the‐art methods. H‐SPOC also proved versatile across various applications, including aspirin's non‐equilibrium conformations, glycine's microstate distributions, and the stereoelectronic anomalies of Janus Sponge and Meldrum's Acid. It addressed challenging supra‐pKa predictions in crystalline environments and accurately correlated pKa with reaction rates, selectivity, tautomerism, and pharmacokinetic properties. With its chemically intuitive design and computational efficiency, H‐SPOC provides an efficient framework for rapid and precise micro‐ and supra‐pKa predictions, offering significant potential in drug discovery, catalysis, and materials science.

Monte Carlo post-processing for radiation hydro simulations of accreting planets in protoplanetary disks

This paper is part of a series investigating the observational appearance of planets accreting from their nascent protoplanetary disk (PPD). We evaluate the differences between gas temperature distributions determined in our radiation hydrodynamical (RHD) simulations and those recalculated via post-processing with a Monte Carlo (MC) radiative transport (RT) scheme. Our MCRT simulations were performed for global PPD models, each composed of a local 3D high-resolution RHD model embedded in an axisymmetric global disk simulation. We report the level of agreement between the two approaches and point out several caveats that prevent a perfect match between the temperature distributions with our respective methods of choice. Overall, the level of agreement is high, with a typical discrepancy between the RHD and MCRT temperatures of the high-resolution region of only about 10 percent. The largest differences were found close to the disk photosphere, at the transition layer between optically dense and thin regions, as well as in the far-out regions of the PPD, occasionally exceeding values of 40 percent. We identify several reasons for these discrepancies, which are mostly related to general features of typical radiative transfer solvers used in hydrodynamical simulations (angle- and frequency-averaging and ignored scattering) and MCRT methods (ignored internal energy advection and compression and expansion work). This provides a clear pathway to reduce systematic temperature inaccuracies in future works. Based on MCRT simulations, we finally determined the expected error in flux estimates, both for the entire PPD and for planets accreting gas from their ambient disk, independently of the amount of gas piling up in the Hill sphere and the used model resolution.

Identification of global main cable line shape parameters of suspension bridges based on local 3D point cloud

Main cable line shape measurement and parameter identification are a critical task in the construction monitoring and service maintenance of suspension bridges. 3D LiDAR scanning can simultaneously obtain the coordinates of multiple points on the target, offering high accuracy and efficiency. As a result, it is expected to be used in applications requiring rapid, large-scale measurements, such as main cable line shape measurement for suspension bridges. However, due to the large span and tall main towers of suspension bridges, the LiDAR field of view often encounters obstructions, making it difficult to obtain high-quality point clouds for the entire bridge. The collected point clouds are typically unevenly distributed and of poor quality. Therefore, LiDAR is used to monitor the local cable line shape. This paper proposes an innovative non-uniform sampling method that adjusts the sampling density based on the main cable’s rate of change. Additionally, the Random Sample Consensus (RANSAC) algorithm, the ordinary least squares, and center-of-mass calibration are applied to identify and optimize the geometric parameters of the cross-section point cloud of the main cable. Given the strong design prior information available during suspension bridge construction, Bayesian theory is applied to predict and adjust the global line shape of the main cable. The study shows that using LiDAR for cable point cloud measurement enables rapid acquisition of high-precision point cloud data, significantly enhancing data collection efficiency. The method proposed in this paper offers advantages such as highly automated, low risk, low cost, and sustainability, making it suitable for green monitoring throughout the entire main cable construction process.

Local 2D Simulations of the Ignition of a Helium Shell Detonation on a White Dwarf by an Impacting Stream

Local 2D Simulations of the Ignition of a Helium Shell Detonation on a White Dwarf by an Impacting Stream

A Graph Neural Network-Based Approach to XANES Data Analysis.

The determination of three-dimensional structures (3D structures) is crucial for understanding the correlation between the structural attributes of materials and their functional performance. X-ray absorption near edge structure (XANES) is an indispensable tool to characterize the atomic-scale local 3D structure of the system. Here, we present an approach to simulate XANES based on a customized 3D graph neural network (3DGNN) model, XAS3Dabs, which takes directly the 3D structure of the system as input, and the inherent relation between the fine structure of spectrum and local geometry is considered during the model construction. It turns out to be faster than the traditional XANES fitting method when the simulation approach and XANES optimization algorithm are combined to fit the 3D structure of the given system. The geometric features of the system are included in the weighted message passing block of XAS3Dabs and their importance is investigated. XAS3Dabs model demonstrates superior accuracy in XANES prediction compared to most machine learning models. By extracting graphs constituted by edges related to the absorbing atom, our model reduces redundant information, thereby not only enhancing the model's performance but also improving its robustness across different hyperparameters. XAS3Dabs model can be generalized to simulate the spectra for the systems with the absorber having the designed absorption edge so as to meet the expectations of online data processing. The method is expected to be the key part of the online 3D structure analysis framework for the XAS-related beamlines of high-energy photon source (HEPS) now under construction.

A Local Adversarial Attack with a Maximum Aggregated Region Sparseness Strategy for 3D Objects.

The increasing reliance on deep neural network-based object detection models in various applications has raised significant security concerns due to their vulnerability to adversarial attacks. In physical 3D environments, existing adversarial attacks that target object detection (3D-AE) face significant challenges. These attacks often require large and dispersed modifications to objects, making them easily noticeable and reducing their effectiveness in real-world scenarios. To maximize the attack effectiveness, large and dispersed attack camouflages are often employed, which makes the camouflages overly conspicuous and reduces their visual stealth. The core issue is how to use minimal and concentrated camouflage to maximize the attack effect. Addressing this, our research focuses on developing more subtle and efficient attack methods that can better evade detection in practical settings. Based on these principles, this paper proposes a local 3D attack method driven by a Maximum Aggregated Region Sparseness (MARS) strategy. In simpler terms, our approach strategically concentrates the attack modifications to specific areas to enhance effectiveness while maintaining stealth. To maximize the aggregation of attack-camouflaged regions, an aggregation regularization term is designed to constrain the mask aggregation matrix based on the face-adjacency relationships. To minimize the attack camouflage regions, a sparseness regularization is designed to make the mask weights tend toward a U-shaped distribution and limit extreme values. Additionally, neural rendering is used to obtain gradient-propagating multi-angle augmented data and suppress the model's detection to locate universal critical decision regions from multiple angles. These technical strategies ensure that the adversarial modifications remain effective across different viewpoints and conditions. We test the attack effectiveness of different region selection strategies. On the CARLA dataset, the average attack efficiency of attacking the YOLOv3 and v5 series networks reaches 1.724, which represents an improvement of 0.986 (134%) compared to baseline methods. These results demonstrate a significant enhancement in attack performance, highlighting the potential risks to real-world object detection systems. The experimental results demonstrate that our attack method achieves both stealth and aggressiveness from different viewpoints. Furthermore, we explore the transferability of the decision regions. The results indicate that our method can be effectively combined with different texture optimization methods, with the average precision decreasing by 0.488 and 0.662 across different networks, which indicates a strong attack effectiveness.

Quantification of optical lensing by cellular structures in the living human eye

Cells and other microscopic phase objects can be visualized in the living retina, non-invasively, using non-confocal light detection schemes in adaptive optics scanning light ophthalmoscopes (AOSLOs). There is not yet widespread agreement regarding the origin of image contrast, nor the best way to render multichannel images. Here, we present data to support the interpretation that variations in the intensity of non-confocal images approximate a direct linear mapping of the prismatic deflection of the scanned beam. We advance a simple geometric framework in which local 2D image gradients are used to estimate the spherocylindrical refractive power for each element of the tissue. This framework combines all available information from the non-confocal image channels simultaneously, reducing noise and directional bias. We show that image derivatives can be computed with a scalable, separable gradient operator that minimizes directional errors; this further mitigates noise and directional bias as compared with previous filtering approaches. Strategies to render the output of split-detector gradient operations have been recently described for the visualization of immune cells, blood flow, and photoreceptors; our framework encompasses these methods as rendering astigmatic refractive power. In addition to astigmatic power, we advocate the use of the mean spherical equivalent power, which appears to minimize artifacts even for highly directional micro-structures such as immune cell processes. We highlight examples of positive, negative, and astigmatic power that match expectations according to the known refractive indices and geometries of the relevant structures (for example, a blood vessel filled with plasma acts as a negatively powered cylindrical lens). The examples highlight the benefits of the proposed scheme for the visualization of diverse phase objects including rod and cone inner segments, immune cells near the inner limiting membrane, flowing blood cells, the intravascular cell-free layer, and anatomical details of the vessel wall.

End of the world brane dynamics in holographic 4d N = 4 SU(N) with 3d N = 2 boundary conditions

We consider 4d N = 4 SU(N) super Yang-Mills on half-space with boundary conditions defined by configurations of Gaiotto-Witten NS5- and D5-branes modded out by a rotated orientifold 5-plane breaking an extra half of the supersymmetries. We focus on configurations in which this O5’-brane is split by an NS5-brane into two oppositely charged halves, leading to a breaking of supersymmetry down to 3d N = 2 at the local level. The 5-brane configurations turn into non-trivial (p, q) webs and lead to non-trivial brane and gauge theory phenomena, including a 5d Z2 global gauge anomaly cancelled by a novel 6d global anomaly inflow, and the appearance of localized 3d N = 2 Chern-Simons couplings and the 3d parity anomaly at the boundary of the 4d theory. The systems have explicit gravity duals, given by orientifolds of the AdS4 × S2 × S2 fibrations over a Riemann surface dual to the Gaiotto-Witten setups. They describe solutions with an asymptotic AdS5 × S5 terminating at AdS4 End of the World boundary configurations, whose rich dynamics reproduces the above physical properties. They also provide the SymTFT of the 4d N = 4 on half-space with a new class of boundary conditions. We explore the interplay of bulk and boundary topological couplings and draw general lessons for the classification of cobordism defects of bulk quantum gravity theories in the swampland program.

Association study of the JAK/STAT signaling pathway with susceptibility to COVID-19 in moroccan patient and in-silico analysis of rare variants.

The goal of our study was to explore the association of the polymorphisms in the JAK/STAT pathway among Moroccan COVID-19 patients, using a case-control approach. Next-generation sequencing was employed to investigate the IFNAR1, IFNAR2, JAK1, TYK2, STAT2, and IRF9 genes within the JAK/STAT pathway. We also performed an in silico study to examine the rare variants in this pathway. Statistical analyses were conducted using MedCalc software. Protein 3D structures were determined via the I-TASSER server, with variant structures generated using PyMOL. YASARA View allowed local 3D analysis comparing native and variant structures for pathogenic rare variants. The study encompassed 206 COVID-19 patients, averaging 45.70 ± 12.73 years and a control group (N=118). Among the examined genes, 15 common polymorphisms and 7 rare variants were identified. Adjustment for age and gender revealed a significant association between TYK2 p.Gly363Ser (p=0.036) and COVID-19 infection, where the GA variant exhibited protective effects (0.6361 [0.3405-1.1884], p=0.035). Additionally, STAT2 p.Met594Ile showed an association to COVID-19 risk (p=0.042), with heterozygous GC being linked to infection (p=0.037, OR=2.7135 [0.5684 -12.9532]). Notably, IFNAR1 p.Val168Leu mutated C allele was significantly associated with reduced susceptibility to COVID-19 severity (p=0.028, OR=0.5936 [0.3725 - 0.9461]), under the additive model (p=0.045, OR=0.626 [0.3958 - 0.9899]). Rare variants IFNAR1 p.Trp318Cys, p.Ser476Phe, and IFNAR2 p.Cys271Tyr were predicted deleterious, impacting protein structure via hydrogen bond and hydrophobic interaction alterations. Burden analysis of rare variants revealed a protective cumulative effect against COVID-19 severity for TYK2 (p=0.0013, OR=0.1438 [0.04237 - 0.4803]) under the dominant model. This study underscores the role of genetic factors in COVID-19 susceptibility and advocates further explorations regarding functional impacts of JAK/STAT pathway rare variants.

Synergizing Plasmonic Local Heating and 3D Nanostructures to Boost the Solar-to-Vapor Efficiency Beyond 100.

Solving the global challenge of freshwater scarcity is of great significance for over one billion people in the world. Solar water evaporation based on plasmonic nanostructures is one of the most promising technologies due to its high efficiency. However, the efficiency of this plasmonic nanostructure-based technology can hardly achieve 100%. Therefore, it is highly desired to develop new solar converters utilizing plasmonic local heating and reasonable structure design to break the limit of solar-to-vapor efficiency for freshwater production. Here, a plasmonic sponge is developed as a solar evaporation converter with excellent full-solar-spectrum absorption, good heat localization performance, and fast evaporation kinetics through 3D nanostructures, achieving a 131% solar-to-vapor efficiency. Distinct from the traditional 2D localized heating-based evaporation and nonmetallic 3D water evaporation, the 3D plasmonic sponge can simultaneously achieve highly efficient local heating and super large water-air interfaces for boosting solar-to-vapor efficiency. The 3D plasmonic sponge can be also used as a universal converter for purifying seawater, metal ion solutions, organic pollutant solutions, and strong acid and strong alkaline solutions. The full-solar-spectrum absorption, high efficiency, and universality in water purification suggest that the novel 3D plasmonic solar converter can bring a significant way to alleviate the crisis of freshwater resources.

The Evolution of Binaries Embedded Within Common Envelopes

Triple stellar systems allow us to study stellar processes that cannot be attained in binary stars. The evolutionary phases in which the stellar members undergo mass exchanges can alter the hierarchical layout of these systems. Yet, the lack of a self-consistent treatment of common-envelope (CE) in triple-star systems hinders the comprehensive understanding of their long-term fate. This paper examines the conditions predicted around binaries embedded within CEs using local 3D hydrodynamical simulations. We explore varying the initial binary separation, the flow Mach number, and the background stellar density gradients as informed by a wide array of CE conditions, including those invoked to explain the formation of the triple system hosting PSR J0337+1715. We find that the stellar density gradient governs the gaseous drag force, which determines the final configuration of the embedded binary. We observe a comparable net drag force on the center of mass but an overall reduction in the accretion rate of the binary compared to the single-object case. We find that, for most CE conditions, and in contrast to the uniform background density case, the binary orbital separation increases with time, softening the binary and preventing it from subsequently merging. We conclude that binaries spiraling within CEs become more vulnerable to disruption by tidal interactions. This can have profound implications on the final outcomes of triple-star systems.

Atomic-Scale Direct Observation on Cation Antisite Intermixing and Identification of Charge Conduction Mechanism in p-Type CuBi2O4 for Photocathodes

Cu-based p-type semiconducting oxides have been investigated for their potential as water-reduction photocathodes in order to enhance energy conversion efficiency in photoelectrochemical cells. Among these oxides, CuBi2O4 has recently gained significant attention as a promising candidate for converting light energy into electrochemical reactions because of its good light absorption property with an adequate bandgap. Despite the importance of identifying the major defect structure to comprehend the electronic conduction behavior, however, no direct experimental analysis has been suggested yet. While the formation of Cu cation vacancies may be discussed as a possible explanation of the p-type conduction behavior, direct evidence regarding the atomic-scale structural and chemical characteristics is still required.In this research, a combination of advanced characterization techniques is employed to figure out a representative defect structure affecting the optoelectronic properties in CuBi2O4. Cs-corrected scanning transmission electron microscopy (STEM) analysis is conducted to identify a noteworthy occurrence of antisite point defects. Atomic-level energy-dispersive X-ray spectroscopy (EDS) analysis is also employed simultaneously, to clearly show the intermixing of BiCu-CuBi antisite cations as a crucial type of point defect in CuBi2O4. Additionally, a combined result of optical and electrical measurement and density functional theory (DFT) calculations demonstrates the presence of local Cu 3d polaron states in the bandgap. A new type of charge conduction mechanism is created by the hopping of hole-polarons between Cu sites, but it is seriously hindered by the BiCu cations occupying Cu sites. A higher degree of intermixing leads to a greater activation energy and decreased electronic conductivity due to the hindrance of hole-polaron hopping, as evidenced in the Arrhenius plot.Overall, this research provides valuable insights into the role of antisite defects in CuBi2O4 and their impact on its potential as a photocathode material. The results highlight the significance of the combination of atomic-scale structure analysis and theoretical calculations to identify the possible existence of defects and gain a comprehensive understanding of the electric characteristics in complex oxides for (photo)electrocatalysis. By understanding how antisite defects affect electronic conductivity, various strategies can be developed by controlling the possible defects to optimize not only CuBi2O4 but also other complex oxides for energy-harvesting applications. Figure 1

Multi-Scale 3D Cephalometric Landmark Detection Based on Direct Regression with 3D CNN Architectures.

Cephalometric analysis is important in diagnosing and planning treatments for patients, traditionally relying on 2D cephalometric radiographs. With advancements in 3D imaging, automated landmark detection using deep learning has gained prominence. However, 3D imaging introduces challenges due to increased network complexity and computational demands. This study proposes a multi-scale 3D CNN-based approach utilizing direct regression to improve the accuracy of maxillofacial landmark detection. The method employs a coarse-to-fine framework, first identifying landmarks in a global context and then refining their positions using localized 3D patches. A clinical dataset of 150 CT scans from maxillofacial surgery patients, annotated with 30 anatomical landmarks, was used for training and evaluation. The proposed method achieved an average RMSE of 2.238 mm, outperforming conventional 3D CNN architectures. The approach demonstrated consistent detection without failure cases. Our multi-scale-based 3D CNN framework provides a reliable method for automated landmark detection in maxillofacial CT images, showing potential for other clinical applications.

On how finite β and three-dimensional magnetic perturbations affect the instability of toroidal ion temperature gradient mode

Abstract The effects of finite β (the ratio of plasma kinetic pressure to magnetic pressure) and three-dimensional (3D) magnetic perturbations (MPs) on the instability of toroidal ion temperature gradient (ITG) mode are studied in this work. The expression of ion magnetic drift frequency ω d i modified by the effects from both finite β and 3D MPs is firstly derived based on the local 3D equilibrium model. Then, under the assumptions of adiabatic electrons and localized mode structure around the outboard mid-plane ( ϑ p = 0 ), the dispersion equation of the long wavelength toroidal ITG mode with considering the parallel ion dynamics is derived and solved. The results show that the distribution of ω d i around the outboard mid-plane, including both ω d i , 0 = ω d i | ϑ p = 0 and ω d i , 0 ′ ′ ≡ ( d 2 ω d i / d ϑ p 2 ) | ϑ p = 0 (twist parameter quantifying the degree of concave or convex of ω d i ), is the key for affecting the toroidal ITG mode instability. The diamagnetic effects from finite β and the effects from 3D MPs can suppress the instability by reducing | ω d i , 0 | . Via reducing | ω d i , 0 ′ ′ | under the prerequisite of unchanged sign of ω d i , 0 ′ ′ , there also exist stabilization effects on the instability from 3D MPs and the modification of local magnetic shear by finite β effects. In addition, the stabilization effects induced by reducing | ω d i , 0 ′ ′ | are closely associated with the global magnetic shear. The mechanisms for the effects of finite β and 3D MPs on the instability of toroidal ITG mode revealed in this work are helpful to the comprehensive understanding of the relationship between internal kink mode induced non-axisymmetric flux surface distortion and internal transport barrier physics in tokamak plasmas.

Particle fragmentation inside planet-induced spiral waves

ABSTRACT Growing planets interact with their surrounding protoplanetary disc, generating feedback effects that may promote or suppress nearby planet formation. We study how spiral waves launched by planets affect the motion and collisional evolution of particles in the disc. To this end, we perform local 2D hydrodynamical simulations that include a gap-opening planet and integrate particle trajectories within the gas field. Our results show that particle trajectories bend at the location of the spiral wave, and collisions occurring within the spiral exhibit significantly enhanced collisional velocities compared to elsewhere. To quantify this effect, we ran simulations with varying planetary masses and particle sizes. The resulting collisional velocities within the spiral far exceed the typical fragmentation threshold, even for collisions between particles of relatively similar sizes and for planetary masses below the pebble isolation mass. If collisions within the spiral are frequent, this effect could lead to progressively smaller particle sizes as the radial distance from the planet decreases, impacting processes such as gap filtering, pebble accretion, and planetesimal formation.

Intelligent recognition and automatic localization of pipeline welds based on multi-vision system

Abstract Currently, the leakage detection of spacecraft pipeline welds relies on manual point-by-point inspection using a detection gun, which is inefficient and inadequate for the automation needs of spacecraft production. However, the accurate recognition and precise localization of widely distributed and small pipeline welds are crucial for automated detection. Therefore, this paper proposes a multi-vision detection and localization system that integrates global and local information, considering both comprehensive global 3D search and high-precision local 3D measurement. The improved YOLOv8 model is employed for pipeline weld recognition, which improves the recognition rate of welds. Based on the deep learning recognized and segmented welds, this paper proposes stereo matching and segmentation extraction methods for 3D localization and pipeline orientation determination. Additionally, the system integrates a robot to perform automated point-by-point inspection of welds within the area without collisions. The experimental results demonstrate the effectiveness of the improved YOLOv8 and the proposed methods for 3D weld localization and pipeline orientation determination. The maximum deviation of the spatial distance of fine weld positioning is 0.20 mm, and the repeatability of the 3D coordinates is around 0.1 mm. The system can perform precise localization and detection, meeting the requirements for automatic weld recognition and localization.

Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue.

Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.

Open-Source Solutions for Real-Time 3D Geospatial Web Integration

Abstract. The recent development of Urban Digital Twin (UDT) structures and the spread of Internet of Things (IoT) technology have extended the concept of Digital Twin (DT) to urban environment representation, enabling real-time connections between geospatial representations and their real-world counterparts. Concurrently, advancements in surveying technologies and web geospatial services have facilitated the acquisition of extensive 2D and 3D geospatial data, making their spatial integration essential. While some proprietary software solutions have recently enabled initial examples of UDT by integrating various 3D geospatial data and real-time sensor acquisition, the development of open-source solutions for real-time web-based geospatial management remains a challenge. This work demonstrates a possible open-source solution for developing a UDT accessible via the web. The case study involves the web visualization platform of the new Faculty of ITC building at the University of Twente in Enschede (The Netherlands), which is connected in real-time with weather data services provided by Visual Crossing (1). The platform is based on an HTML5 framework and employs WebGL JavaScript graphic libraries to visualize different modules of 3D web visualization that integrate various local and remote 3D datasets. The framework adopted in this experiment can be used in the future for developing low-cost UDT web platforms beneficial for researchers, municipalities, and private companies interested in the real-time geospatial management of urban environments.

Impact of Surface Finishing on Ti6Al4V Voronoi Additively Manufactured Structures: Morphology, Dimensional Deviation, and Mechanical Behavior

Additively manufactured medical devices require proper surface finishing before their use to remove partially adhered particles and provide adequate surface roughness. The literature widely investigates regular lattice structures—mainly scaffolds with small pores to enhance osseointegration; however, only a few studies have addressed the impact of surface finishing on the dimensional deviation and the global and local mechanical responses of lattice samples. Therefore, the current research investigates the impact of biomedical surface finishing (i.e., corundum sandblasting and zirconia sandblasting) on Voronoi lattice structures produced by laser powder bed fusion (LPBF) with large pores and different thicknesses on the surface morphology and global and local mechanical behaviors. MicroCT and SEM are performed for the assessment of dimensional mismatch and surface evaluation. The mechanical properties are investigated with 2D digital image correlation (DIC) in quasi-static compression tests to estimate the impact of surface finishes on local maps of strain. In the quasi-static tests, both the global mechanical performances, as expected, and local 2D DIC strain maps were mainly affected by the strut thickness, and the impact of different surface finishings was irrelevant; on the contrary, different surface finishing processes led to differences in the dimensional deviation depending on the strut thickness. These results are relevant for designing lattice structures with thin struts that are integrated into medical prostheses that undergo AM.