3D Model Research Articles

Microsurgical anatomy and approaches to thalamic gliomas. Part 1: A cartography guide for navigating to the thalamus. Integrating 3D model rendering with anatomical dissections.

The selection of appropriate microsurgical approaches to treat thalamic pathologies is currently largely subjective. The objective of this study was to provide a structured cartography map for surgical navigation to treat gliomas involving different surfaces of the thalamus. Fifteen formalin-fixed, silicone-injected cadavers (30 sides) were dissected, and 10 adult brain specimens (20 sides) were used to illustrate thalamic microsurgical anatomy using the Klingler fiber dissection technique. Exposures and trajectories for the six most common microsurgical approaches were depicted using MR data from healthy subjects converted into surface-rendered 3D virtual brain models. Additionally, thalamic surfaces exposed with all six approaches were color mapped on the virtual 3D model and compared side-by-side in 360° views with previously reported microsurgical approaches. These 3D models were then used in conjunction with topographic data to guide cadaveric dissection steps. There are two general surgical routes to thalamic lesions: the subarachnoid transcisternal and transcortical routes. The transcisternal route consists of the following three approaches: 1) anterior interhemispheric transcallosal approach, which exposes the anterior and superior thalamus; 2) posterior interhemispheric transcallosal approach, which exposes the posterosuperior thalamus; and 3) supracerebellar infratentorial approach, which exposes the posteromedial cisternal thalamus and can be extended laterally to approach the posterolateral thalamus by cutting the tentorium. The three transcortical approaches are the 1) superior parietal lobule approach, which exposes the posterosuperior thalamus and is particularly advantageous in the setting of hydrocephalus; 2) transtemporal gyrus approach, which exposes the inferolateral thalamus; and 3) transsylvian transinsular approach, which exposes the lateral thalamus (slightly more superiorly and posteriorly) and is advantageous for pathologies extending laterally into the peduncle, lenticular nucleus, or insula. Microsurgical approaches to thalamic gliomas continue to be challenging. Nonetheless, safe and effective cisternal, ventricular, and cortical corridors can be developed with thoughtful planning, anatomical understanding, and knowledge of the advantages, risks, and limitations of each approach. In some cases, it is wise to combine these approaches with staged procedures, as the authors demonstrate in Part 2. In Part 1 of this two-part series, they discuss thalamic microsurgical anatomy and illustrate the trajectory and exposures of all six approaches to guide decision-making. Part 2 discusses their thalamic glioma microsurgical case series, which utilizes these microsurgical approaches.

3D structural modeling approach by discretization of a basic structural map associated with magnetic data

ABSTRACT This study proposes a 3D structural modeling approach based on the discretization of a 2D structural model associated with magnetic data. The approach proposed in this study requires first to identify the parameters involved in the modeling (geographical position, direction, dip direction and dip angle) and then to transform the whole 2D model into fault segments. The first discretization will allow determining the position, the direction and the dip direction of each fault segment. This discretization phase was done by coupling the Excel program to existing GIS software. The last discretization will allow evaluating the variation of inclinations along the fault segment. It required the elaboration of a depth model from the magnetic data grid. It is this model that provided all the necessary data for this last discretization, which was automated thanks to the DipAngle code developed for this study. All these discretizations have provided to the used modeler and all the databases necessary for the realization of the various models. The application of this methodology to the Central Domain of the Mbere Division has made it possible to develop different models that can be used as basic documents in exploration projects.

Simulation-based inference on virtual brain models of disorders

Connectome-based models, also known as virtual brain models (VBMs), have been well established in network neuroscience to investigate pathophysiological causes underlying a large range of brain diseases. The integration of an individual’s brain imaging data in VBMs has improved patient-specific predictivity, although Bayesian estimation of spatially distributed parameters remains challenging even with state-of-the-art Monte Carlo sampling. VBMs imply latent nonlinear state space models driven by noise and network input, necessitating advanced probabilistic machine learning techniques for widely applicable Bayesian estimation. Here we present simulation-based inference on VBMs (SBI-VBMs), and demonstrate that training deep neural networks on both spatio-temporal and functional features allows for accurate estimation of generative parameters in brain disorders. The systematic use of brain stimulation provides an effective remedy for the non-identifiability issue in estimating the degradation limited to smaller subset of connections. By prioritizing model structure over data, we show that the hierarchical structure in SBI-VBMs renders the inference more effective, precise and biologically plausible. This approach could broadly advance precision medicine by enabling fast and reliable prediction of patient-specific brain disorders.

Geomechanical assessment of mineral deposits based on 3D modeling

Geomechanical assessment of mineral deposits based on 3D modeling

Formulating facial mesh tracking as a differentiable optimization problem: a backpropagation-based solution

Facial mesh tracking enables the production of topologically consistent 3D facial meshes from stereo video input captured by calibrated cameras. This technology is an integral part of many digital human applications, such as personalized avatar creation, audio-driven 3D facial animation, and talking face video generation. Currently, most facial mesh tracking methods are built on computer graphics techniques, which involve complex procedures and often necessitate human annotation within pipelines. As a result, these approaches are difficult to implement and hard to generalize across various scenarios. We propose a backpropagation-based solution that formulates facial mesh tracking as a differentiable optimization problem called the BPMT. Our solution leverages visual clues extracted from the stereo input to estimate vertex-wise geometry and texture information. The BPMT is composed of two steps: automatic face analysis and mesh tracking. In the first step, a range of visual clues are automatically extracted from the input, including facial point clouds, multi-view 2D landmarks, 3D landmarks in the world coordinate system, motion fields, and image masks. The second step can be viewed as a differentiable optimization problem, with constraints comprising stereo video input and facial clues. The primary objective is to achieve topologically consistent 3D facial meshes across frames. Additionally, the parameters to be optimized encompass the positions of free-form deformed vertices and a shared texture UV map. Furthermore, the 3D morphable model (3DMM) is introduced as a form of regularization to enhance the convergence of the optimization process. Leveraging the fully developed backpropagation software, we progressively register the facial meshes to the recorded object, generating high-quality 3D faces with consistent topologies. The BPMT requires no manual labeling within the pipeline, making it suitable for producing large-scale stereo facial data. Moreover, our method exhibits a high degree of flexibility and extensibility, positioning it as a promising platform for future research in the community.

CFD modeling of a modern wood stove - Soot formation

Wood stoves are important domestic heating appliances using renewable bioenergy. However, the emission of Particulate Matter (PM) is the major concern for the application of wood stoves. Thus, improvements in the design of wood stoves are required for the reduction of PM emissions (mainly soot) to fulfill the increasingly stringent pollutant emission limits. To achieve low PM emission of the wood stove, a 3D steady-state CFD model is used to simulate the wood stove with a focus on soot formation in this study. The model is evaluated with the experimental data, the results of which show that the CFD model provides a reasonable prediction of wood stove experiments, indicating that the CFD model can be used as an efficient tool to optimize the design of the wood stove. The model is further used to study the effects of injection direction and mass flow rate of the tertiary air on the soot particle emission. It is found that the horizontal- and down-direction injectors can effectively reduce soot formation and an optimized tertiary air mass flow rate exists in the modern wood stove system. These conclusions are very useful in designing and developing the intelligent control system of the modern wood stove.

An Empirical Study of Portrait Rights on Emotional Evolution in Virtual Social Scenarios by Transformer and Cloud Computing

Facial expression recognition technology can improve the possibility of fugitives and persons subject to execution being discovered by public security and judicial personnel in the virtual world, thereby improving the actual effectiveness and credibility of the law. There may also be a risk of portrait rights infringement with this technology, and the user of the technology needs to inform the person whose facial expression is being extracted in advance and obtain permission. With the rapid progression of deep learning and artificial intelligence, 3D facial expression modeling has garnered increased significance in computer vision and graphics. We propose an innovative approach combining Transformer models with cloud computing to simulate facial expression evolution in virtual social environments. Leveraging Transformer-based feature extraction, our model integrates emotional cues from various modalities to accurately capture subtle changes over time.

Virtual Reality-Enhanced Assessment of the Anterior Glottic Angle Using Cadaveric Models: A Proof-of-Concept Study

ObjectivesVocal fold paralysis (VFP) is a complex disorder that affects voice, speech, swallowing, and overall quality of life. Current evaluation methods for determining the position of paralyzed vocal folds lack the objectivity required for personalized interventions and research on innovative treatments for VFP. This study was designed to validate the accuracy and reproducibility of a Virtual Reality (VR)-based platform to measure the anterior glottic angle (AGA), a critical component in determining the position of a paralyzed vocal fold. Study DesignRetrospective. MethodsA retrospective analysis of Computed Tomography (CT) scans of 39 adult patients was conducted to measure the AGA shortly after death. Two measurement methods were used: 2D-CT for direct measurements on 2D images and a 3D-VR method utilizing a dedicated platform to create a 3D virtual reality model of the larynx. The AGA measurements conducted by two senior otolaryngologists using the 3D-VR method were compared to the 2D-CT measurements made by one of these same otolaryngologists. ResultsThe mean AGA measured by the 3D-VR method was found to be 32.936±6.486° (n=39), and the measurements were highly correlated (r=0.9670, p<0.0001). By contrast, the 2D-CT method without VR yielded a significantly lower mean angle of 23.754° (n=35) with a higher standard deviation of 10.365°. The 3D-VR method demonstrated excellent reliability for AGA measurements (intraclass correlation coefficient of 0.954). ConclusionThe findings underscore the potential value of using a VR-based platform to improve reproducibility and reduce the variability in measurements of AGA in cases of VFP. Data AvailabilityThe data used to support the findings of this study are available from the corresponding author upon request.

Optimization Analysis of Various Parameters Based on Response Surface Methodology for Enhancing NOx Catalytic Reduction Performance of Urea Selective Catalytic Reduction on Cu-ZSM-13 Catalyst

While selective catalytic reduction (SCR) has long been indispensable for nitrogen oxide (NOx) removal, optimizing its performance remains a significant challenge. This study investigates the combined effects of structural and intake parameters on SCR performance, an aspect often overlooked in previous research. This paper innovatively developed a three-dimensional SCR channel model and employed response surface methodology to conduct an in-depth analysis of multiple key factors. This multidimensional, multi-method approach enables a more comprehensive understanding of SCR system mechanics. Through target optimization, we achieved a simultaneous improvement in three critical indicators: the NOx conversion rate, pressure drop, and ammonia slip. It is worth noting that the NOx conversion rate has been optimized from 17.07% to 98.25%, the pressure drop has been increased from 3454.62 Pa to 2558.74 Pa, and the NH3 slip has been transformed from 122.26 ppm to 17.49 ppm. These results not only advance the theoretical understanding of SCR technology but also provide valuable design insights for practical applications. Our findings pave the way for the development of more efficient and environmentally friendly SCR systems, potentially revolutionizing NOx control in various industries.

Suppression of HSV-1 infection and viral reactivation by CRISPR-Cas9 gene editing in 2D and 3D culture models

Although our understanding of HSV-1 biology has been considerably enhanced, developing therapeutic strategies to eliminate HSV-1 in latently infected individuals remains a public health concern. Current antiviral drugs used for the treatment of HSV-1 complications are not specific and do not address latent infection. We recently developed a CRISPR/Cas9-based gene editing platform to specifically target the HSV-1 genome. In this study, we further used 2D Vero cell culture and 3D hiPSC-derived cerebral organoid (CO) models to assess the effectiveness of our editing constructs targeting viral ICP0 or ICP27 gene. We found that targeting the ICP0 or ICP27 gene with AAV2-CRISPR/Cas9 vectors in Vero cells drastically suppressed HSV-1 replication. In addition, we productively infected COs with HSV-1, characterized the viral replication kinetics, and established a viral latency model. Finally, we discovered that ICP0- or ICP27-targeting AAV2-CRISPR/Cas9 vector significantly reduced viral rebound in the COs that were latently infected with HSV-1. In summary, our results suggest that CRISPR/Cas9 gene editing of HSV-1 is an efficient therapeutic approach to eliminate the latent viral reservoir and treat HSV-1 associated complications.

Screening and Anti-angiogenesis Activity of Chiloscyllium plagiosum Anti-human VEGFR2 Single-domain Antibody.

Recently, the incidence of malignant tumors is on the rise and searching for new treatments on it has become the research priority. Blocking the vascular endothelial growth factor (VEGF) and its receptor (VEGFR) is one of the treatment strategies that used in the development of specific anti-angiogenic drugs. The deficiencies in tissue penetration and affinity maturation become the weakness of these drugs in anti-tumors applications. The single heavy chain antibody found in Chiloscyllium plagiosum, which has a low molecular weight and superior tissue penetration of variable region (VNARs), was considered to have the high antigen binding activity and stability. This type of antibody has a simple structure that can be prokaryoticaly expressed, which makes it easily to produce new antiangiogenic target drugs. Specific anti-IgNAR rabbit multiple antibodies have been used to assess the level of VNARs in sharks and have shown a significant enrichment of IgNAR after triple immunization. An anti-VEGFR2 phage library was used for the targeted VNARs screening, and five candidate VNARs sequences were subsequently obtained by phage screening, followed by combined screening with the transcriptome library, and analysis of conserved regions along with 3D modelling matched the VNAR profile. ELISA and cell-based assays showed that two of the VNARs, VNAR-A6 and VNAR-E3, had a superior antigen affinity and anti-angiogenic activity thereby being able to inhibit human Umbilical Vein Endothelial Cells proliferation and migration. The anti-VEGFR2 VNARs derived from the immunized Chiloscyllium plagiosum and screened by phage library, which provide the new research ideas and specific approaches for the development of new drugs. The anti-VEGFR2 VNARs are capable for blocking the VEGF-VEGFR pathway, which of these may contribute to expanding the use of anti-angiogenic drugs.

Nozzle Wear in Abrasive Water Jet Based on Numerical Simulation.

Particle diameters and jet pressure in abrasive water jet (AWJ) are significant jet properties which deserve a better understanding for improving AWJ machining performance. Some influence factors have been verified regarding nozzle wear in abrasive water jet polishing application. A three-dimensional model of a nozzle is established to analyze the influence of internal multi-phase flow field distribution, which is based on Euler-Lagrange methodology. With the increase of jet pressure, the erosion rate decreases; with the increase of the diameter and mass flow rate of the erosion particles, the erosion speed increases as well. When the diameter of the outlet is worn to 1.6 mm, the pressure on the work piece caused by the abrasive water jet increases by more than double compared to the non-worn nozzle; when the diameter of the nozzle outlet is worn to 1.6 mm, the shear force is 2.5 times higher than the shear force when the diameter is 1.0, which means that the jet force is divergent when the diameter is 1.6 mm, and the damage of the work piece is very serious. The obtained results could improve polishing efficiency on the work piece, extend nozzle lifetimes, and guide the future design of AWJ nozzles.

The IGCP 714 Project “3GEO – Geoclimbing & Geotrekking in Geoparks” – Selection of Geodiversity Sites Equipped for Climbing for Combining Outdoor and Multimedia Activities

The IGCP 714 project “3GEO – Geoclimbing & Geotrekking in Geoparks” is financed by the International Geoscience Programme (IGCP) and supported by the International Union of Geological Sciences (IUGS). In this paper, we report on the results of the first phase of the project focused on the criteria to be adopted to select geodiversity sites equipped for climbing or trekking. The selection of geoclimbing sites and geotrekking routes is aimed at combining multimedia tools and outdoor activities for Geosciences promotion and conservation in UNESCO Global Geoparks, aspiring geoparks or geoparks project, and also in protected areas featuring geoheritage sites. Indeed, both outdoor activities and multimedia tools favour the pursuing of many of the United Nations Sustainable Development Goals (e.g., 3, 4, 8, 11). An international consortium of geoscientists from 12 different countries selected, through the proposed procedure, 22 geoclimbing sites, and then they also detected 30 geotrekking routes mirroring Earth geodiversity. At some test sites (geoclimbing and geotrekking) multimedia tools and digital outcrop models have been developed through different methodological approaches (e.g., Structure from Motion and Multi-View Stereo photogrammetry), to open the way to the second part of the project still in progress. These sites and the relative virtual models are herein also shown. The final aim of the IGCP 714 project is indeed to create an open data repository (digital outcrop models, videos, virtual tours, photos, scientific information, and interpretations) to upload data of the selected sites to mirror Earth geodiversity for different users including tourists and school groups.

Extending the Hough transform to recognize and approximate space curves in 3D models

Feature curves are space curves identified by color or curvature variations in a shape, which are crucial for human perception (Biederman, 1995). Detecting these characteristic lines in 3D digital models becomes important for recognition and representation processes. For recognizing plane curves in images, the Hough transform (HT) provided a very good solution to the problem. It selects the best-fitting curve in a dictionary of families of curves through a voting procedure that makes it robust to noise and missing parts. Since 3D digital models are often obtained by scanning real objects and may have many defects, the HT has been extended to recognize and approximate space curves in 3D models that correspond to relevant featuresThis work overviews three HT-based different approaches for identifying and approximating spatial profiles of points extracted from point clouds or meshes. A first attempt at this extension involved projecting the spatial points onto the regression plane, thus reducing the problem to planar recognition and using families of plane curves. A second approach has been proposed to recognize spatial profiles that cannot be projected onto the regression plane, using two types of space curve families. Unfortunately, the main drawback of methods based on traditional HT is that it requires prior knowledge of which family of curves to look for.To overcome this limitation, a third method has been developed that provides a piecewise space curve approximation using specific parametric polynomial curves. Additionally, free-form curves that a parametric or implicit form cannot express can be represented using this technique.In the paper, we also analyze the pros and cons of the various approaches and how they managed and reduced the HT's computational cost, given the large number of parameters introduced when families of space curves are considered.

Digital Twin System of Substation Equipment

This paper adopts the following technical solutions to achieve: a digital twin system for substation, including: database, database configuration module, data warehousing module, background data processing module and front-end browsing module; The front-end browsing module is used to display the data sent by the background data processing module in the corresponding form according to the user's selection; The form includes building the three-dimensional model of the substation based on BIM technology, and displaying the corresponding real-time data and status in the three-dimensional components of the three-dimensional model. Compared with the existing technology, it organically integrates the three-dimensional model and panoramic monitoring data of the substation, realizes the three-dimensional panoramic display of substation assets and the acquisition of substation monitoring data, improves the spatial experience of daily operation and maintenance comprehensive monitoring, and provides a solid data platform for the subsequent in-depth mining and intelligent analysis of multidimensional data of the substation.

Pneumatic extrusion bioprinting-based high throughput fabrication of a melanoma 3D cell culture model for anti-cancer drug screening.

The high incidence of malignant melanoma highlights the need for in vitro models that accurately represent the tumour microenvironment, enabling developments in melanoma therapy and drug screening. Despite several advancements in 3D cell culture models, appropriate melanoma models for evaluating drug efficacy are still in high demand. The 3D pneumatic extrusion-based bioprinting technology offers numerous benefits, including the ability to achieve high-throughput capabilities. However, there is a lack of research that combines pneumatic extrusion-based bioprinting with analytical assays to enable efficient drug screening in 3D melanoma models. To address this gap, this study developed a simple and highly reproducible approach to fabricate a 3D A375 melanoma cell culture model using the pneumatic extrusion-based bioprinting technology. To optimise this method, the bioprinting parameters for producing 3D cell cultures in a 96-well plate were adjusted to improve reproducibility while maintaining the desired droplet size and a cell viability of 92.13± 6.02%. The cross-linking method was optimised by evaluating cell viability and proliferation of the 3D bioprinted cells in three different concentrations of calcium chloride. The lower concentration of 50 mM resulted in higher cell viability and increased cell proliferation after 9 days of incubation. The A375 cells exhibited a steadier proliferation rate in the 3D bioprinted cell cultures, and tended to aggregate into spheroids, whereas the 2D cell cultures generally formed monolayered cell sheets. In addition, we evaluated the drug responses of four different anti-cancer drugs on the A375 cells in both the 2D and 3D cell cultures. The 3D cell cultures exhibited higher levels of drug resistance in all four tested anti-cancer drugs. This method presents a simple and cost-effective method of producing and analysing 3D cell culture models that do not add additional complexity to current assays and shows considerable potential for advancing 3D cell culture models' drug efficacy evaluations.

Deep learning from three-dimensional Lithium-ion battery multiphysics model Part II: Convolutional neural network and long short-term memory integration

Lithium-ion (Li-ion) batteries have emerged as a cornerstone of electric vehicles (EVs), enabling the road transportation towards net zero. The success of electric vehicles largely hinges on the battery performance and safety. It is challenging to test and predict battery performance and safety issues by conventional methods, which are usually time-consuming and expensive, involving significant human and measurement errors. To enable the quick estimation of battery performance and safety, we developed three data-driven machine learning (ML) models, namely a convolutional neural network (CNN), a long short-term memory (LSTM), and a CNN-LSTM to predict battery discharge curves and local maximum temperature (hot spot) under various operating conditions. The developed ML models mitigated data scarcity by employing a three-dimensional multi-physics Li-ion battery model to generate enormous and diverse high-quality data. It was found the CNN-LSTM model outperforms the others and achieved high accuracy of 98.68% to learn discharge curves and battery maximum temperature, owing to the integration of spatial and sequential feature extraction. The battery safety can be improved by comparing the predicted maximum battery temperature against safe temperature threshold. The proposed data development and data-driven ML models are of great potential to provide digital tools for engineering high-performance and safe EVs.

Three-dimensional model and environmental fragility in the Guarani Aquifer System, SE-Brazil

The Guarani Aquifer System (GAS) is a vast transboundary continental sedimentary basin in southern South America, encompassing sedimentary rocks and basalt flows across Uruguay, Paraguay, Argentina, and Brazil. It serves as a crucial water resource for urban supply and irrigation. This study aims to propose geophysical, geometric, and fragility models of the GAS in a critical exploitation area, utilizing geological data, geophysical logs, geomorphometry, and information from tubular wells. The models define distinct geophysical ranges for each formation and identify contacts between sedimentary and basaltic rocks. Integration of horizontal and vertical spatial distributions of geophysical and geological data forms a 3D model, revealing basaltic flows and intrusions distribution in fragile areas between formations, and potentially connecting aquifer layers. Natural fragility zones, characterized by high fracture densities, are observed in the central-east region, while outcrop and recharge areas of the main aquifer hydrofacies are found in the north. The 3D model highlights similarities between the topography of the Botucatu Formation (KJb – eolian sandstones) and the potentiometry of GAS at local scales, and overexploitation zones in Ribeirão Preto's city center. The assessment prioritizes areas at risk and conservation strategies for sedimentary aquifers, emphasizing interactions between surface and groundwater and addressing issues of overexploitation, identifying high-impact risks on GAS hydrodynamics and water quality.

Unlocking the Potential Role of Decellularized Biological Scaffolds as a 3D Radiobiological Model for Low- and High-LET Irradiation.

Decellularized extracellular matrix (ECM) bioscaffolds have emerged as a promising three-dimensional (3D) model, but so far there are no data concerning their use in radiobiological studies. We seeded two well-known radioresistant cell lines (HMV-II and PANC-1) in decellularized porcine liver-derived scaffolds and irradiated them with both high- (Carbon Ions) and low- (Photons) Linear Energy Transfer (LET) radiation in order to test whether a natural 3D-bioscaffold might be a useful tool for radiobiological research and to achieve an evaluation that could be as near as possible to what happens in vivo. Biological scaffolds provided a favorable 3D environment for cell proliferation and expansion. Cells did not show signs of dedifferentiation and retained their distinct phenotype coherently with their anatomopathological and clinical behaviors. The radiobiological response to high LET was higher for HMV-II and PANC-1 compared to the low LET. In particular, Carbon Ions reduced the melanogenesis in HMV-II and induced more cytopathic effects and the substantial cell deterioration of both cell lines compared to photons. In addition to offering a suitable 3D model for radiobiological research and an appropriate setting for preclinical oncological analysis, we can attest that bioscaffolds seemed cost-effective due to their ease of use, low maintenance requirements, and lack of complex technology.

Multimodal Dictionaries for Traditional Craft Education

We address the problem of systematizing the authoring of digital dictionaries for craft education from ethnographic studies and recordings. First, we present guidelines for the collection of ethnographic data using digital audio and video and identify terms that are central in the description of crafting actions, products, tools, and materials. Second, we present a classification scheme for craft terms and a way to semantically annotate them, using a multilingual and hierarchical thesaurus, which provides term definitions and a semantic hierarchy of these terms. Third, we link ethnographic resources and open-access data to the identified terms using an online platform for the representation of traditional crafts, associating their definition with illustrations, examples of use, and 3D models. We validate the efficacy of the approach by creating multimedia vocabularies for an online eLearning platform for introductory courses to nine traditional crafts.