2D Projection Research Articles

Self-Supervised Electroencephalogram Representation Learning for Automatic Sleep Staging: Model Development and Evaluation Study.

Deep learning models have shown great success in automating tasks in sleep medicine by learning from carefully annotated electroencephalogram (EEG) data. However, effectively using a large amount of raw EEG data remains a challenge. In this study, we aim to learn robust vector representations from massive unlabeled EEG signals, such that the learned vectorized features (1) are expressive enough to replace the raw signals in the sleep staging task, and (2) provide better predictive performance than supervised models in scenarios involving fewer labels and noisy samples. We propose a self-supervised model, Contrast with the World Representation (ContraWR), for EEG signal representation learning. Unlike previous models that use a set of negative samples, our model uses global statistics (ie, the average representation) from the data set to distinguish signals associated with different sleep stages. The ContraWR model is evaluated on 3 real-world EEG data sets that include both settings: at-home and in-laboratory EEG recording. ContraWR outperforms 4 recently reported self-supervised learning methods on the sleep staging task across 3 large EEG data sets. ContraWR also supersedes supervised learning when fewer training labels are available (eg, 4% accuracy improvement when less than 2% of data are labeled on the Sleep EDF data set). Moreover, the model provides informative, representative feature structures in 2D projection. We show that ContraWR is robust to noise and can provide high-quality EEG representations for downstream prediction tasks. The proposed model can be generalized to other unsupervised physiological signal learning tasks. Future directions include exploring task-specific data augmentations and combining self-supervised methods with supervised methods, building upon the initial success of self-supervised learning reported in this study.

A method for sensitivity analysis of deviation factor for geometric correction of cone-beam CT system

To propose a sensitivity test method for geometric correction position deviation of cone-beam CT systems. We proposed the definition of center deviation and its derivation. We analyzed the influence of the variation of the three-dimensional spatial center of the steel ball point, the projection center and the size of the steel ball point on the deviation of geometric parameters and the reconstructed image results by calculating the geometric correction parameters based on the Noo analytical method using the FDK reconstruction algorithm for image reconstruction. The radius of the steel ball point was within 3 mm. The deviation of the center of the calibration parameter was within the order of magnitude and negligible. A 10% Gaussian perturbation of a single pixel in the 3D spatial coordinates of the steel ball point produced a deviation of about 3 pixel sizes, while the same Gaussian perturbation of the 2D projection coordinates of the steel ball point produced a deviation of about 2 pixel sizes. The geometric correction is more sensitive to the deviation generated by the three-dimensional spatial coordinates of the steel ball point with limited sensitivity to the deviation generated by the two-dimensional projection coordinates of the steel ball point. The deviation sensitivity of a small diameter steel ball point can be ignored.

Direct Manufacturing Technology for High‐Precision Follow‐the‐Shape Circuits on Complex, Hard, Curved Surfaces

Abstract3D curved electronics are a trend in the microelectronics industry, but conformal printing of circuits on complex curved surfaces remains challenging, especially for electronics comprising concave surfaces with large curvature. In this study, a new manufacturing method is proposed for follow‐the‐shape circuits, using high‐precision direct printing technology to print circuits on hard, arbitrarily curved surfaces. A circuit with any complex curved surface can be directly digitized and programmed for fully autonomous and controlled printing without indirect transfer or pad printing processing. The proposed direct printing method begins with using unique 3D projection technology to map a 2D planar functional circuit onto a 3D digital curved surface. The next step is directly printing the integrated circuit on a complex surface by controlled planning of the spatial motion trajectory, high‐frequency drive control of the precision nozzle, and precise switching control of the heterogeneous functional material. Optimal printing parameters are obtained by exploring the main factors affecting molding quality and electrical conductivity of curved surface circuits. Simple examples, such as an acoustic‐optic touch time‐delay three‐control multifunction system, demonstrate the feasibility and broad potential of the proposed technology.

Growth, structural effects, and non-linear and spectroscopic properties of nanocomposites based on α-NiSO4·6H2O single crystals with TiO2 nanoparticles or sols

Nanocomposites based on nickel sulfate hexahydrate α-NiSO4·6H2O (NSH) with titanium (IV) oxide introduced in the form of nanoparticles (Hombifine N: anatase; Degussa P25: 85 % anatase + 15 % rutile; η-phase: 86 % η - phase + 14 % anatase, NSH:Ti(1)) or sols (NSH:Ti(2)) are synthesized for the first time. X-ray diffraction study reveals a single-phase nature of samples, the full occupancy of all crystallographic sites in the NSH:Ti(1) structures, and the presence of Ti4+ ions in interstitial sites near the vacant Ni site in the NSH:Ti(2) structures. A crystallization of the nanosized η-phase of the composition TiO2-x × mH2O directly in the NSH:Ti(1) crystalline matrix with the formation of TiO2 with the rutile structure, facilitated by the structural-geometric correspondence of 2D projections of NSH and rutile, is observed for the first time. The presence of TiO2 in the interblock space of NSH:Ti(1) crystals affects the unit cell parameters due to the induced stresses, which is practically not described in the literature. The intensity of SHG signals of NSH:Ti varies depending on both the prehistory of TiO2 samples and the crystal state, single-crystal or powdered, of the object under study: the highest values were observed for the NSH:Ti(2) powder with the lowest content of titanium ions. The UV–VIS study reveals similar absorption and transmission bands, but with little difference in band width and intensity, for NSH, NSH:Ti(1) and NSH:Ti(2), which can be perspective for UV filters operating in the solar-blind range.

Embodied mixed reality with passive haptics in STEM education: randomized control study with chemistry titration

Researchers, educators, and multimedia designers need to better understand how mixing physical tangible objects with virtual experiences affects learning and science identity. In this novel study, a 3D-printed tangible that is an accurate facsimile of the sort of expensive glassware that chemists use in real laboratories is tethered to a laptop with a digitized lesson. Interactive educational content is increasingly being placed online, it is important to understand the educational boundary conditions associated with passive haptics and 3D-printed manipulables. Cost-effective printed objects would be particularly welcome in rural and low Socio-Economic (SES) classrooms. A Mixed Reality (MR) experience was created that used a physical 3D-printed haptic burette to control a computer-based chemistry titration experiment. This randomized control trial study with 136 college students had two conditions: 1) low-embodied control (using keyboard arrows), and 2) high-embodied experimental (physically turning a valve/stopcock on the 3D-printed burette). Although both groups displayed similar significant gains on the declarative knowledge test, deeper analyses revealed nuanced Aptitude by Treatment Interactions (ATIs). These interactionsfavored the high-embodied experimental group that used the MR devicefor both titration-specific posttest knowledge questions and for science efficacy and science identity. Those students with higher prior science knowledge displayed higher titration knowledge scores after using the experimental 3D-printed haptic device. A multi-modal linguistic and gesture analysis revealed that during recall the experimental participants used the stopcock-turning gesture significantly more often, and their recalls created a significantly different Epistemic Network Analysis (ENA). ENA is a type of 2D projection of the recall data, stronger connections were seen in the high embodied group mainly centering on the key hand-turning gesture. Instructors and designers should consider the multi-modal and multi-dimensional nature of the user interface, and how the addition of another sensory-based learning signal (haptics) might differentially affect lower prior knowledge students. One hypothesis is that haptically manipulating novel devices during learning may create more cognitive load. For low prior knowledge students, it may be advantageous for them to begin learning content on a more ubiquitous interface (e.g., keyboard) before moving them to more novel, multi-modal MR devices/interfaces.

APPLICATION OF THE RN-GEOSIM SOFTWARE PACKAGE IN HIGHER EDUCATION ESTABLISHMENTS

The article discusses the practical use of the PH-GEOSIM corporate software package in the educational process on the example of higher educational establishments. This complex was developed as part of import substitution in RN-BashNIPIneft LLC, the corporate institute of Rosneft. It is designed to build and maintain geological models of oil and gas fields, contains modern visualization tools that help the geologist-modeler in his work and display the components of the geological model in 1D (correlation scheme), 2D projections, 3D view. The RN-GEOSIM software package, which has all the necessary functionality for working with digital geological models, will allow students to develop general professional competencies of educational programs in accordance with their specialization at a basic and advanced level.

Visual Quality Assessment of Point Clouds Compared to Natural Reference Images

This paper proposes a point cloud (PC) visual quality assessment (VQA) framework that reflects the human visual system (HVS). The proposed framework compares natural images acquired using a digital camera and PC images generated via 2D projection in terms of appropriate objective quality evaluation metrics. Humans primarily consume natural images; thus, human knowledge is typically formed from natural images. Thus, natural images can be more reliable reference data than PC data. The proposed framework performs an image alignment process based on feature matching and image warping to use the natural images as a reference which enhances the similarities of the acquired natural and corresponding PC images. The framework facilitates identifying which objective VQA metrics can be used to reflect the HVS effectively. We constructed a database of natural images and three PC image qualities, and objective and subjective VQAs were conducted. The experimental result demonstrates that the acceptable consistency among different PC qualities appears in the metrics that compare the global structural similarity of images. We found that the SSIM, MAD, and GMSD achieved remarkable Spearman rank-order correlation coefficient scores of 0.882, 0.871, and 0.930, respectively. Thus, the proposed framework can reflect the HVS by comparing the global structural similarity between PC and natural reference images.

3D Information Guided Motion Transfer via Sequential Image Based Human Model Refinement and Face-Attention GAN

Image and video based human motions can be regarded as the deformation processes of person appearances, so motion transfer is usually treated as a pose guided image generation task and implemented in the 2D image plane. However, the 2D plane image generation lacks guidance of the original 3D motion information, which results in blur and shape distortions of the generated motion images. Therefore, we propose to simulate the generation process of real motion images by projecting the 3D human models, which are reconstructed from the training motion images and driven with target poses, into the 2D plane. We then take the 2D projections as the pose representations and input them into the generation model as they naturally inherit the 3D information from the original motions. Considering the unreliability on the invisible surface of the single image based human model reconstruction, we propose a sequential image based human model refinement module which exploits the complementary information between adjacent motion frames to refine the 3D human model. Furthermore, we propose a face-attention GAN model to conduct the final motion transfer, in which we use the Gaussian distribution to match the elliptical face region and design a face enhancement loss function since the faces in the generated motion images influence the performances very much. The generated motion images with reliable depth information, accurate shapes and clear faces demonstrate the effectiveness of the proposed method.

Cerebrovascular segmentation in phase-contrast magnetic resonance angiography by a Radon projection composition network.

Cerebrovascular segmentation based on phase-contrast magnetic resonance angiography (PC-MRA) provides patient-specific intracranial vascular structures for neurosurgery planning. However, the vascular complex topology and spatial sparsity make the task challenging. Inspired by the computed tomography reconstruction, this paper proposes a Radon Projection Composition Network (RPC-Net) for cerebrovascular segmentation in PC-MRA, aiming to enhance distribution probability of vessels and fully obtain the vascular topological information. Multi-directional Radon projections of the images are introduced and a two-stream network is used to learn the features of the 3D images and projections. The projection domain features are remapped to the 3D image domain by filtered back-projection transform to obtain the image-projection joint features for predicting vessel voxels. A four-fold cross-validation experiment was performed on a local dataset containing 128 PC-MRA scans. The average Dice similarity coefficient, precision and recall of the RPC-Net achieved 86.12%, 85.91% and 86.50%, respectively, while the average completeness and validity of the vessel structure were 85.50% and 92.38%, respectively. The proposed method outperformed the existing methods, especially with significant improvement on the extraction of small and low-intensity vessels. Moreover, the applicability of the segmentation for electrode trajectory planning was also validated. The results demonstrate that the RPC-Net realizes an accurate and complete cerebrovascular segmentation and has potential applications in assisting neurosurgery preoperative planning.

In silico and In vitro Assessment of Antibacterial Activity, LPS Binding Affinity, and Toxicity of the GKY25 Peptide.

Extensively and multi-drug resistant isolates of bacteria (MDR, XDR) have caused significant health problems and are responsible for high morbidity and mortality as well. In this critical condition, the discovery, design, or development of new antibiotics is of great concern. According to this necessity, antimicrobial peptides (AMPs) suggested as promising agents. Accordingly, this study aims to evaluate the GKY25 peptide to develop its future antibacterial applications as well as confirmation of LPS neutralization. Predictions of 3D structure and helical wheel projection analysis of the peptide were performed by ITASSER and Heliquest servers. Binding affinity and antibacterial activity were performed using molecular docking and CAMPR4, respectively, followed by experimental binding assay as well as in vitro antibacterial assay. GKY25 was predicted as an alpha-helical peptide, and its helicity showed probable projection of hydrophobic and positively-charged amino acid residues. Docking studies showed binding affinity of GKY25 peptide to gram-positive and outer and inner gram-negative bacterial membranes as -5.7, -6.8, and -4 kcal/mole, respectively. CAMPR4 analysis predicted the peptide as an AMP. Experimental binding assay showed that the peptide binds LPS immediately and their interaction was observed at 274 nm. Gathering all in silico and in vitro data together, GKY25 is a good drug lead that could be examined further using clinical isolates of gram-negative bacteria in vitro.

Optimization of 3D Holographic Projection for a Medical Image System using Taguchi Method and Fuzzy Inference System

Two dimensional projections of three dimensional (3D) objects are used to teach anatomy. These projections are relatively unrealistic, and medical students cannot easily and accurately grasp the position and shape of each anatomical structure. As a remedy, 3D holographic projections allow for 3D anatomical structures to be projected in space without the use of worn contraptions. This study designed a method for optimizing 3D holographic projections with respect to the quality characteristics of 3D imaging definition and stereoscopic quality. The Taguchi method was used to determine the factors that most greatly influenced these quality characteristics, and the Delphi method and fuzzy theory were used to quantify image quality. Among three main factors of material of the projection panel, thickness of the projection panel, and angle made by the projection panel with the horizontal plane, thickness was the most influential. The optimal combination of factors was acrylic material, a thickness of 1 mm, and an angle of 45∘. This paper’s method aids medical pedagogy and can be used by the holographic projection manufacturing industry to optimize 3D imaging definition and stereoscopic quality.

Research on Key Point Detection Method of Mechanical Arm

Accurate keypoint localization is an important research direction in the field of robotic arms. Deep learning is being used more and more for motion capture and pose estimation. This is due to their ability to detect user-defined key points without the use of labels. We present an approach for detecting robot 3D key points coordinate based on two perspectives. Two images of different perspectives are processed by the same deep neural network to detect 2D projections of key points (such as joints) associated with the robot. Triangularization is then applied to recover 3D coordinates. In addition, the existing dataset of robot critical points is obtained by simulation. It seriously impedes the advancement of this field. We establish an actual robot key points dataset and corresponding evaluation criterion. The experimental results demonstrate that our framework achieves cutting-edge detection performance. It is reusable for other robot models.

PRODUCTION OF DIGITAL CONTENT (3D ASSET) SOURCE RESOURCES FOR CULTURAL HERITAGE

Abstract. In Korea, several 3D digital documentation projects have been carried out to preserve cultural heritage, but limitations in high-capacity/high-quality data have hindered their use in virtual restoration. To address this, organizations have produced low-capacity, high-quality 3D assets since 2020, but disseminating 3D assets with metadata containing cultural heritage information is important to reduce errors in historical research during virtual restoration. To overcome this problem, the Cultural Heritage Administration of Korea initiated the ‘Cultural Heritage Digital Content (3D Asset) Source Resource Production’ project in 2022. The project aims to convey and share the value of cultural heritage through 3D assets, which are complex due to the artistic values of units that must be contextually connected. Spatial and asset characteristics were classified into six categories of cultural heritage 3D assets, with the goal of turning tangible and intangible cultural heritage into 3D assets for comprehensive utilization. The cultural heritage digital source resources are a valuable resource for the creative industry.

Tensile Properties of 3D‐Projected 4‐Polytopes: A New Class of Mechanical Metamaterial

In this article, we research the tensile behavior mechanical metamaterial based on the 3D projections of 4D geometries (4‐polytopes). The specific properties of these mechanical metamaterials can be enhanced by more than fourfold when optimized within a framework powered by an evolutionary algorithm. We show that the best‐performing metamaterial structure, the 8‐cell (tesseract), has specific yield strength and specific stiffness values in a similar range to those of hexagonal honeycombs tested out‐of‐plane. The 8‐cell structures are also cubically symmetrical and have the same mechanical properties in three orthogonal axes. The effect of structure is quantified by comparing metamaterial tensile strength against the Young's modulus of constituent solid material. We find that the strength‐to‐modulus value of the 8‐cell structures exceeds that of the hexagonal honeycomb by 76%. The 5‐cell (pentatope) and 16‐cell (orthoplex) metamaterials are shown to be more effective under tensile loading than gyroid structures, while 24‐cell (octaplex) structures display the least optimal structure‐properties relationships. The findings presented in this paper showcase the importance of macro‐scale architecture and highlight the potential of 3D projections of 4‐polytopes as the basis for a new class of mechanical metamaterial.

OPENHERITAGE3D: BUILDING AN OPEN VISUAL ARCHIVE FOR SITE SCALE GIGA-RESOLUTION LIDAR AND PHOTOGRAMMETRY DATA

Abstract. LiDAR and photogrammetry are common mechanisms for the documentation of cultural heritage sites. Their outputs provide foundational primary sources for research and important engineering decisions contributing to the on-going conservation of sites and structures. Unfortunately, due to the complex nature of these data, they are rarely shared with stakeholders in their full forms. Raw data is routinely transferred to portable hard drives and forgotten at a project’s end. Digital heritage documentation, often acquired with great effort and cost, is at risk of loss (UNESCO 2003). When these data are shared, they are rarely presented or formatted in ways which enable their widespread re-use. As processing tools improve at a rapid pace, and offer new pipelines for improved reconstruction and fusion with additional data sources, it is important to preserve the data in a way which maintains all functionality and interoperability between processing platforms. It's not enough to share data or to simply make them "available." Data must be technologically and intellectually intelligible (and useful). A new system framework is required to ensure their integrity and wide-spread utility, and to democratize these data for re-use by the diverse communities of stakeholders with whose purposes fall outside the narrow scopes of a 3D documentation project’s original goals. In this paper we present OpenHeritage3D.org as a platform and framework for an open visual archive seeking to provide authoritative and democratized access to site-scale lidar and photogrammetry through data curation, file-sharing, and web-visualization systems with granular segmentation and data conversion capabilities.

Keck spectroscopy of NGC 1052-DF9: stellar populations in the context of the NGC 1052 group

ABSTRACT In this study, we use Keck/Keck Cosmic Web Imager spectroscopy to measure the age, metallicity, and recessional velocity of NGC 1052-DF9 (DF9), a dwarf galaxy in the NGC 1052 group. We compare these properties to those of two other galaxies in the group, NGC 1052-DF2 and NGC 1052-DF4, which have low dark matter content. The three galaxies are proposed constituents of a trail of galaxies recently hypothesized to have formed as part of a ‘bullet dwarf’ collision. We show that the ages and total metallicities of the three galaxies are within uncertainties of one another which may be expected if they share a related formation pathway. However, the recessional velocity we recover for DF9 (1680 ± 10 km s−1) is higher than predicted for a linearly projected interpretation of the ‘bullet dwarf’ trail. DF9 is then either not part of the trail or the correlation of galaxy velocities along the trail is not linear in 2D projection due to their 3D geometry. After examining other proposed formation pathways for the galaxies, none provide a wholly satisfactory explanation for all of their known properties. We conclude further work is required to understand the formation of this interesting group of galaxies.

A FLEXIBLE WORKFLOW FOR MULTIMODAL 3D IMAGING OF VAULTED PAINTED CEILINGS IN HIGH DETAIL

Abstract. 3D imaging is an increasingly common tool for the investigation of cultural heritage. Painted ceilings offer particular challenges as the art historical requirements necessitate highly detailed and accurate capture of colour textures with sub-millimetre resolution, even of large areas of 100s of square metres, situated in a wide variety of building environments. Geometrical information is also required to represent fully the three-dimensional nature of these sculpted and vaulted ceilings, again at the resolution necessary for both documentation and use by cultural heritage professionals including conservators, restorers, building researchers, architects and art historians. This paper describes a multi-modal campaign of 3D digitisation of three very different sites undertaken as part of the Franco-German Plafond 3D project. We introduce a flexible and adaptable methodology that allows the detailed imaging of large interiors and ceiling paintings in a short period of time and with varying levels of access.

A morphological study and the variability in the number of infraorbital foramina in the African green monkey (Grivet) (Chlorocebus aethiops) using microcomputed tomography.

Knowledge of the nonhuman primate morphology and anatomy related to craniofacial mechanoreception is essential for a fundamental understanding of the incidents that have occurred during the evolution of craniofacial features. The present study focuses on the variability in the number of infraorbital foramina and associated anatomical structures such as the infraorbital canal (IOC) and the infraorbital groove (IOG), as they are considered to play an important role in the behavioral ecology of these animals. A total of 19 skulls of Chlorocebus aethiops were analyzed. The number of infraorbital foramina was assessed macroscopically using a magnifying glass and a small diameter probe. Three dimensional(3D) projections and morphometric analysis of the infraorbital foramina, IOCs, and IOGs were performed using microcomputed tomography (micro-CT) for two skulls that represent one of the most common morphological types. Regardless of sex and body side, the most common morphological type observed in the studied species is the presence of three infraorbital foramina. The IOC takes a funnel or pinched shape. 3D projections were made to assess the course of the infraorbital vascular and nerve bundles in selected individuals. The results indicate a high morphological diversity within the species, although there appears to be a consistent distribution pattern of infraorbital neurovascular bundles in species of the Cercopithecidae family. The use of X-ray micro-CT allowed 3D visualization of the maxillary region to determine the variability of the infraorbital foramina and to track the division of the infraorbital neurovascular bundle in the case of the most common macroscopic expression of the number of the infraorbital foramen in C. aethiops, as well as the morphometric of the IOCs and IOGs which are related to mechanoreception of the primate's snout.

Simple and precise calibration of the line-structured light vision system using a planar target.

When calibrating a line-structured light vision system using a planar target, noise easily affects the solution of the coordinates of light stripe points at the camera coordinate frame. Therefore, the planar target must be placed in the measurement space many times to capture more target images for improving calibration stability and achieving relatively high calibration accuracy. This complicates the calibration process. This paper proposes a calibration method considering the measurement baselines of a planar target. The planar target is placed only two times, and two target images are captured correspondingly. A three-point subset is made up of the two calibration points that form the measurement baseline with the longest 2D projection and any other calibration point. In this way, it is less affected by noise when using the three-point subsets to establish the equations. Then, we use the lengths of the measurement baselines provided by all three-point subsets and their 2D projections to solve the coordinates of light stripe points at the camera coordinate frame more accurately to calibrate the line-structured light vision system. Both the simulation and actual experiment results demonstrate the feasibility of our method. Based on our calibration method, the RMS error is 0.035mm for length measurement and 0.054mm for height measurement. Compared with other existing methods, our method needs only two target images. It can also achieve more accurate calibration results than the other methods. In addition, our calibration method increases the applicability of the line-structured light measurement method by reducing the number of target swings.

Insights on Elastic Anisotropy and Thermal Properties of Mg–Ti–O Compounds from First‐Principles Calculations

First‐principles calculations are employed to explore the elastic anisotropy and thermal properties of Mg–Ti–O compounds (MgTiO3, MgTi2O5, and Mg2TiO4). The structure parameters used in this work are in good agreement with other theoretical and experimental results. The mechanical stability and ductile nature are demonstrated. The elastic anisotropy is characterized by different anisotropy indexes, three‐dimensional (3D) surface constructions, and two‐dimensional (2D) projections of Young's modulus. Besides, the sound velocities, Debye temperature, and minimum thermal conductivity are also investigated from the elastic modulus. The obtained results can provide references for future experimental investigations and engineering applications of these Mg–Ti–O compounds.