Traditional Visualization Techniques Research Articles

11С-methionine PET/CT use in the diagnosis of primary hyperparathyroisis

Background. Primary hyperparathyroidism (PHPT) is an endocrine disorder characterized by autonomous production of parathyroid hormone (PTH). Currently, parathyroidectomy (PTX) is considered the main method of PHPT treatment. Its outcome is largely depended on precise preoperative localization of the parathyroid adenoma. Traditional visualization techniques include ultrasound (US), scintigraphy and computed tomography (CT), each of which has its own limitations. In order to improve visualization results positron emission tomography/ computed tomography (PET/CT) with 11C-methionine is used. Objective. To compare the sensitivity and specificity of 11 C-methionine PET/CT with those of conventional imaging techniques for parathyroid adenomas localization.Design and methods. The data of 91 patients diagnosed with PHPT was analyzed. Ultrasound, scintigraphy with 99mTc-sestamib i/99mTc-pertechnetate and CT were performed in 91, 56, and 86 patients, respectively. Since 2020, 11C-methionine PET/CT has been used as the final diagnostic method in 45 patients. Histologу results were used as the benchmark in order to evaluate the diagnostic accuracy of the studied methods.Results. Histological examination confirmed parathyroid adenoma/ hyperplasia in all patients. Multiple adenomas/hyperplasia were found in 5 cases. Ectopic adenomas were detected in 19 patients. The sensitivity of PET/CT with 11C-methionine was 98 %, CT, scintigraphy and ultrasound — 75 %, 79 %, 67 %, respectively. Specificity — 93 %, 73 %, 75 %, 70 %, respectively.Conclusion. 11C-methionine PET/CT showed higher sensitivity and specificity than traditional methods.

Microbiome maps: Hilbert curve visualizations of metagenomic profiles.

Abundance profiles from metagenomic sequencing data synthesize information from billions of sequenced reads coming from thousands of microbial genomes. Analyzing and understanding these profiles can be a challenge since the data they represent are complex. Particularly challenging is their visualization, as existing techniques are inadequate when the taxa number is in the thousands. We present a technique, and accompanying software, for the visualization of metagenomic abundance profiles using a space-filling curve that transforms a profile into an interactive 2D image. We created Jasper, an easy to use tool for the visualization and exploration of metagenomic profiles from DNA sequencing data. It orders taxa using a space-filling Hilbert curve, and creates a "Microbiome Map", where each position in the image represents the abundance of a single taxon from a reference collection. Jasper can order taxa in multiple ways, and the resulting microbiome maps can highlight "hot spots" of microbes that are dominant in taxonomic clades or biological conditions. We use Jasper to visualize samples from a variety of microbiome studies, and discuss ways in which microbiome maps can be an invaluable tool to visualize spatial, temporal, disease, and differential profiles. Our approach can create detailed microbiome maps involving hundreds of thousands of microbial reference genomes with the potential to unravel latent relationships (taxonomic, spatio-temporal, functional, and other) that could remain hidden using traditional visualization techniques. The maps can also be converted into animated movies that bring to life the dynamicity of microbiomes.

A Lagrangian analysis of partial cavitation growth and cavitation control mechanism

Partial cavitation has a strong unsteadiness, which will cause serious damage to the hydraulic machinery. The spanwise obstacle is nearly the most efficient method for controlling unsteady cavitation. In this study, numerical simulations of partial cavitating flows around NACA (National Advisory Committee for Aeronautics) 66 hydrofoils in two dimensions (2D) were carried out both with and without obstruction. The obstruction is placed at 0.37c, and its height is 0.1c. Utilizing the finite-time Lyapunov exponent, the Lagrangian coherent structures (LCSs) were developed to investigate the dynamic characteristics of the unsteady flow. By showing the dynamic evolution of the Lagrangian behaviors, the time-dependent LCSs over the two different flows demonstrate the effectiveness of LCSs in explaining the evolution of the vortex during the partial cavitation process. With the use of LCSs, the vortex boundary and reentrant jet can be easily located, and the link between the vortexes can be readily seen. In the meantime, the vortex's origin and destination are shown by the stable and unstable manifolds, respectively. LCSs were then utilized to examine how the obstruction had an impact, and the following conclusions were reached. First, the obstruction can stop a portion of reentrant jets from passing through it. Second, the obstruction can curve the pathway of the reentrant jet, which has passed through it. Third, the obstruction prevents the cavity from flowing downstream. Finally, the obstruction continuously obliterates the expanding cavity across it. Simply said, the Lagrangian analysis based on LCSs provides a better understanding of the vortex dynamics than traditional visualization techniques, which is essential to understanding the great performance of the cavitation-induced unsteady flow.

Framework for Armature-Based 3D Shape Reconstruction of Sensorized Soft Robots in eXtended Reality.

Soft robots are typically intended to operate in highly unpredictable and unstructured environments. Although their soft bodies help them to passively conform to their environment, the execution of specific tasks within such environments often requires the help of an operator that supervises the interaction between the robot and its environment and adjusts the actuation inputs in order to successfully execute the task. However, direct observation of the soft robot is often impeded by the environment in which it operates. Therefore, the operator has to depend on a real-time simulation of the soft robot based on the signals from proprioceptive sensors. However, the complicated three-dimensional (3D) configurations of the soft robot can be difficult to interpret using traditional visualization techniques. In this work, we present an open-source framework for real-time 3D reconstruction of soft robots in eXtended Reality (Augmented and Virtual Reality), based on signals from their proprioceptive sensors. This framework has a Robot Operating System (ROS) backbone, allowing for easy integration with existing soft robot control algorithms for intuitive and real-time teleoperation. This approach is demonstrated in Augmented Reality using a Microsoft Hololens device and runs at up to 60 FPS. We explore the influence that system parameters such as mesh density and armature complexity have on the reconstruction's key performance metrics (i.e., speed, scalability). The open-source framework is expected to function as a platform for future research and developments on real-time remote control of soft robots operating in environments that impede direct observation of the robot.

In Situ Visualization of Regional-Scale Natural Hazards With Galaxy and Material Point Method

Visualizing regional-scale landslides is essential to conveying the threat of natural hazards to stakeholders and policymakers. Traditional visualization techniques are restricted to post-processing a limited subset of simulation data and are not scalable to rendering regional-scale models. In situ visualization is a technique of rendering simulation data in real-time, i.e., rendering visuals in tandem while the simulation is running. This study develops a scalable N:M interface architecture to visualize regional-scale landslides. We demonstrate the scalability of the architecture by simulating the long runout of the 2014 Oso landslide using the Material Point Method coupled with the Galaxy ray tracing engine rendering 4.2 million material points as spheres. In situ visualization has an amortized runtime increase of 2% compared to non-visualized simulations. The developed approach can achieve in situ visualization of regional-scale landslides with minimal impact on the simulation process.

Robustness, replicability and scalability in topic modelling

• We identify three key properties a topic model must exhibit for effective application in the social sciences: statistical robustness, descriptive power across all dimensions and reflection of reality. • We propose a simple approach for estimating the statistical robustness of topic models that is based on pairwise similarity scores between documents. • Applying that approach we find that the neural network-based Doc2Vec is more stable than the other topic models tested: Latent Dirichlet Allocation and Non-negative Matrix Factorisation. • We further propose a principal component analysis based approach for assessing the descriptive power of topic models. In applying that approach we find that Doc2Vec performs the best, but LDA does also perform well. • We provide grounds for the application of neural embeddings approaches in the social sciences and also how traditional visualisation techniques can be applied directly to dense vector representations. Approaches for estimating the similarity between individual publications are an area of long-standing interest in the scientometrics and informetrics communities. Traditional techniques have generally relied on references and other metadata, while text mining approaches based on title and abstract text have appeared more frequently in recent years. In principle, topic models have great potential in this domain. But, in practice, they are often difficult to employ successfully, and are notoriously inconsistent as latent space dimension grows. In this manuscript we identify the three properties all usable topic models should have: robustness, descriptive power and reflection of reality. We develop a novel method for evaluating the robustness of topic models and suggest a metric to assess and benchmark descriptive power as number of topics scale. Employing that procedure, we find that the neural-network-based paragraph embedding approach seems capable of providing statistically robust estimates of the document–document similarities, even for topic spaces far larger than what is usually considered prudent for the most common topic model approaches.

A Subjective and Behavioral Assessment of Affordances in Virtual Architectural Walkthroughs

Immersive technologies, such as VR, offer first-person experiences using depth perception and spatial awareness that elucidate a sense of space impossible with traditional visualization techniques. This paper looks beyond the visual aspects and towards understanding the experiential aspects of two popular uses of VR in 3D architectural visualization: a “passive walkthrough” and an “interactive walkthrough”. We designed a within-subject experiment to measure the user-perceived quality for both experiences. All participants (N = 34) were exposed to both scenarios and afterwards responded to a post-experience questionnaire; meanwhile, their physical activity and simple active behaviors were also recorded. Results indicate that while the fully immersive-interactive experience rendered a heightened sense of presence in users, overt behaviors (movement and gesture) did not change for users. We discuss the potential use of subjective assessments and user behavior analysis to understand user-perceived experiential quality inside virtual environments, which should be useful in building taxonomies and designing affordances that best fit these environments.

Study on dynamics of vortices in dynamic stall of a pitching airfoil using Lagrangian coherent structures

The evolution of vortex structure and mass transport process during dynamic stall of the two-dimensional pitching NACA0012 airfoil are studied in detail, using Lagrangian coherent structures (LCSs), and the nature of dynamic stall is given from viewpoint of nonlinear dynamics. First, the numerical method with SST k−ω turbulence model is used to simulate the flow field around the pitching oscillation airfoil. Then, the Lagrangian-averaged vorticity deviation (LAVD) method is used to analyze the formation and evolution of vortex structure during dynamic stall. Further, the circulation development process of the primary leading edge vortex (LEV) is studied, with comparison between LAVD method with Q criterion. Finally, the dynamic behaviors, such as the mass transport and evolution of flow structure during the process of dynamic stall, are analyzed in depth by using LCSs, and the fluctuation of lift coefficient and the dynamic stall are investigated from the viewpoint of nonlinear dynamics. The results show that the evolution of vortex structure and mass transport are closely related to the fluctuation of lift coefficient during the dynamic stall, and the low-pressure region formed by vortices and the complex mass transport and mixing process on the suction surface of the airfoil are the main reasons for the high lift during the dynamic stall process. In particular, the primary LEV, which can be accurately identified and tracked by LAVD method, plays a very important role in lift enhancement, and the primary LEV and the secondary LEV form and grow in turn by the intermittent feeding process of shear layer. Additionally, the fluid particles in front of the leading edge of the airfoil enter the LEV through a special mass transport channel, which is textured by LCSs and opened and closed intermittently. More importantly, the saddle point of LCSs is an important component of vortex boundary, and its dynamic behaviors represent the behaviors of vortex. The first separation of saddle point from the shear layer at leading edge indicate the separation of primary LEV from the suction surface of the airfoil, and the occurrence of dynamic stall. The second separation of saddle point from the shear layer at leading edge indicate that primary LEV begins to leave the upper region of the airfoil, corresponding to a sharp drop in lift coefficient. Generally, compared to the traditional visualization techniques, the Lagrangian analysis based on LCSs and LAVD can provide a deeper insight into the dynamics of the vortex in flow field around pitching oscillation airfoil and the dynamic mechanism of dynamic stall.

Imaging the Subsurface: How Different Visualizations of Cross-sections Affect the Sense of Uncertainty

Geologists struggle to communicate the uncertainty that arise when mapping and interpreting the geological subsurface. Today, open data sharing policies make new value of geological information possible for a broader user group of non-experts. It is crucial to develop standard methods for visualizing uncertainty to increase the usability of geological information. In this study, a web experiment was set up to analyze whether and how different design choices influence the sense of uncertainty. Also, questions about the intuitiveness of symbols were asked. Two-hundred ten participants from different countries completed the experiment, both experts and non-experts in geology. Traditional visualization techniques in geology, like dashed lines, dotted lines and question mark, were tested. In addition, other visualizations were tested, such as hatched area and variations of symbol size, zoom levels and reference information. The results show that design choices have an impact on the participants’ assessment of uncertainty. The experts inquire about crucial information if it is not present. The results also suggest that when visualizing uncertainty, all the elements in the representation, and specifically the line and area symbols that delineate and colour the features, must work together to make the right impression.

Treemaps as a Tool for Social Network Analysis

Abstract : We apply treemap technology in the analysis of large, social network datasets principally for examining network subgroups. A treemap is graphically-based information and exploration tool which is used in diverse fields such as computer science, finance, and human-gene research; from our experience, we find treemaps also useful in the social network analysis setting. A treemap represents hierarchical and categorical data in a mosaic form containing embedded, rectangular shapes, where the size of each shape is germane. Treemap displays are especially helpful when examining data in an interactive mode (as opposed to a static or printed form). We have found that treemaps are a powerful tool for exploring large social-networks, particularly during the exploratory data analysis phase. Their use quickly leads to a thorough perspective of the holistic characteristics of the network and to easier identification of significant subgroups; both of these perspectives may otherwise remain hidden using traditional visualization techniques. In this report, we introduce treemap technology, first broadly, then, specifically how it can be applied to social network analysis. We also show how we have actually applied treemaps to an interactive study of a large, real-world dataset. As a result of our experiences, we encourage other social network analysts to consider applying treemaps in their work.

Dynamic Visualization of Uncertainties in Medical Feature of Interest

In a medical context, uncertainty visualization of a Feature of Interest (FOI) is important, which could provide medical experts with informative feedback to make better decisions for diagnosis or preoperative planning. Traditional uncertainty visualization techniques allow the exploration of the uncertainty visualization of the FOI. However, when the intensity of the FOI and other materials is similar or overlapping, and/or the FOI is occluded by other materials, it would be difficult or impossible for them to reveal the FOI and its uncertainties. To address this problem, we propose an uncertainty visualization technique that includes two main components: the Multiattribute-rule-based FOI Segmentation (M-rule Seg. for short) and the FOI Dynamic Uncertainty Visualization. To demonstrate its effectiveness, we performed an experiment comparing it with two traditional uncertainty visualization techniques. The experimental results show that our proposed uncertainty visualization technique allows to better reveal the FOI and all its uncertainties that are difficult or impossible to be visualized by traditional uncertainty visualization techniques. In addition, we performed another experiment to compare our proposed M-rule Seg. technique with three traditional segmentation techniques. The experimental results show that our M-rule Seg. technique can generate more accurate segmentation results at the cost of a longer computing time.

Virtual Reality for Information Visualization Might Just Work This Time.

In the 1990's, Virtual Reality (VR) was discredited as a means of presenting Information Visualization (InfoViz). Mercurio and Erickon (Mercurio et al., 1990), noted several problems required to be overcome before the potential of VR for scientific visualization could be realized: low image resolution, user navigation, small tracking volume, low tracker update rate, and poor user interfaces. Even with this negative reaction, a number of researchers continued pursuing this line of investigation (for example, the work of Bowman et al., 2003). As hardware and graphics techniques improved, plausible applicability of VR to InfoViz was slowly being realized. Currently, Immersive Analytics (Marriott et al., 2018) is an emerging direction for the use of VR and other immersive technologies to improve understanding of visualization problems. There are a number of factors that influence my belief that VR supported InfoViz can be achieved. Firstly, the hardware is so much better today; this is regarding robustness, availability, and cost. The software support has greatly improved in recent years for VR and InfoViz. Because of these two reasons, far more people can investigate this problem today. Visualization is more advanced from the 1990s in their techniques and the problem domains they are applied to. There have been a number of successes for InfoViz. Still there are domains that are challenging for traditional visualization techniques, such as high dimensional data (Tang et al., 2016). VR is a potential tool for these challenging domains by allowing the user to visualize and interact with the data with new and different techniques (Sherman and Craig, 2018). A major reason VR might be able to support InfoViz is the rise of commercial VR systems. These systems are now commodity devices designed for home use. As with graphics hardware, VR hardware is benefiting from being a large-scale product. Current VR systems are complete. These systems have integrated HMDs, tracking systems, and handheld input devices (Anthes et al., 2016). Today there are well-designed input devices that are part of the commercial systems. What is important to realize is they are reliable and function with minimal set up. The computers today have much better graphics capability than ever before, and Table 1 provides an overview of the improvement of graphics engines over the decades. In comparison to previous VR systems, today's systems are inexpensive. Current systems complete systems (including computing) are approximate $(US) 3K. Five-six years ago1 an equivalent system would cost about $20K, and 20 years ago2 about $1 million. Table 1 Review of graphics engine throughput.

Computational and Experimental Investigation of Janus-like Monolayers on Ultrasmall Noble Metal Nanoparticles.

Detection of monolayer morphology on nanoparticles smaller than 10 nm has proven difficult with traditional visualization techniques. Here matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) is used in conjunction with atomistic simulations to detect the formation of Janus-like monolayers on noble metal nanoparticles. Silver metal nanoparticles were synthesized with a monolayer consisting of dodecanethiol (DDT) and mercaptoethanol (ME) at varying ratios. The nanoparticles were then analyzed using MALDI-MS, which gives information on the local ordering of ligands on the surface. The MALDI-MS analysis showed large deviations from random ordering, suggesting phase separation of the DDT/ME monolayers. Atomistic Monte Carlo (MC) calculations were then used to simulate the nanoscale morphology of the DDT/ME monolayers. In order to quantitatively compare the computational and experimental results, we developed a method for determining an expected MALDI-MS spectrum from the atomistic simulation. Experiments and simulations show quantitative agreement, and both indicate that the DDT/ME ligands undergo phase separation, resulting in Janus-like nanoparticle monolayers with large, patchy domains.

Of Microscopes and Metaphors: Visual Analogy as a Scientific Tool

Throughout history, visualizations have played a central role in articulating scientific ideas and innovation. Even though technological systems and tools enables scientists to explore increasingly more ‘abstract’ scientific domains, sometimes traditional visualization techniques are no longer adequate to guide our understanding. Analogies and conceptual metaphors have often been highlighted as a key component of scientific thinking, especially when dealing with intangible entities and phenomena. In particular, visual metaphors, such as those found in comics, seem uniquely suited to illustrate complex scientific phenomena and promote public understanding of science. This article draws an analogy between microscopes and an imaginary metaphorical apparatus, in order to explore the potential (and limitations) of visual metaphors in scientific research.

Rapid visualization of latent fingerprints using novel CaSiO3:Sm3+ nanophosphors fabricated via ultrasound route

Latent fingerprints (LFPs) were the most significant identification method for individualization. Most commonly available fingerprints (FPs) in crime spot investigation were latent and patent types. Generally, LFPs were invisible and thus the effective visualization technique necessitates for the analysis of such FPs. In the past years, many traditional visualization techniques have been employed, but suffered with low resolution, sensitivity, contrast and high background noise. To overcome such limitations, we synthesized Sm3+ doped CaSiO3 nanophosphors (NPs) via an ultrasound irradiation route using mimosa pudica (m. p.) leaves extract as a bio-surfactant. The morphological behavior of the prepared samples was extensively studied by varying the concentration of the m. p. extract, ultrasound irradiation duration, pH level of the precursor solution and sonication power. The photoluminescence (PL) emission spectra exhibit characteristic peaks at ∼ 561, 601 and 647 nm, which were attributed to 5G5/2→6HJ (J = 5/2, 7/2 and 9/2) transitions of Sm3+ ions. The Judd-Ofelt (J-O) intensity parameters and other radiative properties were estimated using PL data. The Commission International de I'Eclairage (CIE) color coordinates were positioned in orange-red region shows average correlated color temperature (CCT) value of ∼3576 K. The optimized samples can be used as a labeling agent for the visualization of LFPs on various porous and non-porous surfaces under normal light irradiation. The visualized FPs reveals well defined ridge characteristics, namely whorl, loop, arch, bifurcation, eye, island, bridge, sweat pores, etc. with high sensitivity, selectivity, low contrast and background hindrance. Aforementioned results evidence that the prepared CaSiO3:Sm3+ NPs were promising luminescent materials for solid state lighting and forensic applications.

Eye tracking and visualization. Introduction to the Special Thematic Issue

There is a growing interest in eye tracking technologies applied to support traditional visualization techniques like diagrams, charts, maps, or plots, either static, animated, or interactive ones. More complex data analyses are required to derive knowledge and meaning from the data. Eye tracking systems serve that purpose in combination with biological and computer vision, cognition, perception, visualization, human-computer-interaction, as well as usability and user experience research. The 10 articles collected in this thematic special issue provide interesting examples how sophisticated methods of data analysis and representation enable researchers to discover and describe fundamental spatio-temporal regularities in the data. The human visual system, supported by appropriate visualization tools, enables the human operator to solve complex tasks, like understanding and interpreting three-dimensional medical images, controlling air traffic by radar displays, supporting instrument flight tasks, or interacting with virtual realities. The development and application of new visualization techniques is of major importance for future technological progress.

Gaze Self-Similarity Plot - A New Visualization Technique.

Eye tracking has become a valuable way for extending knowledge of human behavior based on visual patterns. One of the most important elements of such an analysis is the presentation of obtained results, which proves to be a challenging task. Traditional visualization techniques such as scan-paths or heat maps may reveal interesting information, nonetheless many useful features are still not visible, especially when temporal characteristics of eye movement is taken into account. This paper introduces a technique called gaze self-similarity plot (GSSP) that may be applied to visualize both spatial and temporal eye movement features on the single two-dimensional plot. The technique is an extension of the idea of recurrence plots, commonly used in time series analysis. The paper presents the basic concepts of the proposed approach (two types of GSSP) complemented with some examples of what kind of information may be disclosed and finally showing areas of the GSSP possible applications.

Facile LaOF: Sm3+ based labeling agent and their applications in residue chemistry of latent fingerprint and cheiloscopy under UV–visible light

Luminescent lanthanum oxyfluoride nano inorganic materials were considered to be prospective building blocks for multifunctional applications. This offers new potentials in surface-based science comprising of visualization of latent fingerprint (LFPs) and lips print on non-porous surfaces. Traditional visualization techniques possess high backward hindrance, low sensitivity, complicated setup and poor visibility. To overcome with these problems, LaOF:Sm3+ (5 mol%) nanopowder (NPs) prepared via sonochemical route were explored. Photoluminescence (PL) emission spectra exhibit strong emission peaks at ∼566 nm, 607 nm, 653 nm and 708 nm attributed to 4G5/2 → 6H5/2, 4G5/2 → 4H7/2, 4G5/2 → 6H9/2 and 4G5/2 → 6H11/2 intra-4f orbital transitions of Sm3+ ions respectively. Estimated photometric properties confirm that the material emits warm orange red color. Therefore, the synthesized phosphor materials may quite be useful for LFPs recovery, cheiloscopy and optoelectronics applications.

Eye Tracking and Visualization: Introduction to the Special Thematic Issue of the Journal of Eye Movement Research

There is a growing interest in eye tracking technologies applied to support traditional visualization techniques like diagrams, charts, maps, or plots, either static, animated, or interactive ones. More complex data analyses are required to derive knowledge and meaning from the data. Eye tracking systems serve that purpose in combination with biological and computer vision, cognition, perception, visualization, human-computer-interaction, as well as usability and user experience research. The 10 articles collected in this thematic special issue provide interesting examples how sophisticated methods of data analysis and representation enable researchers to discover and describe fundamental spatio-temporal regularities in the data. The human visual system, supported by appropriate visualization tools, enables the human operator to solve complex tasks, like understanding and interpreting three-dimensional medical images, controlling air traffic by radar displays, supporting instrument flight tasks, or interacting with virtual realities. The development and application of new visualization techniques is of major importance for future technological progress.

Scalable Visualization of Time-varying Multi-parameter Distributions Using Spatially Organized Histograms.

Visualizing distributions from data samples as well as spatial and temporal trends of multiple variables is fundamental to analyzing the output of today's scientific simulations. However, traditional visualization techniques are often subject to a trade-off between visual clutter and loss of detail, especially in a large-scale setting. In this work, we extend the use of spatially organized histograms into a sophisticated visualization system that can more effectively study trends between multiple variables throughout a spatial domain. Furthermore, we exploit the use of isosurfaces to visualize time-varying trends found within histogram distributions. This technique is adapted into both an on-the-fly scheme as well as an in situ scheme to maintain real-time interactivity at a variety of data scales.